Data management
Data is the heart of the research process. The goal of research is to get data that answers the hypothesis. Analyzing data and sharing the results is what contributes to the world’s knowledge base. Ensuring the integrity of the data is a paramount concern in research. Using sound data management practices allows the research to be reproducible, the opportunity to be validated, and increases transparency – all of which upholds the public’s trust in research.
Good data management requires consideration of the following prior to beginning a research project.
Collection and Analysis
There are a variety of ways to collect and analyze data and the methods you choose will be dependent on the specifics of what you are trying to study. It is important to design your study carefully and thoughtfully. A poorly constructed study will not provide useful data. Use of improper statistical methods can skew results.
Data should also not be collected without the appropriate approvals in place from institutional review boards and should comply with all applicable regulations and institutional policies or data may not be able to be used once collected.
Researchers should also be meticulous in their methods for collecting, recording, and analyzing data.
Sloppy methods will produce invalid results. While honest errors are not research misconduct, serious deviations from accepted standards in conducting research is and can have serious consequences.
Ownership
Institutional policies and funding sources may limit the rights to the data, the results from it, or even the future uses of it. It’s incumbent on the researcher to understand these limitations.
Protection
Since data is at the heart of all research, it must be protected. The data may be needed later to either confirm your findings or allow someone else to reanalyze your results.
Storage and Retention
Data storage is the responsibility of the researcher. There are different considerations for storage, depending on the data you are collecting and the methods used to collect the data. Laboratory notebooks should be properly labeled and stored for safekeeping. If using electronic means for storage, ensure that you have the information backed up and that access to the data is secure. If the data is subject to confidentiality or privacy restrictions, there may be additional requirements for the storage of the data. Laboratory samples should be preserved, if possible.
Institutional record retention policies and sponsor requirements may have an impact on the length of time records should be retained. Records may always be kept longer than required and may be of use later. Research records should be maintained long enough for other researchers to verify your results.
Sharing
Data sharing is an important part of the research process as it allows peers to validate your results and it advances the collective knowledge base. Many sponsors require the data to be widely available after the results are published. Reputable scientific journals may also require that the data used in publications is made available to other researchers. Projects that generate a lot of data may pose logistical challenges for sharing with others but efforts should be made to make the data available.
If research is sensitive in nature, it may be necessary to restrict who the data is shared with.
Reporting
While the goal of performing research is to report the results in publications, researchers should carefully consider the following:
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When should I report?
If your research was sponsored, your sponsor may have requirements on when reporting results is required. Results should not be reported or published until the accuracy and validity of your data has been verified. - Where should I publish the results?
Publishing decisions require thoughtful consideration. Publishing in a high impact journal may allow your research to carry more weight than publishing in five other places. Forethought on the audience of the publications can help influence where to publish. - Are there concerns if I publish?
If the research results have potential to be used for harm, it is necessary to rethink where and what to report to publish responsibly. Consulting your institution’s dual use review entity is highly recommended.
Rigor and Reproducibility
Following rigorous standards in designing research provides more standardization among the resulting data which makes it easier to reproduce the results. This allows science to keep advancing toward understanding the world around us and continue with innovation. As a testament to the importance of these concepts, the National Institutes of Health (NIH) requires these concepts to be addressed in proposal submissions.