Sooner or later, most research-performing organisations decide they need a better grip on their research information — on who is doing what research, what outputs result, what funding supports it, and how it all connects. The usual answer is a current research information system (CRIS): the central system that brings together information about an institution’s research activity. But the most common mistake in adopting one is to treat it as a procurement exercise — a matter of choosing and installing software. A CRIS is only as good as the data that flows into it, the governance that keeps that data trustworthy, and the people and processes that sustain it. Whether an implementation succeeds depends less on the product chosen than on the institution’s research-information-management (RIM) maturity. This article examines what that maturity involves, drawing on the research information systems domain of the CASRAI Dictionary and on our wider learning resources.
What RIM maturity means
Research information management maturity describes how developed and capable an institution is at managing information about its research — not in terms of the software it owns, but its practices. A mature organisation has clarity about what research information it holds and why; it has agreed definitions and consistent data; it has governance that assigns responsibility for quality; and it has a culture in which keeping that information accurate is a normal, valued activity rather than a periodic scramble. A less mature organisation may have data scattered across spreadsheets and disconnected systems, defined differently in each, owned by no one in particular, and trusted by few. The concept is useful because it shifts the question from “which system should we buy?” to “how ready are we to use one well?”. A CRIS dropped into an immature environment tends to automate existing confusion; one built on solid foundations can be transformative.
Data governance as the foundation
At the centre of RIM maturity lies data governance: the framework of policies, responsibilities and processes that determines how research information is defined, who is accountable for it, and how its quality is maintained. Governance answers the unglamorous but decisive questions on which a CRIS depends. What exactly do we mean by a “publication” or a “project”? Who ensures a researcher’s outputs are recorded correctly? How do we resolve conflicting records of the same thing? What is our authoritative source for each kind of information? Without answers, a CRIS becomes a tidy-looking container for untrustworthy data, and the reports it produces — for funders, for assessment, for management — cannot be relied upon. Strong data governance is what makes the information in a CRIS trustworthy, and trustworthiness is the entire point. Establishing governance is therefore not a step that follows implementation; it is the foundation on which a successful implementation is built.
Interoperability and the role of CERIF
A CRIS does not, and should not, stand alone. It needs to exchange information with many other systems — institutional repositories, human-resources and finance systems, funder platforms, persistent-identifier registries and national infrastructures. This makes interoperability a central concern, and it is where shared standards become essential. The Common European Research Information Format (CERIF) is a standard data model for research information, developed to enable research-information systems to exchange data in a consistent, structured way. By describing research entities — people, projects, outputs, organisations, funding — and their relationships in a common model, CERIF allows information to move between systems without being garbled or lost. The standard is maintained and promoted by euroCRIS, the international organisation dedicated to research information and the CRIS community. Choosing a CRIS without attention to interoperability is choosing a future island; designing for exchange from the start, with standards like CERIF in mind, is what lets a CRIS take its place in a connected ecosystem rather than becoming another silo.
Planning an implementation
With maturity, governance and interoperability understood, a CRIS implementation can be approached as the organisational change it really is. Several considerations recur:
- Start with purpose. Be clear about what the CRIS is for — reporting, assessment, profiles, discovery — because purpose drives every later decision about scope and data.
- Audit existing information. Understand what data the institution already holds, where it lives, how good it is and who owns it, before bringing it together.
- Establish governance early. Agree definitions, responsibilities and authoritative sources before loading data, not after.
- Design for interoperability. Plan how the CRIS will connect to repositories, identifiers and external systems, using shared standards from the start.
- Invest in people and process. A CRIS changes how researchers and administrators work; engagement, training and clear processes matter as much as the technology.
Connecting to the wider ecosystem
A well-implemented CRIS becomes a hub that links an institution’s research information to the world beyond it — feeding national assessment exercises, exchanging data with funders, connecting to repositories, and using persistent identifiers to disambiguate people and organisations. The richer this connectivity, the more value the CRIS delivers and the less manual re-entry it demands. This is why interoperability standards, persistent identifiers and the federation of research information — explored in our resources on research administration — are not optional extras but the very things that turn a CRIS from an internal database into part of a connected scholarly infrastructure.
A consistent vocabulary beneath it all
Every theme here — consistent data, governance, interoperability, exchange with other systems — depends on one requirement: that the elements of research information mean the same thing across systems and institutions. A “project”, an “output” or a “contributor role” must be defined compatibly, or no amount of technology will make the data line up. That consistency is what the CASRAI Dictionary provides: a shared vocabulary so that the information held in and exchanged by a CRIS is understood identically wherever it travels. And because so much of what a CRIS records is contribution, that contribution can be described in the same shared framework, the CRediT taxonomy. A CRIS is not bought; it is grown, on foundations of mature practice, sound governance, shared standards and a common vocabulary.