Reference

Core Terms

  • RDM (Research Data Management): Planning, organising, storing, documenting, sharing, and preserving research data across the project lifecycle.
  • DMP (Data Management Plan): A living plan describing how data will be collected, stored, documented, shared, retained, and preserved.
  • FAIR: Data principles that aim to make data Findable, Accessible, Interoperable, and Reusable.
  • Metadata: Descriptive information that helps data be understood, located, and reused.
  • Data lifecycle: The sequence from planning and collection through analysis, sharing, preservation, and reuse.
  • Personal data: Information relating to an identified or identifiable person.
  • Special category data: More sensitive personal data, such as health, genetic, biometric, race, religion, or sexual orientation data.
  • Lawful basis: The legal justification for processing personal data under UK GDPR.
  • DPIA: Data Protection Impact Assessment used to identify and reduce data protection risks.
  • Data controller: The organisation that decides why and how personal data are processed.
  • Processor: A party processing data on behalf of the controller.
  • Ethics review: Formal review of research involving humans, personal data, or other significant risks.
  • Retention: How long data are kept.
  • Preservation: Longer-term keeping of data so they remain usable and understandable.
  • Version control: A way of tracking changes to files, code, documents, or datasets over time.
  • Reproducibility: The ability to understand, check, and rerun a workflow or analysis.

Institutional Platforms

Platform Typical use
Microsoft 365 Day-to-day collaboration, communication, writing, and spreadsheet work
OneDrive Individual working storage with sync and version history
Teams Group communication, meetings, and shared project working space
SharePoint Collaborative document storage with permissions and longer-lived team spaces
RIS (Worktribe) Research lifecycle tracking, outputs, grants, and linked researcher information
UniCore Finance, HR, procurement, and operational research administration
ORCID Persistent researcher identifier used to maintain a consistent research identity
TRE Secure Storage Restricted environment for sensitive or confidential data
CPS Research Storage Group-managed research storage for backed-up project data

Quick Decision Guide

Where should this work live?

Situation Usually the best fit
Personal draft notes or early working files OneDrive
Shared project documents used by a team Teams / SharePoint
Sensitive or confidential research data Approved secure storage such as TRE Secure Storage
Proposal, output, or institutional research record RIS (Worktribe)
Finance or procurement workflow UniCore
Public researcher identity and linked outputs ORCID plus institutional systems

Before you share a file or dataset

Ask:

  1. Does it contain personal, confidential, or commercially sensitive information?
  2. Is the storage location approved for that level of sensitivity?
  3. Are permissions set to the smallest group that needs access?
  4. Is there enough documentation for someone else to understand the file?
  5. Have you recorded the version, source, and context?

Practical Good Practice

File and folder naming

Use names that are consistent, sortable, and readable.

2026-03-23_interview-theme-summary_v01.docx
project-alpha/
  raw-data/
  cleaned-data/
  documentation/
  outputs/

Helpful patterns:

  • use dates in YYYY-MM-DD format
  • avoid spaces if files move across systems regularly
  • use meaningful version labels such as v01, v02, final-reviewed
  • separate raw, cleaned, and derived data

Minimum documentation to keep

For most projects, try to retain:

  • who created or updated the file
  • when it was created or changed
  • what the file contains
  • how values, variables, or categories should be interpreted
  • what processing or transformation has already happened
  • where the authoritative version is stored

Metadata prompts

If you are not sure what metadata to record, start with:

  • title
  • creator or owner
  • date
  • format
  • location
  • description
  • methods or source
  • access restrictions
  • reuse conditions

Governance and Compliance Reminders

  • Ethics approval and data protection are related but not identical.
  • Consent is important, but it is not automatically the lawful basis for research processing.
  • Personal data can include indirect identifiers, not just names and email addresses.
  • Sensitive data requires both stronger justification and stronger safeguards.
  • A good DMP should match your real storage, access, sharing, and retention practices.

Data Quality and Analysis Prompts

When reviewing a dataset or chart, ask:

  • What exactly does each row represent?
  • Are categories used consistently?
  • What is missing, ambiguous, or mixed together?
  • What would a collaborator misunderstand without explanation?
  • Does the chart help interpretation or distort it?
  • What action is the audience expected to take from this output?

AI Use in Research

Use AI most safely when you define:

  • the task
  • the context
  • the source boundary
  • the output format
  • the verification step

A useful prompt pattern:

Help me with [task] for [context]. Use [source or boundary]. Return the result as [format]. Flag uncertainty and do not invent evidence.

Before using AI on research work, ask:

  1. Is the material safe to paste into this tool?
  2. Do I need to use only approved or institutionally permitted services?
  3. What part of the answer must I verify manually?
  4. Am I asking for support, or am I trying to outsource judgement?

End-of-Course Checklist

By the end of the course, you should be able to:

  • choose more appropriate tools for collaboration and storage
  • explain key governance and RDM concepts in practical terms
  • design a clearer folder structure and documentation approach
  • critique charts and data summaries more confidently
  • turn an analysis result into a clearer action or recommendation
  • use AI in a more selective, source-aware, and defensible way