Why manage your research data - the future self
The concept of the future self is helpful for understanding research data management. The hypothetical situation is as follows. A researcher:
- carries out some research and gathers some data;
- analyses the data; and
- publishes a paper based on the research and analysis.
Ten years pass. The researcher’s field moves on, a new method of analysis is developed and redefines the researcher’s discipline. The researcher wakes at 2am one night and sits bolt upright in bed thinking, "I could be on the front page of Nature if I re-analysed that data I collected ten years ago with my discipline’s fashionable new methodology!"
Within that thought experiment, research data management is all the things that the researcher wished she had done ten years ago to ensure that the data was findable and usable. These are the topics that are covered in these guidelines.
Over the last decade, expectations around research data management have risen along with the understanding that research data is an extremely valuable asset and resource. The scope of expectations around research data management has spread from during the research project, to before it (planning) and afterwards (curation, archiving, sharing). Accordingly we have seen the following shifts:
- an international push towards open data in the public sector, including in Victoria (e.g the Victorian Government Data Directory);
- research funders including the ARC and NHMRC setting requirements around research data management in the work they fund;
- an increasing understanding that research data should be preserved in order to facilitate verification of research results and prevent fraud;
- related requirements by publishers that data should be published alongside the publications derived from it;
- a related understanding that making research data available to others in various ways can support further research and innovation;
- increased expectations around responsible stewardship of the taxpayer funds that fund research activity and the generation of research data.
Complementing these increasing expectations, we have observed changing understanding around the benefits of good research data management for research and researchers:
- preventing loss of data through good storage;
- reducing research time lost to inefficient data management practice;
- improving research integrity, including in the verification of research results;
- increasing the visibility of your research and your research profile;
- enabling and attracting collaboration;
- preventing duplication of effort;
- allowing new and different analysis, and enabling meta-analysis across data from multiple studies.
The trend towards research data management and the associated shift towards data sharing where appropriate is related to the Open Access movement for peer reviewed research papers.