lessons, e-learning

Introduction to Data Management Practices - Data organisation practices

Good data organisation is the foundation of any research project. It not only sets you up well for an analysis, but it also makes it easier to come back to the project later and share with collaborators, including your most important collaborator – the future you.

Much of the information of a project is digital, and we need to keep track of our digital records in the same way we have a lab notebook and sample freezer. In this lesson, we’ll go through the project organisation and documentation that will make an efficient research workflow possible. Not only will this make you a more effective researcher, it also prepares your data and project for publication. Grant agencies and publishers increasingly require this information.

Licence: Creative Commons Attribution Share Alike 4.0 International

Contact: [email protected]

Keywords: data organisation, FAIR, Data management, CONVERGE

Target audience: Researcher in life sciences, PhD candidates, Scientists

Resource type: lessons, e-learning

Status: Active

Prerequisites:

None

Learning objectives:

This lesson is divided into five episodes where you will learn:
- The recipients of data organisation and how and why they should be considered
- How to organise files and documentation to support your workflows
- How to structure and store your metadata, tabular data and information about experiments

Authors: Niclas Jareborg, Stephan Nylinder

Contributors: Yvonne Kallberg, Elin Kronander, Wolmar Nyberg Åkerström, Markus Englund, Mattias Strömberg, Erik Hedman

Scientific topics: Data management, FAIR data

External resources:

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