Research Data Management (RDM)
What is Research Data Management?
The importance of effective Research Data Management (RDM) and sharing practices in research is nowadays highly recognized by funding bodies, governments, publishers, and research institutions. The commitment to the Findable, Accessible, Interoperable and Re-usable (FAIR) principles (Wilkinson et al., 2016) is not only a requirement by funders, but it is also one of the key principles of the global Open Science Movement, which incorporates Open Source Software (OSS); Open Educational Resources (OERs), Open Access (OA), etc. that are all fundamental to the concept of “Open Knowledge”.
"Research data management (or RDM) is a term that describes the organization, storage, preservation, and sharing of data collected and used in a research project. It involves the everyday management of research data during the lifetime of a research project (for example, using consistent file naming conventions)." Source: University of Pittsburgh
Pioneers in data curation and managing long-term access to high quality data, our expertise continues to transform social science research, teaching and learning.
By improving the ability to extract knowledge and insights from complex collections of digital data, researchers help to accelerate the pace of discovery and inform evidence-based policy development to strengthen society.
UK data service tutorials
There is a wealth of data available for reuse in research and reports. These free, interactive tutorials are designed for anyone who wants to start using secondary data. They show you how to get started with finding good quality data, understanding it and starting your analyses.
Large-scale and collaborative research is becoming more commonplace, with many research projects taking a cross-national and interdisciplinary approach to research.
MANTRA is a free, online non-assessed course with guidelines to help you understand and reflect on how to manage the digital data you collect throughout your research. It has been crafted for the use of post-graduate students, early career researchers, and also information professionals. It is freely available on the web for anyone to explore on their own.
MANTRA is for you if you want to learn how to manage the data you collect during your research and want to practice with real datasets and learn how to use R, SPSS, NVivo or ArcGIS.
3 things you might want to use MANTRA for:
- Introduction to concepts and terminology of Research Data Management (RDM)
- Overview of strategies to collect and manage research data for dissertations, reports, fieldwork
- Examples of how to plan and develop research projects (data gathering, analysis and storage)
MANTRA is maintained by Research Data Service staff in Information Services, University of Edinburgh. It was originally developed in collaboration with the Institute for Academic Development as part of a Jisc-funded Managing Research Data project (2010-11). The content was developed based on a needs assessment with three postgraduate training programmes at the University of Edinburgh in the fields of geosciences, social and political sciences and clinical psychology.
Through a series of interactive online units you will learn about terminology, key concepts, and best practice in research data management.
There are eight online units in this course and one set of offline (downloadable) data handling tutorials that will help you:
Understand the nature of research data in a variety of disciplinary settings
Create a data management plan and apply it from the start to the finish of your research project
Name, organise, and version your data files effectively
Gain familiarity with different kinds of data formats and know how and when to transform your data
Document your data well for yourself and others, learn about metadata standards and cite data properly
Know how to store and transport your data safely and securely (backup and encryption)
Understand legal and ethical requirements for managing data about human subjects; manage intellectual property rights
Understand the benefits of sharing, preserving and licensing data for re-use
Improve your data handling skills in one of four software environments: R, SPSS, NVivo, or ArcGIS
GOFAIR's RDM Starter Kit lists resources designed to help researchers get started to organize their data.
Six stages of Research Data Management
Creating a Data Management Plan (DMP) is considered good research practice. Decisions made early on in the research project helps researchers save time, consider the necessary resources and costs. These will be required for funding/grant applications.
Collect & Capture
Research data are very much about when they are used as well as what they constitute and the purpose for which they are to be used.
Collaborate & Analyse
Large-scale and collaborative research is becoming more commonplace, with many research projects taking a cross-national and interdisciplinary approach to research.
Discover, Reuse & Cite
Many kinds of data created as part of a research project are subject to the same rights as literary or artistic work. Such items acquire rights like copyright or more general Intellectual Property rights when they are created. This gives the rights owner control over the exploitation of their work, such as the right to copy and adapt the work, the right to rent or lend it, the right to communicate it to the public and the right to licence and distribute.
Share & Publish
Manage, Store & Preserve
The management of data encompasses ensuring the security of data which requires paying attention to physical security, network security, plus the security of computer systems and files to prevent unauthorised access or unwanted changes to data, disclosure or destruction of data. UK Data Service