Bootcamp: Why manage research data?

Why manage research data?
Section 3 of 8

data visualisation image
Image: Data Visualisation With Processing by Info Design

'Research data management', put simply, refers to the effective handling of information that is created in the course of research. Managing research data is usually an integral part of the research process and how it's done will depend on the type of data involved, how that data is created or collected and how the data is to be used. Effective data management extends over the entire life cycle of the data, from the point of creation through to dissemination and archiving, and will usually continue long after the initial research project has concluded. Data management typically involves:

  • Planning for and creating data
  • Organising, structuring, and documenting data
  • Backing up and storing data
  • Preparing data for analysis, to share with others or to preserve for the long-term
  • Some reasons to manage research data

    Research data is 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:
    To ensure compliance with funding and regulatory requirements - in addition to expecting the results of research to be published, funding bodies are taking more interest in what researchers do with the data that is generated in the course of a project. If your research project is supported by industrial and commercial partners it is likely they will have their own data management or sharing policy.

    To ensure compliance with publishers' requirements - journal publishers increasingly require data that form the basis for publications to be shared or deposited in an accessible data centre or repository. This requirement applies to both commercially and publicly-funded research.

    To 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.

    To 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.

    Enhanced data security and minimised 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. Research data is a vitally important University asset and we all have a responsibility to make sure that it is kept safe and used appropriately. Working within the guidelines of the University's Information Security Policy will help you to achieve this.

    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. Initiatives such as DataCite, a registry assigning unique digital object identifiers (DOIs) to research data, helps to make data citable, traceable and findable, so that research data, as well as publications based on those data, form an important part of a researcher's output.

    To ensure accountability - by managing your research data and making it publicly available you will be able to demonstrate the responsible use of public resources to fund research.

    To 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.

    1. How many of the University’s top-10 funders (by total investment) have some form of data sharing requirement (based on 2011 statistics)?

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