CASRAI Dictionary

Tag: implementation

  • Knowledge mobilisation: translating research into policy and practice

    There is a comfortable assumption, still widespread, that good research speaks for itself — that if findings are sound and published, the world will notice and act. The reality is otherwise. The distance between a finding sitting in a journal and that finding changing a policy, a clinical practice or a professional routine is often vast, and it is rarely crossed by accident. Bridging it is a discipline in its own right, variously called knowledge mobilisation, knowledge translation or knowledge exchange: the deliberate, skilled work of moving research into the hands of the people who can use it, in a form they can act on. This article examines that work, drawing on the engagement, impact and SDG domain of the CASRAI Dictionary.

    Why dissemination is not enough

    For a long time the implicit model of getting research used was a one-way push: do the research, publish it, perhaps issue a press release, and assume uptake will follow. This model fails repeatedly, and understanding why is the starting point for everything else. Practitioners and policymakers are busy, work under different pressures and timescales than researchers, and rarely read academic journals. Research findings often arrive in a form — long, hedged, technical — that is ill-suited to a decision that must be made next week. And evidence almost never speaks with one voice; using it well requires interpretation, contextualisation and judgement about how it applies in a particular setting. Simply making research available, in short, does very little. Getting it used requires actively engaging with the people who might use it, understanding their needs, and shaping the evidence so it can inform what they actually do.

    The Knowledge-to-Action cycle

    One of the most widely used frameworks for thinking about this is the Knowledge-to-Action cycle, which models how knowledge moves from creation into application. It distinguishes the knowledge creation process — in which raw research is refined and synthesised into more usable forms such as syntheses and tools — from an action cycle of activities involved in applying knowledge: identifying a problem and the relevant knowledge, adapting it to the local context, assessing barriers and facilitators to its use, selecting and tailoring interventions, monitoring use, evaluating outcomes, and sustaining the change. The framework’s great value is that it treats application as an active, iterative process with its own steps, rather than as something that simply happens once research exists. It makes clear that adapting knowledge to context, and attending to the barriers in a particular setting, are not afterthoughts but central to whether evidence ever gets used.

    Tools of the trade

    Knowledge mobilisation has developed a repertoire of practical instruments and tactics. Among the most important:

    • Policy briefs. Short, accessible documents that distil what the evidence says on a question into a form a policymaker can absorb quickly — framed around the decision at hand, clear about implications, honest about uncertainty.
    • Plain-language summaries. Versions of research stripped of jargon and written for a non-specialist audience, so that the substance is reachable by those who need it.
    • Engaging users early. Involving the eventual users of research — practitioners, policymakers, communities — in shaping the questions and the work from the outset, so the research is relevant and the relationships exist when it is time to act.
    • Tailored interaction. Workshops, briefings, secondments and sustained relationships that move evidence through conversation and trust rather than through documents alone.

    What these share is a recognition that mobilisation is relational and active. Evidence travels through people and relationships, not merely through publications.

    Boundary organisations and brokers

    Because the worlds of research and practice differ in language, culture and incentives, a special role has emerged to span them: that of the boundary organisation and the knowledge broker. Boundary organisations sit deliberately between research and policy or practice, translating in both directions, building relationships, and helping each side understand the other. Knowledge brokers are the individuals who do this work — people fluent in both worlds who can interpret research for users and convey users’ needs back to researchers. Their importance reflects a hard-won lesson: the gap between knowledge and action is often best bridged not by asking researchers to become communicators or policymakers to become scholars, but by sustaining intermediaries whose explicit job is to connect the two. Investing in these connective roles is frequently what turns sporadic, accidental uptake into reliable flow.

    Mobilisation as part of impact

    Knowledge mobilisation is closely tied to the wider conversation about research impact — the difference research makes beyond academia — but it is the active practice rather than the retrospective measurement. Where impact assessment asks what difference research made, mobilisation asks how to make that difference happen, and does the work of bringing it about. The two are complementary: mobilisation is the cause, demonstrable impact often the effect. Recognising mobilisation as skilled, valuable work in its own right — rather than as something researchers should do in their spare time — is part of valuing the full range of what research careers involve, a theme explored in our resources on research practice and impact.

    Recording mobilisation consistently

    For mobilisation activity to be recognised, planned and connected to the research and people behind it, it has to be describable in consistent terms across institutions, funders and reporting systems — what was produced, for whom, through what route, with what uptake. That consistency is what the CASRAI Dictionary provides: a shared vocabulary so that engagement and mobilisation activities are understood the same way wherever they are recorded. And because translating research into use is genuine, often substantial contribution, the work can be described within the same framework as every other — the CRediT taxonomy and its full set of contribution roles. Producing knowledge is only half the task; mobilising it — deliberately, skilfully, in partnership with those who can use it — is how research earns its keep in the world.

  • Research information management maturity: planning and implementing a CRIS

    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.