Mika/Temp/WikiFCD/Course

This page is for planning a course on how to contribute to and use data from WikiFCD.

About the course

This course aims to introduce students to 1) the issues surrounding FCDs in global nutrition research and 2) the concept of peer production. Students will gain knowledge and practical skills to engage directly in building a global food composition database.

The course will have two parts. During the first term, the students will learn about peer production and how to contribute to Wiki-based projects. In the second term, students will learn to use the data from WikiFCD to explore their own research questions while they continue to also contribute various FCDs to WikiFCD.

Schedule

• JHSPH has 4 terms (7 weeks each; 39-40 instruction days) + 1 summer term (8 weeks) and 1 winter intersession term (2 weeks):

Summer Term: Wednesday, July 1 - Wednesday, August 26 (39 class days)

1st Term: Monday, August 31 - Monday, October 26 (40 class days)

2nd Term: Tuesday, October 27 - Wednesday, December 23 (39 class days)

Winter Intersession: Monday, January 4 - Friday, January 15

3rd Term: Monday, January 25 - Friday, March 19 (39 class days)

4th Term: Monday, March 29 - Friday, May 21 (40 class days)

• If we can teach in the 1st and/or 2nd term, that would be nice for the grant application to be submitted in November.
• It seems it's about 1 hour instruction time per credit. Students register 16 credits per semester (2 terms).
• Aim for meet once a week for 2 hours = 2 credits?

Course Aims

1. To learn about issues with FCDs in global nutrition research
2. To learn about peer production
3. To learn about Wikidata and Wikibase
4. To learn how to contribute to WikiFCD
5. To learn how to use data from WikiFCD

Structure of the course

• Lecture
• Lab
• Individual projects

Course schedule

1st term: Aim 1 through 4

Week	Aim/Learning objectives	Content	Assignment	Assignment Due date
Week 1	Aim 1: Learn about FCDs	Learn about FCDs Learn about issues related to FCDs and history of global databases Discuss potential solutions	Readings on peer production Create an account on Wikimedia Wiki Education Wikidata Professional Development Training Modules: Orientation, Introduction to Wikidata	Week 2
Week 2	Aim 2/3: Learn about peer production Learn about Wikimedia projects, Wikidata, and Wikibase Learn how to participate in wiki-based projects	Lecture on peer production Discussion on pros and cons of peer production for global FCD development Lecture on Wikimedia projects, Wikidata, and Wikibase - pull materials from Wiki Education on Wikidata? Example of material we could adapt that I created for another event Edit an Wikipedia article	Readings Databases and Linked Data Make Edits on Wikipedia or Wikidata Create an account on WikiFCD
Week 3	Aim 4: Learn more about wiki editing Learn about structured data	Lecture on Wiki markup Edit Wikidata	Readings Edit food/nutrition related pages on Wikidata
Week 4	Aim 4: Learn about WikiFCD and Open Food Facts Learn about different ways to import data from elsewhere Learn about licensing	Lecture on structured data and how this could help our research Examples of good and bad Wikidata pages Edit meta data (FCD information)	Readings Search and add missing FCD meta data Python tutorial
Week 5	Aim 4: Learn about online communities and collaboration OR Learn how nutrient data are produced (field trip to USDA chemical analysis lab)	Lecture on successful online communities Discussion on how to build a successful global WikIFCD community OR Field trip.	Readings Learn a script to import example FCD csv (develop for this class)
Week 6	Aim 4: Explore ways to connect knowledge bases	Learn about other Wikimedia projects and Wikibase based projects Discuss potential research questions that can be answered by connecting these projects	Choose your research proposal topi
Week 7	individual project consultation
Week 8	Presentation on research proposals

2nd Term: Aim 5

• Students will select their own research questions and try to answer them analyzing data from WikiFCD.
• Skills: SPARQL
• Optional skills: statistical software

Week	Aim	Content	Assignment	Assignment Due date
Week 1	Aim 5
Week 2	Aim 5
Week 3	Aim 5
Week 4	individual project consultation
Week 5	Aim 4
Week 6	Aim 5
Week 7	Aim 5
Week 8	Presentation