Overview
Benefits
Required Commitments
Use Cases
How to Apply
Timeline

APRU Social Impact Data Science Accelerator (SIDSA)

Leveraging AI and Data for Inclusive Growth

Period:    July 2025 – May 2026
Application Deadline:  June 30, 2025

                           

While cutting-edge companies and well-resourced governments are increasingly adopting data science to enhance their services, many social impact organizations (SIOs) in less developed regions still lack the tools and talent to fully harness the power of data.

The APRU Social Impact Data Science Accelerator (SIDSA) is set up as part of data.org’s APAC Capacity Accelerator Network (CAN) to empower SIOs in Southeast Asia (SEA) to leverage data science by connecting them with academic-led student teams from leading universities. Together, they co-develop practical, data-driven solutions tailored to real-world challenges as set out in the project’s use cases.

The SIDSA aims to improve decision-making, amplify impact, and build long-term data capabilities within SIOs. The initiative focuses on advancing financial inclusion and economic resilience through solutions that are ethical, feasible, and grounded in operational realities. Participating SIOs in SEA have been selected through a combination of self-nomination and referrals. 

For this SIDSA, we are seeking teams to collaborate with selected Southeast Asian SIOs in the main implementation period from July to December 2025

Teams will consist of a lead academic, a core group of at least 3 undergraduate or graduate students, and may additionally include research assistants and postdoctoral fellows (see the “How to Apply” section for details).

Application Deadline: June 30, 2025 (Closed)

Objectives

Teams will work closely with SIOs to develop data science solutions that address one or more of the following key challenge areas:

1. Strengthening Inclusive Financial and Entrepreneurial Ecosystems

Develop data-driven tools that enable personalized engagement, enhance financial literacy, and support long-term impact tracking for rural entrepreneurs.

2. Advancing Data-Driven Decision-Making for Community Impact

Create integrated data systems and real-time monitoring tools to support evidence-based planning in food security and livelihood programs.

3. Enhancing Equity and Accountability in Sustainable Value Chains

Use data to assess progress toward inclusion, transparency, and sustainability in certification or supply chain systems—improving how support, pricing, and commitments are tracked and communicated.

4. Supporting Business Model Transitions in Social Impact Systems

Design data schemas, digital tools, and reporting workflows that help mission-driven enterprises shift from informal, manual processes to legally recognized, app-based operations.

Download the SIDSA Document

*All of the workshops and meetings will be conducted online.

Benefits

Teams selected to participate in the SIDSA will gain the following opportunities:

1. Gain Real-World Project Experience

Collaborate with social impact organizations to address urgent, data-driven challenges. Teams will work with real datasets to develop actionable solutions in areas such as food security, financial inclusion, environmental sustainability, and equitable development.

2. Present at the SIDSA Summit

Top-performing teams (academic lead and a student representative from each team) will be invited to present their work at the SIDSA Summit (location to be confirmed) in Q4 2026. Travel funding support will be provided. The Summit will bring together SIO partners, academic leaders, policy experts, and other stakeholders from across Southeast Asia and the Pacific.

3. Build Pedagogical and Career Impact

Participants will develop a strong professional portfolio showcasing applied data science work. This experience is ideal for job interviews, graduate school applications, and industry exposure. Students will engage in real-world projects with a focus on impact, ethics, and feasibility.

Additional Benefits Include

4. Extended Collaboration Opportunities

Select teams may be invited to continue working with their partner SIOs beyond the challenge period. Opportunities may include internships, independent study projects, or longer-term research collaborations aligned with the SIO’s goals.

5. Academic Outputs and Recognition

Projects may evolve into published case studies, collaborative papers, or teaching materials focused on data science for social impact. Faculty advisors are encouraged to support students in producing academically valuable outputs.

6. Eligibility for Funding Support

Teams may receive funding to support project-related expenses and travel for selected members to attend the SIDSA Summit. Further details will be provided following the project output presentations.

Required Commitments

Teams selected for the SIDSA must commit to the following:

Time Commitment

Each team should dedicate sufficient weekly hours to collaborate with their assigned SIO during the implementation phase. Each student member is expected to contribute approximately 40 hours over an 8–12 week period. Activities may include data analysis, prototyping, development, testing, documentation, and regular feedback sessions with SIO partners and SIDSA organizers.

Workshops

Lead Academics are required—and other team members are encouraged—to attend two workshops taking place at the end of July 2025 (dates TBC):

  • On-boarding Workshop: Covers lean data methods, ethical engagement, and collaboration in low-resource settings.
  • Joint Implementation Workshop: Focuses on finalizing work plans, timelines, and team-SIO collaboration strategies.

 

Meetings

Teams will participate in regular check-in sessions (weekly or bi-weekly) with their SIO partners to align on deliverables, clarify data issues, and co-develop feasible solutions.

Project Outputs

All final outputs must be openly accessible and freely shareable through project reports and open repositories.

Data Use and Confidentiality

Participating teams must sign a Letter of Intent and, where applicable, a Non-Disclosure Agreement (NDA).

*All of the workshops and meetings will be conducted online.

Use Cases

Each team should select two of these use cases while submitting the application.

Use Case #1: Dashboard-Driven Insights for Entrepreneur Engagement and Financial Inclusion

A nonprofit organization supporting rural entrepreneurs in Cambodia offers a mobile application that delivers financial literacy training and small business management tools. To improve program effectiveness, the organization seeks to segment users based on financial behavior, training participation, and revenue levels using data such as 7-day and 30-day activity logs and financial records.

