Resource Directory

Training example: How to publish datasets in a Dataverse setting

Dataverse user guide by Harvard.

The CESSDA Data Access Policy has been developed to provide a set of principles for CESSDA Service Providers (SPs) covering common standards for the provision of data and metadata access. The policy also aims to demonstrate CESSDA’s commitment to open science while protecting both privacy and int...

This Dataverse manual aims to provide a practical, user-friendly, and concise guide intended for typical end users of Dataverse. The manual includes instructions for the essential functions of Dataverse such as creating, managing and sharing Dataverse collections and datasets; a technical setup g...

This SSHOC Legacy booklet covers the main outcomes of the SSHOC project, marking a major step towards the exploitation of tools and services during the project’s funding lifecycle and from there the path towards sustainability. The first part showcases the work performed by SSHOC partners to achi...

Figures and case studies related to accessing and reusing the data produced in the course of scientific production.

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 the last two chapters of the Data Management Expert Guide outlining Archiving and Publishing data discovery. Responsible Open Science Workshop was organised by CESSDA Training and ODISSEI.

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 webinar is intended for everyone who wants to learn about ways of finding and reusing research data. Managing your research data in a FAIR and transparent manner is important. It helps researchers to meet requirements of funding institutions and ensures long-term re-usability of their data....