I was recently asked to speak on the topic of “Data Visiting as Design-Based Stewardship Supporting a Multi-Dimensional Governance Configuration.” I want to take issue with a word in that title.

The word is “stewardship.” It is the wrong frame.

Stewardship avoids the language of ownership. A steward keeps something safe. An owner uses something. An owner has legal rights — the right to exploit, to license, to build value. A steward has none of those rights.

Why does this matter? It matters because in Africa, we need institutions — universities, hospitals, biobanks, research councils — to understand themselves as owners of data. Ownership has legal bite. Ownership means you can decide how your data is used, who benefits, and on what terms. If African institutions see themselves merely as stewards — as custodians keeping data safe until someone from the Global North comes to analyse it — then we have not escaped data colonialism. We have institutionalised it.

Data visiting, properly understood, is a tool that empowers data owners. It allows an institution to say: you may analyse our data, but on our terms, in our environment, under our control. That is not stewardship. That is ownership in action.

What data visiting is — and what it is not

Data visiting is a form of data sharing in which data are analysed within the provider’s computing environment, without being physically transferred. The researcher visits the data; the data does not travel to the researcher.

Data visiting is not the entirety of data governance. Ethics committees, data access committees, institutional review boards, data use agreements — all of these remain part of the governance landscape. What data visiting offers is something different: it is a design-based governance tool that can be integrated into a broader governance framework. It gives data owners a configurable technical architecture through which governance decisions can be implemented directly.

A call for terminological convergence

Before going further, a point on terminology. The field must converge on data visiting — not “data visitation,” not other variants. GA4GH has adopted “data visiting.” The academic literature overwhelmingly uses “data visiting.” If we are serious about building a shared governance vocabulary, we cannot afford terminological fragmentation. The concept is hard enough to communicate without muddying it with competing labels. Data visiting is the term. Let us use it consistently.

The one-dimensional trap

Too often, we hear: “We use data visiting” — as if that settles the governance question. It does not.

Consider two systems. In the first, the researcher has full autonomy to run custom code on identifiable data, with unrestricted output — that is data visiting. In the second, the researcher submits a fixed query and receives only reviewed aggregate statistics — that is also data visiting. The governance implications could not be more different.

Saying “we do data visiting” is like saying “we have a contract.” It tells you nothing about the terms. Data visiting is not one thing. It is a configuration space — a multi-dimensional design surface. And if you reduce it to one dimension, you will get your governance wrong.

Seven dimensions, seven governance levers

This is why I developed the Seven-Dimensional Data Visiting Framework — the 7D-DVF. It disaggregates data visiting into seven adjustable dimensions: researcher autonomy, data location, data visibility, the nature of the shared data, output governance, the trust and control model, and auditability and traceability.

Each dimension is a governance lever — a concrete design decision with direct legal and ethical consequences. Researcher autonomy: how much freedom does the visiting researcher have? Data visibility: can they see raw records, or only aggregates? Output governance: are results reviewed before release, or exported freely?

The power of the framework is that it makes the governance configuration legible. An ethics committee reviewing a data visiting proposal can assess each dimension independently and ask: is this calibration proportionate to the risk? And a data owner — an African university, a national biobank — can use these levers to assert control over how their data is accessed, on their terms, in service of their priorities.

Design as governance

This brings me to the central insight. In data visiting, design functions as governance. When you choose to restrict data visibility to query-only access, that is a governance decision implemented through technical design. When you require output review before release, that is governance embedded in the system architecture.

Data visiting gives data owners the ability to embed governance decisions directly into the technical infrastructure. This is not governance layered on top of a system — it is governance built into the system. The 7D-DVF provides the language and the structure to do this rigorously, deliberately, and in a way that serves the interests of the data owner.

For Africa, this is transformative. It means that an institution that owns genomic data can participate in global research collaborations without surrendering control — without the data leaving, without ceding sovereignty, and with every governance parameter configured to build local capacity and contribute to an African bio-economy. Not as shepherds. As owners.

A challenge

Stop treating data visiting as a binary. It is a multi-dimensional configuration space. Stop saying “we do data visiting” as if that answers the governance question. Specify which data visiting — along how many dimensions, calibrated to what risks, in what legal and ethical context. And recognise data visiting for what it is — not a stewardship tool, but an ownership tool. A tool that lets data owners govern on their own terms, build their own capacity, and participate in global science as equals.

The tools exist. Use them.