Notes for Round 2 of Open Science: An Introduction

• Course sign-up opens July 22
• Course begin Aug 5 mon
• Open science will start Aug 2 - first synchronous session, on Fridays - 4 Fridays

1. Updates
   1. Updates/reorganization
   2. Send to selected open science folks for review
   3. Send to SOO for community review (one p2pu, one cc)
2. Facilitation
   1. Schedule (use collaborate or hangout)
      1. Aug 2 - 4 fridays following
      2. Aug 2 - will be longer
      3. 3 subsequent will be shorter - hopefully with guest speakers
      4. Outlined in About page
   2. Needs?
      1. Disqus, links to blog posts
      2. Google group for either discussion about course or content. 
      3. Emails - get Billy emails after sign-up closes Aug 4
3. Badge for the course
   1. Badge workflow on SOO list
   2. One badge for each module - so 3 total. - Default p2pu badge system
   3. One badge for facilitated session. - SOO partner badge
   4. Billy send to Vanessa and SOO list - remove CC logos
4. Promotion
   1. open science listservs
   2. okfn - school of data
   3. citizen science groups
   4. puneet - ping

Jane will check back w/billy July 8

Open Data Day February 23rd,  2013 - Open Science Course Sprint (Peer to Peer University)

= Guidelines for a School of Open course =
Below are some questions to think about in creating a School of Open course. 

What course are you interested in creating as part of the School of Open? 
When you think about creating a course, ask yourself, "What do I want to help people DO?" versus "What do I think people should know or learn?" For example, I want to help:

I want to help people (who specifically? citizens? scientists? researchers? who is your ideal target audience for this course?) get "hands on" with Open Science, understanding what makes science "open", how they can find/use/build on Open Science work, and how to share their contributions back to the commons.

How can open content, tools, or processes help people do what they do better?
Open practices include using the content, tools and processes shared with us, enabling others to use, share and adapt what we create, and supporting transparency in our content, tools and processes. If a course involves teaching or learning about any of these practices, either broadly or in a particular field, then it probably fits in the School of Open.

This course will involve learners accessing openly-licensed scientific datasets, understanding open source tools available for them to examine/manipulate the data/research, and basic "open" practices to allow others to built upon their work.

Is there a specific aspect or mechanism that keeps people from taking advantage of open stuff?
Think about the key obstacles that discourage someone from learning about openness, applying open tools, or sharing their work openly. For example, what might cast doubt into a musician's mind when it comes to using openly licensed material? Why might a graphics designer refrain from sharing her/his works openly? Are there good reasons for not going fully open or are certain misconceptions playing a role?

Many open science datasets are hard to find (unlabeled, held in instututional silos, etc) or are not "open" for reuse based on confusing/conflicting policies. Software tools for working with this data are often unknown to potential users, though OpenOffice Calc, R, Gephi, and other open-source tools are available for free. When others work with open data, scientific or not, the results of their work are often not shared in a way others can reuse it.  This course will show learners how to spot open science data, how they can work with it within the limits of licensing and with the open tools available to them, and how to share it back to open repositories or host it in a way it can be found and use by others (linked back to original datasets/publications/repositories).

Who are you trying to help? Think about the course from the learner's standpoint. 
Who will be taking the course? What real world questions is s/he likely to ask? What needs is s/he likely to have and barriers s/he is likely to run into? 

