The world burns while the rich get richer, the poor get poorer, and a global pandemic mutates faster than we can vaccinate people. These are complex and intractable problems, and we know that data can power more targeted and effective solutions. So why don’t we see more data sharing or evidence-based policies? And why do so many tech-driven solutions fall into disuse? The answer is because of people.

From technical to human interoperability.

A key tenet in data for development is that addressing complex problems requires bringing data sources together to draw information from different sectors and disciplines. This is interoperability, or the ability to join up and merge data without losing meaning or context. When people talk about interoperability, they almost exclusively mean technical interoperability: data meaning, structure, file formats, etc. (For more on this, see this practical guide from the Global Partnership and UN Statistics Division.) But what about the people behind the data?

People are engaged at every step in the data value chain in collecting, analyzing, interpreting, and using data. In many cases, people themselves are data points. All these people bring perspectives, values, world views, and expectations, which are also embedded in political and organizational cultures. If we want data to work together, we need people to work together. We need human interoperability

A search for literature on human interoperability yields little to guide or stimulate ideas or actions. However, many organizations are already working on this. The following examples inspire us to develop strategies for collaboration between organizations, nations, and communities.

Trust and the social contract: the World Development Report.

The World Bank’s latest annual development report, Data for Better Lives, emphasizes that data alone is not enough. It takes people—from governments, civil society, and the private sector—using data to "generate insights that can turn into action to improve development outcomes." The World Development Report calls for a new social contract based on trust. Facilitating collaboration, translating between communities, and fostering communication and mutual understanding are foundations of trust upon which effective data collaboration can be built. As people collaborate they develop better understandings of other perspectives and figure out ways to work together—they become more interoperable. This collaboration can then shift organizational and institutional cultures.

Putting people before technology: sharing data in Senegal.

Prioritizing collaboration among partners is essential to ensure data platforms are usable and sustainable, as examples from Senegal’s food and agriculture sector demonstrate. When faced with data dispersed across siloed governmental and non-governmental entities, Senegalese think tank Initiative Prospective Agricole et Rurale (IPAR) developed a project with the National Statistical Office to identify gaps and crossovers in data among key stakeholders. 

It took years to identify who was collecting and holding important data sources, convene these actors, and create working data partnerships. This process was ultimately successful because it broke down political obstacles, enabling stakeholders to identify common interests and build understanding. Once key stakeholders developed a foundation of trust and common goals, the project built a data platform with multiple data sources that is now used for agriculture and food security decision making at the national, local, and household levels.

Cross-sector collaboration: the Coalition for Digital Environmental Sustainability.

The first flagship report by the Coalition for Digital Environmental Sustainability (CODES) lays out a roadmap for sustainable digital transformation “in which all stakeholders play a role.” The irony here, as Digital Planet for Sustainability states, is that half of all people globally do not have access to the internet. In seeking to bring together two global movements—digital transformation and environmental sustainability—the authors thus make achieving universal connectivity by 2030 a primary goal of the project: "Action cannot be undertaken by governments alone; success depends on deep collaboration, trust, and transparency across civil society, governments, and the private sector. Creatively combining bottom-up and top-down approaches, as well as high- and low-tech solutions, will be critical to successfully tackling this many-headed problem." A broad range of stakeholders must come together to determine the extent to which digital technology contributes to a more sustainable, equitable, safe, and prosperous future. 

Community engagement and ownership: Indigenous data sovereignty.

The open data movement promotes the advancement of scientific knowledge, but it does not address profound historical inequalities associated with Indigenous data stewardship. This makes data sharing a double-edged sword for historically marginalized people around the world. The Group on Earth Observations (GEO) Indigenous Alliance advocates for Indigenous Data Sovereignty (IDS), to strengthen people’s right to participate in decision making in ways that are consistent with their values and collective interests. This fundamental tension between data sharing and the rights of Indigenous Peoples to control their data can only be resolved through meaningful collaboration with Indigenous Peoples.

In 2019, the Global Indigenous Data Alliance (GIDA) created the CARE Principles for Indigenous Data Governance to complement existing FAIR Principles for Scientific Data and provide a roadmap to ensure that Indigenous Peoples rights are at the heart of data endeavours. The GEO Indigenous Alliance is drawing attention to these power imbalances and working to ensure that CARE principles are applied by the GEO community. Here we see how collaboration, rather than being a challenge, is the means of enabling interoperability.

Seeking input and looking ahead 

Technical platforms and data-driven solutions can be a force of change for good, but experience shows that they require foundations of trust, collaboration, and mutual understanding. Getting the technical side of interoperability figured out isn’t easy, and the human side can be even harder. It requires time, energy, and money. Building working partnerships requires staff with specific skills to facilitate productive collaboration and may also demand that stakeholders themselves change, developing their skills and shifting organizational cultures.

To better understand these human dimensions, the Data Values Project’s leaders want to dig into the concept of human interoperability. Contact us at to tell us what you think and share your experiences.