Research data management/FAIR data
|OpenAIRE Task Forces||
The task forces are a new programme in OpenAIRE Advance to enable capacity building, competencies and awareness raising on different relevant open science topics, involving all partners and NOADs, demonstrating a vertical approach for knowledge exchange. NOADs with more engaged activity levels are involved throughout and are also encouraged to facilitate these groups, aiming to strengthen understanding, steer project activities and, mobilise community ties.
In OpenAIRE Advance there are three task forces (at the bottom of the page you find useful resources (guidelines, blogs, checklists, etc):
|Research Data Management Toolkit||
This toolkit includes a number of resources on research data management. However, due to its broad scope, the toolkit is not structured as an online course.It contains courses, videos, infographics, books and other materials
|Research Data Management and Sharing||
This course will provide learners with an introduction to research data management and sharing. After completing this course, learners will understand the diversity of data and their management needs across the research data lifecycle, be able to identify the components of good data management plans, and be familiar with best practices for working with data including the organization, documentation, and storage and security of data. Learners will also understand the impetus and importance of archiving and sharing data as well as how to assess the trustworthiness of repositories.
|Train-the-trainer concept for research data management||
As part of the project FDMentor, a German-language train-the-trainer program on research data management was created and piloted in a series of workshops. The comments and tips from the participants in the two pilot phases and the feedback from the relevant community were gradually incorporated over 2019. The second version of the train-the-trainer concept now available offers a revised script with the contents of the teaching units, detailed teaching scripts, working materials, lecture slides and numerous worksheets and templates that are intended to support teaching. The topics covered include both aspects of research data management, such as data management plans and the publication of research data, as well as didactic units on learning concepts.
|Guidelines on FAIR Data Management in Horizon 2020||
Guidelines to help researchers make their research data findable, accessible, interoperable and reusable (FAIR), to ensure sound managementd. 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.
|DIY Research Data Management Training Kit for Librarians||
Training kit for librarians who wish to gain confidence and understanding of research data management, based on open educational materials, covering five topics:
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.
|RDM for librarians||
Content for a three-hour introductory RDM session for librarians. The course covers:
The materials consist of presentation slides and an accompanying handbook.
|Digital Curation 101||
Digital Curation 101 employs the curation lifecycle model sections as a means of presenting content to students. The DC 101 has been developed because the DCC, in its role as a source of expert advice and guidance to the community, identified a need for a contextual, theoretical introduction to the basics of digital curation with practical examples and exercises. The target audience is new grant holders with Research Council curation mandates to fulfil. The course indicates what should be considered in planning and implementing projects.
|Research Data Management in Life Sciences||
Upon completion of this course, participants should have an understanding of what Research Data Management is, and why it is important in academic research. They should have an understanding of the FAIR data principles, and how they can make data more FAIR. They should be able to successfully manage all types of research data and to document both the research itself, as well as the data in a comprehensive way.
|Best practices in research data management and stewardship||
This two-day course (27 and 28 May, 2020) is aimed at project managers, researchers and graduate students in the biomedical sciences who wish to improve their skills on data handling. The course will introduce the concepts of the FAIR principles for data, the concept and implementation of data stewardship as well as practical aspects of day to day data management and data management plans, which are required in many grant applications.