Research data or datasets are the evidence collected during the course of a research project which can be used to support, validate, or reproduce the project’s published findings. These data can be quantitative or qualitative, digital or physical, and can be collected through a range of methods or derived from existing sources. This could include statistics, collections of images, survey data, results of experiments, or many other forms of data.
Research Data Management (RDM) covers the entire research data lifecycle – essentially everything that a researcher might do with their data. This includes collection, storage, curation, publication, archiving and disposal.
Good data management is fundamental to the research process. It is a dynamic process that must be carefully considered throughout the course of a research project, from the planning stage through to final publication of results.
The Library's Open Research Team can provide support and guidance on:
Funder requirements, Data Management Plans, Copyright, Uploading your Datasets to Pure & Processing applications for the Active Data Storage Service.
Watch this video to discover about the basics of Research Data Management and how to apply this when creating or reviewing a Data Management Plan (DMP). This video discusses data formats and metadata standards, persistent identifiers, licensing, controlled vocabularies and data repositories.
The presentation slides available here.
The University has a Research Data Management Policy (see below) which applies to all researchers, including postgraduate research students. Anyone undertaking or supporting research at Queen’s should ensure that they are familiar with the Policy and the supporting guidance. In summary, the Policy states that: