File naming and organisation

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 Library service of Standford University has compiled a series of case studies with examples of good and bad practices about different RDM topics, such as file organization and naming, data storage, metadata, spreadsheets and publishing data online. The examples explain the consequences of bad practices and provide solutions.

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.

The Massachusetts Institute of Technology (MIT) has developed a series of file organization handouts. The handout for version control briefly summarise different techniques for version control and provides an overview of the main differences between automatic change log platforms and tools.

This course prepare by the Software Carpentry guides through how Git (and GitHub) can be used to manage versions during a project. It starts with the basics (setting up Git and creating a repository), and follows with practical guidelines to track changes, collaborate or resolve conflicts. It has also dedicated sections about the impact of version control on Open Science, licensing and citations.