Science researchers, both novice and experienced - with varying famliarity with open
Citizen scientists

Three major questions these people would have about open science
Problems they have that could be solved by the use of open tools

Example user scenarios:

• John is a student in his 20's, returning to a masters program in Biology and has not conducted any research since his undergrad (~5yrs ago).  He's heard about Open Science and understands that he can make use of the work of others, but does not know the first thing about how to find it, use it, or push his work back into the system.  He'd like to refresh his research skills while making his research more open, contributing to the open movement.  This is a starting point for him. Ok - so this is a person with passing interest. Is there an incentive for him to learn about open and incorporate it in his work?
• Edward is a tentured professor at a well-known university, having published from his research findings many times over.  He's never shared his research data and has only used proprietary software to work with his data...until now.  He's interested in understanding what open science is about (why?), how he can share his datasets in a way that others can use it, and also how he might find collaborative partnerships in Open Science around his research interests.  He has data and wants to create more, but is not sure how to do it.
• Allison is a hacker.  She is a hobbyist, heavy into botany, and cross-breeds her own plants.  She's kept loose notes on her work, but stored them in plain text documents on her local computer and is the only person who can understand them.  She hopes that other people can benefit from her work, and would love to solve some of the issues she's been having crossing certain types of plants.  If she knew about a repository that allowed her to use similar research data from others, she would want to both use and contribute back to the system.  She doesn't know where to start. Ok - so her motivation is to find people to help solve these issues/problems she's been having. 

What can you reuse and build on?
Do openly licensed resources already exist that explain/teach any of this? Are people already teaching or learning about related topics elsewhere that you can tap to collectively build the course?

• You don't have to start from scratch; adapt existing courses/resources to your audience: http://pad.p2pu.org/p/school-of-open-resources

This Google Doc has some education-related resources for working with Open Science Data: http://bit.ly/Xa7WeO

The Open Knowledge Foundation has a Open Research Handbook in final stages of being built: http://www.booki.cc/open-research-data-handbook/
OKF also has a lot of great information in the Open Data Handbook, though not science-specific: http://opendatahandbook.org/en/index.html

We can also borrow snippets of text or link out to Open Copyright or other School of Open courses for those that want to dive deeper into information about copyright beyond the data-specific basics of what we will touch on in the course

Document your thinking behind the course and learning activities
The learner may ask, why am I doing this? What am I learning? Be transparent about the learning objectives.

Learners will, at the very least, gain an understanding of how open content/tools/processes can assist with their exploration of science, and ideally will give them a starting point from which they can build out their understanding and contribute back to the science commons.

Step 1 - list skills and map activities/exercises to skills, starting from https://p2pu.org/en/groups/make-a-course/content/what-is-the-problem-that-you-are-asking-your-peers-to-solve/

Example of skills mapped to activities:
+ Finding/discovering educational resources that are open for sharing and remix (CC licensed or in the public domain)

• Project: Exercise of finding several open educational resources for use in the classroom.

+ Remixing open educational resources

• Project:  Exercise of adapting an open educational resource for classroom use.  Optional: may work with others if they are working in same subject area.

+ Sharing remixes on the web

Step 2 - start building in beta

Course sprint

Flipchart - I would have them start with drawing the person they want to help. Having them list 3 questions/problems of that person. Listing out skills that will be mastered in the course, and coming up with projects/activities/exercises that would lead to learning those skills. Then prioritize/organize those skills/activities into an outline of the course.

Here's an example to start with from what we did in Palo Alto: https://creativecommons.org/weblog/entry/34550

Module/Skill Development for Course

Module 1: INTRO TO OPEN SCIENCE

• What is Open Access?
• What is Open Data?
• What is Open Research?
• Why does this matter to me?

Module 2: EXPLORE OPEN ACCESS

• Publications and Articles
  • Copyright
  • Citation Management
  • Groups/Shared Libraries
• Journal Repositories
  • Open Repositories
  • Limited-Access Repositories

Module 3: EXPLORE OPEN DATA

• Data Types
• Tools to work with Data
  • Statistical Analysis
  • Visualization
• Open Datasets

Module 4: EXPLORE OPEN RESEARCH


Module 5: PARTICIPATE IN OPEN SCIENCE

• Projects in Progress (ie Zooniverse)
• Platforms for Starting Projects (Crowdcrafting)
• Sharing your Work back to the Commons (PLoS, Figshare, or other public documents/wikis)