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Managing Qualitative Social Science Data An interactive online course

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.

DataWiz Knowledge Base

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 Research Data Management system

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.

Guidelines and examples of transcription of qualitative data

The UK Data Service has compiled a set of instructions and best practices to transcribe qualitative data from interviews. This guide seeks to provide advice to ensure methodological consistency and to increase the shareability and reuse of qualitative research data. It provides links to further instructions, examples and a template transcriber confidentiality agreement.

Data processing recommendations for Social Sciences

The CESSDA (Consortium of European Social Science Data Archives) Data Management Expert guide provides a specific chapter about processing data, which includes tips and examples on topics such as quantitative and qualitative coding, adequate weights of survey data and data quality assurance.

Compilation of data sources per research discipline

The Southern Methodist University has compiled a list of recommended resources to find existing data, together with a list of sources categorized by research discipline.