The MAPME community recently held a workshop on project location mapping, a crucial initiative for using project geospatial data to plan, monitor, and evaluate development initiatives. Despite its importance, the sector currently faces major gaps: there are no binding standards or widely adopted tools, very little publicly available information, and limited institutional capacities with GIS technologies. These constraints make it difficult to analyze development investments spatially, coordinate across organizations, and ensure transparency. The workshop provided a space for information exchange and peer learning, allowing participants to share experiences and explore practical solutions.
The event brought together development banks, independent funders, technical cooperation agencies, and NGOs to identify challenges and discuss ways to improve project location mapping.
The workshop was organized around two main parts:
1. Experience Sharing
Participants worked in small groups to exchange insights from their institutional practices. Organizations taking active part in this session included IFAD, World Bank (GEMS), GEF, KfW, WFP (AIMS), and ADB. Additionally, representatives from AFD, GIZ, IEG, Development Gateway, and IDB joined as participants. Each shared the status of databases and workflows, the tools and processes used and the challenges encountered.
From this experience sharing, the following key purposes of collecting project locations emerged:
- Strategic Planning and Decision Support – Improves understanding of regional contexts, identifies vulnerable areas, informs prioritization of resources, and supports program design and risk management. Strengthens portfolio planning and strategic alignment.
- Portfolio and Project Design and Management – Enhances portfolio oversight and resource allocation, including the management of climate change, disaster risk, and safeguard considerations across programs.
- Monitoring and Supervision – Facilitates systematic tracking of project implementation (time, date, location, photos), supports supervision during rollout, and enables monitoring of environmental and social safeguards.
- Coordination and Collaboration – Facilitates donor coordination, identifies synergies across sectors and countries, and improves knowledge sharing and decision-making through shared geotagged data.
- Impact Assessment and Evaluation – Supports evaluation, impact assessments, accurate measurement of results, operational risk identification, and compliance with geospatial reporting requirements.
- Accountability, Transparency and Verification – Ensures projects are implemented, prevents “ghost investments,” verifies infrastructure developments, and supports audits and procurement procedures.
Communication – Improves reporting, visualization, communication, and promotion of project impact vie map and geodata products.
The second session aimed at co-design optimal process for project-location mapping. One group looked at the data processing workflow—from planning to collection, validation, storage, and use while the other group worked on the use of project location mapping along the entire project cycle from project design to ex-post evaluation —drawing on the experiences of all participating organizations. Groups mapped their ideal end-to-end workflows, identified pain points and proposed improvements for collective action.
Challenges identified included:
- Institutional Buy-In and Awareness – Securing management support for mandatory project data collection requires clearly demonstrating the added value of geospatial data and analytics. Without strong institutional commitment, many organizations struggle to obtain timely and complete submissions, revealing gaps in compliance, capacity, and workflow efficiency. As a result, institutions are unable to fully leverage geospatial data for global portfolio analysis and strategic insight.
- Collaboration and Engagement – Engaging local partners in data collection is challenging, and lack of common workflows and data models across teams and institutions hinders coordination.
- Data Quality and Accuracy – Low capacity of data collectors leads to errors, misinterpretation of questions, and inconsistent reporting. Manual entry increases the risk of mistakes that persist through the project cycle.
- Privacy and PII Concerns – Despite instructions, data collectors sometimes enter personal information (names, photos), creating compliance risks.
- Resource and Funding Constraints – Limited funding affects data collection efforts and development of a cohesive system accessible to all partners. Misaligned incentives reduce motivation.
- Standardization and Interoperability Issues – Lack of international location data standards, fragmented mapping initiatives, disjointed workflows, and varying practices across teams and partners make sharing, aggregation, and cross-portfolio analysis difficult.
- Operational and Technical Challenges – Need for automated workflows, data cleaning and validation, simple data standards and formats, timely input, and user interfaces suitable for non-GIS experts. An abundance of tools, lack of user-friendly guides, and multiple stakeholders (“too many cooks”) can confuse field teams.
- Dynamic Project Contexts – Changing project cycles and portfolios can make datasets incomplete or not fully representative. Capturing projects where locations are not obvious adds complexity.
Suggestions for improvements proposed by participants included:
- Open online space to share tools, standards, guidelines, and training materials, with institutions having rights to upload their resources
- Standardized data model for harmonized project location data
- Standardization of requirements, tools and guidelines to improve interoperability and consistency
- Raise Awareness Strategically – Start with monitoring and evaluation teams for “low-hanging fruit” using an IMPACT perspective
- Start Small, but Structured - collecting some crucial location data in a structured way and then gradually expand instead of trying to collect all types of information from the beginning, resulting in too much data collection efforts and low data quality
- Highlight Geolocations for Risk Management – Demonstrate how project locations can reveal, reduce, and manage social, environmental, and climate risks
The plenary debrief highlighted shared challenges, good practices, and opportunities for standardization, laying the groundwork for ongoing collaboration within the MAPME community.
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Building on the outcomes of this workshop, a second online workshop is planned for 15th January to focus specifically on comparing and discussing existing project location data models of MAPME community members, aiming to create a common project location data standard across the development sector.