Writing a Data Management Plan

Introduction
What is Data?
5 Topics
Introduction
What Is the Typical Lifecycle of Research Data?
What Is Research Data Management (RDM)?
What Are the Benefits of RDM?
Questionnaire – Rate Your Data Management
FAIR Data
6 Topics
FAIR Data – Introduction
Exercise: Identify FAIR data
How to Achieve FAIR Data
OPEN Data
FAIR vs OPEN
Open Science
Research Data Frameworks
1 Topic
University Policies
Funder Requirements
3 Topics
Funder Requirements – Introduction
European Commission – Horizon 2020
FWO
The Data Management Plan (DMP)
2 Topics
DMP – Introduction
Questionnaire – Your Main Reason for Writing a DMP
RDM Support
1 Topic
Contact Details
1. Preparing a DMP
Tools
1 Topic
Tools – Introduction
VIB Forms
10 Topics
General Information & Datasets Information
Data Types & Data Purpose
Ethical and Legal Issues
Making Data Findable
Documentation and Metadata
Data Storage & Backup During the Project
Data Access: for Whom and under Which Conditions?
Data Preservation after the End of the Project
Responsibilities
Ready to Submit?
DMPOnline
9 Topics
What is DMPOnline?
7 Main Themes
Theme 1 Data Description
Theme 2 Ethical and Legal Issues
Theme 3 Data Documentation and Metadata
Theme 4 Data Storage and Backup During the Project
Theme 5 Data Preservation after the End of the Project
Theme 6 Data Sharing and Reuse
Theme 7 Responsibilities
Data Collection
5 Topics
Data Collection – Introduction
The Data Flow
Discover Data
Assess the Usefulness of Existing Data
Training Video: Current Ways of Finding Existing Data
Copyright and Intellectual Property Rights (IPR) Issues
2 Topics
About Data Ownership
Confidential or Privacy-Sensitive Data
Licences
3 Topics
About Licences
Software Licences
Training Video: Providing Licences to meet requirements for reuse of datasets and software
Costs Involved with Managing Your Data
2 Topics
Costs – introduction
Data Management Cost Guide
2. Documenting and Organizing Data
Data Documentation
7 Topics
Data Documentation – Introduction
Why Document Your Data?
Examples of Data Documentation
Different Levels of Data Documentation
Metadata
Data Standards
Exercise: Data Standards
Organizing
9 Topics
Research and Lab Notebooks
File Formats
File Naming
Good File Management
Benefits of Good File Management
Do’s and Don’ts
Batch Renaming of Automatically Generated Files
Version Control
Folder Structure
Documenting & Organizing – References
1 Topic
Documenting & Organizing – References
3. Storing Data and Data Security
Data Storage
11 Topics
Data Storage – Introduction
Things That Can Go Wrong
Questions to Consider
Shared or Individual Data
Access Management
External/Cloud Storage
Single or Multiple Storage
Additional or Tailored Services
Store Your Masterfile
Backups
Questionnaire: How Much Data Would You Lose if Your Laptop Got Stolen?
Data Security
6 Topics
Data Security- Introduction
Data Breaches
Prevent Unauthorised Access
Questionnaire: Prevent Unauthorised Access
Legal Agreements and Contracts
Exercise: When to Use Which Legal Contract?
Privacy
8 Topics
Privacy in a Nutshell
Privacy-sensitive Data
Six Principles from the European General Data Protection Regulation
Privacy by Design
Exercise: Which Data Breach Is Breached?
Storing Personal Data
Cases on How to Make Personal Data Accessible
Informed Consent
Storing Data & Data Security – References
1 Topic
Storing Data & Data Security – References
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Theme 3 Data Documentation and Metadata

Writing a Data Management Plan DMPOnline Theme 3 Data Documentation and Metadata
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This section contains the following questions:

  • What documentation will be provided to enable understanding and reuse of the data collected/generated in this project?
  • Will a metadata standard be used?

Later in this course you will learn more about data documentation. Suffice it here to say that documentation basically is any information needed to understand & reuse research data, and to reproduce your research – ideally following standards in your domain. In other words, this could be

  • a codebook/data dictionary explaining variables
  • a dataset structure, relation between files
  • a study context
  • protocols, methods, SOPs
  • notes/annotations
  • machine configurations
  • the software used
  • processing & analysis scripts
  • consent information
  • etc.

Ensure that it is clear what the study was about, what the variables in your data mean and what the codes mean if used. There should be no blind spots.

Metadata refers to a highly structured form of data documentation.

‘Metadata’ by Jørgen Stamp, attribution: digitalbevaring.dk, licensed under CC-BY 2.5 DK
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