Configure metadata (Maintenance App)¶

Note

This page documents the legacy Maintenance app. If you are using the Metadata Management app see Configure metadata in the Metadata Management app available from the DHIS2 App Hub and compatible from version 41.

Sobre o aplicativo de manutenção¶

In the Maintenance app you configure all the metadata objects you need to collect and analyze data:

• Categorias

• Elementos de dados

• Conjuntos de dados e formulários de entrada de dados

• Indicadores

• Unidades organizacionais

• Regras de validação

• Atributos

• Constantes

• Conjuntos de opções

• Legendas

• Preditores

• Relatórios push

• Camadas de mapa externas

• SQL views

• Locales

• Analytics table hooks

Note

The functions you have access to depend on your user role's access permissions.

Navegando em objetos de metadados¶

Metadata objects are presented in a list with predefined columns that are relevant for each object. You may customize which columns are shown in the list for the current object. These customizations are per user, and therefore will not affect other users. Note that these changes do not edit any metadata, just how the list is presented.

Gerenciando colunas visíveis¶

1. Click the icon to the top right of the list of objects you want to configure.
2. Um menu suspenso aparecerá, selecione ** Gerenciar colunas **.
3. Uma caixa de diálogo aparecerá, com as colunas padrão selecionadas.
4. Clique em qualquer nome de coluna na lista de ** Colunas disponíveis ** para adicioná-las à lista de colunas selecionadas.
5. You may reorder the selected columns by drag-and-dropping the icon.
6. Você também pode remover qualquer coluna da visualização clicando no ícone X ao lado do nome.
7. Click Save once you are satisfied with your changes.

Você pode redefinir facilmente para os valores padrão clicando no botão ** Redefinir para o padrão **.

Baixar metadados¶

Você pode baixar os metadados do objeto que está visualizando no momento. O download dos metadados respeitará todos os filtros que você tiver ativo para a lista.

1. Click the icon to the top right of the list of objects you want to configure.
2. Um menu suspenso aparecerá, selecione ** Download **.
3. Uma caixa de diálogo aparecerá, onde você pode selecionar o formato e compactação desejados.
4. ** Com compartilhamento ** pode ser selecionado para incluir compartilhamento de dados para os metadados.

Gerenciar categorias¶

Sobre categorias¶

Categories are typically a concept, for example "Gender", "Age" or "Disease Status". Data elements such as "Number of cases of confirmed malaria" are often broken into smaller component parts to determine, for example, the number of confirmed malaria cases of particular age groups.

Use categories to disaggregate data elements into individual components. You can also use categories to assign metadata attributes to all data recorded in a specific dataset, such as "Implementing partner" or "Funding agency."

Create three categories: "Under 1", "1-5" and "Over 5". Assign them as categories to the data element. This creates three separate fields for this data in the data entry forms:

• Número de casos de malária confirmados (menos de 1)

• Número de casos de malária confirmados (1-5)

• Número de casos de malária confirmados (mais de 5)

Without categories, you would have had to create each of the data elements listed above separately.

In the Maintenance app, you manage the following and category objects:

Fluxo de Trabalho¶

1. Crie todas as opções de categoria.

2. Create categories composed by the multiple category options you've created.

3. Create category combinations composed by either one or multiple categories.

4. Crie elementos de dados e atribua-os a uma combinação de categorias.

Crie ou edite uma opção de categoria¶

When possible, recycle category options. For instance, there might be two categories which might share a particular category option (for example \<1 year of age). When creating the categories, this category option could be reused. This is important if particular category options (or category option combinations) that need to be analyzed together.

1. Open the Maintenance app and click Category > Category option.

2. Clique no botão adicionar.

3. Preencher o formulário:

   1. Nome

   2. Short name (optional)

   3. Code (optional)

   4. Form name (optional) Category options can have a form name. These will be displayed in the data entry app as a column header instead of the display name for the respective category option.

   5. Descrição

   6. Start date (optional)

   7. End date (optional)

4. Selecione unidades de organização e atribua-as.

   Tip

   You can automatically select all organisation units that belong to an organisation unit level or organisation unit group, for example "Chiefdom" or "Urban". To do this:

   Select an Organisation unit level or Organisation unit group and click Select.

5. Clique em Salvar.

Crie ou edite uma categoria¶

When you have created all category options for a particular category, you can create that category.

1. Abra o aplicativo ** Manutenção ** e clique em ** Categoria ** > ** Categoria **.

2. Clique no botão adicionar.

3. Preencher o formulário:

   1. Nome

   2. Nome curto

   3. Código

   4. Descrição

   5. ** Tipo de dimensão de dados **

      A category can either be of type "Disaggregation" or "Attribute". For disaggregation of data elements, you select Disaggregation. The data dimension type "Attribute" allows the category to be used to assign a combination of categories to data recorded through a data set.

   6. ** Dimensão de dados **

      If you select Data dimension, the category will be available to the analytics as another dimension, in addition to the standard dimensions of "Period" and "Organisation unit".

4. Selecione as opções de categoria e atribua-as.

5. Clique em Salvar.

Crie ou edite uma combinação de categorias¶

Category combinations let you combine multiple categories into a related set.

You can disaggregate the data element "Number of new HIV infections" into the following categories:

• Serviço de HIV: "Outro", "PMTCT", "TB"

• Gênero Masculino Feminino"

In this example, there are two levels of disaggregation that consist of two separate data element categories. Each data element category consists of several data element category options.

In DHIS2, different data elements are disaggregated according to a common set of categories. By combining these different categories into a category combination and assigning these combinations to data elements, you can apply the appropriate disaggregation levels quickly to a large number of data elements.

1. Open the Maintenance app and click Category > Category combination.

2. Clique no botão adicionar.

3. Preencher o formulário:

   1. Nome

   2. Código

   3. ** Tipo de dimensão de dados **

   4. ** Pular categoria total em relatórios **

4. Selecione categorias e atribua-as.

5. Clique em Salvar.

Criar ou editar um grupo de opções de categoria¶

You can group and classify category options by using category option groups. The main purpose of the category option group set is to add more dimensionality to your captured data for analysis in for example the Pivot table or Data Visualizer apps.

Consider a system where data is collected by "projects", and projects are modelled as category options. The system must be able to analyse data based on which donor supports the project. In this case, create a category option group set called "Donor". Each donor can be created as a category option group, where each category option / project is put in the appropriate group. In the data analysis applications, the "Donor" group set will appear as a data dimension, while each donor appears as a dimension item, ready to be included in reports.

Para criar um grupo de opções de categoria:

1. Open the Maintenance app and click Category > Category option group.

2. Clique no botão adicionar.

3. Preencher o formulário:

   1. Nome

   2. ** Nome curto **: Defina um nome curto para o elemento de dados.

   3. Código

   4. Descrição

   5. ** Tipo de dimensão de dados **

4. Selecione ** Opções de categoria ** e atribua-as.

5. Clique em Salvar.

Criar ou editar um grupo de opções de categoria definido¶

You can group category option groups in category option group sets. The main purpose of the category option group set is to add more dimensionality to your captured data for analysis in for example the Pivot table or Data Visualizer apps.

1. Open the Maintenance app and click Category > Category option group set.

2. Clique no botão adicionar.

3. Preencher o formulário:

   1. Nome

   2. Nome curto

   3. Descrição

   4. ** Dimensão de dados **

   5. ** Tipo de dimensão de dados **

4. Selecione ** Grupos de opções de categoria ** e atribua-os.

5. Clique em Salvar.

Use combinações de categorias para conjuntos de dados¶

When categories and category combinations have the data dimension type "Attribute", they can apply a common set of attributes to a related set of data values contained in a data set. When category combinations are used as an attribute, they serve as another dimension (similar to "Period" and "Organisation unit") which you can use in your analysis.

Suppose that an NGO is providing ART services in a given facility. They would need to report each month on the "ART monthly summary", which would contain a number of data elements. The NGO and project could potentially change over time. In order to attribute data to a given NGO and project at any point in time, you need to record this information with each data value at the time of data entry.

1. Create two categories with the data dimension type "Attribute": "Implementing partner" and "Projects".

2. Create a category combination with the data dimension type "Attribute": "Implementing partners and projects".

3. Atribua as categorias que você criou à combinação de categorias.

4. Create a data set called "ART monthly summary" and select the "Implementing partners and projects" category combination.

When you enter data in the Data entry app, you can select an "Implementing partner" and a "Project". Each recorded data value is assigned a specific combination of these categories as an attribute. These attributes (when specified as a dimension) can be used in the analysis applications similar to other dimensions, for example the period and organisation unit.

Atribuir um código a uma combinação de opção de categoria¶

You can assign a code to category option combinations. This makes data exchange between DHIS2 and external systems easier. The system creates the category option combinations automatically.

1. Open the Maintenance app and click Category > Category option combination.

2. Na lista, encontre o objeto que deseja modificar.

3. Clique no menu de opções e selecione ** Editar **.

4. Insira um código.

5. Clique em Salvar.

Clone metadata objects¶

Cloning a data element or other objects can save time when you create many similar objects.

1. Open the Maintenance app and find the type of metadata object you want to clone.

2. Na lista de objetos, clique no menu de opções e selecione ** Clonar **.

3. Modifique as opções que você deseja.

4. Clique em Salvar.

Alterar as configurações de compartilhamento para objetos de metadados¶

You can assign different sharing settings to metadata objects, for example organisation units and tracked entity attributes. These sharing settings control which users and users groups that can view or edit a metadata object.

Some metadata objects also allow you to change the sharing setting of data entry for the object. These additional settings control who can view or enter data in form fields using the metadata.

Note

The default setting is that everyone (Public access) can find, view and edit metadata objects.

1. Open the Maintenance app and find the type of metadata object you want to modify.

2. In the object list, click the context menu and select Sharing settings.

3. (Optional) Add users or user groups: search for a user or a user group and select it. The user or user group is added to the list.

4. Altere as configurações de compartilhamento dos grupos de acesso que você deseja modificar.

   • Can edit and view: The access group can view and edit the object.

   • ** Pode visualizar apenas **: O grupo de acesso pode visualizar o objeto.

   • No access (only applicable to Public access): The public won't have access to the object.

5. Change data sharing settings for the access groups you want to modify.

   • Can capture data: The access group can view and capture data for the object.

   • Can view data: The access group can view data for the object.

   • No access: The access group won't have access to data for the object.

6. Clique em ** Fechar **.

Excluir objetos de metadados¶

Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

1. Open the Maintenance app and find the type of metadata object you want to delete.

2. Na lista de objetos, clique no menu de opções e selecione ** Excluir **.

3. Clique em ** Confirmar **.

Exibir detalhes de objetos de metadados¶

1. Open the Maintenance app and find the type of metadata object you want to view.

2. In the object list, click the options menu and select Show details.

Traduzir objetos de metadados¶

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

1. Open the Maintenance app and find the type of metadata object you want to translate.

2. Na lista de objetos, clique no menu de opções e selecione ** Traduzir **.

   Tip

   If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

3. Selecione um local.

4. Digite um ** Nome **, ** Nome curto ** e ** Descrição **.

5. Clique em Salvar.

Gerenciar elementos de dados¶

Sobre os elementos de dados¶

Data elements are the base of DHIS2. Data elements define what is actually recorded in the system, for example number of immunisations or number of cases of malaria.

Data elements such as "Number of cases of confirmed malaria" are often broken into smaller component parts to determine, for example, the number of confirmed malaria cases of particular age groups.

In the Maintenance app, you manage the following data elements objects:

Fluxo de Trabalho¶

1. Crie todas as opções de categoria.

2. Create categories composed by the multiple category options you've created.

3. Create category combinations composed by either one or multiple categories.

4. Crie elementos de dados e atribua-os a uma combinação de categorias.

Crie ou edite um elemento de dados¶

1. Open the Maintenance app and click Data elements > Data element.

2. Clique no botão adicionar.

3. No campo ** Nome **, defina o nome preciso do elemento de dados.

   Cada elemento de dados deve ter um nome exclusivo.

4. In the Short name field, define a short name for the data element.

   Typically, the short name is an abbreviation of the full data element name. This attribute is often used in reports to display the name of the data element, where space is limited.

5. (Opcional) No campo ** Código **, atribua um código.

   Em muitos países, os elementos de dados são atribuídos a um código.

6. (Optional) In the Color field, assign a color which will be used for this data element in the data capture apps.

7. (Optional) In the Icon field, assign an icon which will be used for this data element in the data capture apps.

8. In the Description field, type a description of the data element. Be as precise as possible and include complete information about how the data element is measured and what its purpose is.

9. (Optional) In the Field mask field, you may type a template that's used to provide hints for correct formatting of the data element.

   NOTE

   So far this is only implemented in the DHIS2 Android Capture app; not in the Capture web app.

A seguir estão os caracteres especiais que podem ser usados na máscara. Os caracteres especiais correspondem exatamente a um caractere do tipo fornecido.

For example, the pattern can be used to show hyphens as needed in the input field of the data element. E.g "\d\d\d-\d\d\d-\d\d\d, would show a hyphen for every third digit.

1. In the Form name field, type an alternative name of the data element. This name can be used in either section or automatic data entry forms. The form name is applied automatically.

2. In the Domain type field, select whether the data element is an aggregate or tracker type of data element.

3. In the Value type field, select the type of data that the data element will record.

   Value types

   Value type	Description
   Age	Dates rendered as calendar widget OR by entering number of years, months and/or days which calculates the date value based on current date. The date will be saved in the backend.
   Coordinate	A point coordinate specified as longitude and latitude in decimal degrees. All coordinate should be specified in the format [-19.23 , 56.42] with brackets and a comma separating the longitude and latitude.
   Date	Dates rendered as calendar widget in data entry.
   Date & time	Is a combination of the DATE and TIME data elements.
   Email	Email.
   File	A file resource where you can store external files, for example documents and photos.
   Image	A file resource where you can store photos. Unlike the FILE data element, the IMAGE data element can display the uploaded image directly in forms.
   Integer	Any whole number (positive and negative), including zero.
   Letter	A single letter.
   Long text	Textual value. Renders as text area with no length constraint in forms.
   Negative integer	Any whole number less than (but not including) zero.
   Number	Any real numeric value with a single decimal point. Thousands separators and scientific notation is not supported.
   Percentage	Whole numbers inclusive between 0 and 100.
   Phone number	Phone number.
   Positive integer	Any whole number greater than (but not including) zero.
   Positive or zero integer	Any positive whole number, including zero.
   Organisation unit	Organisation units rendered as a hierarchy tree widget. If the user has assigned "search organisation units", these will be displayed instead of the assigned organisation units.
   Unit interval	Any real number greater than or equal to 0 and less than or equal to 1.
   Text	Textual value. The maximum number of allowed characters per value is 50,000.
   Time	Time is stored in HH:mm format. HH is a number between 0 and 23 mm is a number between 00 and 59
   Username	DHIS2 user. Rendered as a dialog with a list of users and a search field. The user will need the "View User" authority to be able to utilise this data type
   Yes/No	Boolean values, renders as drop-down lists in data entry.
   Yes only	True values, renders as check-boxes in data entry.

4. In the Aggregation type field, select the default aggregation operation that will be used on the data element.

   Most data elements should have the Sum operator. This includes all data elements which should be added together. Other data elements, such as staffing levels, should be set to use the Average operator, when values along the time dimension should not be added together, but rather averaged.

   Aggregation operators

   Aggregation operator	Description
   Average	Average the values in both the period as and the organisation unit dimensions.
   Average (sum in organisation unit hierarchy)	Average of data values in the period dimension, sum in the organisation unit dimensions.
   Count	Count of data values.
   Min	Minimum of data values.
   Max	Maximum of data values.
   None	No aggregation is performed in any dimension.
   Sum	Sum of data values in the period and organisation unit dimension.
   Standard deviation	Standard deviation (population-based) of data values.
   Variance	Variance (population-based) of data values.

5. If you want to save zeros for a particular reason, select Store zero data values. By default, DHIS2 does not store zeros entered in the data entry module.

6. In the URL field, enter a link to an in-depth description of the data element.

   For example a link to a metadata repository or registry that contains detailed technical information about the definition and measurement of the data element.

7. In the Category combination field, define which category combination the data element should have. This is also known as the "disaggregation".

8. Selecione um ** Conjunto de opções **.

   Option sets are predefined lists of options which can be used in data entry.

