Tools

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...

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...

Pre-registration and registered reports are increasingly advocated to improve the credibility and rigor of empirical research. Pre-registration and more strongly registered reports are expected to reduce reporting and publication bias because they request researchers to define a detailed research...

This document provides points of reference for researchers seeking to manage their data in the most ethical way possible in the era of open research data. Through a presentation of binding and non-binding regulatory frameworks, it addresses some points to be taken into account in order to make da...

This guide helps drafting a data management plan (DMP) from the perspective of the social sciences. Drawing on the model developed by the Swiss National Science Foundation, it provides recommendations and tips on how to address the main topics of the DMP so that it fulfils the funder’s requiremen...

Drawing on the Swiss context, this Guide illustrates key considerations in crafting a coherent anonymization strategy that is compliant with legal requirements and ethical norms. It shows how to strike the right balance between anonymization and other data protection measures, namely informed con...