Workshop FAIR & Data stewardship for the 2020 ITN ProEVLifeCycle

This material is part of an introductory FAIR data stewardship workshop for the Marie Curie ITN ProEVLifeCycle (The prostate cancer Extracellular Vesicle LifeCycle)

FAIR and data stewardship - October 14th, 2020
Organiser: Dutch Techcentre For Life Sciences, DTL
Setup: Virtual meeting (corona-pandemic)
Duration: 2 hours

Topics:

* Introduction (the relevance of research data management, research data management and the data life cycle, open science, open access and open data, FAIR guiding principles, data stewardship)
* Planning data (data management plans, informed consent procedures, funder and journal requirements, costing data management)
* Collecting data (finding data (and the importance of FAIR data), capture data (importance of metadata, pre-registration), data security and privacy)
* Processing and analysing data (tools for processing and analysing data, Infrastructure for storing and sharing data, organising data, versioning and documenting data, anonymisation, pseudonymisation and personal data)
* Publishing, preserving data & reusing data (what data should be archived, archiving for scientific integrity, archiving for reuse, archiving non-digital data, FAIR data, data rights)

Scientific topics: FAIR data, Data management

Operations: Analysis, Data handling

Keywords: Data analysis, Data management planning, Data processing, Data sharing, Data collection, Data preserving, Data reuse

Resource type: Slidedeck

Target audience: PhD candidate

Difficulty level: Beginner

Licence: Creative Commons Attribution 4.0

Authors: Mijke Jetten, Celia van Gelder

DOI: https://doi.org/10.5281/zenodo.4687214

External resources:
Workshop FAIR & Data stewardship for the 2020 ITN ProEVLifeCycle https://tess.elixir-europe.org/materials/workshop-fair-data-stewardship-for-the-2020-itn-proevlifecycle This material is part of an introductory FAIR data stewardship workshop for the Marie Curie ITN ProEVLifeCycle (The prostate cancer Extracellular Vesicle LifeCycle) FAIR data Data management Data analysis, Data management planning, Data processing, Data sharing, Data collection, Data preserving, Data reuse PhD candidate