Research Data Management

A key component within many research projects is the collection and interpretation of a defined range of data. Essential to this process is the requirement, to build into the design of the research project a Data Management Plan. Increasingly most academic institutions now insist that a Data Management Plan is part of any research proposal. Additionally many public and private sector organisations seek to articulate Data Management Strategies, and this includes Tusla. Click here to view and download Tusla’s Data Management Strategy 2019-2022 (Search under ‘D’)

Research Data Management aims to

“maximise the value of research data by ensuring that such data is managed according to good practices for collection, curation, storage, management, retrieval, re-use, sharing, archiving and access, appropriate for the data and discipline concerned and thereby to ensure compliance with the requirements of funding agencies and other stakeholders”.[1]

A range of tools and guides exist to assist you with understanding what is required in building a Data Management Plan as well as testing the effectiveness of your plan. A number of these are described and linked to below;