Data documentation

Training kit for librarians who wish to gain confidence and understanding of research data management, based on open educational materials, covering five topics:

• Data management planning
• Organising & documenting data
• Data storage & security
• Ethics & copyright
• Data sharing

The kit uses the Research Data Mantra online course and selected exercises from the UK Data Archive. It further contains a training schedule, podcasts for short talks, presentation slides, evaluation forms, data curation profiles and reflective writing questions based on the experience of academic librarians who have taken the course.

Data Curation Profiles provide a complete framework for interviewing a researcher in any discipline about their research data and their data management practices.

Chapter on how to properly organise and document data and metadata, discussing good practices in designing an appropriate data file structure, file naming and organising data within suitable folder structures; how organising data facilitates orientation in the data file, contributes to the understanding of the information contained and helps to prevent errors and misinterpretations. Also what counts as appropriate documentation of data, development of rich metadata to make data FAIR and standards to promote data sharing.

Focus on:

• elements which are important in setting up an appropriate structure for organising data for intended research work and data sharing
• overview of best practices in file naming and organising data files in a well-structured and unambiguous folder structure
• how comprehensive data documentation and metadata increases the chance data are correctly understood and discovered
• common metadata standards and their value
• relevant DMP questions on this topic.

Online data management guidance and resources for researchers, developed by the UK Data Service. This resource provides best practice guidance and advice, including examples, exercises, tools and templates. The focus is on the social sciences and research with human participants. Particular areas covered are:

• Data management planning
• Legal and ethical aspects of managing and sharing data
• IP Rights
• Documenting data
• Formatting data
• Storing data

Free online course for those who manage digital data as part of the research process. It has been created for the use of post-graduate students, early career researchers, and also information professionals.

There are eight online units in this course and four data handling tutorials that will help you:

1. Understand the nature of research data in a variety of disciplinary settings
2. Create a data management plan and apply it from the start to the finish of your research project
3. Name, organise, and version your data files effectively
4. Gain familiarity with different kinds of data formats and know how and when to transform your data
5. Document your data well for yourself and others, learn about metadata standards and cite data properly
6. Know how to store and transport your data safely and securely (backup and encryption)
7. Understand legal and ethical requirements for managing data about human subjects; manage intellectual property rights
8. Understand the benefits of sharing, preserving and licensing data for re-use
9. Improve your data handling skills in one of four software environments: R, SPSS, NVivo, or ArcGIS

Each unit takes up to one hour, plus time for further reading and carrying out the data handling exercises. In the units you will find explanations, descriptions, examples, exercises, and video clips in which academics, PhD students and others talk about the challenges of managing research data. 

The Data Management Expert Guide is designed by European experts from the CESSDA Training Working Group to help social science researchers make their research data Findable, Accessible, Interoperable and Reusable (FAIR).

The guide is written for social science researchers who are in an early stage of practising research data management. With this guide, CESSDA wants to contribute to professionalism in data management and increase the value of research data.

The guide leads through the research data lifecycle from planning, organising, documenting, processing, storing and protecting data to sharing and publishing them. Taking the whole roundtrip will take approximately 15 hours.

Particular specialties of the guide is a focus on European diversity (for example in data protection legislation, research ethics, research funder DMP requirements, etc), developing a Data Management Plan as you progress through the guide, and topical expert tips.