Basic

Goodtables is a free online service for tabular data validation, developed by the Frictionless Data team of the Open Knowledge Foundation. This open source tool will check basic structural errors such as blank or duplicate rows, duplicate headers, whether all rows have the same number of columns, etc. The data can be validated by providing a URL to the file (e.g. link to GitHub repository) or by uploading a file. Several formats are admitted: csv, excel, LibreOffice, Data Package, etc. Besides, a data schema can be uploaded to enable further checks, such as whether the data type (e.g. date), format (e.g. YYYY-MM-DD) and possible data constrains (e.g. no later than 2000-01-01) are respected. Documentation about the tool is available at: http://docs.goodtables.io/index.html

This guideline helps researchers to use OneNote as an Electronic Laboratory Notebook (ELN). It provides tips to adapt OneNote to an ELN workflow with a focus on the biomedical sciences, which can be adjusted to other nonscientific ELNs. It covers several topics such as how to structure and label experiments, data acquisition and representation. It also provides relevant recommendations on how to approach data storage and security to comply with applicable legislation.

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.

The Digital Curation Centre has prepared a tool to guide researchers in their preservation strategy. Through a series of checklist, researchers are guided to reflect on what purposes the data could serve in the future, to consider what requirements they need to fulfill and what should be preserved according to the data reuse potential and its replicability. Finally, the costs of the preservation are considered to make a final decision.

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.

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.

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.

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.

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.

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.