Resource Directory

The CESSDA Data Management Expert Guide (DMEG) is designed by European experts to help social science researchers make their research data Findable, Accessible, Interoperable, and Reusable (FAIR). This is the online version of the DMEG.

This guide provides an overview of data linkage, analyses the main advantages, and summarizes the challenges quantitative researchers and data practitioners face when working with multiple data sources. Moreover, this document aims to provide examples of the developments of data linkage in Switze...

The advent of Open Science poses a number of challenges for researchers with regard to research data management. Amongst the most salient is the necessary balance between data protection and openness. This guide aims to clarify the rights and obligations of researchers regarding the protection of...

In the social sciences in recent years, replication has received increased attention, as there has been a growing understanding that for research to be credible it is crucial that studies can be repeated. Replication allows for determining the validity of scientific conclusions. This FORS Guide p...

This guide is for users of research data accessed via the UK Data Service through its online services provided by the UK Data Service. In particular, all users who obtain data available under a Special Licence Agreement or Controlled data, where disclosure risk is increased, are required to read...

This guide covers standards and procedures for the preparation and preservation of documentation for UK Data Archive studies.

This brief guide presents key information for researchers to understand Dataverse, its features, and how to access and use it.

Many journals, publishers, and funding agencies require researchers to deposit replication datasets in a public repository. The Dataverse Project helps researchers fulfill this requirement by supporting the deposit of replication datasets, making this special type of data easily discoverable for...

One of the most useful features of the Dataverse repository software is the large number of metadata fields it provides for describing research data. This guide is intended to support both the novice and experienced user in creating metadata for datasets in a Dataverse repository. It provides off...

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...