Why is Data Management Important?
By Le Yang
A recent news story released by the Chronicle of Higher Education has come to the attention of many researchers. A UCLA graduate student was unable to provide original survey research data to justify
his results after his previously sent data set results were unable to be replicated
by an Emory professor. Science then retracted the published paper citing three reasons, one of which is the author's
inability to provide original data.
This news story highlights one of the reasons why data management is important for researchers. That reason being validating the research results. Research data are a key part in the research process, it is what supports the results and any conclusions. Publishers often ask for data for both validating the results and accepting publications. Not being able to provide original data may result in the refusal or retraction of published works, discrediting of the researcher, or law suits.
Additionally, managing the original data throughout the research life cycle ensures the current usability and availability, improves research through a more efficient retrieval process, allows for the reuse of data, and the avoidance of data loss. In the long term, managing research data can also guarantee integrity and consistency of data files. Finally, it also makes the data more reusable, which helps researchers to avoid duplication. Consistent research data management will increase the visibility of research outcomes and facilitate the development of open-access scholarly knowledge.
The third reason data management is important is primary funding agencies and the government are now requiring grant proposals to include supplementary data management plans that conform to the agencies' policy on the dissemination and sharing of research results. Such data management policies mandate that the investigators implement data management to prevent duplication, to maximize the potential use for the data created, and to encourage open access of their funded projects. For example, in its Grant Proposal Guide, National Science Foundation stated that "investigators are expected to share with other researchers the primary data, samples, physical collections, and other supporting materials created or gathered in the course of work under NSF grants." National Institutes of Health has the similar requirement in its policy, stating that "all data should be considered for data sharing and made as widely and freely available as possible..."
Understanding why data management is important can help the Texas Tech researchers plan, prepare and complete research projects with the highest standards. If you think you may need help with your data management planning Texas Tech Libraries' Data Management team is here to help. You can contact us directly and we will work with you to tailor a data management plan to s specific agency, or we can come to your area and work with faculty to give a seminar on data management.
For more information or questions contact email@example.com
Le Yang is an assistant librarian and part of the data management team at the University Library.