Open Data Training

Instructor Guides

This site is a resource for train-the-trainer type materials on Open Data. It's meant to provide a series of approachable, fun, collaborative workshops where each of the modules is interactive and customizable to meet a variety of audiences.

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Basics

Introduction to Open Data

Guides 1-5

These Instructor Guides are introductory-level, non-technical, guides to conducting a Open Data workshops that serve as introductions to basic Open Data content

1. Why Open Data - Why open data is valuable and important.

2. How to Open Your Data - How to make your data open and available for others to use.

3. Sharing Your Data - How to publish your data and make it accessible to others.

4. Become a Data Hunter - How and where to find data shared by others.

5. Making Friends with Other People's Data - What you need to do to be able to reuse other people's data.

Disciplinary

Disciplinary Open Data Needs

These guides focus on the specific open data needs and challenges of researchers in different disciplines.

Planned for 2017

Health Sciences - Covering issues and needs around qualitative and quantitative data, IRB, physical specimens, privacy and ethical issues, as well as considerations surrounding large and dynamic data sets.

Life Sciences - Primarily focusing on quantitative data, as well as the other issues mentioned in Health Sciences but focused on life sciences subject areas.

Humanities - Concerns with more multimedia and qualitative forms of data, with a special focus on publishing considerations and copyright issues.

Social Sciences - Very similar to Health Sciences topics from a Social Sciences perspectives.

Physical Sciences - Greater focus on quantitative data and large and dynamic data sets.

Advanced

Advanced Topics in Open Data

The guides in this series go beyond the basics and dig deeper into more advanced areas of open data and data management.

Planned for late 2017 - early 2018

Data Visualization

Advocacy

Preservation & Archiving

Deep Dive into Privacy & Ethics

Data Analysis Methods

Sharing Code

Help

  1. Getting Help

    Here we'll hopefully answer questions you might have.

    • QUESTION

      ANSWER

      QUESTION

      ANSWER

  2. Resources

    Here we'll list some persistent resources that you might use throughout the workshop.