Since the launch of the IATI Data Standard, DG has been in the forefront in promoting its uptake and use – particularly amongst national governments.
A little over a year ago, we began a program which sought to create sustainable integrations of IATI data across five nationally-owned Aid Information Management Systems (AIMS). One of the outcomes of this work were recommendations around proposed enhancements to the data standard and improvements to publisher quality.
Fully integratable with AIMS – Aid Management Platforms and other systems – the tool has already been used to import hundreds of millions of dollars of additional aid flow data into the AIMS of Burkina Faso, Chad, Cote d’Ivoire, Madagascar, and Senegal. Furthermore, this tool can be updated to support new versions of the IATI Standard, and now comes as a standard part of DG’s Aid Management Platform.
Technology and Architecture
The tool has a flexible architecture, designed specifically to make the tool easily adaptable to future IATI versions and different AIMS. This flexibility is achieved through the use of data processing modules called “processors”. New processors can be added to support any source data or destination system.
The integration to an AIMS is done via REST API endpoints. Documentation of the endpoints that the AIMS system should provide is available on the IATI Import Tools’ GitHub page.
The IATI Import Tool has a user friendly user interface that is organized as a wizard, which takes users through the following steps:
Step 1: Source Input
The source input is uploaded into the system and processed. Currently we support IATI 1.03, IATI 1.04, IATI 1.05 and IATI 2.01. This can be easily expanded to support other types of data files, too – IATI and otherwise.
Step 2: Filter Data
The source activity/project information is then parsed and processed. The user can select the criteria of inclusion in the import process from a list of known fields, like “Status”, “Recipient Country”.
Step 3: Choose Projects
After applying filters, the next step returns only projects/activities that match the applied filters. In this step, a user can select which projects/activities to import. The user can also map the projects to existing projects in the destination system.
Step 4: Choose Fields
Users can now select and map fields that will be included in the import. The user can also save mappings for use in future imports.
Step 5: Mapping Values
This step allows users to map field values in the source file to values used in the destination system. These value mappings can be saved as a template, then selected from the “Load Existing Template” menu. This uses the previous mappings with the new file’s field values.
Step 6: Importing
Once the source files are processed and filtered, and their projects, fields, and values are mapped the destination system is contacted through a series of REST Endpoints with the new and/or updated project information
The IATI Import Tool is licensed under an Apache 2.0 open-source license, now comes as a standard part of the Aid Management Platform, and is compatible with other AIMS. If you are interested in using or extending the tool you can get it on our GitHub repository. Please also check the wiki for additional documentation on how to integrate the tool with a target system, and let us know about your experiences!
As we review our strategy, we plan to share here much of what we’ve learned through programming in more than a dozen countries – from our work and from our excellent partners – about the state of data in agriculture, tobacco control, open contracting, and the extractive industries. For each theme, we’ll explore who are the key data users, the decisions they make, the most important data gaps, and the crucial risks of data (mis)use. Here we share previews from some of our flagship programs.
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With support from DCDJ, local youth in Côte d’Ivoire organized a successful mapathon to get community resources, landmarks, and risk zones in Daloa – particularly those relevant to young people – on the map. Through the process, they acquired new skills including OSM tracker to develop map layers, how to collect local data, and how to communicate results stored in a new database developed through the program.