Tools

Humanities and social sciences researchers encounter a number of data protection issues in their work. An example is scientific events where photos and videos are taken and legal participant consent is required in order to comply with the General Data Protection Regulation (GDPR). Surveys and ot...

This training event is devoted specifically to FAIR Data in SSH, and it provides answers to the following questions, among others: - How is research data in SSH defined? - Why are FAIR principles important for the management of research data in SSH? - How can the FAIR principles be implemented in...

This presentation focuses on legal and ethical issues in Data Management with a particular focus on the General Data Protection Regulation (GDPR). It provides advice on researchers working with personal data on how to comply with GDPR across different phases of the life cycle. Responsible Open S...

Welcome and introduction presentation of the Responsible Open Science Workshop. This presentation introduces CESSDA and ODISSEI as infrastructures for the social sciences and outlines the first four chapters of the Data Management Expert Guide. Responsible Open Science Workshop was organised by...

How can you make your data FAIR? In this webinar, Anca Vlad — data repository administrator at UK Data Service — will share tools and resources applying to the entire data lifecycle. The knowledge she will share is based on her experience at the UK Data Service. Anca will use, among others, the S...

This introductory webinar is for anyone who is involved in the collection of data and is considering making (some of) their data available in accordance with funders’ requirements. More and more funders are requiring that research data be made available after completion of the research project, u...

Anna Schwickerath explains how to make your data findable, accessible, interoperable and reusable (FAIR).

As part of the 2019 SERISS train-the-trainer workshop, Libby Bishop discusses ethical and legal issues for data.

Work of the RDA 2020 Hackathon on maDMPs is based on the idea of automated quality-control metrics ​ as part of a ​ Linked Data Pipeline for the ​ Research Data Connectome​. We propose a novel quality analyser that uses keywords obtained from 24 DMPs to generate standardisable DMP quality-control...

Data science technology promises to improve people's lives, accelerate scientific discovery and innovation, and bring about positive societal change. Yet, if not used responsibly, this same technology can reinforce inequity, limit accountability, and infringe on the privacy of individuals. In thi...