Improving the visibility of local and national actors in humanitarian aid data

The limited visibility of local and national organisations ^[1] in humanitarian open aid data adds to the challenges of meeting and tracking the Grand Bargain commitment to provide more direct support to local and national actors.

In support of the Grand Bargain transparency workstream and with funding from the Netherlands’ Ministry of Foreign Affairs, Development Initiatives (DI) explored the technical options for increasing the visibility of local and national actors in International Aid Transparency Initiative (IATI) data. In this pilot project, DI looked specifically at Somalia, examining how the activities of local Somali organisations could gain visibility and better integration in the IATI data ecosystem – without placing any additional reporting or technical burdens on those organisations. This was achieved by investigating additional data sources at the local and national levels and exploring the potential for data interoperability to enable a clearer picture of on-the-ground activities.

The Somali organisations interviewed for this report were eager for their aid activities to have more international visibility. They also wanted the opportunity to work directly with international government donors, without intermediation by multilateral organisations or international NGOs. However, both the local organisations and the international government donors pointed to a series of systemic barriers that hindered these outcomes, including the difficulty of learning about local partners and the problem of trust (donors often do not recognise the certifications and qualifications that local organisations hold).

The UN Office for the Coordination of Humanitarian Affairs (OCHA)’s monthly 3W (who? what? where?) reports are less detailed than IATI, but they contain information about more local activities and actors. While it was not possible to trace specific activities and financial flows, we were able to create a prototype tool that combines 3W and IATI data for Somalia to produce a much richer picture of the aid work in the country that better represents the foundational role of local organisations. Once information about local actors is integrated with existing IATI data, it is possible for international donors to become better informed in a number of ways. Specifically, they can discover:

• Who the local organisations are
• What international partners the local organisations have worked with previously (potential references)
• What sectors the local organisations have worked in (skills and qualifications)
• What districts and regions the local organisations have worked in (local knowledge).

Likewise, local and national organisations can improve their international visibility by:

• Receiving the acknowledgement they deserve for their aid activities
• Directing international donors to their past experience in specific locations and sectors
• Establishing their international credentials by referring to past partnerships with international actors.

Interviews conducted for this report confirm how this information could go far in bridging the trust and knowledge gap that currently exists between international government donors and local organisations, as well as enhance transparency of the humanitarian system by contributing to a more expansive and interoperable source of open data on activities.

The aim of this project was to begin to show what is technically feasible using existing data sources to expand understanding of local activities and their linkages to international activities/funding. The prototype demonstrates a significant potential in enhancing data interoperability down to the local and national levels. With the strategic prioritisation of localisation under the Grand Bargain 2.0 framework, this should be further explored and expanded in order to improve opportunities for localisation and enhance accountability of associated funding commitments.

This report highlights the technical methodology we pursued through our prototype tool development, key findings and recommendations for next steps.