The goal is to develop a dashboard that visualizes usage patterns, identifies when users are ready for advanced training or upgraded tools, and supports regional scaling through location-based segmentation. Additionally, the organization plans to embed new metrics—such as debt management practices, financial decision-making, and selected financial literacy questions from global benchmarks—into the app to track long-term impact beyond standard baseline and endline assessments. This will require updates to the app’s data collection process, with careful attention to data privacy, question frequency, and usability for low-resource users.

Use Case #2: Data Integration and Visualization for Multi-Community Program Insights

A nonprofit organization working to improve food security, health, and income in rural communities across the Philippines has collected household- and community-level data from 10 batches of program implementation, covering 100 farming and fishing communities. These datasets are fragmented, follow inconsistent database schemas, and vary in granularity—some at the household level, others at the community level.

The organization aims to integrate these datasets into a unified database and develop an interactive dashboard to enhance program evaluation and decision-making. Key questions include: What factors influence family participation and productivity (e.g., timing, geographic or cultural factors)? How does a municipality’s income classification or rural/urban status affect its capacity to co-invest and generate outcomes?

The solution must support filtering, trend exploration, and insight generation across batches, while managing occasional missing identifiers and data inconsistencies. Ultimately, the dashboard should help the organization identify actionable patterns and design more responsive, inclusive development strategies.

Use Case #3: Tracking Smallholder Inclusion in a Global Palm Oil Certification System

A global certification body for palm oil producers and users seeks to monitor how its members—ranging from large producers to supply chain actors—are fulfilling their commitments to smallholder inclusion. Members submit self-reported data annually through Shared Responsibility (SR) reports, scorecards, and Annual Communications of Progress, which detail their certified sustainable palm oil uptake and support activities for smallholders.

Due to inconsistencies in structure and reporting quality across sectors and regions, analysis is challenging. The organization aims to develop a dashboard that visualizes member progress over time, identifies sectoral and regional trends, and highlights replicable models of effective support. The dashboard should also flag implementation gaps and generate downloadable summary briefs to support policy discussions, member engagement, and public accountability.

Application

Pease submit your application here by June 30, 2025 (Closed), and include the following:

Team Composition

Each team must be led by a university faculty member (or equivalent) who will serve as the lead academic and primary contact. Teams will consist of:

  • A core group of at least 3 undergraduate or graduate students

 

And may also include:

  • Research assistants
  • Postdoctoral fellows
  • Colleagues with relevant skills

 

*Note: Team size is flexible and may vary based on the needs of the partner SIO.

While domain expertise (e.g., agri-food, health, recycling) is not required, it is considered beneficial. Teams must demonstrate a commitment to ethical data science, responsible AI, and sound data governance. Experience in applied, community-based, or capstone research is a plus.

Required Information

Each application must include:

  • Full names, genders, and university affiliations of all team members
  • [For students] Academic program and year level 
  • [For lead academic and non-student members] A short bio or credentials summary, outlining relevant skills, interests, or experiences related to data science, policy, development, and/or the chosen use cases/project objectives. 
  • Highlight two preferred use cases from selection provided that are of interest to the team
  • A 1-page motivation statement (approximately 500 words) covering;
    • Why the team is interested in SIDSA and its mission
    • How the team plans to collaborate with and contribute to their preferred SIO(s)
    • The two selected use cases and the rationale behind the choice
    • Relevant skills, experiences, or prior work (e.g., coursework, tools, fieldwork, capstones)

Evaluation Criteria

Applications will be reviewed based on:

  • Alignment with SIDSA’s goals: Data/AI × Social Impact × Capacity Building
  • Diversity of disciplines and genders within the team
  • Originality, clarity, and depth of motivation statement
  • Relevance of the team’s approach to the selected use cases

Priority will be given to teams whose proposed approaches and intended outcomes most closely align with the needs outlined in their selected use cases.

Timeline

Jun – Jul 2025

Selection

  • Expression of interest 

  • Selection and matching of each team with its SIO partner 

Jul – Aug 2025

Onboarding

  • Lead Academics develop Initial Engagement Proposals including details such as team composition/roles, problems to be addressed, initial approach/solution

  • On-boarding Workshop for Lead Academics  

  • Joint Implementation Workshop for both SIOs and Lead Academics

  • Lead Academics develop Project Implementation Plans based on the SIO use case needs and Final Engagement Proposal. Key points to include will be engagement kick off, mid point review and final presentation and reflections. 

Sep 2025 – Jan 2026 

Implementation 

  • Sep – Dec 2025: Teams dedicate the weekly hours set out in their Project Implementation Plans to work with their partner SIOs. These activities include, but not limited to, data analysis, prototyping, development, testing, meetings, documenting technical approaches, feedback collection from SIO partners, APRU/Tandemic and other experts.

 

  • Dec 2025/Jan 2026: Teams present their solutions to the SIOs and SIDSA, and reflect on their experience. 

Aug 2025 – May 2026

Reporting

  • Teams Develop case study reports drawing on documented approaches and learnings (from the lead academics and students). 

Q4 2026 

Presentation

  • Final SIDSA Summit (dates and location TBC but will be in a SEA city)

*All of the workshops and meetings will be conducted online.

Contact
Us

For inquiries, please contact Mr. Benjamin Zhou at [email protected].

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