Bridging the Data Divide: Operationalizing FAIR and CARE Principles in Water, Sanitation, and Hygiene (WASH) Systems

Main Facts

The global Water, Sanitation, and Hygiene (WASH) sector generates monumental quantities of data daily. From subterranean groundwater monitoring records and detailed borehole inventories to comprehensive sanitation surveys, water quality tests, and infrastructural functionality reports, this digital footprint serves as the foundational bedrock for long-term planning, targeted resource allocation, and critical public policy decision-making. Yet, a persistent paradox plagues the sector: while data collection is robust, the actual utility of this information remains critically constrained.

Across myriad international development programs, governmental agencies, and non-governmental organizations (NGOs), datasets frequently remain siloed within disparate institutional repositories, stored in incompatible digital formats, poorly documented, and virtually undiscoverable beyond the specific project boundaries that birthed them. When data is technically accessible, it often lacks the vital contextual metadata required for accurate interpretation. Furthermore, community-generated data is frequently harvested, analyzed, and shared without adequate consideration for the rights, sovereignty, and welfare of the human populations represented.

To resolve these systemic shortcomings, WASH data management is undergoing a philosophical and structural evolution. Experts are increasingly championing the dual integration of two premier global data governance frameworks: the FAIR principles (Findable, Accessible, Interoperable, and Reusable) and the CARE principles (Collective Benefit, Authority to Control, Responsibility, and Ethics).

While FAIR provides the rigorous technical architecture required to ensure datasets can be discovered, integrated, and utilized efficiently, CARE injects an essential human-centric governance layer, ensuring that data stewardship prioritizes ethical considerations, community empowerment, and equitable distribution of benefits. As highlighted by data stewards operating at the intersection of open-source science and international development—such as through initiatives like openwashdata and institutional efforts in regions like Malawi—bridging the gap between raw data collection and actionable intelligence is no longer merely an administrative luxury. It is an urgent operational necessity capable of directly dictating the success or failure of vital public infrastructure projects.

Chronology

The movement toward responsible, open, and community-centered WASH data stewardship has evolved significantly over the past decade, marked by key milestones in both data science theory and practical field application:

• 2016 (The Birth of FAIR): Wilkinson and colleagues formally introduce the FAIR principles in Scientific Data, providing a standardized global blueprint for making scientific research data Findable, Accessible, Interoperable, and Reusable.
• 2018–2019 (The Emergence of Indigenous Data Sovereignty): Recognizing that technical FAIR frameworks often overlook power dynamics and community rights, the Global Indigenous Data Alliance (GIDA) develops and formally launches the CARE principles to complement technical data practices with ethical governance guidelines.
• Mid-2020s (The Silo Crisis in WASH): As digital transformation accelerates across the international development sector, WASH organizations increasingly recognize that uncoordinated data collection efforts are resulting in massive digital waste. Datasets concerning borehole statuses, water table fluctuations, and sanitation access remain trapped on local office computers, hindering broader regional planning and inter-agency coordination.
• October 27, 2026 (The BASEflow and UNICEF Milestone): Emmanuel Mhango, working as a Data Steward at BASEflow Malawi in collaboration with the openwashdata community and ETH Zurich, publishes foundational infrastructure data for Mwanza District onto an open data platform. Prior to this, the dataset was restricted to local organizational hard drives.
• Late October 2026 (Rapid Action and Real-World Impact): Merely five days after public release, UNICEF discovers, downloads, and utilizes the open dataset. This timely discovery directly informs and accelerates borehole rehabilitation activities in the targeted Malawian districts, swiftly restoring functional water points to local communities and proving the tangible, life-changing value of open WASH data stewardship.
• Present Day (Operationalizing the Dual Framework): WASH institutions globally are actively transitioning from theoretical discussions of FAIR and CARE to embedding these principles into institutional hiring, metadata standardization, software architecture, and community engagement protocols.

Supporting Data and Technical Architecture

To fully appreciate the scope of the data challenge in the WASH sector, one must examine how technical and ethical frameworks intersect in practice. The management of water resources is inherently multifaceted, requiring seamless collaboration between hydrologists, public health officials, community leaders, and international donors.

