Data Publication

Research Data Management for Psychology and Neuroscience
Course at University of Hamburg, RTG 2753: Emotional Learning and Memory
Slides | Source

Dr. Lennart Wittkuhn

lennart.wittkuhn@tutanota.com

14:00

Schedule

Day	Date	Time	Title
2	2026-02-06	09:30 - 10:00	Introduction to Version Control
2	2026-02-06	10:00 - 12:00	Version Control of Data with DataLad
2	2026-02-06	12:00 - 13:00	Lunch Break
2	2026-02-06	13:00 - 14:00	Data publication
2	2026-02-06	14:00 - 16:00	Integrating with data infrastructure at UHH (and beyond)
2	2026-02-06	16:00 - 16:30	Summary & Outlook

1 This session: Data Publication

Objectives

💡 You understand the importance of data publication for FAIR research data management.
💡 You can write Data Availability Statements for research articles.
💡 You know how to choose appropriate licenses for research data.
💡 You understand the role of persistent identifiers in ensuring reliable data access.
💡 You can select suitable repositories for different types of research data.
💡 You are aware of legal considerations when publishing research data.

Overview

Data publication is a crucial step in FAIR data management, ensuring data findability and accessibility.

Key components of data publication:

Data Availability Statements
Appropriate licenses
Persistent identifiers
Suitable repositories

2 Data Availability Statements

What is a Data Availability Statement?

A Data Availability Statement is a special section in an article that states:

Whether the authors have made their research data available
Where readers can access the supporting data
Under what conditions the data can be accessed

Typical placement:

Usually before the Reference section
Some journals require these statements
Highly recommended even when not required

Open Data Example:

“The datasets generated and analyzed during the current study are available in the Zenodo repository: https://doi.org/10.5281/zenodo.123456”

Note: This is an example. The DOI does not resolve.

Restricted data example:

“The datasets generated during the current study are not publicly available due to privacy restrictions but are available from the corresponding author on reasonable request.”

3 Licensing Data

Why Licenses Matter

Licenses are standard contracts that regulate usage rights:

Enable reuse by clearly stating conditions
Protect your interests as a data creator
Prevent legal uncertainty for potential users

⚠️ Without a license, it’s unclear how others can reuse your data, and they might avoid it entirely!

Copyright Considerations

Important: You can only assign licenses to work you hold copyright for!

Data from creative processes (humanities, qualitative social sciences) → likely copyrighted
Data from simple measurements (natural sciences, quantitative social sciences) → likely not copyrighted
When in doubt → use CC0 (public domain dedication)

Creative Commons Licenses

License elements:

BY: Attribution required
SA: Share-alike (same license)
NC: Non-commercial use only
ND: No derivatives allowed

From most to least permissive:

CC0 (public domain)
CC BY
CC BY-SA
CC BY-NC
CC BY-NC-SA
CC BY-ND
CC BY-NC-ND

Licensing Recommendations

Best practices for research data:

CC0 - when data likely not copyrighted (preferred)
CC BY - when copyright applies but you want maximum reusability
Avoid restrictive licenses (NC, ND, SA) unless absolutely necessary

⚠️ Why avoid restrictive licenses?

Can prevent combining datasets
May block follow-up research
Creates compatibility issues

4 Persistent Identifiers

The Problem with URLs

Imagine this scenario:

You publish data at https://repository.university.edu/dataset123
Repository shuts down or migrates
Your dataset gets a new URL
Papers linking to the old URL can’t find the data

Solution: Persistent identifiers (PIDs) that redirect to current location!

Choo Choo Choose Your License!

Digital Object Identifier (DOI)

What is a DOI?

Points directly to digital object, not location
Format: 10.5281/zenodo.4322849
Access via: https://doi.org/10.5281/zenodo.4322849
Redirects to current location

Benefits:

Permanent access
Reliable citation
Professional appearance
Required by many journals

ORCID and ROR

ORCID (Open Researcher and Contributor ID)

Unique identifier for researchers
Links all your professional work
Handles name changes, moves
Free and self-maintained

ROR (Research Organization Registry)

Persistent identifiers for institutions
Disambiguates affiliations
Used by many platforms
Easier than typing full details

5 Choosing Repositories

Types of Repositories

Discipline-specific

OpenNeuro (neuroscience)
GenBank (genomics)
Preferred when available
Community standards

General purpose

Zenodo
Figshare
OSF
Good fallback option

Institutional

University repositories
May have restrictions
Good for compliance

Repository Selection Criteria

Essential features:

Assigns DOIs or other PIDs
Supports appropriate licenses
Long-term preservation commitment
Good metadata support

Consider also:

File size limits
Access control options
GDPR compliance
Community usage
Costs

Finding Repositories

Use these tools to find suitable repositories:

re3data.org

Registry of research data repositories
Search by discipline
Filter by features
Shows criteria with icons

Publisher recommendations:

PLOS ONE recommended repositories
Springer Nature guidance
Journal-specific lists

6 Exercises

Exercise 1

Exercise 1: Data Availability Statement Analysis

Task: Examine published research articles and analyze their Data Availability Statements.

Instructions:

Find 2-3 research articles from your field published in the last 2 years
Look for Data Availability Statements in each article
For each article, answer:
- Does it include a Data Availability Statement?
- If yes, where is it located in the article?
- Does it provide clear information about how to access the data?
- Are any restrictions or conditions mentioned?
- Is the data actually accessible through the provided link/information?

Discussion: What makes a good vs. poor Data Availability Statement?

Exercise 2

Exercise 2: Repository Selection

Task: Find and evaluate repositories for your research data.

Instructions:

Visit re3data.org
Search for repositories relevant to your research field
Select 2-3 repositories and evaluate them based on:
- Does it assign DOIs?
- What file size limits exist?
- What access control options are available?
- Is it recognized in your research community?
- What are the costs (if any)?
- Does it support your preferred license?

Exercise 3

Exercise 3: Create Your Data Publication Plan

Task: Develop a data publication plan for your current or planned research.

Components to address:

What data will you publish? (consider legal and ethical constraints)
Which repository will you use? (justify your choice)
What license will you apply? (explain your reasoning)
How will you link your data to publications?
What documentation will you provide?
When will you publish the data? (consider embargoes, journal requirements)

7 Summary

Best Practices Summary