Scholarly Communications: Research Data Management

Research data are a valuable resource that often requires a great deal of time and money to create. There are a number of very good reasons why research data should be managed in an appropriate and timely manner. Here we will consider data management at a number of levels:

1. Basic quality assurance within the project

Increase research efficiency. Good research data management will enable you to organise your files and data for access and analysis without difficulty. Consider for instance what would happen if a member of a research team were to leave during the course of a particular project. Well managed research data helps newcomers to understand the nature and the extent of work done so far. Well managed data also helps individual researchers track the course of their own progress.

Facilitate data security and minimise the risk of data loss. Use of robust and appropriate data storage facilities will help to reduce the loss of your data through accidents, or neglect.

Examples:

• Storage: back-up strategy within the project
• Organisation: data collection and versioning guidelines
• File formats: file formats that fulfill the needs of the primary research group
• Metadata & Documentation: Minimal documentation, e.g. sampling, variable and code labels
• Legal / ethical issues: informed consent for use of data within the project

2. Reproducibility of the research findings

Ensure research integrity and validation of results. Accurate and complete research data are an essential part of the evidence necessary for evaluating and validating research results and for reconstructing the events and processes leading to them.

​Examples:

• Storage: back-up strategy for storing data after the project (for 10 years)
• ​File formats: for keeping data & documentation accessible for at least 10 years
• Metadata & Documentation: metadata to describe the entire research process
• Legal / ethical issues: informed consent for data storage or making it accessible to others

3. Re-use of the data by other researchers

Ensure wider dissemination and increased impact. Research data, if correctly formatted, described and attributed, will have significant ongoing value and can continue to have impact long after the completion of a research project. Perhaps the most common reason to retain and manage research data, is to facilitate online sharing. 

Enable research continuity through secondary data use. Good research data management will permit new and innovative research to be built on existing information. So the importance of research data quality and provenance is paramount, particularly when data sharing and re-use is becoming increasingly important within and across disciplines. Sharing well-managed research data and enabling others to use it will also help to prevent duplication of effort.

Examples:

• Storage: plan submission to an archive for long-term preservation
• Organisation: standardisation, e.g. by employing licensed scales
• File formats: file formats that facilitate data reuse in the future
• Metadata & Documentation: detailed documentation & metadata for reuse
• Legal / ethical issues: informed consent for archiving and reuse 

Additionally research data should be managed to ensure compliance with a funding agency’s requirements. An increasing number of funding bodies (for example Horizon 2020, Health Research Board, Irish Research Council) request or require that their funding recipients create and follow plans for managing data, storing or preserving it in the long term, and sharing some, or all data products with the public.