CREATE & MANAGE DATA

STRATEGIES FOR CENTRES

CO-ORDINATING DATA MANAGEMENT

Research centres and programmes can support researchers through a co-ordinated data management framework of shared best practices. This can include local guidance, templates and pointers to key policies.

During 2010 we worked closely with selected ESRC research centres and programmes to increase the data management and sharing capability of such research hubs within the social sciences. Our Data Management Planning for ESRC Centres and Programmes (DMP-ESRC) project, funded as part of JISC's Managing Research Data programme, produced a range of data management planning procedures, tools and advice for centres and programmes.

Research centres and departments benefit from dedicated central research co-ordination, which can provide important input into planning and implementing data management and sharing activities. They also benefit from a centralised approach to data management providing both economies of scale and a lasting framework.

Benefits include:

  • researchers can share good practice and data management experiences with each other, thereby building capacity, collective knowledge and resources for the centre
  • a uniform approach to data management and creating standard policies on various data-related procedures and activities
  • a record of who owns data and keeping track of projects and data over time, especially when researchers move
  • data can be stored in a central location
  • all researchers and staff can be made aware of duties, responsibilities and funder requirements regarding research data, with easy access to relevant information

At the same time, researchers may also need to take responsibility for managing their own data, which might rqeuire some flexibility to adapt to both distinct methodological or disciplinary requirements.

Data management framework

To provide a data management framework, research hubs can develop:

  • the assignment of data management responsibilities to named individuals
  • standardised forms, for example for consent procedures, ethical review and data management plans
  • standards and protocols, for example data quality control standards, data transcription standards and confidentiality agreements for data handlers
  • file sharing and storage procedures
  • a security policy for data storage and transmission
  • a data retention and destruction policy
  • data copyright and ownership statements for the centres and for individual researchers
  • standard data format recommendations
  • version control and file naming guidelines
  • information on funder requirements or policies on managing and sharing data that apply to projects or the centre
  • a research data sharing strategy, for example via an institutional repository, data centre or website

Centralised data management is especially beneficial for data formatting, storage and back-up. It also helps to govern data sharing policies, establish copyright and IPR over data and assign roles and responsibilities.

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