Learning resources and teaching methods
2024-09-19
Books
https://geographicdata.science/book/intro.html
https://juliaearth.github.io/geospatial-data-science-with-julia/
https://pygis.io/docs/a_intro.html
“Python Scripting for ArcGIS Pro”
“Python for Geospatial Data Analysis”
Websites, blogs, and courses
Videos and podcasts
Qiusheng Wu: https://www.youtube.com/@giswqs
Milos Popovic: https://www.youtube.com/@milos-makes-maps
Ujaval Gandhi: https://www.youtube.com/@spatialthoughts
Teaching methods
Asynchronous learning
Textbooks with code examples
Step-by-step guides
Exercises with solutions (?)
Case studies
Interactive tutorials
Video lectures (podcasts?)
Discussion forums
Synchronous learning
Lectures
Demonstrations
Discussion groups (?)
Practical exercises
Teaching others
Project-based learning
Flipped classroom
Geocomputation with R
Geocomputation with Python
Geocomputation with Python, 1st edition:
- An introduction to geocomputation using the Python programming language
- The book is based on the same principles as the R book, but focuses on the foundations only
- An almost complete version is available online at py.geocompx.org
- It will be published in a similar hybrid model (early 2025)
Blog posts
GitHub organization
Social media
Our infrastructure
Publishing systems: R Markdown with bookdown, Quarto
Collaboration, version control, and continuous integration: GitHub, GitHub Actions with Docker
Hosting: Netlify
References: Zotero
R packages: geocompkg, spData
How does it work?
- Get the recent book source code (git pull)
- Write, write, write
- Update the book (git push)
- The book is automatically built and deployed
- Once a week the solution website is automatically updated1
Larger changes or additions are discussed in issues, made in branches, and reviewed in pull requests
Writing new FOSS4G materials
https://quarto.org/ is a great tool for writing books, blog posts, and other materials1
Technical stuff is (mostly) easy: look at the source code of other works
(or just type quarto create in your terminal)
The hard things
Getting started
Some technical challenges, e.g., having consistent html and pdf versions, incorporating reviewers’ and copy editors’ comments to the book
Finding time
Getting feedback
Making decisions about the content (a trade-off between being timely and timeless)
Measuring impact (externalities)
Considerations
To publish or to self-publish, that is the question (or not to publish at all?)
Publishers allowing for a hybrid model books: CRC Press, O’Reilly, Princeton University Press
Self-publishing venues: Lulu.com, leanpub.com, Amazon.com
Self-publishing advices: Data Science Heroes Blog, Bruno Rodrigues
Copyrights? Licenses?
Motivation(s)
Audience
Benefits vs costs
Generality vs specificity (also: new technologies?)
Maintanance (being up-to-date)
Social media
Hashtags: #rspatial, #geopython, #juliageo