9. Selecione um ** Conjunto de opções para comentários **.

   Option sets for comments are predefined lists of options which can be used to specify standardized comments for data values in data entry.

10. Atribua uma ou várias ** Legendas **.

    Legends are used in for example the Maps app to display certain data elements with certain icons.

11. Set the Aggregation levels to allow the data element to be aggregated at one or more levels:

    1. In the left pane, select the levels you want to assign to the data element.

    2. Clique na seta para a direita para atribuir os níveis de agregação.

    By default, the aggregation will start at the lowest assigned organisation unit. If you for example select "Chiefdom", it means that "Chiefdom", "District", and "National" aggregates use "Chiefdom" (the highest aggregation level available) as the data source, and PHU data will not be included. PHU data will still be available for the PHU level, but not included in aggregations to the levels above.

    If you select both "District" and "Chiefdom", it means that the "District" and "National" level aggregates use District data as their source, "Chiefdom" will use Chiefdom, and "PHU" will use PHU.

12. If applicable, enter custom attributes values, for example Classification or Collection method.

    Note

    You create custom attributes in the Maintenance app: Other > Attributes.

13. If applicable, select compulsory data element group sets, for example Main data element group or Tracker-based data.

    Note

    You'll only see data element group sets in this form if you've created them and set them to Compulsory.

    You create data element group sets in the Maintenance app: Data element > Date element group set.

14. Clique em Salvar.

Crie ou edite um grupo de elementos de dados¶

Data element groups lets you classify related data elements into a common theme. For example, two data elements "Measles immunisation" and "BCG Immunisation" might be grouped together into a data element group "Childhood immunisation".

Para criar um grupo de elementos de dados:

1. Open the Maintenance app and click Data elements > Data element group.

2. Clique no botão adicionar.

3. Preencher o formulário:

   1. Nome

   2. Nome curto

   3. Código

4. Selecione os elementos de dados e atribua-os.

5. Clique em Salvar.

Crie ou edite um conjunto de grupos de elementos de dados¶

Data element group sets allows you to categorise multiple data element groups into a set. The system uses data element group sets during analysis and reporting to combine similar data element groups into a common theme. A data element group can be part of multiple data element group sets.

1. Open the Maintenance app and click Data elements > Data element group set.

2. Clique no botão adicionar.

3. Preencher o formulário:

   1. Nome
   2. Nome curto
   3. Código
   4. Descrição
   5. Obrigatório
   6. ** Dimensão de dados **

4. Selecione grupos de elementos de dados e atribua-os.

   Available data element groups are displayed in the left panel. Data element groups that are currently members of the data element group set are displayed in the right hand panel.

5. Clique em Salvar.

Clone metadata objects¶

Cloning a data element or other objects can save time when you create many similar objects.

1. Open the Maintenance app and find the type of metadata object you want to clone.

2. Na lista de objetos, clique no menu de opções e selecione ** Clonar **.

3. Modifique as opções que você deseja.

4. Clique em Salvar.

Alterar as configurações de compartilhamento para objetos de metadados¶

You can assign different sharing settings to metadata objects, for example organisation units and tracked entity attributes. These sharing settings control which users and user groups can view or edit a metadata object.

Some metadata objects also allows you to change the sharing setting of data entry for the object. These additional settings control who can view or enter data in form fields using the metadata.

Note

The default setting is that everyone (Public access) can find, view and edit metadata objects.

1. Open the Maintenance app and find the type of metadata object you want to modify.

2. In the object list, click the context menu and select Sharing settings.

3. (Optional) Add users or user groups: search for a user or a user group and select it. The user or user group is added to the list.

4. Altere as configurações de compartilhamento dos grupos de acesso que você deseja modificar.

   • Can edit and view: The access group can view and edit the object.

   • ** Pode visualizar apenas **: O grupo de acesso pode visualizar o objeto.

   • No access (only applicable to Public access): The public won't have access to the object.

5. Change data sharing settings for the access groups you want to modify.

   • Can capture data: The access group can view and capture data for the object.

   • Can view data: The access group can view data for the object.

   • No access: The access group won't have access to data for the object.

6. Clique em ** Fechar **.

Excluir objetos de metadados¶

Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

1. Open the Maintenance app and find the type of metadata object you want to delete.

2. Na lista de objetos, clique no menu de opções e selecione ** Excluir **.

3. Clique em ** Confirmar **.

Exibir detalhes de objetos de metadados¶

1. Open the Maintenance app and find the type of metadata object you want to view.

2. In the object list, click the options menu and select Show details.

Traduzir objetos de metadados¶

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

1. Open the Maintenance app and find the type of metadata object you want to translate.

2. Na lista de objetos, clique no menu de opções e selecione ** Traduzir **.

   Tip

   If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

3. Selecione um local.

4. Digite um ** Nome **, ** Nome curto ** e ** Descrição **.

5. Clique em Salvar.

Gerenciar conjuntos de dados e formulários de entrada de dados¶

Sobre conjuntos de dados e formulários de entrada de dados¶

All data entry in DHIS2 is organised in data sets. A data set is a collection of data elements grouped together for data entry and data export between instances of DHIS2. To use a data set to collect data for a specific organisation unit, you must assign the organisation unit to the data set. Once you have assigned the data set to an organisation unit, that data set is available in the Data entry app. Only the organisation units that you have assigned the data set to can use the data set for data entry.

A category combination can link to both data elements and data sets. If you use a category combination for a data set, the category combinations is applicable for the whole form. This means that you can use categories to capture information which is common to an entire form, for example the name of the a project or grant. When a data set is linked to a category combination, those categories will be displayed as drop-down boxes in the Data entry app. Data captured in the form will then be linked to the selected category options from those drop-down boxes. For information about how to create categories and category combinations, see section "Manage data elements and categories". Make sure that you set the type of categories and category combinations to "Attribute".

A scenario for when categories are useful is when you need to capture a data entry form for an implementing partner organisation and a project. In that case:

1. Create category options and categories for all partner organisations and projects and link them in a new category combination.

2. Assign the category combination to the data set (form) for which you need to capture this information.

   When opening this data set in data entry module, the partner organisation and project categories will automatically be rendered as drop-down boxes, allowing you to select a specific implementing partner organisation and project before continuing to do data entry.

You create and edit data sets in the Maintenance app. Here you define, for example, which data elements you want to include in the data set and the data collection frequency.

You enter data in the Data entry app. The Data entry app uses data entry forms to display the data sets. There are three types of data entry forms:

Note

If a data set has both a section form and a custom form, the system displays the custom form during data entry. Users who enter data can't select which form they want to use. In web-based data entry the order of display preference is:

1. Custom form (if it exists)

2. Section form (if it exists)

3. Default form

Mobile devices do not support custom forms. In mobile-based data entry the order of display preference is:

1. Section form (if it exists)

2. Default form

No aplicativo ** Manutenção **, você gerencia os seguintes objetos de conjunto de dados:

Fluxo de Trabalho¶

You need to have data elements and categories to create data sets and data entry forms.

1. Crie um conjunto de dados.

2. Atribua o conjunto de dados às unidades de organização.

   Um formulário padrão é criado automaticamente.

3. Crie um formulário de seção ou um formulário personalizado.

   Agora você pode registrar dados no aplicativo ** Entrada de dados **.

Crie ou edite um conjunto de dados¶

1. Abra o aplicativo ** Manutenção ** e clique em ** Conjunto de dados ** > ** Conjunto de dados **.

2. Clique no botão adicionar.

3. No campo ** Nome **, digite o nome preciso do conjunto de dados.

4. No campo ** Nome abreviado **, defina um nome abreviado para o conjunto de dados.

   Typically, the short name is an abbreviation of the full data set name. This attribute is often used to display the name of the data set where space is limited.

5. (Opcional) No campo ** Código **, atribua um código.

6. No campo ** Descrição **, digite uma descrição do conjunto de dados.

7. Insira o número de ** Dias de expiração **.

   The number of expiry days controls for how long it should be possible to enter data in the Data entry app for this data set. Expiry days refer to the number of days after the end date of the selected data entry period where the data entry form should be open for entry. After the number of days has expired, the data set will be locked for further entry.

   You can set manual exceptions to this using the lock exception functionality in the Data Administration app.

   Note

   To allow data entry into all possible historical time periods, set the number of expiry days to zero.

8. If you want it to be possible to enter data for future periods, type the number of periods in the Open future periods for data entry field.

   The value is the number of future periods which are available for data entry.

   For a monthly data set a value of 2 allows you to enter data for 2 months in advance. This is useful for, by example, population, target and planning data.

9. In the Days after period to qualify for timely submission field, type the number of days in which data can be entered to be considered reported on time.

   To verify the number of timely reports submitted, go to Reports > Reporting rate summary.

10. Selecione um ** Tipo de período **.

    The period type defines the frequency of reporting for the particular data set. The frequency can for example be daily, quarterly or yearly.

11. Selecione uma ** Combinação de categoria ** para atribuí-la ao conjunto de dados.

    Tip

    Click Add new to create category combinations that you're missing. In the form that opens, create the category combinations you need. When you're done, click Refresh values.

12. If you selected a category combination other than None, you may enter zero or a positive number for Open periods after category option end date. This lets you enter data in this data set for a category option up to the specified number of periods after that category option's end date.

13. In the Complete notification recipients list, select a user group that should receive a message when the data set is marked as complete in the Data Entry app.

    A mensagem é entregue por meio do sistema de mensagens DHIS2.

14. If you want the user who entered the data to receive a message when the data set is marked as complete in the Data entry app, select Send notification to completing user.

    A mensagem é entregue por meio do sistema de mensagens DHIS2.

15. Se aplicável, selecione um ** Fluxo de trabalho de aprovação de dados **.

16. If you want it to be possible to use the data set within the Java mobile DHIS2 application, select Enable for Java mobile client.

17. If you want it to be mandatory to fill all values for a data element in data entry if one or more values have been filled, select All fields for data elements required.

    This means that if you enter one data value for a data element in an entry field (that is for a category option combination), then you must enter data for all fields belonging to that data element (that is all category option combinations).

18. If you want it to be possible to mark a data entry form as complete only if the validation of that form is successful, select Complete allowed only if validation passes.

    If you select this option, you can't mark the form as complete if validation fails.

19. If you want it to be mandatory that any missing values require a comment to justify their absence, select Missing values requires comment on complete.

20. (Opcional) Atribua uma ou várias ** Legendas **.

21. Se aplicável, selecione ** Pular offline **.

    This option controls whether this data entry form should be downloaded and saved in the user's web browser. Normally you shouldn't select Skip offline. This is the default setting. If you have big forms which are rarely used you can consider selecting this option to speed up initial loading in the data entry module.

22. Se aplicável, selecione ** Decoração do elemento de dados **

    If you select this option, descriptions of data elements render in call-outs in downloaded data sets in offline mode in the Data entry app.

23. Se aplicável, selecione ** Renderizar seções como guias **.

    This option is only applicable for section forms. The option allows you to render each section as a tab above the data set. You can choose whether to render the tabs horizontally or vertically. This is useful for long data sets as it allows appropriate sections to be selected quickly without going through the entire form.

24. If applicable, select Add custom title/subtitle.

    This option allows you to add a title and/or subtitle to the dataset. You can choose whether to display the title and subtitle in the center, at line start or at line end. For security reasons, only basic styling and HTML link elements are allowed, specifically these tags: a for adding a link, u for underlining a text, and b, strong or em for styling text in bold format.

25. Se aplicável, selecione ** Renderizar verticalmente **.

    This option is only applicable for section forms that are multi-organisation unit forms.

26. Selecione os elementos de dados e atribua-os.

    You can override the category combination for each selected data set by clicking on the gear icon above the list of selected data elements. This allows you to utilize a specific category combination (disaggregation) within the current data set instead of the category combination associated directly with the data element itself.

27. Selecione indicadores e atribua-os.

28. In the organisation unit tree, select the organisation units you want to assign the data set to.

    Tip

    • Click Organisation unit level to select all organisation units that belong to a certain organisation level.

    • Click Organisation unit group to select all organisation units that belong to a certain organisation unit group.

29. Clique em Salvar.

You can now use the data set in the Data Entry app for the organisation units that you have assigned to and for periods according to the selected frequency (period type).

Criar ou editar notificação de conjunto de dados¶

1. Open the Maintenance app and click Data set > Data set notification.

2. Clique no botão adicionar.

O que enviar?¶

1. In the Name field, type the precise name of the data set notification.

2. (Opcional) No campo ** Código **, atribua um código.

3. Insira ** Conjuntos de dados **.

   These data sets will be associated to this notification. In case any of them is completed for a certain period and organisation unit, notification will be generated by the system.

   Note

   Nothing will happen if no data set is selected

4. Na seção ** Modelo de mensagem **, existem dois parâmetros.

   • Subject template subject of the notification sent in notification. It can have values from the list of variables available on the right side.

   • Message template actual message sent in notification. It can have values from the list of variables available on the right side.

   Note

   Subject is only relevant in case of Email and internal DHIS2 messages. It is ignored in case of SMS.

Quando enviar?¶

1. Data set notification trigger field determine when to send notification.

   • Data Set Completion will trigger notification as soon as data set is completed.

   • Schedule Days will schedule notification based on number days relative to scheduled date. Schedule date will be decided by Period associated with Data set.

     • Send notification as provides two different types of notifications

       • ** Resumo coletivo ** enviar notificação em modo resumido

       • Single notification sends notification in single mood

   Note

   Send notification as option is only available in case of scheduled notification. This option is set to default which is Single notification in case of completion notification

Quem enviar?¶

1. Notification recipient field determine recipients of the notification.

   • Organisation Unit contact will send notification to contact assigned to organisation unit which the data has been collected from.

   • UserGroup will send notification to all the member of the selected UserGroup.

   Note

   An internal DHIS2 message will be sent in case if recipient is UserGroup. Moreover user will also receive SMS/EMAIL if phone number and email address exist for that user and SMS/EMAIL notifications are enabled in SystemSettings

Substituir combinações de categorias de elementos de dados em um conjunto de dados¶

You can override which category combination to use for a data element within the context of a data set. This means that a data element can use different category combinations within different data sets. This is useful when you want to reuse a data element since you don't have to replicate the data element to allow multiple category combinations.

If different regions within your organisation unit hierarchy use different disaggregations, or if the disaggregations change over time, you can represent this by creating different data sets with the appropriate category combinations.

1. Abra o aplicativo ** Manutenção ** e clique em ** Conjunto de dados ** > ** Conjunto de dados **.

2. Na lista, encontre o conjunto de dados que deseja modificar.

3. Clique no menu de opções e selecione ** Editar **.

4. Vá para a seção de elementos de dados e clique no ícone de chave inglesa.

5. Selecione novas combinações de categoria e clique em ** Fechar **.

6. Clique em Salvar.

Editar elementos de dados obrigatórios em um conjunto de dados¶

You can add or remove data elements which will be marked as compulsory during data entry.

1. Abra o aplicativo ** Manutenção ** e clique em ** Conjunto de dados ** > ** Conjunto de dados **.

2. Na lista, encontre o conjunto de dados que deseja editar.

3. Clique no menu de opções e selecione ** Editar elementos de dados obrigatórios **.

4. Atribua os elementos de dados obrigatórios.

5. Clique em Salvar.

Baixe formulários de dados padrão em formato PDF¶

You can download a default data from in PDF format for offline data entry.

1. Abra o aplicativo ** Manutenção ** e clique em ** Conjunto de dados ** > ** Conjunto de dados **.

2. Na lista, encontre o objeto que deseja baixar.

3. Clique no menu de opções e selecione ** Obter PDF para entrada de dados **.

Gerenciar formulários de seção¶

Criar um formulário de seção¶

Section forms are separated automatically by data element category combinations, which produce a spreadsheet like data entry form for each section.

1. Abra o aplicativo ** Manutenção ** e clique em ** Conjunto de dados ** > ** Conjunto de dados **.

2. In the list, find the data set you want to create a section form for.

3. Clique no menu de opções e selecione ** Gerenciar seções **.

4. Clique no botão adicionar.

5. (Opcional) No campo ** Nome **, digite o nome da seção.

6. (Optional) In the Description field, type a description of the section.

7. (Optional) To display totals for rows in the section form during data entry, select Show row totals.

8. (Optional) To display totals for columns in the section form during data entry, select Show column totals.

