Managing research outputs according to the research lifecycle: a phased approach
Phase 1: Output Management Planning
Knowing funders' policies & expectations; Writing Data Management Plans; Costing data management; Writing grant applications.
When do I need a Data Management Plan? Why they are useful; Tools, models and support.
Key questions to estimate costs; Time & budget-anticipating tools; Funding.
Using personal data in research; Ethical approval & registration; Anonymising data; Data protection; NHS data.
Collecting data; Collecting sensitive data; Organising data; Formats; Describing data: metadata & documentation; Analysing data; Improving software.
Choosing your formats; Text, images & audiovisual files; Recommended formats; Preservation; Dissemination.
Phase 3: Archiving, preserving and curating
Options for data storage; Information security; Long-term preservation & archiving; Storing sensitive & personal information; Retention & disposal of records.
Why preserve software; How to preserve software; Citing software; Archiving GitHub repositories.
Phase 4: Discovery, access and sharing
Handling copyright, Intellectual Property Rights & licences issues; Where to deposit data; Constraints to release data; Metadata, documentation & DOIs; Anonymising; Sharing publications; Citing data.
Finding data for re-use; Finding publications & projects; Citing data; Handling copyright, Intellectual Property Rights & licences issues; Analysing data.