Research Data Management

Video is a talk by Libby Bishop (GESIS) on ethical and legal issues in managing and sharing data. 

Guidelines to help researchers make their research data findable, accessible, interoperable and reusable (FAIR), to ensure sound management. Good research data management is not a goal in itself, but rather the key conduit leading to knowledge discovery and innovation, and to subsequent data and knowledge integration and reuse.

Content for a three-hour introductory RDM session for librarians. The course covers:

• Research data and RDM
• Data management planning
• Data sharing
• Skills

The materials consist of presentation slides and an accompanying handbook.

Data Archiving and Networked Services (DANS) is the Netherlands institute for permanent access to digital research resources.

Since 2005, DANS has been supporting researchers, data professionals, other data archives, research institutions and research financiers with questions in the field of data management, certification, and topics such as FAIR, open access and software sustainability.

In addition to data services, DANS also offers training and consultancy.

Do you want to know more about depositing, sharing and reusing data? Or, for example, about research data management, digital sustainability, certification, FAIR, open access or software sustainability?

The expertise built up in national and European projects is reflected in the training courses and advice provided by DANS, intended for researchers, research institutions, research funders, data professionals and other archives. Examples can be found on the DANS Training site.

We are happy to share our knowledge with researchers, data professionals, research institutions, research funders and other repositories. We regularly organise interactive workshops on data publishing, archiving, reusability and interoperability. The developments in the field of Open Science, research data management planning and tools are also addressed.

In addition, DANS organises successful interactive training courses together with others, such as: RDNL Essentials 4 Data Support, RDNL AVG and develops training materials such as the DANS Data Game and CESSDA Data Management Expert Guide. 

Roadmaps, recommendations for action and good practice examples for the strategic development and improvement of research data management at German-speaking universities are developed for subsequent use. The focus is on the development of tools for strategy development for research data management, models for institutional research data policies, and a consulting and training concept

European Commission guidance on the context and Horizon 2020 rules on open access to scientific publications, open access to research data and research data management. Contains multiple reference documents.

The Digital Curation Centre (DCC) is a centre of expertise in digital curation with a focus on building capability and skills for research data management. They provide expert advice and practical help to research organisations wanting to store, manage, protect and share digital research data.

Amongst the many resources they provide, they have a section of training materials available for developing and/or delivering research data management training. This includes their own DC 101 training materials for training researchers, as well as training materials for librarians and research administrators. They also point to training materials made available by other providers.

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.