GRF · Research Nexus
Collaborative research
Much risk research is now done by consortia: universities, public agencies, international organisations and private partners working under one agreement. How those collaborations are governed decides who sets the questions, who controls the data, who is named as author and who carries responsibility when something goes wrong. This page sets out how research communities form and fail, how their governance can be observed, and which institutions hold the decisions.
Collaborative research in seven parts.
- 01The questionCollaborative research: how the risk develops
- 02IndicatorsWhat is measured, and how well
- 03SourcesWhere the evidence comes from
- 04DecisionsWho decides, and what the evidence serves
- 05Core questionsWhat experts ask about research collaboration
- 06MechanismsWhat makes collaboration work
- 07Methods and limitsPractices for collaborative research
Collaborative research: how the risk develops.
Institutional research communities. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Agreements set power
Consortium and data-sharing agreements fix ownership, publication rights and decision rules early. Partners with legal capacity and control of funding shape the terms, and imbalances persist for the life of the project.
Credit is contested
Authorship and contribution rules vary by field. Without agreed criteria, junior researchers, data collectors and partners in lower-income settings are under-credited, which weakens the next collaboration.
Data stay siloed
Data collected under one agreement are often unusable by others because consent, licences or formats do not permit reuse. The community repeats collection instead of building on what exists.
Momentum ends with funding
Networks built around a grant lose staff, infrastructure and memory when the grant ends. Knowledge held in people rather than records disappears, and the next collaboration starts again.
Evidence synthesis workspace.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Evidence synthesis workspace
Collaborative research · Science-policy panel · Synthesis SY-95
- Records found4828
- Screened2382Active
- Included68Normal
- Reviewer agreement0.83kappaNormal
Systematic review
- QuestionPICO
- Protocolregistered
- Search5 databases
- Screentwo reviewers
- Extractform v2
- Appraisecertainty
- Briefpolicy owner
Certainty of evidence
| Reduced losses | 5 | Moderate | Benefit |
| Faster recovery | 4 | Low | Unclear |
| Equity of access | 3 | Very low | Unclear |
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Multi-institution awards by funder | count of awards | annual | Funder award records | Published statistics |
| Outputs with contributor role statements | percent of outputs | annual | Publication metadata | OBSERVED |
| Datasets deposited with persistent identifiers | count per project | per project | Repository and DOI records | OBSERVED |
| Lead institution location by income group | share of awards by World Bank income group | annual | Funder award records | Published statistics |
| Consortia with published data-sharing terms | percent of projects | per project | Project disclosures | DECLARED |
| Networks active after funding ends | share of networks | periodic | Follow-up surveys | REPORTED |
How collaborative research is governed: instruments, mandates and commitments.
The instruments, mandates, actors and accountability arrangements a policymaker, diplomat or development agency works with, citing the agreements that set them. Structures follow the frameworks named. Any state or progress drawn is illustrative, not a record.
Who holds which role
The actors around collaborative research: who decides, who implements, who finances and who brings knowledge and voice.
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| CORDIS (European Commission) | Partners, roles and outputs of EU-funded collaborative projects | Free reuse, attribution |
| NIH RePORTER and NSF award search | Awards, collaborating institutions and linked publications | Public domain |
| OpenAlex | Co-authorship and institutional affiliation networks | Open, CC0 |
| DataCite metadata | Persistent identifiers and metadata for deposited datasets | Open, CC0 |
| ORCID public data file | Researcher identifiers linked to works and affiliations | Open, CC0 |
| CRediT contributor roles taxonomy (NISO) | Standard contributor roles used in publication metadata | Open standard |
Who decides, and what the evidence serves.
Research Nexus prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Research funders and councils | Which governance, data and authorship terms to require of funded consortia | Comparative agreement terms; evidence on partnership equity and data reuse |
| University research and legal offices | Which consortium and data-sharing terms to accept | Model agreements and their known problems; dialogue records from partners |
| Intergovernmental and international research programmes | How to structure lead and partner roles across countries | Patterns of lead institution location and credit; records of partner experience |
| Data repositories and infrastructure bodies | Which metadata and access terms to require at deposit | FAIR practice; reuse barriers recorded in dialogue |
Outputs this topic produces
- Peer learning briefs comparing consortium agreement terms
- Dialogue records on authorship and data rights in partnerships
- Methods seminars on network analysis of research communities
- Notes on what research communities need to keep after funding ends
What experts ask about research collaboration.
- Who sets the research questions, and do all partners have a real voice?
- How are credit, data and intellectual property shared?
- How does the collaboration survive beyond its first funding cycle?
- Do partners from less-resourced institutions gain lasting capacity, or only provide data and access?
What makes collaboration work.
Studies of research collaboration identify a few recurring conditions for success: shared goals that partners helped define, clear agreements on data, authorship and intellectual property, sustained coordination capacity, and trust built through repeated interaction. Collaborations that are designed by one partner and staffed by others tend to produce less and dissolve when funding ends.
Equity is a persistent issue. In many international collaborations, researchers from lower-income countries have been treated as data collectors rather than co-investigators, with limited authorship and little lasting capacity. Fair partnership practice addresses this through shared leadership, budget control and capacity investment.
Why now: cross-border research collaboration on risk depends on agreements about data, credit and access that are often settled late. Research Nexus convenes research institutions and funders on those terms, records what works, and can propose common agreement elements as change proposals to the Nexus Standards.
Practices for collaborative research.
Good practice is increasingly documented, but much of it is learned by doing. Comparing how different collaborations handled the same problems, such as a partner leaving or a dispute over data, is a core use of dialogue.
- 01
Collaboration agreements
Written terms for governance, data, authorship and intellectual property. Limits: take time to negotiate and cannot anticipate everything.
- 02
Fair partnership frameworks
Principles for equitable international research partnerships. Limits: voluntary and unevenly applied.
- 03
Network analysis of collaboration
Studying co-authorship and partnership patterns. Limits: publications capture only part of collaboration.
- 04
Evaluation
Assessing what collaborations achieve, using causal inference and impact evaluation. Limits: long-term effects are hard to attribute.
How it is studied, and what the methods cannot say.
- 01Policy, institutional and decision scienceComparing science advice systems · Mapping integrity proceduresApplied here
- 02Probability and statisticsBuilding bibliometric indicators · Detecting selective reportingApplied here
- 03Causal inference and impact evaluationEvaluating funder policy changes · Assessing knowledge brokerage schemesApplied here
Questions and answers.
What is a contributor role statement?
Why do equitable partnership terms matter?
Can collaboration be measured from co-authorship?
Who owns the data in a research consortium?
Can Research Nexus help form a research consortium?
Who owns data produced in a collaboration?
What is fair partnership?
Does Research Nexus keep a list of collaborations?
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Legal documents.
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