The Technical Interplay: FAIR Meets CARE

Implementing these frameworks requires breaking down data silos. For instance, when a district water office collects physical parameters on water tables (such as electrical conductivity, temperature, and historical drawdowns), the data is analytically useless if it cannot be cross-referenced with asset management logs detailing pump maintenance histories. By standardizing identifiers and enforcing strict metadata templates, agencies can transition from reactive emergency repairs to proactive, data-driven preventative maintenance models.

Official Responses and Institutional Perspectives

The paradigm shift toward operationalizing FAIR and CARE principles has garnered significant commentary from sector professionals, data scientists, and international development organizations.

Data stewards and WASH engineers emphasize that the historical norm—where data gathered during field assessments remains locked in proprietary institutional software or personal hard drives—is no longer justifiable in an era of climate volatility and resource scarcity.

“Data creates greater value when the people who need it can find it and act on it,” notes Emmanuel Mhango, reflecting on the rapid intervention by UNICEF following the publication of Mwanza District’s infrastructure data. When information is shielded behind bureaucratic red tape or technical incompetence, response times to failing water infrastructure drag on, directly compromising human health and community resilience.

At the same time, institutional leaders caution against naive interpretations of openness. Total, uninhibited public exposure of all WASH data is neither practical nor ethical. Government ministries and humanitarian agencies frequently stress that while aggregate indicators (such as district-wide water point functionality percentages) should be openly accessible to all, hyper-local data—such as the exact GPS coordinates of critical water security infrastructure or sensitive household-level sanitation surveys—demands rigorous access controls, authentication protocols, and robust privacy safeguards.

Furthermore, international bodies point out that compliance with technical frameworks like FAIR does not automatically equate to data accuracy. Interoperable datasets can still harbor systematic biases, human recording errors, or outdated observations. Consequently, institutional responses increasingly highlight the absolute necessity of pairing technical data standardization with rigorous, ongoing data quality assurance programs and continuous community feedback loops.

Implications

The widespread adoption and operationalization of FAIR and CARE principles carry profound implications for the future of global water and sanitation governance, stretching across administrative, financial, and humanitarian domains.

1. From Administrative Compliance to Measurable Service Impact

Historically, monitoring and evaluation (M&E) in the WASH sector has often treated data collection as a terminal bureaucratic checkbox—a report compiled to satisfy a donor’s end-of-project requirements before being archived indefinitely. By embracing FAIR and CARE, institutions pivot toward an impact-oriented culture. Success is no longer measured simply by the volume of datasets harvested or published, but by tangible metrics: reduced borehole downtime, faster emergency repair deployments, more equitable distribution of financial resources, and verifiable improvements in community-level water security.

2. Transforming Inter-Agency Collaboration and Resource Efficiency

The Malawi case study involving BASEflow and UNICEF serves as a watershed proof-of-concept for regional development. When local organizations publish standardized, clean, and well-documented data, international humanitarian agencies can bypass months of redundant, costly independent baseline surveys. This efficiency preserves scarce financial capital, allowing non-profits and governmental bodies to redirect operational funds straight into physical infrastructure rehabilitation, capacity building, and direct service delivery.

3. Redefining Power Dynamics Through Community-Centric Governance

The integration of the CARE principles ensures that local populations are not viewed merely as passive subjects of study or extraction, but as active co-creators and sovereigns of their own development data. In an age where digital profiling and spatial data can inadvertently expose marginalized communities to risks—such as land speculation, targeted marginalization, or the stigmatization of poor sanitation practices—ethical data governance acts as a vital shield. By institutionalizing community consultation, local consent, and feedback mechanisms, WASH programs build long-term trust and ensure that technological interventions genuinely align with local needs.

4. Navigating the Realities of Digital Infrastructure and Institutional Capacity

Ultimately, the implications of this shift extend down to the internal workings of resource-constrained agencies. Realizing the full potential of FAIR and CARE does not inherently require purchasing expensive, proprietary software suites or building massive, monolithic digital portals from scratch. Rather, true success relies on incremental institutional reform: standardizing metadata templates, training local staff in data stewardship, establishing clear internal policies for data sharing, and fostering a collaborative culture where information is treated as a vital public utility.

As the WASH sector marches further into the digital age, the core mandate remains strikingly clear: the goal is not simply to make water and sanitation data available, but to make it profoundly useful, deeply trustworthy, and relentlessly accountable to the human lives it is designed to serve.