DHIS 2.34 Overview
DHIS2 version 2.34 is out with many new features, apps, improvements, and bug fixes. On this page you can find information on this software version, including feature descriptions, links to technical documentation, and more
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Feature Spotlight Videos
Discover some highlights of new features in this DHIS2 release with our Feature Spotlight video series.
Pivot tables in Data visualizer app
The Data visualizer app now supports pivot tables, meaning the functionality of the pivot table app is merged into the data visualizer app. A pivot table is now just another visualization type within the data visualizer app. This provides users with a more intuitive experience for building pivot tables, and it more seamlessly allows moving between pivot tables and other chart types. The performance of pivot tables is also dramatically improved, allowing for very large pivot tables with at least three times more data than the classic pivot table app.
[ Video ][ Screenshot 1 | 2 | 3 ][ Jira ]
In the data visualizer app, pivot tables now support “dimension recommendations”, which means that dimensions which are relevant to the select data elements will be indicated in the left panel with a green dot.
[ Video ] [ Screenshot 1 ]
Continuous analytics table update
The analytics table scheduler now supports continuous updates of analytics tables, offering a “real-time analytics” experience. The delay between data being entered and data becoming visible in analytics apps can now be expected in seconds as opposed to hours or a day previously. Essentially a new table partition which holds the latest data is introduced which allows for quicker updates. Configure this in the Scheduler app by selecting the Continuous analytics table job type. The Delay in seconds field refers to the number of seconds in between each update of the latest data. The Full update hour of day field refers to the time of the day to perform the full analytics table update.
[ Screenshot 1 ][ Docs ]
Legends for single values
Legends can now be added to single value chart types. The text color of the value is decided by the legend that the value falls within. This enables users to more effectively communicate the relative performance of values.
[ Screenshot 1 ][ Jira 1 ]
Improved gauge charts
The usefulness of gauge charts has been dramatically improved. Now a gauge chart can include baselines and target lines, a legend that will change the color of the chart based on the value shown, and minimum and maximum data ranges.
Sort by totals in pivot tables
You can now sort by subtotal and total columns in pivot tables.
[ Screenshot 1 ]
Dashboard item visual improvements
Each dashboard item has text wrapping for long names. All dashboard item options are now available as a menu instead of icons, giving more space for the title and makes titles more visible in the dashboard.
[ Screenshot 1 ]
Pivot table and Chart general options in visualization filter
Now in the data visualizer application when the user searches for a saved visualization the type of visualization will be shown and users can filter by visualization type.
[ Video ][ Screenshot 1 ][ Jira 1 ]
Progressive caching reduces the time to render dashboards and speeds-up analytics by creating a new cache layer. Essentially this enables data to be viewed in the analytics immediately after being entered without running the analytics tables.
[ Jira ]
Map Enhancements and WebGL
The mapping engine in version 2.34 is brand new and based on the WebGL technology which is much more performant compared to the previous solution. The following key features are now available in Maps:
- Performance: We are now capable of showing thousands of features on a map simultaneously, and the maps are much more responsive.
- Map rotation and tilting: You can now rotate and tilt the map to enhance the view of your data.
- Continuous zoom: The zoom is now continuous, allowing you to fit the map perfectly to your content. We have added a fullscreen button, especially useful for maps on the Dashboard where space is limited.
- Full-screen view Maps can now be viewed in full-screen mode. This is especially useful for dashboard maps where space is limited. You can click the full-screen button on the right side of the map to enable it.
- Bing Maps: Google Maps is no longer supported due to technical and legal issues, but we have included four new base maps from Bing, which should be a good replacement.
- Donut clusters: We have added support for “donut clusters” which will show you the event cluster distribution if you style by a data element.
Tracker and Event Features
Predefined list views in Capture app
In the capture app it is now possible to save and share custom predefined list views/event filters. A user can save a named filter based on any otherwise filterable attributes like event data values, event dates, assignees, and so on. This can be a private filter or shared so that other users can see and utilize it. One use case for such filters can be to create a default working list of events assigned to the logged in user.
[ Screenshot 1 ][ Docs ][ Jira]
Tracker capture search for relatives
It is now possible for a user to search for and link a relationship to any tracked entity instance in their search scope. Previously it was only possible to search and link relationships within the users reporting organization unit. Searching across different organizations is useful in Covid-19 contact tracing where the contacts might live in another part of the country. This functionality was also backported to 2.33.
[ Screenshot 1 ][ Docs 1 ][ Jira 1 ]
Enhanced audit service
An audit trail is now stored for all types of metadata and data. The audit trail is enabled by default and is configurable in this dhis.conf configuration file. The solution is centralized and is based on the Apache ActiveMQ Artemis asynchronous message broker. The audit solution covers create, read, update and delete operations across metadata, aggregate data and tracker data. Audit logs can currently be retrieved from the audit table in the DHIS2 database.
The data approval functionality is re-introduced as a separate app called Data approval. It offers the same functionality which was previously accessible through the Reports app. It allows for approving data by data set and time period. We are working on a new approval app using our new technology stack which will support the data approval workflow model.
[ Screenshot 1 ]
Attribute ID schemes in data import-export
The import-export app now allows for selecting attribute-based identifier schemes for data import and export.
[ Screenshot 1 ][ Jira 1 ]
The App Store has been rebranded as the App Hub. The App Hub has been rewritten to support improved management of apps. DHIS2 2.34 uses the new App Hub (https://apps.dhis2.org) by default. Apps from the old App Store have been migrated to the new App Hub where possible. The old App Store link, used by previous versions of DHIS2, will continue to work, but will be seamlessly redirected to the new App Hub in the near future. App developers should now use the new App Hub for sharing your apps.
[ App Hub ]
New combined endpoint for analytics visualizations
The reportsTables and charts endpoints have been deprecated in favour of a new and consolidated visualizations endpoint.
[ Docs 1 ]
This version of the DHIS2 is compatible with the DHIS2 Android Capture App version 2.1.
Click on the links in the table below for more information about this software release and to access an interactive demo.
|To find more details about...||Follow this link:|
|Download release and sample database||Downloads|
|Documentation and Javadocs||Documentation|
|Upgrade notes||Upgrade notes for 2.34 on Github|
|Details about each feature on JIRA (requires login)||Details on JIRA|
|Overview of issues on JIRA (requires login)||Overview on JIRA|
|Source code on Github||DHIS2 source code|
|DHIS2 community||DHIS2 Community of Practice|