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
DMPOnline
9 Topics
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
What is DMPOnline?
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?
Data Collection
5 Topics
The Data Flow
Discover Data
Assess the Usefulness of Existing Data
Data Collection – Introduction
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
Version Control
Folder Structure
Good File Management
Benefits of Good File Management
Do’s and Don’ts
Batch Renaming of Automatically Generated Files
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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FAIR Data – Introduction

Writing a Data Management Plan FAIR Data FAIR Data – Introduction

FAIR stands for ‘Findable, Accessible, Interoperable, and Reusable‘. The FAIR data principles act as an international guideline for the result of high-quality data management.

With the increase in volume, complexity and creation speed of data, humans are more and more relying on computational support for dealing with data. The principles were defined with the focus on machine-actionability, i.e. the capacity of computational systems to find, access, interoperate and reuse data with none or minimal human intervention.

F – Findable

By using correct metadata to describe the data, it will be findable. By using a persistent identifier the data can be found by computer systems automatically.

A – Accessible

The data should be accessible for the long term. Even when underlying data is not accessible, the describing metadata should remain available.

I – Interoperable

The data can be used and combined with other datasets. To achieve this, the data should be stored in generic file types, not in software specific file types.

R – Reusable

The options for reuse should be stated clearly in a licence. Without a licence there is no certainty about the options for reuse and creator rights are implicit.

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