9. (Optional) To prevent automatic grouping of data of data elements with the same category combo, select Disable automatic grouping of data elements. This is useful if you want the order of the data elements to be respected regardless of differing category combos.

10. Atribua elementos de dados à seção:

    1. (Opcional) Selecione um ** Filtro de combinação de categoria **.

       Note

       You can only use one category combination per section.

       Option	Description
       None	Displays all data elements that don't have a category combination.
       <No filter>	Displays all data elements.

    2. Select data elements and assign them.

11. (Optional) Sort the data elements within the section by using the up and down arrows to the left of the assigned data elements field.

12. Clique em Salvar.

13. Repeat add section steps for each section you want to have in your section form.

    In the Data Entry app you can now use the section form. The section form appears automatically when sections are available for the selected data set. Data sets which have section forms will automatically display the section form.

Note how each data element category has been separated into a separate section, and a data entry table has been automatically generated by the system. Use of section forms in combination with data element categories can drastically reduce the amount of time which is required to create data entry forms for data sets.

Editar um formulário de seção¶

1. Abra o aplicativo ** Manutenção ** e clique em ** Conjunto de dados ** > ** Conjunto de dados **.

2. In the list, find the data set you want to edit the section form for.

3. Clique no menu de opções e selecione ** Gerenciar seções **.

4. Na lista, encontre a seção que deseja editar.

5. Clique no menu de opções e selecione ** Editar **.

6. Edite a seção e clique em ** Salvar **.

7. Repita as etapas de edição da seção para cada seção que deseja editar.

Gerenciar campos cinza em um formulário de seção¶

You can disable data elements and category options for data entry. That means it won't be possible to enter data into these fields during data entry.

1. Abra o aplicativo ** Manutenção ** e clique em ** Conjunto de dados ** > ** Conjunto de dados **.

2. In the list, find the data set you want to edit the section form for.

3. Clique no menu de opções e selecione ** Gerenciar seções **.

4. Na lista, encontre a seção que deseja editar.

5. Clique no menu de opções e selecione ** Gerenciar campos cinza **.

6. Selecione quais campos você deseja desativar.

   Note

   If you've sections that contain data elements assigned to multiple category combinations, switch between the category combinations to view all fields.

7. Clique em Salvar.

Alterar a ordem de exibição da seção em um formulário de seção¶

Você pode controlar em que ordem as seções são exibidas em um formulário de seção.

1. Abra o aplicativo ** Manutenção ** e clique em ** Conjunto de dados ** > ** Conjunto de dados **.

2. In the list, find the data set you want to edit the section form for.

3. Clique no menu de opções e selecione ** Gerenciar seções **.

4. Na lista, encontre a seção que deseja mover.

5. Clique no menu de opções e selecione ** Mover para cima ** ou ** Mover para baixo **.

   If the section you want to move is the first or last section in the list, you'll only see one of the move options.

Excluir uma seção em um formulário de seção¶

1. Abra o aplicativo ** Manutenção ** e clique em ** Conjunto de dados ** > ** Conjunto de dados **.

2. In the list, find the data set you want to edit the section form for.

3. Clique no menu de opções e selecione ** Gerenciar seções **.

4. Na lista, encontre a seção que deseja excluir.

5. Clique no menu de opções e selecione ** Excluir **.

Traduzir uma seção em um formulário de seção¶

1. Abra o aplicativo ** Manutenção ** e clique em ** Conjunto de dados ** > ** Conjunto de dados **.

2. In the list, find the data set you want to edit the section form for.

3. Clique no menu de opções e selecione ** Traduzir **.

4. Selecione um local.

5. Insira as informações necessárias.

6. Clique em ** Fechar **.

Form Configuration options¶

In version 41, we have added extra form configuration options that change how a section form is displayed in the new Data Entry App (beta). These options allow users to apply functionality that was not possible before without custom forms. We will be adding more options in the future releases.

The options available in v41 are:

Transpose (pivot) functionality¶

Users are able to choose to transpose (pivot) a form when displayed in the new Data Entry (beta) app. They are able to either fully transpose the form, i.e. move categories to be displayed as rows and data elements as columns, or move a certain category to be displayed as rows. The default display mode is for data elements to be displayed as rows and categories as columns.

Content before and after a section¶

Users are able to display custom text before and/or after a section. This is helpful for adding help text, for example. For security reasons, only basic styling and HTML link elements are allowed, specifically these tags: a for adding a link, u for underlining a text, b, strong for styling text in bold format, or em to style it in italic.

Gerenciar formulários personalizados¶

Crie um formulário personalizado¶

Note

Support for JavaScript in custom forms has changed in the new version of the Data Entry app. See Support for JavaScript in custom forms for details.

You design custom forms in a built-in WYSIWYG HTML editor. If you select Source, you can paste HTML code directly in the editing area. For a complete guide on how to use the editor, refer to http://docs.ckeditor.com/.

Para criar um formulário personalizado:

1. Abra o aplicativo ** Manutenção ** e clique em ** Conjunto de dados **.

2. Na lista, encontre o conjunto de dados ao qual deseja adicionar um formulário personalizado.

3. Clique no menu de opções e selecione ** Formulário de entrada de dados do projeto **.

4. Na área de edição, crie o formulário personalizado.

   • Double-click on a object in the left-hand list to insert it in the form.

   • If you already have the HTML code for your form, click Source and paste the code.

5. Selecione um ** Estilo de exibição de formulário **.

6. Clique em Salvar.

Criação de scripts em formulários personalizados¶

In custom data entry form you can use JavaScript to create dynamic behaviour and customizations. As an example, you can hide form sections based on specific user input for data elements, or show specific information when a form loads.

Eventos¶

The DHIS2 data entry module provides a range of events which you can register for and use to perform actions at certain times. The events are registered on the document element. The jQuery event object and the data set identifier are always the first two arguments provided to the callback functions. The table below provides an overview of the events and when they are triggered.

Para se inscrever em um evento:

<script type="text/javascript">

dhis2.util.on( 'dhis2.de.event.formReady', function( event, ds ) {
  console.log( 'The form with id: ' + ds + ' is loaded!' );
} );

dhis2.util.on( 'dhis2.de.event.dataValueSaved', function( event, ds, dv ) {
  console.log( 'Data value: ' + dv.value + ' was saved with data element: ' + dv.de );
} );

dhis2.util.on( 'dhis2.de.event.completed', function( event, ds, cr ) {
  console.log( 'Form was completed for org unit: ' + cr.ou );
} );

</script>

Note

Be careful to only use "namespaced" events like the ones in the example above and not general ones like "click" as the dhis2.util.on method will deregister the event first.

If your function only applies to certain data sets you can use the supplied data set identifier and shortcut your function for unwanted data sets like this:

dhis2.de.on( 'dhis2.de.event.validationSuccess', function( event, ds ) {
  if ( $.inArray( ds, ['utXOiGbEj14', 'Re7qzHEThSC'] ) == -1 ) {
    return false;
  }
  console.log( 'Form with id: ' + ds + ' validated successfully!' );
} );

The identifiers of the input fields in the data entry form is on the format described below. This format can be used to select the input fields in your script and perform actions on them:

<dataelementid>-<optioncomboid>-val

Since the data set identifier is provided for all events a feasible alternative is to utilize the "files" Web API resource and keep your callback functions in a single file, where you let the JavaScript code take action based on which data set is currently loaded.

Funções¶

The DHIS2 data entry module contains JavaScript API functions which can be accessed from custom data entry forms.

dhis2.de.api.getSelections: This function returns a JavaScript object which contains properties for all dimensions with corresponding values for the identifiers of the selected options. It contains properties for "ds" (data set), "pe" (period), "ou" (organisation unit) and identifiers for all data set categories.

Um exemplo de resposta é o seguinte:

{
 +  ds: "lyLU2wR22tC",
 +  pe: "201605",
 +  ou: "g8upMTyEZGZ",
 +  LFsZ8v5v7rq: "CW81uF03hvV",
 +  yY2bQYqNt0o: "yMj2MnmNI8L"
 +}

Exemplo de uso de JavaScript desta função:

var sel = dhis2.de.api.getSelections();
 +var orgUnit = sel["ou"];
 +var partner = sel["LFsZ8v5v7rq"];

Alterar as configurações de compartilhamento para objetos de metadados¶

You can assign different sharing settings to metadata objects, for example organisation units and tracked entity attributes. These sharing settings control which users and users groups that can view or edit a metadata object.

Some metadata objects also allows you to change the sharing setting of data entry for the object. These additional settings control who can view or enter data in form fields using the metadata.

Note

The default setting is that everyone (Public access) can find, view and edit metadata objects.

1. Open the Maintenance app and find the type of metadata object you want to modify.

2. In the object list, click the context menu and select Sharing settings.

3. (Optional) Add users or user groups: search for a user or a user group and select it. The user or user group is added to the list.

4. Altere as configurações de compartilhamento dos grupos de acesso que você deseja modificar.

   • Can edit and view: The access group can view and edit the object.

   • ** Pode visualizar apenas **: O grupo de acesso pode visualizar o objeto.

   • No access (only applicable to Public access): The public won't have access to the object.

5. Change data sharing settings for the access groups you want to modify.

   • Can capture data: The access group can view and capture data for the object.

   • Can view data: The access group can view data for the object.

   • No access: The access group won't have access to data for the object.

6. Clique em ** Fechar **.

Excluir objetos de metadados¶

Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

1. Open the Maintenance app and find the type of metadata object you want to delete.

2. Na lista de objetos, clique no menu de opções e selecione ** Excluir **.

3. Clique em ** Confirmar **.

Exibir detalhes de objetos de metadados¶

1. Open the Maintenance app and find the type of metadata object you want to view.

2. In the object list, click the options menu and select Show details.

Traduzir objetos de metadados¶

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

1. Open the Maintenance app and find the type of metadata object you want to translate.

2. Na lista de objetos, clique no menu de opções e selecione ** Traduzir **.

   Tip

   If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

3. Selecione um local.

4. Digite um ** Nome **, ** Nome curto ** e ** Descrição **.

5. Clique em Salvar.

Gerenciar indicadores¶

Sobre indicadores¶

An indicator is a formula that can consist of multiple data elements, constants, organisation unit group counts and mathematical operators. The indicator consist typically of a numerator and denominator. You use indicators to calculate coverage rates, incidence and other values that are a result of data element values that have been entered into the system. Calculated totals do not have a denominator.

** Nota **

Você nunca insere os valores do indicador diretamente no DHIS2, você os calcula.

An indicator formula can consist of mathematical operators, for example plus and minus; functions (see below); and of the following elements:

Você pode usar as seguintes funções em uma fórmula de indicador:

Valid aggregation types:

Examples of .aggregationType, .maxDate, .minDate, and .periodOffset functions:

Indicator SubExpressions¶

When fetching data for a data element, indicators usually aggregate the data before evaluating it in the expression. For example, consider the indicator expression:

if( #{nYahlae7fe6} > 10, 1, 0 )

If the data element has aggregation type SUM, this will sum all the values of the data element nYahlae7fe6 for the relevant period and then test to see if the sum is greater than 10. It will return 1 if the sum of all the data element values is greater than 10, otherwise it will return 0.

Sometimes you may wish to evaluate a data value in an expression before aggregating it. For example, you may want to show at a district level how many facilities within the district have a data value greater than 10. This can be done by using the subExpression function as follows:

subExpression( if( #{nYahlae7fe6} > 10, 1, 0 ) )

This will test each data element value to see if it is greater than 10. If it is greater than 10, the if statement will return 1, otherwise 0. Then, assuming that data element nYahlae7fe6 has aggregation type SUM, it will sum the 1's and 0's, resulting in a count of how many data elements had a value greater than 10.

SubExpression notes:

1. An example such as the one above will sum the 1's and 0's only if the data element has an aggregation type of SUM. If the data element has a different aggregation type and you want to sum the 1's and 0's, you can override the aggregation type inside the subexpression by using the .aggregationType() function as follows:

   subExpression( if( #{nYahlae7fe6} > 10, 1, 0 ) ).aggregationType(SUM)

2. A SubExpression may reference only one data element, but it may reference it multiple times. For example:

   subExpression( if( #{nYahlae7fe6} > 10 && #{nYahlae7fe6} <= 20, 1, 0 ) )

3. A SubExpression may reference a data element with a category option combination and/or an attribute option combination, but it must be exactly the same reference each time. For example:

   subExpression( if( #{nYahlae7fe6.beec4Dewah8} > 10 && #{nYahlae7fe6.beec4Dewah8} <= 20, 1, 0 ) )

4. If you wish to evaluate an expression before aggregating that involves other types of data such as program data, or that involves more than one data element, category option combination or attribute option combination, you can use a Predictor to do so and store the result as a different data element. Then you can reference the predicted data element in an indicator or directly in analytics.

Indicator Year-to-date¶

Indicators can compute year-to-date values using the expression elements yearToDate(), [periodInYear], and [yearlyPeriodCount].

In the examples below, #{a} can be: #{dataElementUID}, or any valid indicator expression item that returns a data value such as #{dataElementUID.catOptionComboUid}, I{programIndicatorUID}, N{indicatorUID}, etc.

Notes on [yearlyPeriodCount]¶

For monthly periods, [yearlyPeriodCount] is always 12, for quarters is always 4, etc. There are two advantages of using [yearlyPeriodCount] rather than hard-coding numbers like 12 or 4:

1. For weekly periods [yearlyPeriodCount] will be 52 or 53 depending on the year. For biweekly periods it will be 26 or 27.

2. If the user chooses a different period type in analytics, [periodInYear] and [yearlyPeriodCount] will adjust accordingly. For example if monthly data is collected, the user can choose to report monthly where [periodInYear] is 1: Jan, 2: Feb, ..., and [yearlyPeriodCount] is 12; or the user can report quarterly where [periodInYear] is 1: Q1, 2: Q2, ..., and [yearlyPeriodCount] is 4.

Notes on missing data¶

.yearToDate() returns a value if there is any data in the year before or during the period. For example, if the values of #{a} are:

Jan: (no data)
Feb: 1
Mar: 2
Apr: (no data)
May: 3
Jun: (no data)

then the values of #{a}.yearToDate() are:

Jan: (no data)
Feb: 1
Mar: 3
Apr: 3
May: 6
Jun: 6

No aplicativo ** Manutenção **, você gerencia os seguintes objetos indicadores:

Fluxo de Trabalho¶

1. Crie tipos de indicadores.

2. Crie indicadores.

3. Crie grupos de indicadores.

4. Crie conjuntos de grupos de indicadores.

Crie ou edite um tipo de indicador¶

Indicator types define a factor that is applied during aggregation. Indicator values that are calculated during a data mart export or report table generation process will appear properly formatted, and will therefore not require an additional multiplier (for example 100 in the case of percent) for the values to appear correctly formatted.

Note

As of version 2.4 of DHIS2, the "Calculated data element" object has been deprecated. Instead, you can create a calculated data element by creating an indicator type with a factor of "1" and by setting the "Number" option to "Yes". The effect of setting the "Number" option to "Yes" will be that the indicator will effectively not have a denominator. You will therefore only be able to define a numerator, which will serve as the formula of the calculated data element.

1. Open the Maintenance app and click Indicator > Indicator type.

2. Clique no botão adicionar.

3. In the Name field, type the name of the indicator type, for example "Per cent", "Per thousand", "Per ten thousand".

4. Digite um ** Fator **.

   The factor is the numeric factor that will be multiplied by the indicator formula during the calculation of the indicator.

5. Clique em Salvar.

Crie ou edite um indicador¶

1. Open the Maintenance app and click Indicator > Indicator.

2. Clique no botão adicionar.

3. In the Name field, type the full name of the indicator, for example "Incidence of confirmed malaria cases per 1000 population".

4. In the Short name field, type an abbreviated name of the indicator, for example "Inc conf. malaria per 1000 pop".

   The short name must be less than or equal to 25 characters, including spaces.

5. (Opcional) No campo ** Código **, atribua um código.

   Em muitos países, os indicadores recebem um código.

6. (Opcional) No campo ** Cor **, atribua uma cor para reenviar o indicador.

7. (Opcional) No campo ** Ícone **, atribua um ícone para ilustrar o significado do indicador.

8. In the Description field, type a brief, informative description of the indicator and how it is calculated.

9. If you want to apply an annualization factor during the calculation of the indicator, select Annualized.

   Typically, an annualized indicator's numerator is multiplied by a factor of 12, and the denominator is for instance a yearly population figure. This allows for monthly coverage values to be calculated with yearly population figures.

