Research Data Management: About

Research data is the recorded information necessary to support or validate a research project’s observations, findings, or outputs.

Research data depending on discipline can be textual, numerical, qualitative, quantitative, final, preliminary, physical, digital, or print.

Sources:  Research Data Oxford

Open Data is freely available on the internet, permitting any user to download, copy, analyze, re-process, pass to software, or use for any other purpose without financial, legal, or technical barriers.

Source: SPARC

NO! All research data can not be open reasons legal, commercial, etc. However, all research data should manage!

"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. 

Source: Research Data Oxford

Data management is a key part of responsible research.  Good practice in managing your data will ensure benefits ensue for you, your fellow researchers and the wider public.

• Funding and regulatory body requirements are met.
• Research data remains accurate, authentic, reliable and complete. 
• Duplication of effort is kept to a minimum.  
• Research data keeps its integrity and research results may be replicated.   
• Data security is enhanced, thus minimising the risk of data loss.