Glossary

Key Points

Introduction	The main steps of the Research Data Life Cycle are: plan, create, process, analyse, preserve, give access, re-use. Research Data are generated once but can be re-used extensively. Research Data Management encompass the whole Research Data Life Cycle.
Data Management Plan (DMP)	Research Data are generated once but can be re-used extensively. Research Data Management encompass the whole Research Data Life Cycle.
Project and file management	.
Analysing Data	A workflow (e.g. an R script) link raw to processed data. A workflow is essential to keeping trace of the steps that a dataset underwent.
Version control your analysis with git	Version control allows you to retrieve the complete history of your processed data and analytical workflows.
Data archiving	SURF data archive is to be used for larger files or a tar collection of smaller files and not for day to day access.
Generic open-access data repositories	Next-Generation Sequencing techniques are massively parallel cDNA sequencing.
Open-access repositories	Next-Generation Sequencing techniques are massively parallel cDNA sequencing.
Licenses: Who can use my data?	K1.
Licenses: Who can use my data?	K1.
The FAIR principles	K1.
Open Science	Open Science is both a set of principles and a way to perform scientific work.

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