10. Selecione o número de ** decimais na saída de dados **.

11. Selecione um ** tipo de indicador **.

    This field determines a factor that will automatically be applied during the calculation of the indicator. Possible choices are determined by the indicator types. For example, a "Percent" indicator will automatically be multiplied by a factor of 100 when exported to the data mart, so that it will display as a percentage.

12. (Opcional) Atribua uma ou várias ** Legendas **.

13. In the URL field, enter a link, for example a link to an indicator registry, where a full metadata description of the indicator can be made available.

14. (Optional) Enter a Category option combination for aggregate data export..

    You use this setting to map aggregated data exported as raw data to another server. Typically you do this type of data exchange mapping when you want to create anonymous aggregated data from patient data recorded in programs (event data).

15. (Optional) Enter an Attribute option combination for aggregate data export..

    You use this setting to map aggregated data exported as raw data to another server. Typically you do this type of data exchange mapping when you want to create anonymous aggregated data from patient data recorded in programs (event data).

16. If applicable, enter custom attributes values, for example Classification or Collection method.

    Note

    You create custom attributes in the Maintenance app: Other > Attributes.

17. Clique em ** Editar numerador **.

    1. Digite uma descrição clara do numerador.

    2. Define the numerator by double-clicking components in the right-hand field. The components then appears as part of the formula in the left-hand field. Add mathematical operators by double-clicking the icons below the left-hand field.

       You formula must be mathematically valid. This includes correct use of parentheses when necessary.

    3. Clique em ** Concluído ** para salvar todas as alterações no numerador.

18. Clique em ** Editar denominador **.

    1. Digite uma descrição clara do denominador.

    2. Define the denominator by double-clicking components in the right-hand field. The components then appears as part of the formula in the left-hand field. Add mathematical operators by double-clicking the icons below the left-hand field.

       You formula must be mathematically valid. This includes correct use of parentheses when necessary.

    3. Clique em ** Concluído ** para salvar todas as alterações no denominador.

19. If applicable, select compulsory indicator group sets, for example Human resources.

    Note

    You'll only see indicator group sets in this form if you've created them and set them to Compulsory.

    You create indicator group sets in the Maintenance app: Indicator > Indicator group set.

20. Clique em Salvar.

Crie ou edite um grupo de indicadores¶

1. Open the Maintenance app and click Indicator > Indicator group.

2. Clique no botão adicionar.

3. Digite um nome.

4. Selecione indicadores e atribua-os.

5. Clique em Salvar.

Criar ou editar um conjunto de grupos de indicadores¶

Indicator group sets create combined groups of similar indicators. For example, you might have a group of indicators called "Malaria" and "Leishmaniasis". Both of these groups could be combined into a group set called "Vector-borne diseases". Indicator groups sets are used during analysis of data to combine similar themes of indicators.

1. Open the Maintenance app and click Indicators > Indicator group.

2. Clique no botão adicionar.

3. Preencher o formulário:

   1. Nome
   2. Nome curto
   3. Código
   4. Descrição
   5. Obrigatório

4. Selecione grupos de indicadores e atribua-os.

   Available indicator groups are displayed in the left panel. Indicator groups that are currently members of the indicator group set are displayed in the right hand panel.

5. Clique em Salvar.

Clone metadata objects¶

Cloning a data element or other objects can save time when you create many similar objects.

1. Open the Maintenance app and find the type of metadata object you want to clone.

2. Na lista de objetos, clique no menu de opções e selecione ** Clonar **.

3. Modifique as opções que você deseja.

4. Clique em Salvar.

Alterar as configurações de compartilhamento para objetos de metadados¶

You can assign different sharing settings to metadata objects, for example organisation units and tracked entity attributes. These sharing settings control which users and users groups that can view or edit a metadata object.

Some metadata objects also allows you to change the sharing setting of data entry for the object. These additional settings control who can view or enter data in form fields using the metadata.

Note

The default setting is that everyone (Public access) can find, view and edit metadata objects.

1. Open the Maintenance app and find the type of metadata object you want to modify.

2. In the object list, click the context menu and select Sharing settings.

3. (Optional) Add users or user groups: search for a user or a user group and select it. The user or user group is added to the list.

4. Altere as configurações de compartilhamento dos grupos de acesso que você deseja modificar.

   • Can edit and view: The access group can view and edit the object.

   • ** Pode visualizar apenas **: O grupo de acesso pode visualizar o objeto.

   • No access (only applicable to Public access): The public won't have access to the object.

5. Change data sharing settings for the access groups you want to modify.

   • Can capture data: The access group can view and capture data for the object.

   • Can view data: The access group can view data for the object.

   • No access: The access group won't have access to data for the object.

6. Clique em ** Fechar **.

Excluir objetos de metadados¶

Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

1. Open the Maintenance app and find the type of metadata object you want to delete.

2. Na lista de objetos, clique no menu de opções e selecione ** Excluir **.

3. Clique em ** Confirmar **.

Exibir detalhes de objetos de metadados¶

1. Open the Maintenance app and find the type of metadata object you want to view.

2. In the object list, click the options menu and select Show details.

Traduzir objetos de metadados¶

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

1. Open the Maintenance app and find the type of metadata object you want to translate.

2. Na lista de objetos, clique no menu de opções e selecione ** Traduzir **.

   Tip

   If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

3. Selecione um local.

4. Digite um ** Nome **, ** Nome curto ** e ** Descrição **.

5. Clique em Salvar.

Gerenciar unidades de organização¶

Nesta seção, você aprenderá como:

• Create a new organisation unit and build up the organisation unit hierarchy

• Create organisation unit groups, group sets, and assign organisation units to them

• Modifique a hierarquia da unidade organizacional

Sobre unidades organizacionais¶

The organisation unit hierarchy defines the organisation structure of DHIS2, for example how health facilities, administrative areas and other geographical areas are arranged with respect to each other. It is the where dimension of DHIS2, similar to how periods represent the when dimension.

The organisation unit hierarchy is built up by parent-child relations. In DHIS2, each of these nodes is an organisation unit. A country might for example have eight provinces, and each province might have a number of districts as children. Normally, the lowest levels consist of facilities where data is collected. Data collecting facilities can also be located at higher levels, for example national or provincial hospitals. Therefore, you can create skewed organisation trees in DHIS2.

• Você só pode ter uma hierarquia organizacional ao mesmo tempo.

• Você pode ter qualquer número de níveis em uma hierarquia.

  Typically national organisation hierarchies in public health have four to six levels.

• You can create additional classifications by using organisation groups and organisation group sets.

  For example to create parallel administrative boundaries to the health care sector.

• It is recommended to use organisation unit groups to create a non-geographical hierarchy.

• An organisation unit can only be a member of a single organisation unit group within an organisation unit group set.

• An organisation unit group can be part of multiple organisation unit group sets.

• The organisation unit hierarchy is the main vehicle for data aggregation on the geographical dimension.

• When you close an organisation unit, you can't register or edit events to this organisation unit in the Capture app.

Important

You can change the organisation unit hierarchy after you've created it, even organisation units that collect data. However, DHIS2 always uses the latest hierarchy for data aggregation. So if you change the hierarchy, you loose the temporal representation of the hierarchy across time.

District A is sub-divided into District B and District C. Facilities which belonged to District A are reassigned to District B and C. Any historical data, which you entered before the split occurred, is still registered as belonging to District B and C, not to the obsolete District A.

In the Maintenance app, you manage the following organisation unit objects:

Fluxo de Trabalho¶

O fluxo de trabalho recomendado é:

1. Crie unidades de organização.

2. Crie grupos de unidades de organização.

3. Crie conjuntos de grupos de unidades de organização.

Crie ou edite uma unidade organizacional¶

You add organisation units to the hierarchy one by one, either as a root unit or as a child of a selected organisation unit. You can only have one root unit.

1. Open the Maintenance app and click Organisation unit > Organisation unit.

2. Clique no botão adicionar.

3. Select which organisation unit your new organisation unit will belong to:

   1. Clique em ** Unidade de organização pai **.

   2. In the organisation unit tree, locate the parent organisation unit and select it. Your selection is marked in yellow.

      Tip

      Click the arrows to expand the organisation unit tree.

   3. Clique em ** Selecionar **.

4. Insira um ** Nome ** da unidade organizacional.

   Cada unidade organizacional deve ter um nome exclusivo.

5. Insira um ** Nome abreviado ** para a unidade organizacional.

   Typically, the short name is an abbreviation of the full organisation unit name. This attribute is often used in reports to display the name of the organisation unit, where space is limited.

6. (Opcional) Atribua um ** Código **.

   Em muitos países, as unidades organizacionais recebem um código.

7. (Optional) Upload a / remove the Organisation unit image

8. (Opcional) Digite uma ** Descrição ** da unidade organizacional.

9. Selecione uma ** Data de abertura **.

   The opening dates control which organisation units that existed at a point in time, for example when analysing historical data.

10. Se aplicável, selecione uma ** Data de fechamento **.

11. In the Comment field, enter any additional information that you would like to add.

12. (Optional) In the URL field, enter a link to an external web site that has additional information about the organisation unit.

13. Insira as informações de contato:

    • Pessoa de contato

    • Endereço

    • O email

    • Número de telefone

14. (Opcional) Insira ** Latitude ** e ** Longitude **.

    You must have latitude and longitude values to create maps in the Maps app. Then your organisation units can be represented as points on a map, for example a health facility. Without this information, the Maps app will not work.

    It might be more efficient to import coordinates later as a batch job for all organisation units using the Import-Export app. You also use the Import-Export app to create polygons. A polygon is an organisation unit that represent an administrative boundary.

15. Se aplicável, selecione ** Conjuntos de dados ** e atribua-os.

    Note

    You control whether a user should be able to assign data sets to an organisation unit in the System Settings app:

    Open the System Settings app, click Access and select Allow assigning object to related objects during add or update.

16. Se aplicável, selecione ** Programas ** e atribua-os.

    Note

    You control whether a user should be able to assign programs to an organisation unit in the System Settings app:

    Open the System Settings app, click Access and select Allow assigning object to related objects during add or update.

17. If applicable, enter custom attributes values, for example HR identifier.

    Note

    You configure the custom attributes in the Maintenance app:

    Open the Maintenance app and click Other > Attribute.

18. Clique em Salvar.

Criar ou editar um grupo de unidades organizacionais¶

Organisation unit groups allow you to classify related organisation units into a common theme. You can for example group all organisation units that are hospitals in an Hospital group.

1. Open the Maintenance app and click Organisation unit > Organisation unit group.

2. Clique no botão adicionar.

3. Preencher o formulário:

   1. Name: Provide a precise, unique and descriptive name for the organisation unit group.

   2. Short name: The short name should be less than 25 characters. Typically, the short name is an abbreviation of the full organisation unit name. This attribute is used in certain places in DHIS2 where space is limited.

   3. Código

   4. Symbol: Select a symbol which will be used to display the organisation unit (points only) when the layer is displayed in the Maps app.

4. In the organisation tree, click the organisation units you want to add to the organisation unit group.

   You can locate an organisation unit in the tree by expanding the branches (click on the arrow symbol), or by searching for it by name.

   As unidades de organização selecionadas são exibidas em laranja.

5. Clique em Salvar.

Criar ou editar um conjunto de grupos de unidades organizacionais¶

Organisation unit group sets allows you to create additional classifications of organisation units. The group sets create new dimensions so that you can make a more detailed data analysis. You an easily filter, organise or aggregate data by groups within a group set.

• Você pode ter qualquer número de conjuntos de grupos de unidades de organização.

• The default organisation unit group sets are Type and Ownership.

• An organisation unit can only be a member of a single organisation unit group within an organisation unit group set.

• An organisation unit group can be part of multiple organisation unit group sets.

• You can define whether an organisation unit group set is compulsory or not, which will affect the completeness of the data. Compulsory means that all organisation units must be member of a group in that group set.

Note

In the Data integrity part of the Data administration app you can verify if you've accidentally assigned the same organisation unit to multiple groups within the same group set. In this app you also find information about organisation units that are not members of a compulsory organisation unit group set.

1. Open the Maintenance app and click Organisation unit > Organisation unit group set.

2. Clique no botão adicionar.

3. Preencha:

   1. Name: Provide a precise name for the organisation unit group set.

   2. Short name: Provide a short name for the organisation unit group set.

   3. Código

   4. Description: Describe what the organisation unit group set measures or captures.

4. If you want all organisation units to be members of a group within the group set, select Compulsory.

5. (Opcional) Selecione ** Dimensão de dados **.

   If you select **Data dimension**, the group set will be available to the analytics as another dimension, in addition to the standard dimensions of "Period" and "Organisation unit".
   

6. (Opcional) Selecione ** Incluir sub-hierarquia na análise **.

   If you select this, a sub-organisation unit will inherit the organisation unit group property from its closest "parent" organisation unit. Any property on the sub-organisation unit will override the inherit value.

   If an organisation unit have no associated organisation unit group, the organisation unit can inherit its closest parent's organisation unit group. If none of the parent organisation unit groups have an organisation unit group for a given org unit group set, the result will still be "blank", but if at least one parent has an organisation unit group, sub-organisation unit will inherit it.

   include subhierarchy in analytics" is enabled, which means the org units inherit their closest parents org unit group IF the org unit is white (no org unit group associated with it).

7. Selecione grupos de unidades de organização e atribua-os.

   In the left-hand list, you find the available organisation unit groups. Use the arrows to move selected groups between the two lists.

   If there are no organisation unit groups in the left-hand list, click Add new. In the form that opens, create the organisation units group you need. When you're done, click Refresh values.

   Note

   An organisation unit can only be a member of a single organisation unit group within an organisation unit group set.

8. Click Save.

You want to analyse data based on the ownership of the facilities. All facilities have an owner so you need to make sure that all organisation units get this classification. To do that you can use the Compulsory option:

1. Create a group for each ownership type, for example "MoH", "Private" and "Faith-based".

2. Atribua todas as instalações do banco de dados a um desses grupos.

3. Create an organisation unit group set called "Ownership" and select Compulsory.

4. Assign the organisation unit groups "MoH", "Private" and "Faith-based" to the "Ownership" organisation group set.

Group you organisation unit in two ways and aggregate data on these two parallel hierarchies

Use para agregar dados (apenas em aplicativos de análise)

An additional setting to the organisation unit group set, creates a dynamic "membership" to a organisation unit group set.

Você não muda a hierarquia da unidade organizacional

Escalável e dinâmico

Inclusão dinâmica de hierarquia

Classificação adicional dinâmica

Atribuir nomes a níveis de unidade organizacional¶

When you add children to an organisation unit, DHIS2 automatically creates a new organisation unit level if necessary. The system also assigns a generic name to this level, for example "Level 5". You can replace the generic name with a contextual name, for example "Country", "Province", "District" or "Health Facility". DHIS2 uses the contextual names anywhere levels are referred to, for example in the Maps app.

1. Open the Maintenance app and click Organisation unit > Organisation unit level.

   The loading time of the list depends on the depth of the organisation unit hierarchy tree.

2. Para os níveis de unidade de organização que você deseja modificar, digite um nome.

3. Selecione o número de níveis offline.

   Note

   You configure the default value in the System Settings app:

   Open the System Settings app, click General and select a level in the Max offline organisation unit levels list.

4. Clique em Salvar.

Mover unidades organizacionais dentro de uma hierarquia¶

You can move organisation units within in the hierarchy by changing the parent of a selected organisation unit.

1. Open the Maintenance app and click Organisation unit > Hierarchy operations.

2. In the left-hand hierarchy tree, select the organisation unit(s) you want to move.

   Note

   If the selected organisation unit is has sub-organisation units, all of them move to the new parent organisation unit.

3. In the right-hand hierarchy tree, select which organisation unit you want to move the selected organisation unit(s) to.

4. Click Move x organisation units, where x stands for the number of organisation units you have selected.

   Your changes are immediately reflected in the left-hand side hierarchy tree.

Fechar uma unidade organizacional¶

When you close an organisation unit, you can't register or edit events to this organisation unit in the Capture app.

1. Open the Maintenance app and click Organisation unit > Organisation unit.

2. Na lista de objetos, clique no menu de opções e selecione ** Editar **.

3. Selecione uma ** Data de fechamento **.

4. Clique em Salvar.

Clone metadata objects¶

Cloning a data element or other objects can save time when you create many similar objects.

