Research Data Management

Research Data

Research data varies by discipline, but is considered to be the information collected, observed or created during the research process that is analyzed to produce original results and validate research findings. Research data management refers to the treatment of data throughout all stages of a research project.

The benefits of good data management include:

* Meets funder requirements on open research
* Provides enhanced data security and ensures research evidence is protected against loss or corruption
* Complies with data protection and information security legislation
* Demonstrates compliance with ethical codes
* Represents best practice in research
* Better quality data leads to better quality research
* Creates an infrastructure that enables collaborative research
* Ensures data are suitable for sharing
* Increases research efficiency

Data Management Plans

Data Management is implemented through creating and adhering to a data management plan and formalises the approach to existing practices.

* Data management plans should address:
* Planning and designing data management
* Collecting and capturing data
* Analysing data
* Storing and preserving data
* Sharing and publishing data
* Reusing data
* Legal and ethical aspects of data management 

The use of data management plans and following guidelines for good data management represents best practice in research, resulting in higher quality research outputs. Systematic management of research data throughout the research life-cycle, from creation to preservation or disposal, enables the value of the data to be maximised.

Research Data Management Policy

The University of Wolverhampton  has been created to ensure that research data is managed in accordance with the University’s commitment to research excellence and with an open research approach as the default. 

The development of the policy is driven by a combination of best practice principles, funder requirements, a shift towards open data as default, changes in research practice and the need to comply with legal and ethical principles that relate to information management. Although currently limited to a few funders, the shift towards open data will become an increasing influence with stricter requirements.

Research Council and Funder Policies

It is becoming increasingly common for funders to:

* Request data management and sharing plans in grant proposals
* Mandate that data are made openly available post project
* Ask for data to be preserved after the end of the award, with the duration informed by funder and data type

Key policies outline the expectations for good practice that will enable a sustainable open research environment:

* FAIR principles for research data management and stewardship
* RCUK Common principles on data policy
* Concordat on open research data 
* Data management policy for Horizon 2020
* Guidelines on FAIR data management in Horizon 2020

Open Data

Research data management has been given greater impetus in the drive towards open data, whereby research data is published alongside publications to verify findings and for others to use and reuse wherever possible, creating opportunities for new research and making the research process more transparent and replicable.

This practice has been focused particularly on scientific disciplines, although the EU, UK government, research funders and representative bodies are now working towards open research data as the default for all funded projects.

Ensuring data is intelligible and reusable to others relies on efficient and systematic management from the beginning of a project. The default preference for open data should always be balanced by legal, commercial and ethical restraints. This can be summarized by the EU maxim ‘as open as possible, as closed as necessary’.  

The FAIR principles for research data management and stewardship represent best practice in data management and recommend that data should be Findable, Accessible, Interoperable, and Reusable in order to be useful to others in an open data environment.

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