Research Data Management: Research Data Management

How can I best manage my data throughout the lifecycle of my research to save time and money in the future?

"Data Management refers to the storage, access, and preservation of data produced from a given investigation. Data management practices cover the entire lifecycle of the data, from planning the investigation to conducting it, and from backing up data as it is created and used to long-term preservation of data deliverables after the research investigation has concluded..."

Source: CASRAI. (n.d.). Research Data Management Glossary. 

Includes:

• Planning how your data will be looked after – many funders now require data management plans as part of applications
• What do you do with your data on a day-to-day basis over the lifetime of a project? (storage, backup, organization, etc.)
• What happens to data in the longer term – what do you do with it after the project concludes?

Both research funders and publishers increasingly expect that data resulting from research projects should be made available for scrutiny and re-use, whenever legal and ethical requirements allow. 

What data should I manage?

We refer to research data as any information or artifact that serves as evidence for a research discovery or result. Data can be qualitative (e.g., text interviews, images and videos, audio recordings) or quantiative (e.g., tabular data, structured databases). Our focus here is on digital data, both qualitative and quantiative.

As part of your research data management you should manage any data and code, as well as documentation about them, that are created or used as part of a research project. This might include:

• Quantitative and qualitative data
• Primary (raw) and secondary (cleaned or analyzed) data
• Notes
• Laboratory or research notebooks
• Codebooks
• Code or software used to run data analyses
• Data workflows or pipelines
• Metadata (documentation describing the data)

Overall, you should know the location of all data produced by or used in a research project. It should be annotated sufficiently so that others can understand and reproduce your work, and possibly re-use your data in future studies.

Source: Research Data Oxford