1. Open the Maintenance app and find the type of metadata object you want to clone.

2. Na lista de objetos, clique no menu de opções e selecione ** Clonar **.

3. Modifique as opções que você deseja.

4. Clique em Salvar.

Alterar as configurações de compartilhamento para objetos de metadados¶

You can assign different sharing settings to metadata objects, for example organisation units and tracked entity attributes. These sharing settings control which users and users groups that can view or edit a metadata object.

Some metadata objects also allows you to change the sharing setting of data entry for the object. These additional settings control who can view or enter data in form fields using the metadata.

Note

The default setting is that everyone (Public access) can find, view and edit metadata objects.

1. Open the Maintenance app and find the type of metadata object you want to modify.

2. In the object list, click the context menu and select Sharing settings.

3. (Optional) Add users or user groups: search for a user or a user group and select it. The user or user group is added to the list.

4. Altere as configurações de compartilhamento dos grupos de acesso que você deseja modificar.

   • Can edit and view: The access group can view and edit the object.

   • ** Pode visualizar apenas **: O grupo de acesso pode visualizar o objeto.

   • No access (only applicable to Public access): The public won't have access to the object.

5. Change data sharing settings for the access groups you want to modify.

   • Can capture data: The access group can view and capture data for the object.

   • Can view data: The access group can view data for the object.

   • No access: The access group won't have access to data for the object.

6. Clique em ** Fechar **.

Excluir objetos de metadados¶

Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

1. Open the Maintenance app and find the type of metadata object you want to delete.

2. Na lista de objetos, clique no menu de opções e selecione ** Excluir **.

3. Clique em ** Confirmar **.

Exibir detalhes de objetos de metadados¶

1. Open the Maintenance app and find the type of metadata object you want to view.

2. In the object list, click the options menu and select Show details.

Traduzir objetos de metadados¶

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

1. Open the Maintenance app and find the type of metadata object you want to translate.

2. Na lista de objetos, clique no menu de opções e selecione ** Traduzir **.

   Tip

   If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

3. Selecione um local.

4. Digite um ** Nome **, ** Nome curto ** e ** Descrição **.

5. Clique em Salvar.

Manage validation rules¶

Sobre regras de validação¶

A validation rule is based on an expression. The expression defines a relationship between data element values. The expression forms a condition with certain logical criteria.

A expressão consiste em:

• Um lado esquerdo

• Um lado direito

• Uma operadora

A validation rule asserting that the total number of vaccines given to infants is less than or equal to the total number of infants.

The left and right sides must return numeric values.

In the Maintenance app, you manage the following validation rule objects:

Sobre janelas de correr¶

You can use sliding windows to group data across multiple periods as opposed to selecting data for a single period. Sliding windows have a size, that is to say, the number of days to cover, a starting point and an end point. The example below shows disease surveillance data:.

• The data in the orange section, selects data based on the current period. There is a threshold, which is calculated once for each week or period, and this is shown in the "Result" section.

• The data in the blue section is the sliding window. It selects data from the past 7 days. The "Result" shows the total number of confirmed cases of a disease.

• The validation rule makes sure users are notified when the total number of cases breaks the threshold for the period.

See also: How to use sliding windows when you're Creating or editing a validation rule.

Sobre grupos de regras de validação¶

A validation rule group allows you to group related validation rules. When you run a validation rule analysis, you can choose to run all of the validation rules in your system, or just the validation rules in one group.

Sobre notificações de validação¶

You can configure a validation rule analysis to automatically send notifications about validation errors to selected user groups. These messages are called validation notifications. They are sent via the internal DHIS2 messaging system.

You can send validation rule notifications as individual messages or as message summaries. This is useful, for example, if you want to send individual messages for high-priority disease outbreaks, and summaries for low-priority routine data validation errors.

About validation rule functions¶

You can use the following functions in a validation rule left side or right side:

Crie ou edite uma regra de validação¶

1. Open the Maintenance app and click Validation > Validation rule.

2. Clique no botão adicionar.

3. Digite um ** Nome **.

   O nome deve ser único entre as regras de validação.

4. (Opcional) No campo ** Código **, atribua um código.

5. (Opcional) Digite uma ** Descrição **.

6. Selecione uma ** Importância **: ** Alta **, ** Média ** ou ** Baixa **.

7. Selecione um ** Tipo de período **.

8. Select an Operator: Compulsory pair, Equal to, Exclusive pair, Greater than, Greater than or equal to or Not equal to.

   The Compulsory pair operator allows to require that data values must be entered for a form for both left and right sides of the expression, or for neither side. This means that you can require that if one field in a form is filled, then one or more other fields must also be filled.

   The Exclusive pair allows to assert that if any value exist on the left side then there should be no values on the right side (or vice versa). This means that data elements which compose the rule on either side should be mutually exclusive from each other, for a given time period / organisation unit /attribute option combo.

9. Crie o lado esquerdo da expressão:

   1. Clique em ** Lado esquerdo **.

   2. Select Sliding window if you want to view data relative to the period you are comparing. See also About validation rules.

   3. Select a Missing value strategy. This selection sets how the system evaluates a validation rule if data is missing.

      Option	Description
      Skip if any value is missing	The validation rule will be skipped if any of the values which compose the expression are missing. This is the default option. Always select this option you use the Exclusive pair or Compulsory pair operator.
      Skip if all values are missing	The validation rule will be skipped only if all of the operands which compose it are missing.
      Never skip	The validation rule will never be skipped in case of missing data, and all missing operands will be treated effectively as a zero.

   4. Type a Description.

   5. Build an expression based on the available data elements, program objects, organisation units, counts and constants.

      In the right pane, double-click the data objects you want to include in the expression. Combine with the mathematical operators located below the left pane.

   6. Click Save.

10. Crie o lado direito da expressão:

    1. Clique em ** Lado direito **.

    2. Select a Missing value strategy. This selection sets how the system evaluates a validation rule if data is missing.

       Option	Description
       Skip if any value is missing	The validation rule will be skipped if any of the values which compose the expression are missing. This is the default option. Always select this option you use the Exclusive pair or Compulsory pair operator.
       Skip if all values are missing	The validation rule will be skipped only if all of the operands which compose it are missing.
       Never skip	The validation rule will never be skipped in case of missing data, and all missing operands will be treated effectively as a zero.

    3. Select Sliding window if you want to view data relative to the period you are comparing. See also About validation rules.

    4. Type a Description.

    5. Build an expression based on the available data elements, program objects, organisation units, counts and constants.

       In the right pane, double-click the data objects you want to include in the expression. Combine with the mathematical operators located below the left pane.

    6. Click Save.

11. (Optional) Choose which Organisation unit levels this rule should be evaluated for. Leaving this empty will cause the validation rule to be evaluated at all levels.

12. (Optional) Click Skip this rule during form validation to avoid triggering this rule while doing data entry

13. Clique em Salvar.

Crie ou edite um grupo de regras de validação¶

1. Open the Maintenance app and click Validation > Validation rule group.

2. Clique no botão adicionar.

3. Digite um ** Nome **.

4. (Opcional) No campo ** Código **, atribua um código.

5. (Opcional) Digite uma ** Descrição **.

6. Double-click the Validation rules you want to assign to the group.

7. Clique em Salvar.

Crie ou edite uma notificação de validação¶

1. Open the Maintenance app and click Validation > Validation notification.

2. Clique no botão adicionar.

3. Digite um ** Nome **.

4. (Opcional) No campo ** Código **, atribua um código.

5. Selecione ** Regras de validação **.

6. Selecione ** Grupos de usuários destinatários **.

7. (Opcional) Selecione ** Notificar usuários apenas na hierarquia **.

   If you select this option, the system will filter the recipient users. (The system derives the recipient users from the recipient user groups.) The filter is based on which organisation unit the recipient user belongs to. The users linked to organisation units which are ancestors of the organisation unit where the violation took place will receive validation notifications. The system will ignore other users and these users won't receive validation notifications.

8. Crie o modelo de mensagem:

   1. Crie o ** modelo de assunto **.

      Double-click the parameters in the Template variables field to add them to your subject.

   2. Crie o ** modelo de mensagem **.

      Double-click the parameter names in the Template variables field to add them to your message.

9. Clique em Salvar.

Clone metadata objects¶

Cloning a data element or other objects can save time when you create many similar objects.

1. Open the Maintenance app and find the type of metadata object you want to clone.

2. Na lista de objetos, clique no menu de opções e selecione ** Clonar **.

3. Modifique as opções que você deseja.

4. Clique em Salvar.

Alterar as configurações de compartilhamento para objetos de metadados¶

You can assign different sharing settings to metadata objects, for example organisation units and tracked entity attributes. These sharing settings control which users and users groups that can view or edit a metadata object.

Some metadata objects also allows you to change the sharing setting of data entry for the object. These additional settings control who can view or enter data in form fields using the metadata.

Note

The default setting is that everyone (Public access) can find, view and edit metadata objects.

1. Open the Maintenance app and find the type of metadata object you want to modify.

2. In the object list, click the context menu and select Sharing settings.

3. (Optional) Add users or user groups: search for a user or a user group and select it. The user or user group is added to the list.

4. Altere as configurações de compartilhamento dos grupos de acesso que você deseja modificar.

   • Can edit and view: The access group can view and edit the object.

   • ** Pode visualizar apenas **: O grupo de acesso pode visualizar o objeto.

   • No access (only applicable to Public access): The public won't have access to the object.

5. Change data sharing settings for the access groups you want to modify.

   • Can capture data: The access group can view and capture data for the object.

   • Can view data: The access group can view data for the object.

   • No access: The access group won't have access to data for the object.

6. Clique em ** Fechar **.

Excluir objetos de metadados¶

Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

1. Open the Maintenance app and find the type of metadata object you want to delete.

2. Na lista de objetos, clique no menu de opções e selecione ** Excluir **.

3. Clique em ** Confirmar **.

Exibir detalhes de objetos de metadados¶

1. Open the Maintenance app and find the type of metadata object you want to view.

2. In the object list, click the options menu and select Show details.

Traduzir objetos de metadados¶

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

1. Open the Maintenance app and find the type of metadata object you want to translate.

2. Na lista de objetos, clique no menu de opções e selecione ** Traduzir **.

   Tip

   If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

3. Selecione um local.

4. Digite um ** Nome **, ** Nome curto ** e ** Descrição **.

5. Clique em Salvar.

Gerenciar atributos¶

Sobre atributos¶

You can use metadata attributes to add additional information to metadata objects. In addition to the standard attributes for each of these objects it may be useful to store information for additional attributes, for example the collection method for a data element.

No aplicativo ** Maintenance **, você gerencia os seguintes objetos de atributo:

Crie ou edite um atributo¶

1. Abra o aplicativo ** Manutenção ** e clique em ** Atributo **.

2. Clique no botão adicionar.

3. No campo ** Nome **, digite o nome do atributo.

   Cada atributo deve ter um nome único

4. (Opcional) No campo ** Código **, atribua um código.

5. Selecione um ** Tipo de valor **.

   If the value supplied for the attribute does not match the value type you will get a warning.

6. Selecione um ** Conjunto de opções **.

7. Selecione as opções desejadas, por exemplo:

   • Select Mandatory if you want an object to always have the dynamic attribute.

   • Select Unique if you want the system to enforce that values are unique for a specific object type.

8. Clique em Salvar.

   The dynamic attribute is now available for the objects you assigned it to.

Clone metadata objects¶

Cloning a data element or other objects can save time when you create many similar objects.

1. Open the Maintenance app and find the type of metadata object you want to clone.

2. Na lista de objetos, clique no menu de opções e selecione ** Clonar **.

3. Modifique as opções que você deseja.

4. Clique em Salvar.

Excluir objetos de metadados¶

Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

1. Open the Maintenance app and find the type of metadata object you want to delete.

2. Na lista de objetos, clique no menu de opções e selecione ** Excluir **.

3. Clique em ** Confirmar **.

Exibir detalhes de objetos de metadados¶

1. Open the Maintenance app and find the type of metadata object you want to view.

2. In the object list, click the options menu and select Show details.

Traduzir objetos de metadados¶

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

1. Open the Maintenance app and find the type of metadata object you want to translate.

2. Na lista de objetos, clique no menu de opções e selecione ** Traduzir **.

   Tip

   If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

3. Selecione um local.

4. Digite um ** Nome **, ** Nome curto ** e ** Descrição **.

5. Clique em Salvar.

Gerenciar constantes¶

Sobre constantes¶

Constants are static values which can be made available to users for use in data elements and indicators. Some indicators, such as "Couple year protection rate" depend on constants which usually do not change over time.

No aplicativo ** Maintenance **, você gerencia os seguintes objetos constantes:

Crie ou edite uma constante¶

1. Abra o aplicativo ** Manutenção ** e clique em ** Outro ** > ** Constante **.

2. Clique no botão adicionar.

3. No campo ** Nome **, digite o nome da constante.

4. (Optional) In the Short name field, type an abbreviated name of the constant.

5. (Opcional) No campo ** Código **, atribua um código.

6. In the Description field, type a brief, informative description of the constant.

7. No campo ** Valor **, defina o valor da constante.

8. Clique em Salvar.

   A constante agora está disponível para uso.

Clone metadata objects¶

Cloning a data element or other objects can save time when you create many similar objects.

1. Open the Maintenance app and find the type of metadata object you want to clone.

2. Na lista de objetos, clique no menu de opções e selecione ** Clonar **.

3. Modifique as opções que você deseja.

4. Clique em Salvar.

Alterar as configurações de compartilhamento para objetos de metadados¶

You can assign different sharing settings to metadata objects, for example organisation units and tracked entity attributes. These sharing settings control which users and users groups that can view or edit a metadata object.

Some metadata objects also allows you to change the sharing setting of data entry for the object. These additional settings control who can view or enter data in form fields using the metadata.

Note

The default setting is that everyone (Public access) can find, view and edit metadata objects.

1. Open the Maintenance app and find the type of metadata object you want to modify.

2. In the object list, click the context menu and select Sharing settings.

3. (Optional) Add users or user groups: search for a user or a user group and select it. The user or user group is added to the list.

4. Altere as configurações de compartilhamento dos grupos de acesso que você deseja modificar.

   • Can edit and view: The access group can view and edit the object.

   • ** Pode visualizar apenas **: O grupo de acesso pode visualizar o objeto.

   • No access (only applicable to Public access): The public won't have access to the object.

5. Change data sharing settings for the access groups you want to modify.

   • Can capture data: The access group can view and capture data for the object.

   • Can view data: The access group can view data for the object.

   • No access: The access group won't have access to data for the object.

6. Clique em ** Fechar **.

Excluir objetos de metadados¶

Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

1. Open the Maintenance app and find the type of metadata object you want to delete.

2. Na lista de objetos, clique no menu de opções e selecione ** Excluir **.

3. Clique em ** Confirmar **.

Exibir detalhes de objetos de metadados¶

1. Open the Maintenance app and find the type of metadata object you want to view.

2. In the object list, click the options menu and select Show details.

Traduzir objetos de metadados¶

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

1. Open the Maintenance app and find the type of metadata object you want to translate.

2. Na lista de objetos, clique no menu de opções e selecione ** Traduzir **.

   Tip

   If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

3. Selecione um local.

4. Digite um ** Nome **, ** Nome curto ** e ** Descrição **.

5. Clique em Salvar.

Gerenciar conjuntos de opções¶

Sobre conjuntos de opções¶

Option sets provide a pre-defined drop-down (enumerated) list for use in DHIS2. You can define any kind of options.

An option set called "Delivery type" would have the options: "Normal", "Breach", "Caesarian" and "Assisted".

Crie ou edite um conjunto de opções¶

Important

Option sets must have a code as well as a name. You can change the names but you can't change the codes. Both names and codes of all options must be unique, even across different option sets.

1. Abra o aplicativo ** Manutenção ** e clique em ** Outro ** > ** Conjunto de opções **.

2. Clique no botão adicionar.

3. Na guia ** Detalhes primários **, defina o conjunto de opções:

   1. No campo ** Nome **, digite o nome da constante.

   2. No campo ** Código **, atribua um código.

   3. Selecione um ** Tipo de valor **.

   4. Clique em Salvar.

4. Para cada opção necessária, execute as seguintes tarefas:

   1. Clique na guia ** Opções **.

   2. Clique no botão adicionar.

   3. Type a Name and a Code. Optionally also select a Color and an Icon which will be used for this option in the data capture apps.

