Research Data Management, or RDM as you will often see it referred to, is simply managing and organizing the data that is generated as a result of your research throughout the entire research life cycle. You certainly have some form of RDM already; this guide is intended to relate current best practices and assist you in taking what you are already doing to the next level.
Why should you care?
- you can better find and recognize your data both during and after your research - especially if team members come and go
- your funder may require that you have a Data Management Plan and/or that you deposit your data in a repository once the research is complete
- by depositing that data, you are contributing to open science - the ability for others to potentially reuse your data, or replicate your study
Overall, RDM is just good practice!
Remember, Data can be widely defined and can include everything from massive SPSS files, to photographs, to handwritten field notes, to an excel spreadsheet... and far, far more! Basically anything you generate in the process of research. The Tri-Agency RDM Policy FAQ defines it::
- What are data?
Data are facts, measurements, recordings, records, or observations about the world collected by researchers and others, with a minimum of contextual interpretation. Data may be in any format or medium taking the form of writings, notes, numbers, symbols, text, images, films, video, sound recordings, pictorial reproductions, drawings, designs or other graphical representations, procedural manuals, forms, diagrams, work flow charts, equipment descriptions, data files, data processing algorithms, or statistical records.Footnote 1
- What are research data?
Research data are data that are used as primary sources to support technical or scientific enquiry, research, scholarship, or artistic activity, and that are used as evidence in the research process and/or are commonly accepted in the research community as necessary to validate research findings and results. All other digital and non-digital content have the potential of becoming research data. Research data may be experimental data, observational data, operational data, third party data, public sector data, monitoring data, processed data, or repurposed data