Accessibility

This interactive on-line course prepared by the Social Science Research Council and the Qualitative Data Repository contains four modules about different aspects of RDM of qualitative data in Social Sciences. Each module is composed by multiple lessons and can also function as a stand-alone resource to be completed individually. Most lessons include associated readings, resources, exercises, and activities.

The knowledge base’s of the DataWiz is a complete RDM guideline for Psychology research to support or complement the use of the DataWiz data management tool. The content is structured in three sections: before, during and after data collection & analysis. The first section covers data management planning as well as the various legal and ethical aspects related to data management. The second section focuses on best practices and tips for handling and documenting data during research. Finally, the last section focuses on how to share and preserve data at the end of the project.

DataWiz is an automated assistant for data management in Psychology, developed by the Leibniz Institute for Psychology Information. It is a web-based application that supports researchers in planning their data management before the project starts and in managing their research data during the project. It provides functions to cover the entire research data lifecycle: data preparation, documentation and archiving. It also provides a digital collaborative working environment for you and your team. With DataWiz researchers can reduce the time spent on RDM, increase the quality and ensure the long-term reusability of research data.

The Australian National Data Service has developed three guides about Persistent Identifiers for three different types of users. The basic guide focus on awareness level and explains the basics about PIDs. The working level guide expands on the basic, going into technical and policy details. The expert level guide is intended to provide in-depth understanding for research administrator and technical staff on how to set up a PID infrastructure.

Utrecht University has created a simple decision-tree tool that helps researchers to choose a generic repository that best fits their needs. To do so, criteria such as restriction of access and cost of the repository are taken into account.

ANDS has published a comprehensive guide about best practice for the publication and sharing of research data (in the Australian context). The guide helps researchers with the publishing phase of senstitive data with a step-by-step approach which covers several phases of the research data lifecycle. These steps are summarized in a decision tree.

Ghent University has elaborated an encryption manual for researchers. It begins with basic information about what encryption is and when is it needed. Then, it describes different encryption strategies and frames them into different scenarios, and provides step by step instructions for each of these scenarios.

The University of Helsinki created, upon request, a compact guide for researchers to help with research data documentation. It first introduces the basic elements of documentation, and then provides practical instructions and strategies to proceed with documentation during the research project, but also for the publishing phase.

Utrecht University provides an overview of possible legal instruments and agreements that might be necessary to establish prior to data collection. The information is provided in a user friendly approach departing from the perspective of different stakeholders perspective: data subject, third party and data reuser. It then provides extended details of what it instrument entails with further guidance, templates or examples for each case.

This Open Source tool developed by the Institute of Formal and Applied Linguistics of Charles University guides the user through a decision tree approach to select a license for their research output. The tool considers scenarios where the user does not own copyright or similar rights in some of all of the constitutive parts of the dataset and provides further guidance based on whether those elements are clearly licensed or not.