   4. Classifique as opções por nome, código / valor ou manualmente.

   5. Clique em Salvar.

Crie ou edite um grupo de opções¶

You can group and classify options within an option set by using option groups. This way you can create a subset of options in an option set. The main purpose of this is to be able to filter huge option sets into smaller, related parts.

Options that are grouped can be hidden or shown together in the Capture app through program rules.

** Nota **

Você não pode alterar o ** Conjunto de opções ** selecionado em um ** grupo de opções ** depois de criado.

1. Abra o aplicativo ** Maintenance ** e clique em ** Other ** > ** Grupo de opções **.

2. Clique no botão adicionar.

3. Preencher o formulário:

   1. Nome
   2. Nome curto
   3. Código
   4. ** Conjunto de opções **

4. Depois de selecionar um ** Conjunto de opções **, você pode atribuir as ** Opções ** que deseja agrupar.

5. Clique em Salvar.

Criar ou editar um conjunto de grupo de opções¶

Option group sets allows you to categorise multiple option groups into a set. The main purpose of the option group set is to add more dimensionality to your captured data for analysis.

** Nota **

Você não pode alterar o ** Conjunto de opções ** selecionado em um ** Conjunto de grupos de opções ** depois de criado.

1. Abra o aplicativo ** Manutenção ** e clique em ** Outro ** > ** Conjunto de grupos de opções **.

2. Clique no botão adicionar.

3. Preencher o formulário:

   1. Nome
   2. Código
   3. Descrição
   4. ** Conjunto de opções **

   5. ** Dimensão de dados **

      If you select Data dimension, the group set will be available to the analytics as another dimension, in addition to the standard dimensions of "Period" and "Organisation unit".

4. Selecione grupos de opções e atribua-os.

Os grupos de opções disponíveis são exibidos no painel esquerdo. Os grupos de opções que são atualmente membros do conjunto de grupos de opções são exibidos no painel direito.

1. Clique em Salvar.

Clone metadata objects¶

Cloning a data element or other objects can save time when you create many similar objects.

1. Open the Maintenance app and find the type of metadata object you want to clone.

2. Na lista de objetos, clique no menu de opções e selecione ** Clonar **.

3. Modifique as opções que você deseja.

4. Clique em Salvar.

Alterar as configurações de compartilhamento para objetos de metadados¶

You can assign different sharing settings to metadata objects, for example organisation units and tracked entity attributes. These sharing settings control which users and users groups that can view or edit a metadata object.

Some metadata objects also allows you to change the sharing setting of data entry for the object. These additional settings control who can view or enter data in form fields using the metadata.

Note

The default setting is that everyone (Public access) can find, view and edit metadata objects.

1. Open the Maintenance app and find the type of metadata object you want to modify.

2. In the object list, click the context menu and select Sharing settings.

3. (Optional) Add users or user groups: search for a user or a user group and select it. The user or user group is added to the list.

4. Altere as configurações de compartilhamento dos grupos de acesso que você deseja modificar.

   • Can edit and view: The access group can view and edit the object.

   • ** Pode visualizar apenas **: O grupo de acesso pode visualizar o objeto.

   • No access (only applicable to Public access): The public won't have access to the object.

5. Change data sharing settings for the access groups you want to modify.

   • Can capture data: The access group can view and capture data for the object.

   • Can view data: The access group can view data for the object.

   • No access: The access group won't have access to data for the object.

6. Clique em ** Fechar **.

Excluir objetos de metadados¶

Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

1. Open the Maintenance app and find the type of metadata object you want to delete.

2. Na lista de objetos, clique no menu de opções e selecione ** Excluir **.

3. Clique em ** Confirmar **.

Exibir detalhes de objetos de metadados¶

1. Open the Maintenance app and find the type of metadata object you want to view.

2. In the object list, click the options menu and select Show details.

Traduzir objetos de metadados¶

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

1. Open the Maintenance app and find the type of metadata object you want to translate.

2. Na lista de objetos, clique no menu de opções e selecione ** Traduzir **.

   Tip

   If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

3. Selecione um local.

4. Digite um ** Nome **, ** Nome curto ** e ** Descrição **.

5. Clique em Salvar.

Gerenciar lendas¶

Sobre lendas¶

You can create, edit, clone, delete, show details and translate legends to make the maps you're setting up for your users meaningful. You create maps in the Maps app.

Note

Continuous legends must consist of legend items that end and start with the same value, for example: 0-50 and 50-80. Do not set legend items like this: 0-50 and 51-80. This will create gaps in your legend.

Crie ou edite uma legenda¶

** Nota **

Não é permitido que haja lacunas em uma legenda.

Não é permitido ter itens de legenda sobrepostos.

1. Abra o aplicativo ** Maintenance ** e clique em ** Other ** > ** Legend **.

2. Clique no botão adicionar.

3. No campo ** Nome **, digite o nome da legenda.

4. (Opcional) No campo ** Código **, atribua um código.

5. Crie os itens de legenda que você deseja ter em sua legenda:

   1. Selecione ** Valor inicial ** e ** Valor final **.

   2. Selecione ** Número de itens de legenda **.

   3. Selecione um esquema de cores.

   4. Clique em ** Criar itens de legenda **.

   Tip

   Click the options menu to edit or delete a legend item.

6. (Opcional) Adicione mais itens de legenda:

   1. Clique no botão adicionar.

   2. Insira um nome e selecione um valor inicial, um valor final e uma cor.

   3. Clique OK.

7. (Opcional) Altere as escalas de cores.

   1. Click the colour scale to view a list of color scale options, and select a color scale.

   2. To customize a color scale, click the add button. In the Edit legend item dialog, click the color scale button and hand-pick colors, or enter your color values.

8. Clique em Salvar.

Clone metadata objects¶

Cloning a data element or other objects can save time when you create many similar objects.

1. Open the Maintenance app and find the type of metadata object you want to clone.

2. Na lista de objetos, clique no menu de opções e selecione ** Clonar **.

3. Modifique as opções que você deseja.

4. Clique em Salvar.

Alterar as configurações de compartilhamento para objetos de metadados¶

You can assign different sharing settings to metadata objects, for example organisation units and tracked entity attributes. These sharing settings control which users and users groups that can view or edit a metadata object.

Some metadata objects also allows you to change the sharing setting of data entry for the object. These additional settings control who can view or enter data in form fields using the metadata.

Note

The default setting is that everyone (Public access) can find, view and edit metadata objects.

1. Open the Maintenance app and find the type of metadata object you want to modify.

2. In the object list, click the context menu and select Sharing settings.

3. (Optional) Add users or user groups: search for a user or a user group and select it. The user or user group is added to the list.

4. Altere as configurações de compartilhamento dos grupos de acesso que você deseja modificar.

   • Can edit and view: The access group can view and edit the object.

   • ** Pode visualizar apenas **: O grupo de acesso pode visualizar o objeto.

   • No access (only applicable to Public access): The public won't have access to the object.

5. Change data sharing settings for the access groups you want to modify.

   • Can capture data: The access group can view and capture data for the object.

   • Can view data: The access group can view data for the object.

   • No access: The access group won't have access to data for the object.

6. Clique em ** Fechar **.

Excluir objetos de metadados¶

Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

1. Open the Maintenance app and find the type of metadata object you want to delete.

2. Na lista de objetos, clique no menu de opções e selecione ** Excluir **.

3. Clique em ** Confirmar **.

Exibir detalhes de objetos de metadados¶

1. Open the Maintenance app and find the type of metadata object you want to view.

2. In the object list, click the options menu and select Show details.

Traduzir objetos de metadados¶

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

1. Open the Maintenance app and find the type of metadata object you want to translate.

2. Na lista de objetos, clique no menu de opções e selecione ** Traduzir **.

   Tip

   If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

3. Selecione um local.

4. Digite um ** Nome **, ** Nome curto ** e ** Descrição **.

5. Clique em Salvar.

Atribuir uma legenda ao indicador ou elemento de dados¶

You can assign a legend to an indicator or a data element in the Maintenance app, either when you create the object or edit it. When you then select the indicator or data element in the Maps app, the system automatically selects the assigned legend.

Veja também¶

• Using the GIS app

Gerenciar preditores¶

Sobre preditores¶

A predictor defines how to generate an aggregate data value from an expression containing aggregate and/or event data. The predicted value may be based on:

• Data from the same period as the predicted value, and/or

• Data from periods previous to the predicted value

Data from the same period¶

A predictor can use data from the same period as the predicted value. For example, you can count the number of organisation units having a non-zero value of a data element by using a predictor expression such as:

if( #{ji7o0ILHuU2} != 0, 1, 0 )

When you run this predictor at the organisation unit level where the data is collected, it will store 1 as the predicted value if the data element has a nonzero value for that organisation unit, otherwise 0. (If the data element that you predict into does not store zeros, then zeros will not be stored in the database, to save space.) You can then sum this predicted value in analytics at a higher organisation unit level, to count the number of organisation units with a nonzero value that are under each organisation unit in the report.

Data from previous periods¶

A predictor will use data from previous periods when you specify an aggregation function such as sum() or avg(). For example, the following generator expression identifies a value that is the average plus twice the standard deviation of previous period data:

avg( #{ji7o0ILHuU2} ) + 2 * stddev( #{ji7o0ILHuU2} )

Data from the same and previous periods¶

A predictor expression can access data both from same period as the prediction and previous periods by accessing data both within an agregate function (for previous periods), and outside any aggregate function (for the same period). For example, an expression like the following can be used to take a balance of something from the previous period (#{KOh02hHko7C}), add to that the net change in this period (#{ji7o0ILHuU2}), resulting in the balance for this period:

sum( #{KOh02hHko7C} ) + #{ji7o0ILHuU2}

The first data value is inside an aggregate expression (sum) to indicate that it is sampling previous period data (even if there is only one previous period), while the second data value is not in an aggreate function to indicate that it is referencing data from the same period.

If you want to, a predictor's output data element can be referenced in the same predictor's expression. For instance, the expression in this example could be used to predict the balance in a period, and then combine that value with the change in the next period to compute the balance for the next period. When a predictor is run across multiple periods, the periods are processed in chronological order, and the result from an earlier period may be used as input for a later period.

Predictor organisation unit levels¶

You need to select one or more organisation unit levels for a predictor's output. All values generated by the predictor are stored for organisation units at the level(s) you select. Each item in the predictor expression is the sum of the value stored for that organisation unit (if any) plus any values stored in organisation units below that one (if any).

Note

In configuring a predictor, you must choose one or more organisation unit levels at which predicted data will be output. If no level is selected, no predicted values will be generated.

Warning

If you want to use the predicted values in analytics reporting, or to make other predictions, do not select more than one organisation unit level. When you select more than one level, predictions at the higher level(s) will also include any data used in lower level(s) predictions. If the predictions from multiple levels are subsequently used in analytics, or in the expressions of other predictors, this can result in double counting because the predicted values for a higher level include the predicted values from a lower level.

You may select multiple organisation unit levels if you use the predicted values only in validation rules. For example in disease surveillance, you could have a validation rule alert if an actual value is higher than the range of expected values for that period based on previous period data. To do this, you could create a predictor to compute the average plus twice the standard deviation of previous period data. You could use a validation rule to compare this higest expected value with the actual value. You could run the predictor and validation rule at multiple levels to detect different outbreak scenarios. In one scenario, there might be a significant increase in one facility that exceeds its expected range, but the district containing that facility might not exceed its expected range because the district values are combined with many other facilities. Yet in another scenario, there may be a moderate increase in several facilities that does not exceed the expected range for each facility (because the standard deviation for each facility may be high), but it does exceed the expected range for the district (because the standard deviation for the district as a whole may be lower).

If you want to generate predictions at multiple levels, you could also use different predictors at different levels. For example, you might want to be alerted if the value at one level exceeds the average plus twice the standard deviation, but alerted at another level if it exceeds the average plus 1.8 times the standard deviation. If you want, you could configure the different predictors to have the same output data element. If you use the same output data element, this will still work with validaiton rules at different organisaiton unit levels, but you also must be careful not to use the results in analytics or in other predictor calculations to avoid double counting.

No aplicativo ** Maintenance **, você gerencia os seguintes objetos preditores:

Sampling previous periods¶

Predictors can generate data values for periods that are in the past, present, or future. These values are based on data from the predicted period, and/or sampled data from periods previous to the predicted period.

If you need data only from the same period in which the prediction is made, then you don't need to read this section. This section describes how to sample data from periods previous to the predicted period.

Contagem de amostra sequencial¶

A predictor's Sequential sample count gives the number of immediate previous periods to sample. For example, if a predictor's period type is Weekly and the Sequential sample count is 4, this means to sample four previous weeks immediately preceding the predicted value week. So the predicted value for week 9 would use samples from weeks 5, 6, 7, and 8:

If a predictor's period type is Monthly and the Sequential sample count is 4, this means to sample four previous months immediately preceding the predicted value month. So the predicted value for May would use samples from weeks January, February, March, and April:

The Sequential sample count can be greater than the number of periods in a year. For example, if you want to sample the 24 months immediately preceding the predicted value month, set the Sequential sample count to 24:

Contagem de saltos sequenciais¶

A predictor's Sequential skip count tells how many periods should be skipped immediately previous to the predicted value period, within the Sequential sample count. This could be used, for instance, in outbreak detection to skip one or more immediately preceding samples that might in fact contain values from the beginning of an outbreak that you are trying to detect.

For example, if the Sequential sample count is 4, but the Sequential skip count is 2, then the two samples immediately preceding the predicted period will be skipped, resulting in only two periods being sampled:

Contagem de amostra anual¶

A predictor's Annual sample count gives the number of previous years for which samples should be collected at the same time of year. This could be used, for instance, for disease surveillance in cases where the expected incidence of the disease varies during the year and can best be compared with the same relative period in previous years. For example, if the Annual sample count is 2 (and the Sequential sample count is zero), then samples would be collected from periods in the immediately preceding two years, at the same time of year.

Contagens de amostras sequenciais e anuais juntas¶

You can use the sequential and annual sample counts together to collect samples from a number of sequential periods over a number of past years. When you do this, samples will be collected in previous years during the period at the same time of year as the predicted value period, and also in previous years both before and after the same time of year, as determined by the Sequential sample count number.

For example, if the Sequential sample count is 4 and the Annual sample count is 2, samples will be collected from the 4 periods immediately preceding the predicted value period. In addition samples will be collected in the previous 2 years for the corresponding period, as well as 4 periods on either side:

Contagens sequenciais, anuais e de amostra ignoradas juntas¶

You can use the Sequential skip count together with the sequential and annual sample counts. When you do this, the Sequential skip count tells how many periods to skip in the same year as the predicted value period. For example, if the Sequential sample count is 4 and the Sequential skip count is 2, then the two periods immediately preceding the predicted value period period will be skipped, but the two periods before that will be sampled:

If the Sequential skip count is equal to or greater than the Sequential sample count, then no samples will be collected for the year containing the predicted value period; only periods from past years will be sampled:

Teste de salto de amostra¶

You can use the Sample skip test to skip samples from certain periods that would otherwise be included, based on the results of testing an expression within those periods. This could be used, for instance, in disease outbreak detection, where the sample skip test could identify previous disease outbreaks, to exclude those samples from the prediction of a non-outbreak baseline expected value.

The Sample skip test is an expression that should return a value of true or false, to indicate whether or not the period should be skipped. It can be an expression that tests any data values in the previous period. For example, it could test for a data value that was explicitly entered to indicate that a previous period should be skipped. Or it could compare a previously predicted value for a period with the actual value recorded for that period, to determine if that period should be skipped.

Any periods for which the Sample skip test is true will not be sampled. For example:

Predictors and category option combinations (disaggregations)¶

The category option combination (disaggregation) for predictor output data is chosen in one of three ways:

1. Default category option combination.

If the predictor's output data element has no disaggregations (category combination "None", also known as the default category combination), then all predictor output data will be made in the default category option combination. In this case, predictor output data is not disaggregated.

1. Fixed category option combination

If the predictor's output data element has a category combination other than "None", you can choose a fixed disaggregation for the predictor "Output category option combo". If you do so, all output from this predictor will have this category option combination.

