Open Data Training

Guide 1: An Introduction to Open Data

Why open data is valuable and important.

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This training module is a very quick introduction to open data for newcomers to the topic, and for those who know a bit but want to know more. This material was produced by Mozilla Science Lab, a program to encourage the use of open source practices and web technologies to do better science.



Student Prerequisites


Total Time to Complete

About 1 hour, including transitions.

Learning Objectives

  • Define open data
  • Describe the benefits of open data
  • Respond to common challenges to open data

Content Outline

Instructor Guide

Instructor Prerequisites:

  1. Topic 1: Introductions and Discussion about Open Data

    • Introductions

      • Instructor (3 minutes)
        • Explain your background, how you became involved in open data.
      • Why this training, why Mozilla? (2 minutes)
        •   • Intro the training series, and how it was created (collaboration, sprints, output of fellows program)
        •   • Structure of the session, content exploration through activities
        •   • Why MSL and Mozilla are involved, your relationship to Mozilla
      • Why open data now? (2 minutes)
        •   • More data than ever-- define types of data here
        •   • Pressure from funders, want more impact from data
        •   • The web as sharing/collaboration tool
      • Data Management SNAFU Video (YouTube) (3 minutes)
  2. Topic 2: Think-Pair-Share Exercise

    • What is Open Data?

      1. Participants spend 2 minutes thinking of a definition and, if possible, supporting examples.
      2. Participants pair up to share and talk through their thoughts with another participant.

        Depending on the size of the group, insights can be shared whole group or recorded on a white board, etherpad or other shared document.

      3. Once think-pair-share is complete, the instructor should help the group come to a definition (5 minutes)
  3. Topic 3: Case Study Exploration

    Group case studies allow participants to interpret and draw conclusions from the cases without instructor intervention; several cases can be discussed quickly.

    Working together, students review a case to summarize the details and present any controversies involved in the case. Suggested cases:
      • Reinhart and Rogoff (PDF)
      • Celera and HGP (PDF)

    Cases may be assigned prior to the session, if possible and preferable.

    Instructors should select cases that have elements of controversy for good discussions.

  4. Topic 4: Benefits of Open Data

    Run through the seven benefits from Primer 1 (Why Open Data?), with brief explanations.

  5. Topic 5: Challenges to open data

    Participants practice responding to common challenges to opening data, and advocating for open data.

    Instructor starts by asking group for challenges they’ve heard, suggests a few.

    See “Common Challenges” document for challenges to mention, but give group a chance to come up with their own. Share the document AFTER the role-play.

    Instructor assigns roles to participants using cards: each role has a position (for or against open data), a background (ie, administrator), and motivation (for example, publishing a first paper, getting more grants, making administrative tasks easier, getting a post-doc position, getting tenure).

    Participants can ask for a blank card and make their own character/scenario if they’d prefer.

    Participants pair up (pro with con/undecided) and do a 3 minutes role play conversation.

    Ask for reflections/thoughts on how this felt, what did you learn, any insights.
    Point users to the Challenges document as a guide for these conversations.

  6. Topic 6: Resources and Wrap

    Provide links to Primer 1, and other relevant resources.

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