Publishing and sharing sensitive data: guidelines and decision tree

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.

Encryption guidelines

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.

Metadata tutorial

The University of North Caroline has developed a step-wise tutorial about metadata. It addresses what metadata is and why is it needed, explains the basic elements of metadata and how these are represemted in standards, as well as how controlled vocabularies are related to metadata. It finally provides a list of best practices resources for metadata.

Making a research project understandable - Guide for data documentation

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.

LEGO® Metadata for Reproducibility

The University of Glasgow has designed a LEGO® based game for 4-24 players to teach about metadata and reproducibility. In their own words: "The game addresses issues including planning for metadata, formats of metadata recording, standards and automation. The game also draws multiple parallels between recording and communicating the research process and documenting and the creation of a LEGO® model. The process of playing the game draws researchers into discussions on how metadata is captured, recorded and disseminated, which in turn provides an opportunity for signposting to further resources in this area."

Version control tools & techniques handout

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.

Version control with Git course

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.

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.

Legal instruments and agreements before collecting data

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.

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