For example, if the output data element has a category combination of "Sex and Age", you can decide that all predictor output will go to a category option combination such as "Female under 5", "Male 5 - 10", or any other.

1. Use the input category option combo (available in v40.1 and following)

If the predictor's output data element has a category combination other than "None", you can choose "Predict according to input category option combo" as the value for "Output category option combo". If you do so, a different prediction is made for each category option combo in the output data element's category combination (that is, one prediction for "Female under 5", a second for "Male under 5", a third for "Female 5 - 10", and so on).

(In v40.1, this feature is enabled by selecting the choice "\<no value>" for "Output category option combo".)

> **Tip**
>
> In some installations, the options in a category may have changed over time.
For example, a category "Age" may have had three options "1-5", "6-10", and "over 10",
but then was changed to only have two options "10 and under" and "over 10".
Historical data may have values with any of these options.
To use a predictor with such data, you can define another category
such as "Reporting Age" with all the options ever used, such as "1-5", "6-10",
"10 and under", and "over 10". Use this category in the category combination
for the predictor's output data element. This means that all the input category
options will be reflected in the output.
>
> If you then want a single report for the output data that covers
all the disaggregations, you can use category option groups
in a category option group set. For example use a category option group
"10 and under" that contains category options "1-5", "6-10", and "10 and under".

Predictors and attribute option combinations¶

If the input data to a prediction has attribute option combinations, a different prediction will be made for each attribute option combination where there is data.

For example, you could use attribute option combinations to represent different projects on your system. The predictor will generate a value with the attribute option combination for Project A when it finds input data for Project A; it will generate a value with the attribute option combination for Project B when it finds input data for Project B; and so on.

For any input data without attribute option combinations (in other words, with the default attribute option combination), predictions are generated using the default attribute option combination. If you don't use attribute option combinations in the data, they will not be used in predictor output data.

If you use attribute option combinations and also "Predict according to input category option combo", there will be a separate prediction for each combination of disaggregation and attribute option combination. For example, there could be a prediction for Project A data for "Female under 5", a prediction for Project A data for "Male under 5", a prediction for Project B data for "Female under 5", and so on.

Crie ou edite um preditor¶

1. Abra o aplicativo ** Maintenance ** e clique em ** Other ** > ** Predictor **.

2. Clique no botão adicionar.

3. No campo ** Nome **, digite o nome do preditor.

4. (Opcional) No campo ** Código **, atribua um código.

5. (Opcional) Digite uma ** Descrição **.

6. Select an Output data element. Values generated by this predictor are stored as aggregate data associated with this data element and the predicted period.

   The value is rounded according to the value type of the data element: If the value type is an integer type, the predicted value is rounded to the nearest integer. For all other value types, the number is rounded to four significant digits. (However if there are more than four digits to the left of the decimal place, they are not replaced with zeros.)

7. (Optional) Select an Output category option combo. This dropdown will only show if the selected data element has a category combination other than "None". If so, you can select which disaggregation category option combo you would like to output to, or you can select "Predict according to input category option combo" (see the discussion above).

8. Selecione um ** Tipo de período **.

9. Assign one or more organisation unit levels. The output value will be assigned to an organisation unit at this level (or these levels). For aggregate data, the input values depends on the selection below; organisation units providing data. For tracker based data, the input values will come from the organisation unit to which the output is assigned, or from any level lower under the output organisation unit.

10. Organisation units providing data controls where the input values comes from for aggregate data. If "at selected levels only", only organisation units at the selected levels are included. If "At selected levels and all levels below" is selected, organisation units at the selected level(s) and all organisation units below are also included.

11. Crie um ** Gerador **. O gerador é a expressão usada para calcular o valor previsto.

    1. Digite uma ** Descrição ** da expressão geradora.

    2. Selecione uma ** Estratégia de valor ausente **. Esta seleção define como o sistema avalia uma regra de validação se houver dados ausentes.

       Opção	Descrição
       Pule se algum valor estiver faltando	A regra de validação será ignorada se algum dos valores que compõem a expressão estiver faltando. Esta é a opção padrão. Sempre selecione esta opção, você usa o operador ** Par exclusivo ** ou ** Par obrigatório **.
       Ignorar se todos os valores estiverem ausentes	A regra de validação será ignorada apenas se todos os valores que a compõem estiverem ausentes.
       Nunca pule	A regra de validação nunca será ignorada no caso de dados ausentes e todos os valores ausentes serão tratados efetivamente como zero.

    3. Insira a expressão do gerador. Você pode construir a expressão selecionando elementos de dados para dados agregados ou elementos de dados de programa, atributos ou indicadores. As contagens de unidades organizacionais ainda não são suportadas.

       Para usar dados de amostra de períodos anteriores, você deve incluir todos os itens selecionados em uma das seguintes funções de agregação (observe que esses nomes de função diferenciam maiúsculas de minúsculas):

       Aggregate function	Means
       avg(x)	Average (mean) value of x
       count(x)	Count of the values of x
       max(x)	Maximum value of x
       median(x)	Median value of x
       min(x)	Minimum value of x
       percentileCont(p, x)	Continuous percentile of x, where p is the percentile as a floating point number between 0 and 1. For example, p = 0 will return the lowest value, p = 0.5 will return the median, p = 0.75 will return the 75th percentile, p = 1 will return the highest value, etc. Continuous means that the value will be interpolated if necessary. For example, percentileCont( 0.5, #{FTRrcoaog83} ) will return 2.5 if the sampled values of data element FTRrcoaog83 are 1, 2, 3, and 4.
       stddev(x)	Standard deviation of x. This function is eqivalent to stddevSamp. It's suggested that you use the function stddevSamp instead for greater clarity.
       stddevPop(x)	Population standard deviation of x: sqrt( sum( (x - avg(x))^2 ) / n )
       stddevSamp(x)	Sample standard deviation of x: sqrt( sum( (x - avg(x))^2 ) / ( n - 1 ) ). Note that this value is not computed when there is only one sample.
       sum(x)	Sum of the values of x

       Note

       Any items inside an aggregate function will be evaluated for all sampled past periods, and then combined according to the formula inside the aggregate function. Any items outside an aggregate function will be evaluated for the period in which the prediction is being made.

       You can build more complex expressions by clicking on (or typing) any of the elements below the expression field: ( ) * / + - Days. Constant numbers may be added by typing them. The Days option inserts [days] into the expression which resolves to the number of days in the period from which the data came.

       You can also use the following non-aggregating functions in your expression, either inside aggregate functions, or containing aggregate functions, or independent of aggregate functions:

       Function	Means
       contains(expr, sub1, ...)	Searches an expression for one or more substrings. Returns true if the expression contains all the substrings. For example, the following are all true: contains("abcd", "abcd"); contains("abcd", "b"); and contains("abcd", "ab", "bc"). Comparisons are case-sensitive.
       containsItems(expr, item1, ...)	Searches an expression for one or more items. The expression is made up of comma-separated elements. containsItems returns true if every item exactly matches an element in the expression. For example, containsItems("abcd", "abcd") and containsItems("ab,cd", "ab", "cd") are true, but containsItems("abcd", "b") and containsItems("abcd", "ab", "bc") are false. Comparisons are case-sensitive. containsItems can be used for multi-valued data elements to see if an item is contained in the data element values.
       if(test, valueIfTrue, valueIfFalse)	Evaluates test which is an expression that evaluates to a boolean value -- see Boolean expression notes below. If the test is true, returns the valueIfTrue expression. If it is false, returns the valueIfFalse expression.
       is(expr1 in expression [, expression ...])	Returns true if expr1 is equal to any of the following expressions, otherwise false.
       isNull(item)	Returns the boolean value true if the item is null (missing), otherwise returns false. The item can be any selected item from the right (data element, program data element, etc.).
       isNotNull(item)	Returns true if the item value is not missing (not null), otherwise false.
       firstNonNull(item [, item ...])	Returns the value of the first item that is not missing (not null). Can be provided any number of arguments. Any argument may also be a numeric or string literal, which will be returned if all the previous items have missing values.
       greatest(expression [, expression ...])	Returns the greatest (highest) value of the expressions given. Can be provided any number of arguments.
       least(expression [, expression ...])	Returns the least (lowest) value of the expressions given. Can be provided any number of arguments.
       log(expression [, base ])	Returns the natural logarithm (base e) of the numeric expression. If an integer is given as a second argument, returns the logarithm using that base.
       log10(expression)	Returns the common logarithm (base 10) of the numeric expression.
       normDistCum(x [,mean [,stddev]])	Returns the cumulative distribution function (CDF) value for x given the normalized distribution described by the mean and stddev. Equivalent to Excel NORM.DIST(x,mean,stddev,TRUE) or LibreOffice NORMDIST(x,mean,stddev,1). If stddev is not given, it is computed from past sampled values of x. If neither mean nor stddev are given, they are computed from past sampled valeus of x. See examples.
       normDistDen(x [,mean [,stddev]])	Returns the probability density function (PDF) value for x given the normalized distribution described by the mean and stddev. Equivalent to Excel NORM.DIST(x,mean,stddev,FALSE) or LibreOffice NORMDIST(x,mean,stddev,0). If stddev is not given, it is computed from past sampled values of x. If neither mean nor stddev are given, they are computed from past sampled valeus of x. See examples.
       null	Returns no result. For example, if( #{FH8ab5Rog83}<0, null, 1 ) returns nothing if the data element value is less than 0, otherwise 1.
       orgUnit.ancestor(orgUnitUid [, orgUnitUid ...])	Returns true if the organisation unit is a descendant of any of the (1 or more) organisation units, otherwise false.
       orgUnit.dataSet(dataSetUid [, dataSetUid ...])	Returns true if the organisation unit is assigned to any of the (1 or more) data sets, otherwise false.
       orgUnit.group(ouGroupUid [, ouGroupUid ...])	Returns true if the organisation unit is a member of any of the (1 or more) organisation unit groups, otherwise false.
       orgUnit.program(programUid [, programUid ...])	Returns true if the organisation unit is assigned to any of the (1 or more) programs, otherwise false.
       removeZeros(expression)	Returns nothing if the expression value is 0, otherwise returns the expression value.
       .maxDate(yyyy-mm-dd)	For a data element (not program data), value from periods ending on or before a maximum date.
       .minDate(yyyy-mm-dd)	For a data element (not program data), value from periods starting on or after a minimum date.

       Boolean expression notes: A boolean expression must evaluate to true or false. The following operators may be used to compare two values resulting in a boolean expression: \<, >, !=, ==, >=, and \<=. The following operators may be used to combine two boolean expressions: && or the keyword and (logical and), and || or the keyword or (logical or). The unary operator ! or the keyword not may be used to negate a boolean expression.

       Generator expression examples:

       Generator expression	Means
       sum(#{FTRrcoaog83.tMwM3ZBd7BN})	Sum of the sampled values of data element FTRrcoaog83 and category option combination (disaggregation) tMwM3ZBd7BN
       avg(I{GSae40Fyppf}) + 2 * stddevSamp(I{GSae40Fyppf})	Average of the sampled values of of program indicator GSae40Fyppf plus twice its sample standard deviation
       sum(D{IpHINAT79UW.eMyVanycQSC}) / sum([days])	Sum of all sampled values of data element eMyVanycQSC from porgram IpHINAT79UW divided by the number of days in all sample periods (resulting in the overall average daily value)
       sum(#{FTRrcoaog83}) + #{T7OyqQpUpNd}	Sum of all sampled values of data element FTRrcoaog83 plus the value of data element T7OyqQpUpNd in the period being predicted for (includes all disaggregations)
       1.2 * A{IpHINAT79UW.RKLKz1H20EE}	1.2 times the value of attribute RKLKz1H20EE of program IpHINAT79UW, in the period being predicted for
       if(isNull(#{T7OyqQpUpNd}), 0, 1)	If the data element T7OyqQpUpNd is null in the period being predicted, then 0, otherwise 1
       if(is(#{jeiTh8ahyae} in 'NEGATIVE','UNKNOWN'), 0, 1)	If the data element jeiTh8ahyae has value 'NEGATIVE' or 'UNKNOWN' then 0, otherwise 1
       percentileCont(0.5, #{T7OyqQpUpNd})	Continuous 50th percentile of the sampled values for data element T7OyqQpUpNd. Note that this is the same as median(#{T7OyqQpUpNd})
       if(count(#{T7OyqQpUpNd}) == 1, 0, stddevSamp(#{T7OyqQpUpNd}))	If there is one sample value present for data element T7OyqQpUpNd, then 0, otherwise the sample standard deviation of these sample values. (Note that if no samples are present then the stddevSamp returns no value, so no value is predicted.)
       normDistCum(#{T7OyqQpUpNd})	The cumulative distribution function for the current period value of data element T7OyqQpUpNd based on the normalized distribution defined by the mean and standard deviation of past sampled periods of data element T7OyqQpUpNd
       normDistCum( #{T7OyqQpUpNd}, median(#{T7OyqQpUpNd}) )	The cumulative distribution function for the current period value of data element T7OyqQpUpNd based on the distribution defined by the median (instead of the mean) and standard deviation of past sampled periods of data element T7OyqQpUpNd
       normDistCum( #{T7OyqQpUpNd}, median(#{T7OyqQpUpNd}) )	The cumulative distribution function for the current period value of data element T7OyqQpUpNd based on the distribution defined by the median (instead of the mean) and standard deviation of past sampled periods of data element T7OyqQpUpNd
       normDistCum( #{T7OyqQpUpNd}, avg(#{T7OyqQpUpNd}), stddev(#{T7OyqQpUpNd}) )	Same as normDistCum( #{T7OyqQpUpNd} )
       normDistDen( #{T7OyqQpUpNd}, avg(#{IKahz1Quie3}), stddev(#{IKahz1Quie3}) )	The probability density function for the current period value of data element T7OyqQpUpNd based on the distribution defined by the mean and standard deviation of past sampled periods of the different data element IKahz1Quie3
       normDistDen( median(#{T7OyqQpUpNd}), avg(#{IKahz1Quie3}), stddev(#{IKahz1Quie3}) )	The probability density function for the median of past sampled values of data element T7OyqQpUpNd based on the distribution defined by the mean and standard deviation of past sampled periods of the different data element IKahz1Quie3
       #{T7OyqQpUpNd}.minDate(2022-10-1)	Value on or after 1-Oct-2022
       #{T7OyqQpUpNd}.maxDate(2022-12-31)	Value on or before 31-Dec-2022
       #{T7OyqQpUpNd}.minDate(2022-10-1).maxDate(2022-12-31)	Value bewteen 1-Oct-2022 and 31-Dec-2022

12. (Optional) Create a Sample skip test. The sample skip test tells which previous periods if any to exclude from the sample.

    1. Digite uma ** Descrição ** do teste de salto.

    2. Enter the sample skip test expression. You can build the expression by selecting data elements for aggregate data, or program data elements, attributes or indicators. Organisation unit counts are not yet supported. As with the generator function, you may click on (or type) any of the elements below the expression field: ( ) * / + - Days.

       The non-aggregating functions described above for generator expressions may also be used in skip tests.

       The expression must evaluate to a boolean value of true or false. See Boolean expression notes above.

       Pule os exemplos de expressão de teste:

       Skip test expression	Means
       #{FTRrcoaog83} > #{M62VHgYT2n0}	The value of data element FTRrcoaog83 (sum of all disaggregations) is greater than the value of data element M62VHgYT2n0 (sum of all disaggregations)
       #{uF1DLnZNlWe} > 0	The value of data element uF1DLnZNlWe (sum of all disaggregations) is greater than the zero
       #{FTRrcoaog83} > #{M62VHgYT2n0} || #{uF1DLnZNlWe} > 0	The value of data element FTRrcoaog83 (sum of all disaggregations) is greater than the value of data element M62VHgYT2n0 (sum of all disaggregations) or the value of data element uF1DLnZNlWe (sum of all disaggregations) is greater than the zero

13. Insira um valor de ** Contagem de amostra sequencial **.

    This is for how many sequential periods the calculation should go back in time to sample data for the calculations.

14. Insira um valor de ** Contagem de amostra anual **.

    This is for how many years the calculation should go back in time to sample data for the calculations.

15. (Opcional) Insira um valor de ** Contagem sequencial de pulos **.

    This is how many sequential periods, immediately preceding the predicted value period, should be skipped before sampling the data.

