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Research Data Management: Research Data Management: An Introduction

Research Data Management

The Research Data Management Policy at NUI Galway states that the " purpose of research data management is to maximise the academic 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."

The aim of the Research Data Management Policy at NUI Galway "is to advise NUI Galway staff engaged in Research on their responsibilities with regard to data collected/stored as part of a research project which NUI Galway staff/students are engaged in, and the supports that are available for same, and to ensure that research data is managed in line with Data Protection Regulations. The policy covers all research related data generated, collected and processed by NUI Galway staff as part of a project, which is led or contributed to by NUI Galway staff/students."

What are research data?

The Research Data Management Policy at NUI Galway defines Research Data as "Information in digital, computer-readable format or paper-based that is collected, generated or obtained during the course of or as a result of undertaking research, which is subsequently used by the Researcher as a basis for making calculations or drawing conclusions to develop, support or revise theories, practices and findings."

Examples of research data

  • Documents (text, MS Word), spreadsheets
  • Scanned laboratory notebooks, field notebooks, diaries
  • Online questionnaires, transcripts, surveys or codebooks
  • Digital audiotapes, videotapes and other digital recording media
  • Scanned photographs or films
  • Transcribed test responses
  • Database contents (video, audio, text, images)
  • Digital models, algorithms, scripts
  • Contents of an application (input, output, logfiles for analysis software, simulations)
  • Documented methodologies and workflows
  • Records of standard operating procedures and protocols
  • Historical documents
  • Physical objects .g. blood samples
See Research Data Bootcamp (University of Bristol)

Research Data Lifecycle

"The notion of a data lifecycle is one that has gained popularity as the culture of data sharing becomes part of our everyday research language. The data lifecyle extends the typical research cycle" 

Corti, Louise, Van den Eynden, Veerle, Bishop, Libby, & Woolard, Matthew. (2014). Managing and sharing research data: a guide to good practice. London: Sage. p.17

Why do you need to manage your research data?

  • Understand what data you have and what direction you might go in the future
  • Improves quality: data accuracy, integrity, integration, timeliness of data capture and presentation, relevance and usefulness
  • Maximizes the effective use and value of data and information assets
  • Increases research efficiency and saves money
  • Data is more secure
  • Planning the selection and release of data (allowing for licensing terms)
  • Facilitates data sharing, data is more accessible/more discoverable
  • Facilitates continuity of research as staff/researchers change
  • Avoids duplication in research
  • Data is maintained allowing validation of research published
  • Data sharing leads to more collaboration and advances research
  • Research is more visible and increases impact and increases citation by other researchers
  • Funders are demanding research data management plans​
  • Ensure appropriate use of data and information
  • Ensure sustainability and accessibility in long term for re-use in science
  • Publishers are signing up to the Transparency and Openness Promotion (TOP) guidelines for journals thereby addressing transparency of research, fraud concerns and reproducibility issues

Reference: CONUL Research Support Task and Finish Group (2014) Briefing Document & Recommendations, http://www.conul.ie/publications/

Some of the benefits of good research data management practice

  • Increases the impact and visibility of research e.g. data citation
  • Promotes innovation and potential new data uses
  • Leads to new collaborations between data users and creators
  • Maximizes transparency and accountability
  • Enables scrutiny of research findings
  • Encourages improvement and validation of research methods
  • Reduces cost of duplicating data collection
  • Provides important resources for education and training

Read more from the UK Data Archive

"How open science creates better research"

"How open science creates better research" a recent article by John Cox, University Librarian, NUI Galway and Dr. Elaine Toomey, School of Psychology, NUI Galway explains the benefits of open science and what it involves. Read more on RTÉ Brainstorm at https://www.rte.ie/eile/brainstorm/2018/1021/1005713-how-open-science-creates-better-research/