Research intelligence for universities: turn your publications into strategy

Every university already produces the data that should drive its research strategy. Tens of thousands of publications, each with authors, citations, fields, journals, and an open-access status. A repository full of theses, datasets, and full text. Researcher identities, grants, and faculty rosters. The problem isn't a shortage of data — it's that answering a simple leadership question ("how do we compare to our peers on open access?") means a licensed bibliometric tool, a manual export, and an analyst who is always a few weeks behind.

This guide is for research offices, libraries, and university leadership who want to stop treating bibliometrics as an annual report and start treating it as live intelligence.

What "research intelligence" actually means

Research intelligence is the ability to answer questions about your institution's research output — its volume, impact, openness, integrity, and collaboration — without commissioning a project for each one. It's the difference between "we'll pull that for the annual review" and "let me check" in the middle of a meeting.

Concretely, it answers four kinds of question:

• Output & impact — How much are we publishing, in which fields, and how is it cited?
• Standing — How do we rank against comparable institutions?
• Openness — What share of our work is open access, and where are the gaps?
• Integrity — Are any of our publications retracted, and who is linked to them?

The data to answer all of these already exists. It just needs to be in one place that anyone can ask questions of.

The data that matters

You don't need a data warehouse. You need to connect a handful of sources and let them join.

1. Open bibliographic data (by ROR)

The anchor source is the open bibliographic record of your institution's output, identified by your ROR (Research Organization Registry) id. It provides every indexed work with its authors, citations, publication year, type, journal, primary topic and field, open-access status, field-weighted citation impact (FWCI), and even retraction flags — for the whole institution, with no licensed key. This single source powers output analytics, author metrics, topic analysis, benchmarking, and integrity monitoring.

2. The institutional repository (DSpace and equivalents)

Your repository holds what the bibliographic record doesn't: deposits, full text, embargo status, and the items your researchers actually submitted. Connecting it lets you reconcile indexed output against deposited output — which is exactly where open-access compliance gaps hide.

3. Researcher identity (ORCID)

ORCID ties works to people unambiguously, which makes per-researcher profiles and a researcher self-service portal possible.

4. Internal systems (grants, HR, faculty rosters)

Grants spreadsheets and the faculty roster live in your own databases and Excel files. Joined with publication data, they answer the questions funders ask: output per grant, output per department, productivity by faculty cohort.

The questions worth asking

Once these sources sit in one queryable workspace, the valuable questions are the ones that used to take weeks.

Output & impact:

• "Show publications and citations by year for the last decade, with field-weighted impact."
• "Which fields are we strongest in by citations, and which are growing fastest?"
• "Who are our 20 most-cited researchers, and what is each one's h-index?"

Peer benchmarking:

• "Rank us against the other universities in our country by total citations."
• "How does our open-access share compare to our three closest peers?"
• "Where do we sit on field-weighted impact versus the regional average?"

Open-access monitoring:

• "What's our gold / green / hybrid / closed mix, and how has it changed over five years?"
• "Which high-impact papers are still closed — the ones worth prioritising for opening?"
• "What's our OA share by field, and where is compliance weakest?"

Research integrity:

• "How many of our indexed publications are retracted, and in which years?"
• "Which researchers are linked to retracted work, and how many each?"
• "Are any retracted papers still being cited?"

Collaboration & people:

• "Show the co-authorship network for this researcher — who do they actually work with?"
• "Which researchers are the most connected hubs in the institution?"
• "Which departments collaborate the least with each other?"

None of these should require a ticket. They should each take a sentence.

Why a connection beats another dashboard licence

The usual answer to "we need research intelligence" is to buy a bibliometric platform with a fixed set of dashboards and a per-analyst seat. That gets you exactly the views the vendor built, for exactly the people who have a login.

The alternative is to put the data in a workspace where:

• Anyone can ask in plain language — English, Arabic, or any other. "How many open-access papers in Engineering since 2020, and which are most cited?" returns a chart, and the answer comes back in the language you asked in. No SQL, no seat for every analyst.
• The curated screens are still there. A dashboard, publications and author explorers, a peer-benchmark view, an open-access monitor, an integrity view, and per-researcher profiles with an interactive co-authorship network.
• Reports are repeatable. Build an annual-output or OA-compliance report once; refresh it with one click next cycle.
• An autonomous analyst gives you the briefing. Pointed at the data, it produces the "what matters" summary — what's growing, where open access is lagging, what to watch on integrity — instead of waiting for someone to ask the right question.

The point isn't a prettier dashboard. It's that the same underlying data serves the dean's benchmark view, the librarian's OA monitor, the integrity officer's retraction scan, and a researcher's own profile — from one connection.

Getting started

The first slice is one end-to-end vertical, and it's fast:

1. Connect your institution by ROR. The full publication and author corpus ingests automatically — every work, every researcher — and joins like any other data source.
2. The screens populate. Output, benchmarking, open access, integrity, and researcher profiles all render off the ingested data immediately.
3. Ask, report, brief. Chat with the data for ad-hoc questions, build shareable reports, and let the analyst produce the standing briefing.
4. Keep it current. A scheduled refresh re-pulls the corpus so the numbers stay live, not annual.

Add the institutional repository next, then ORCID for the researcher portal, then your internal grants and roster data — each one makes the questions richer without rebuilding anything.

Research intelligence isn't a report you commission once a year. It's a question you can answer in the meeting you're already in.