16. Clique em Salvar.

Predictions by Data Element Group¶

You can use a single predictor to operate on all the data elements in a group instead of a different predictor for each data element. This can be used, for example, in logistics management when a data element is used for each commodity and a category option combination is used for each count related to that commodity.

The syntax is:

forEach ?de in :DEG:degUid --> main expression

where:

The predictor will execute once for each data element in the data element group. For each data element, instances of the variable in the main expression are replaced by that data element. The same data element is also used as the predictor output data element. The predicted value will be written to that data element using the configured output category option combination.

The predictor must be configured with an output data element, but it is effectively ignored when the predictor is run. It is suggested that you configure the predictor with one of the data elements in the data element group that the predictor will use. That way you can select a valid output category option combination for that data element.

At the time the predictor is created, the data element group must contain at least one data element of the type that you will use. (The data type of the data element is used during syntax checking of the predictor.)

Example 1¶

You have data elements that represent various commodities, all belonging to a data element group with UID aIMu0nieph7.

You have category option combinations with the following UIDs:

The following predictor generator expression will compute the stock balance at the beginning of the next period as ( starting balance + restock - used - lost ):

forEach ?de in :DEG:aIMu0nieph7 -->
sum( #{?de.Gvoecom5muL} + #{?de.CWa6eew5uco} - #{?de.nthohhie8Ba} - #{?de.Faey8Iphooy} )

The predictor configuration includes:

The predictor will execute once for each data element in the data element group. Because the aggregation function sum() is used in the predictor generator expression, all the values in the expression will be fetched from the previous period (since the sequential sample count is 1). The predictor will write out the starting balance for each data element for the periods within the predictor run start and end date, for organisation units at the selected level(s).

Predictions are always made forward through time. The starting balance predicted for one period can be used as an input to compute the starting balance of the following period.

Example 2¶

If you want to make predictions for the same period as the input data, just omit the aggregation function such as sum(). Adding to the previous example, say you have another category option combination that computes the net inventory change during the period:

You can use the following expression to compute the inventory change as ( restock - used - lost ):

forEach ?de in :DEG:aIMu0nieph7 -->
#{?de.CWa6eew5uco} - #{?de.nthohhie8Ba} - #{?de.Faey8Iphooy}

The output category option combo is:

Since there is no aggregation function such as sum() around the expression elements, the input data is taken from the same period as the predictor output.

Criar ou editar um grupo de previsão¶

1. Open the Maintenance app and click Other > Predictor group.

2. Clique no botão adicionar.

3. Digite um ** Nome **. Este campo precisa ser único.

4. (Optional) In the Code field, assign a code. This field needs to be unique.

5. (Opcional) Digite uma ** Descrição **.

6. Clique duas vezes nos ** Preditores ** que deseja atribuir ao grupo.

7. Clique em Salvar.

Clone metadata objects¶

Cloning a data element or other objects can save time when you create many similar objects.

1. Open the Maintenance app and find the type of metadata object you want to clone.

2. Na lista de objetos, clique no menu de opções e selecione ** Clonar **.

3. Modifique as opções que você deseja.

4. Clique em Salvar.

Excluir objetos de metadados¶

Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

1. Open the Maintenance app and find the type of metadata object you want to delete.

2. Na lista de objetos, clique no menu de opções e selecione ** Excluir **.

3. Clique em ** Confirmar **.

Exibir detalhes de objetos de metadados¶

1. Open the Maintenance app and find the type of metadata object you want to view.

2. In the object list, click the options menu and select Show details.

Traduzir objetos de metadados¶

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

1. Open the Maintenance app and find the type of metadata object you want to translate.

2. Na lista de objetos, clique no menu de opções e selecione ** Traduzir **.

   Tip

   If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

3. Selecione um local.

4. Digite um ** Nome **, ** Nome curto ** e ** Descrição **.

5. Clique em Salvar.

Gerenciar relatórios push¶

Sobre relatórios push¶

Push reports allows you to increase awareness and usage of data analysis by sending reports with charts, tables and maps directly to users e-mail addresses.

• Um relatório push obtém seu conteúdo de painéis existentes.

• A push report lists the dashboard items in the same order as on the dashboard.

• A push report can only contain dashboard items with charts, maps or tables.

• You create the push report and its schedule in the Maintenance app.

• The Title and Message parameters you set up in the Maintenance app, are included in each report. The Name you give the report is not included in the report. Instead, the name is used to identify the push analysis object in the system. This way a report can be named one thing, and the title of the report can be another.

• When you run a push report job, the system compiles a list of recipients from the user groups you've selected. The system then generates a report for each member of the selected user groups. Each of the dashboard items are generated specifically for each user. This means that the data included in the report reflects the data the user has access to. All users could therefore get the same report (if all the data is "static") or custom reports (if all the data is "dynamic"), or a combination of the two.

• Push reports are sent by e-mail to the recipients, not through the internal DHIS2 messaging system. If a user doesn't have a valid e-mail, or if the job fails, no e-mails are sent. In this case, the problem is logged on the server.

Note

The data generated in the push reports is public so verify that you don't include any sensitive data.

In the Maintenance app, you manage the following push reports objects:

Crie ou edite um relatório push¶

1. Open the Maintenance app and click Other > Push analysis.

2. Clique no botão adicionar.

3. No campo ** Nome **, digite o nome do relatório programado.

   This name is not included in the report e-mail. Instead, the name is used to identify the push analysis object in the system.

4. (Opcional) No campo ** Código **, atribua um código.

5. Adicione um relatório ** Título **.

   Este título está incluído no e-mail do relatório.

6. (Opcional) Adicione uma ** Mensagem **.

   Esta mensagem está incluída no e-mail do relatório.

7. Selecione um ** Painel ** para basear o relatório.

8. Selecione e atribua os grupos de usuários para os quais deseja enviar o relatório.

9. Select a Scheduling frequency: Daily, Weekly or Monthly.

   Note

   If you schedule a push report to "Monthly" and "31", the scheduled report job will not run if the month has less than 31 days.

10. (Opcional) Selecione ** Ativar ** para ativar o trabalho de relatório push.

    O trabalho não será executado até que você o ative.

11. Clique em Salvar.

Visualize relatórios push¶

1. Open the Maintenance app and click Other > Push analysis.

2. Na lista de relatórios de envio, localize o relatório de envio que deseja visualizar.

3. Clique no menu de opções e selecione ** Visualizar **.

   Uma visualização do relatório push é aberta em uma nova janela.

Executar trabalhos de relatório push¶

1. Open the Maintenance app and click Other > Push analysis.

2. Na lista de relatórios push, localize o relatório push que deseja executar.

3. Clique no menu de opções e selecione ** Executar agora **.

   O trabalho de relatório push é executado imediatamente.

Clone metadata objects¶

Cloning a data element or other objects can save time when you create many similar objects.

1. Open the Maintenance app and find the type of metadata object you want to clone.

2. Na lista de objetos, clique no menu de opções e selecione ** Clonar **.

3. Modifique as opções que você deseja.

4. Clique em Salvar.

Excluir objetos de metadados¶

Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

1. Open the Maintenance app and find the type of metadata object you want to delete.

2. Na lista de objetos, clique no menu de opções e selecione ** Excluir **.

3. Clique em ** Confirmar **.

Exibir detalhes de objetos de metadados¶

1. Open the Maintenance app and find the type of metadata object you want to view.

2. In the object list, click the options menu and select Show details.

Traduzir objetos de metadados¶

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

1. Open the Maintenance app and find the type of metadata object you want to translate.

2. Na lista de objetos, clique no menu de opções e selecione ** Traduzir **.

   Tip

   If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

3. Selecione um local.

4. Digite um ** Nome **, ** Nome curto ** e ** Descrição **.

5. Clique em Salvar.

Gerenciar camadas de mapa externas¶

Sobre camadas externas do mapa¶

You can customize GIS by including map layers from various sources and combine them with your own data in DHIS2. DHIS2 supports these common map service formats: Web Map Service (WMS), Tile Map Service (TMS), XYZ tiles and Vector tiles (Vector Style).

Crie ou edite uma camada externa do mapa¶

Note

DHIS2 only supports the Web Mercator projection (EPSG:3857) so make sure that the external service supports this projection.

1. Open the Maintenance app and click Other > External map layer.

2. Clique no botão adicionar.

3. In the Name field, type a name that describes the content of the external map layer.

   Este é o nome que você verá no aplicativo ** Maps **.

4. (Opcional) No campo ** Código **, atribua um código.

5. Selecione um formato de ** serviço de mapas **.

   DHIS2 supports four common map service formats:

   • Serviço de mapas da web (WMS)

     Image format: PNG format allows layers to be transparent, JPG format offers better compression and is often faster to load.

     Layers: A WMS can contain several individual layers, and you can specify which you want to include (comma separated). Refer to the WMS GetCapabilities document to see the available layers.

   • Serviço de mapa de blocos (TMS)

   • Ladrilhos XYZ (também podem ser usados para WMTS)

   • Vector tiles (Vector Style)

   When Vector Style is chosen, you can then add a value for "Before layer id". It indicates the layer id in the Vector tile (layer) stack at which the user's layers (such as Thematic, Events) will be inserted. If this value isn't set, then the user's layers will be placed on top of the layers in the Vector Style. The map service URL should be to a JSON document that follows the Mapbox GL Style Spec.

6. Insira o ** URL ** para o serviço de mapas.

   Note

   XYZ and TMS URLs must contain placeholders {}, for example: http://{s}.tile.osm.org/{z}/{x}/{y}.png.

7. (Optional) Enter Source of the map layers. The field can contain HTML tags if you want to link to the source.

   When you use an external map service it is important to highlight where the data comes from.

8. Selecione um ** Posicionamento **:

   • Bottom - basemap: For the Maps app, this makes the external map layer selectable as the basemap (i.e. as an alternative to the DHIS2 basemaps).

   • Top - overlay: For the Maps app, this allows the external map to be added from the Add Layer selection and placed anywhere above the basemap.

   Note that Vector Style layers can only be added as a basemap.

9. (Opcional) Adicione uma legenda.

   Você pode adicionar uma legenda de duas maneiras:

   • Select a predefined Legend to describe the colors of the map layer.

     Tip

     Click Add new to create legends that you're missing. In the form that opens, create the legends you need. When you're done, click Refresh values.

   • Enter a link to an external image legend in Legend image URL.

     These are often provided for WMS. See under LegendURL in the WMS GetCapabilites document.

10. Clique em Salvar.

Clone metadata objects¶

Cloning a data element or other objects can save time when you create many similar objects.

1. Open the Maintenance app and find the type of metadata object you want to clone.

2. Na lista de objetos, clique no menu de opções e selecione ** Clonar **.

3. Modifique as opções que você deseja.

4. Clique em Salvar.

Excluir objetos de metadados¶

Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

1. Open the Maintenance app and find the type of metadata object you want to delete.

2. Na lista de objetos, clique no menu de opções e selecione ** Excluir **.

3. Clique em ** Confirmar **.

Exibir detalhes de objetos de metadados¶

1. Open the Maintenance app and find the type of metadata object you want to view.

2. In the object list, click the options menu and select Show details.

Traduzir objetos de metadados¶

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

1. Open the Maintenance app and find the type of metadata object you want to translate.

2. Na lista de objetos, clique no menu de opções e selecione ** Traduzir **.

   Tip

   If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

3. Selecione um local.

4. Digite um ** Nome **, ** Nome curto ** e ** Descrição **.

5. Clique em Salvar.

Manage SQL views¶

The SQL View functionality of DHIS2 will store the SQL view definition internally, and then materialize the view when requested.

Database administrators must be careful about creating database views directly in the DHIS2 database. For instance, when the resource tables are generated, all of them will first be dropped and then re-created. If any SQL views depend on these tables, an integrity violation exception will be thrown and the process will be aborted.

The SQL views are dropped in reverse alphabetical order based on their names in DHIS2, and created in regular alphabetical order. This allows you to have dependencies between SQL views, given that views only depend on other views which come earlier in the alphabetical order. For instance, "ViewB" can safely depend on "ViewA". Otherwise, having views depending on other view result in an integrity violation error.

Criação de uma nova visão SQL¶

To create a new SQL view, click Apps > Maintenance > Other > SQL View and click the Add + button.

The "Name" attribute of the SQL view will be used to determine the name of the table that DHIS2 will create when the view is materialized by the user. The "Description" attribute allows one to provide some descriptive text about what the SQL view actually does.

The "SQL type" attribute allows the creation of three kinds of views: - A "View" is stored in the database and regenerated when queried - A "Materialized View" is stored in the database and its results are cached in the database - A "Query" is not stored in the database

Finally, the "SQL query" should contain the SQL view definition.

Only SQL "SELECT" statements are allowed and certain sensitive tables (i.e., user information) are not accessible.

Press "Save" to store the SQL view definition. If you created a "View" or a "Materialized View", you must also "Execute query" to finish the creation of the SQL view.

Keep in mind that the the columns returned by the used SELECT statement become table columns, that means they must be of a valid table column type. When functions are used it might be necessary to explicitly cast the result to a type by adding ::{TYPE} after the function.

For example, instead of jsonb_each (which would return a record type that cannot be a column type) use jsonb_each_text and cast the result to text, like in the below sample:

select jsonb_each_text(eventdatavalues)::text from ...

SQL views that call other SQL views¶

If you wish to make a SQL view that can be called be other SQL views, then its SQL type must be either "View" or a "Materialized View" (not "Query"). It also must have Execute query run on it before being called.

For instance, if you created a view named Data element count with SQL type "View" and this SQL:

select count(*) as count from dataelement;

...then you could run Execute query from the context menu and create a second SQL view named More than 100 data elements with this SQL:

select case when count > 100 then 1 else 0 end as result from _view_data_element_count;

Gerenciamento SQL View¶

In order to utilize the SQL views, simply click the view and from the context menu, choose "Execute query". Once the process is completed, you will be informed that a table has been created. The name of the table will be provided, and is composed from the "Description" attribute provided in the SQL view definition. Once the view has been generated, you can view it by clicking the view again, and selecting "Show SQL View".

Tip

If you have a view which depends on another view, you should be careful about how the views are named. When analytics is run on the DHIS2 server, all views must be dropped, and are recreated. When analytics starts, the views are dropped in alphabetical order, and then recreated in reverse alphabetical order. Thus, if view A depends on view B, it must appear before view B in alphabetical order. If it appears after view B in alphabetical order, analytics may fail, as the view with dependencies will not be dropped in the correct order.

Manage analytics table hooks¶

The Analytics Table Hooks functionality of DHIS2 stores SQL code that is run during different phases of the analytics table generation process.

See also /api/analyticsTableHooks in the Developer documentation.

Creating a new analytics table hook¶

To create a new analytics table hook, click Apps > Maintenance > Other > Analytics table hooks and click the Add + button.

Press "Save" to store the analytics table hook.

Gerenciar localidades¶

It is possible to create custom locales in DHIS2. In addition to the locales available through the system, you might want to add a custom locale such as "English" and "Zambia" to the system. This would allow you to translate metadata objects to local languages, or to account for slight variants between countries which use a common metadata definition.

The locale is composed of a language along with a country. Select the desired values and press "Add". This custom locale will now be available as one of the translation locales in the system.

Editar vários grupos de objetos de uma vez¶

The Metadata group editor in the Maintenance app allows you to edit multiple object groups at the same time. You can edit the following objects types:

Editar vários objetos em um grupo de objetos¶

1. Abra o aplicativo ** Manutenção ** e clique em ** Editor de grupo de metadados **.

2. Clique em ** Gerenciar itens no grupo **.

3. Selecione um tipo de grupo de objetos, por exemplo ** Grupos de indicadores **.

4. Selecione um grupo de objetos, por exemplo ** HIV **.

5. In the left-hand list, select the object(s) you want to add to the object group and click the right arrow.

6. In the right-hand list, select the object(s) you want to remove from the object group and click the left arrow.

Editar um objeto em vários grupos de objetos¶

1. Abra o aplicativo ** Manutenção ** e clique em ** Editor de grupo de metadados **.

2. Clique em ** Gerenciar grupos para o item **.

3. Selecione um tipo de objeto, por exemplo ** Indicadores **.

4. Selecione um objeto, por exemplo ** cobertura ANC LLITN **.

5. In the left-hand list, select the objects group(s) you want to add the object to and click the right arrow.

6. In the right-hand list, select the object group(s) you want to remove the object from and click the left arrow.