Resource Directory

This guide provides step-by-step instructions for curating new datasets deposited in Dataverse. The guide is framed around the acronym CURATION to provide an easy reminder for curators, especially those starting out, of the main steps in the curation process. This framework is adapted from the Da...

This report provides an inventory of data formats and metadata standards that are currently used and relevant for the research infrastructures currently managed by the SSHOC main stakeholders, recommendations of specific formats and standards for increasing interoperability, and prioritisations f...

The breadth of the Social Science and Humanities sector has led not only to the diversification of the research methods and work practices in the field but also to diversity in the way vocabularies are used to describe, discover and access research content. The SSHOC EU thematic cluster project a...

SSHOC will build the Social Sciences and Humanities part of the European Open Science Cloud. One of the SSHOC project’s core objectives is to foster the transition from the current Social Sciences and Humanities landscape to a cloud-based infrastructure that will operate according to the FAIR pri...

MICA, or “Measuring and Improving the Efficacy of Curation Activities in Data Archives” is a three-year National Digital Infrastructures and Initiatives project led by investigators at ICPSR and the University of Michigan School of Information. The goal of this project is to understand how curato...

DDI - Cross Domain Integration (DDI-CDI) which is a specification aimed at helping implementers integrate data across domain and institutional boundaries. Modern research increasingly involves large amounts of data, much of which comes from non-traditional sources (sensors, big data, social medi...

The Recommendations for FAIR Data Citation, produced by SSHOC T3.4 "Making Data Findable by being Citable," are born out of the growing need for guidelines for data citation in the social sciences and humanities (SSH). Based on the Force 11 Data Citation Principles and adapted for the SSH, this d...

FAIR data are the pillar of Open Science which is at the core of the SSHOC project. In order to ensure findability of data and other resources, it is crucial to provide easy-to-use recommendations for data citation in the SSH domains. Certainly, there are different needs and practices with regard...

De-identifying qualitative data poses unique challenges given their structure and contextual richness. As the sharing of qualitative data is becoming more common, reliably de-identifying such data is crucial because participants in qualitative research projects commonly receive assurances of conf...

The Recommendations on FAIR Metrics for EOSC document contains an analysis of activities relevant to the definition of FAIR Metrics in the EOSC context. It makes recommendations on the definition and implementation of metrics, proposes a set of metrics for FAIR data in EOSC to be extensively test...