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Open Data

Workshop Description

Open data is essential for fostering transparency, collaboration, and reproducibility in research. This workshop introduces participants to the principles of open data sharing and practical tools for depositing, managing, and sharing datasets on various open-access platforms. Participants will learn how to use platforms such as GitHub, Hugging Face, Zenodo, Figshare, and Dryad to make their research data FAIR (Findable, Accessible, Interoperable, and Reusable).

This session is ideal for researchers, educators, and students looking to enhance their data-sharing practices. No prior experience with open data repositories is required, making it accessible to beginners.

Learning Outcomes

By the end of the workshop, participants will be able to:

Format

This is an interactive, hands-on workshop. Participants will follow along with demonstrations and practice key concepts through guided exercises.

Prerequisites

To ensure a smooth learning experience, participants are encouraged to create accounts on the following platforms before the workshop:

Date and Time

Instructors

Who Should Attend?

This workshop is ideal for:

No prior experience with open data repositories is required.

Registration

To attend, please complete the registration form at this link. Once registered, you will receive a confirmation email with the Zoom link and preparation instructions.

Workshop Recording

A recording of the workshop will be available on the Open Geospatial Solutions YouTube channel after the event.

1. Introduction to Open Data

Why Open Data?

Tools for Open Data Sharing

2. Hands-on: Depositing Data on Open Repositories

Hosting Data on GitHub

  1. Create a new repository.
  2. Add dataset files.
  3. Write a README.md file with dataset descriptions.
  4. Use GitHub releases to archive data snapshots.
  5. Generate a DOI using Zenodo-GitHub integration.

Using Hugging Face for Datasets

  1. Create a new dataset repository on Hugging Face.
  2. Upload your dataset files (e.g., CSV, JSON).
  3. Add a README.md file to describe the dataset.
  4. Use the Hugging Face Datasets library to load and share datasets easily.
  5. Optionally, create a model card for machine learning datasets.
  6. Share the dataset link for public access.

Uploading Data to Zenodo

  1. Log in to Zenodo.
  2. Click on New Upload.
  3. Fill in metadata fields (title, description, keywords, funding, etc.).
  4. Upload dataset files.
  5. Choose a license (e.g., Creative Commons).
  6. Publish and obtain a DOI.

Using Figshare for Data Sharing

  1. Log in to Figshare and create a new dataset.
  2. Upload data files and add metadata.
  3. Assign a DOI and select an appropriate license.
  4. Publish and share dataset links.

Depositing Data on Dryad

  1. Submit datasets associated with published research.
  2. Fill out required metadata and dataset descriptions.
  3. Comply with journal and funding agency data-sharing mandates.
  4. Publish with a DOI for citation and tracking.

3. Best Practices for Open Data Sharing

Ensuring Data Quality and FAIR Principles

Licensing and Attribution

Long-term Data Management

UTK Libraries Resources

More Open Data Repositories

For those interested in exploring additional open data repositories, here are some other popular platforms:

Resources & Further Reading

This hands-on workshop will equip participants with the skills to deposit, manage, and share research data on open-access platforms effectively.

Open Science Workshop
Open Code
Open Science Workshop
Open Access Funding