DR-02 — Research Data Management Platforms

Purpose: Profile AI-enabled and Jisc-procurable research data management platforms for University of Sheffield evaluation. This is the largest single cataloguing gap in the landscape — only 2 tools are currently indexed against 35+ known platforms.

Use with: Claude Research mode (or equivalent deep research tool)


Prompt

You are helping a UK research university (University of Sheffield) build a catalogue of research data management (RDM) tools. The university uses a structured evaluation schema and needs profiles of the platforms listed below, organised by sub-area.

For each platform, research and return:

  1. What it does — one sentence description of primary function
  2. AI features — any AI/ML capabilities (automated metadata, smart search, classification, recommendations, etc.) — note “none” if the tool is not AI-enhanced
  3. Licensing model — open-source / freemium / subscription / institutional
  4. Jisc CHEST availability — is this available through Jisc CHEST or a Jisc-negotiated framework? Check chest.ac.uk and jisc.ac.uk/procurement
  5. GDPR/data residency — EU/UK hosting available? DPA available?
  6. Typical HE deployment — how many UK universities use it? Any named Sheffield region or Russell Group examples?
  7. Integration ecosystem — does it integrate with Pure, DSpace, ORCID, DMPonline, or other common HE research infrastructure?
  8. Catalogue status recommendation — suggest one of adopt | trial | assess | hold based on maturity and HE adoption

Sub-area A: Research Information Systems (CRIS)

Profile these platforms:

  • Pure (Elsevier) — CRIS and research output management
  • Symplectic Elements (Digital Science) — research information management
  • Converis (Clarivate) — research management platform
  • IRIS (Interfolio) — faculty and research lifecycle management

Sub-area B: Institutional Repositories

Profile these platforms:

  • DSpace — open-source institutional repository (DSpace-CRIS variant too)
  • EPrints — open-source repository software (University of Southampton origin)
  • Figshare for Institutions — commercial research data repository
  • Zenodo (CERN/OpenAIRE) — open research repository
  • Open Science Framework (OSF) — open research platform (Center for Open Science)

Sub-area C: Electronic Lab Notebooks (ELNs)

Profile these platforms:

  • RSpace (Research Space) — ELN and research data management
  • eLabFTW — open-source ELN
  • LabArchives — cloud-based ELN for academia
  • SciNote — open-source ELN
  • Labfolder (now part of MilliporeSigma/Merck) — ELN platform
  • Benchling — life sciences ELN and LIMS

Sub-area D: Data Management Planning

Profile these platforms:

  • DMPonline (Digital Curation Centre / DCC) — UK-standard DMP tool
  • Argos (OpenAIRE) — European DMP platform
  • DMP Tool (California Digital Library) — US-focused, but used internationally

Sub-area E: Open Infrastructure & Identifiers

Profile these platforms:

  • ORCID — persistent researcher identifiers
  • DataCite — persistent identifiers for research data (DOIs)
  • OpenAlex — open index of scholarly works, replacing Microsoft Academic Graph
  • FAIRsharing — registry of data standards, databases, and policies
  • UK Data Service — ESRC-funded social science data repository

Output format

For each sub-area, return a markdown table:

PlatformPrimary functionAI featuresLicensingJisc CHESTGDPR/data residencyHE adoption (UK)IntegrationsRecommended status

Follow each table with a short gap analysis: which platforms are absent from this list but commonly deployed in UK HE for this sub-area?

Finally, provide a top 5 priority list of platforms the University of Sheffield should create detailed tool notes for first, with one-sentence justification for each.


Context for prioritisation

The University of Sheffield:

  • Uses Pure (Elsevier) as its CRIS — already deployed, so focus on AI features within Pure
  • Uses DSpace for its institutional repository (ORDA — Online Research Data)
  • Uses DMPonline for data management plans
  • Has ORCID institutional membership
  • Seeks to understand the ELN landscape for wet-lab and field research
  • Is interested in AI-enhanced metadata generation, automated data deposit, and FAIR data tooling