Skip to Main Content
It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.

Research Data: Introduction

 

"Research data management concerns the organisation of data, from its entry to the research cycle through to the dissemination and archiving of valuable results." (Whyte & Tedds, 2011)

This LibGuide aims to promote good research data practices and presents the Data Support Services offered by the Glucksman Library. In order to create data sets that are findable, accessible, interoperable, and reusable (FAIR), data needs to be managed from the start of the research project. This process is supported by Data Management Plans (DMPs). The publishing of data is covered as well as finding and re-using data sets.

Welcome

Welcome to the research data LibGuide. My name is Armin Straube and I am the Research Data Manager for UL. I provide support and advice around research data, are available to review Data Management Plans and are happy to organise training sessions in your department.  Please do get in touch with me: armin.straube@ul.ie.  

What is Research Data?

Research data is all original sources or material (digital or not) created or collected to conduct a research project. It includes all data that is created, sourced, used and analysed to answer the research question(s). Research Data underpins research results and forms part of the scholarly record.

The great variety of research methods and topics is reflected in the diversity of formats of research data.  Examples include questionnaires, audio recordings, database entries, blood samples, literary texts, lab notebooks, list of measurements, photographs, maps, and much much more.

Why bother with Research Data Management?

Handling research data is an integral part of the research process. Putting some time and effort into good data management yields many benefits for the research:

Quality and Efficiency: Data management improves research processes.

Security: Data loss could seriously delay or even derail a research project.

Integrity: Research data can be used to validate research results.

Compliance: More and more funders require provisions for data management.

Impact: The publication of data sets enables data re-use and attribution, increasing the visibility and impact of the research.

The Research Data Lifecycle

The aim of research data management is to go from a linear process to a virtuous cycle of data creation and re-use, retaining money and time spent on the creation of data.

Depending on the type of research only a subset of the data created during the research might be published and preserved.