Syllabus
: In this lesson, we will get an introduction to the course.
Middlebury College Geography Course GEOG0323
- Email: josephh@middlebury.edu
- Office: McCardell Bicentennial Hall 6th Floor: conference room, GIS lab, or room 634
- Zoom Meetings: Please find this information on the secure CourseHub site
- Availability: W 2pm–4pm F 11am–12pm
- Lecture: MWF 12:40–1:30 in The Orchard
- Lab: W 7:30–10:25 in BiHall 403/411
- Kufre Udoh Office Hours Friday 3:00-4:30, BiHall 6th Floor West Study Area (Except Thurs, April 22)
For assistance outside of office hours, your resources include:
- The course wiki and issues
- Classmates
- Documentation, Issues, Forums, or Support/FAQs for the data or software we are using
- Stack Exchange or similar
- Post a new course issue
- Only private/confidential concerns should be sent to email
Course Description
In this course we will study geographic information science (GIS) with open-source software and critical GIS scholarship. In labs, we will practice techniques to include: data acquisition and preparation for analysis, spatial SQL database queries, automating analysis, spatial interpolation, testing sensitivity to error and uncertainty, and data visualization. We will read and apply critical research of GIS as a subject and with GIS as a methodology. Spatial data sources for labs and independent research projects may include remote sensing, micro-data, smart cities and open government data, and volunteered geographic information (e.g. OpenStreetMap and social media).
Prerequisite: GEOG0120 Human Geography with GIS. Programming experience is not assumed or required! You just need to be willing to learn how to translate the spatial analysis that you know from desktop GIS (QGIS, ArcGIS, etc.) into code.
Learning Goals
- Survey FOSS4G (Free and Open Source for Geospatial) in terms of its landscape of organizations and projects, research applications, and (radically) unique political economy of knowledge production.
- Expand your functional knowledge of the nature of geographic information with respect to data standards, structures, metadata, provenance, error, and uncertainty.
- Creatively apply FOSS4G to address compelling questions in human geography and problems in social and environmental sustainability.
- Critically reflect on emerging opportunities and ethical dilemmas in open-source geographic information science.
- Learn how to reproduce existing geographic research and to produce geographic research that is open, reproducible and replicable.
- Design and communicate research effectively in multiple media, including digital media, reports, presentations, maps, graphs, tables, data, and code.
- Become competent and confident in conducting research, learning new methods, and overcoming errors, uncertainty, and technical difficulties. Learn to “debug” problems and teach yourself new techniques through structured experimentation.
To be honest, I’m excited to learn and share new open source GIS technologies with you as we expand our imagination for future research and careers in Open GIScience.
Expectations
- Inclusivity: Consciously and actively include yourself and others in learning, participation, collaboration, and discussions. Inclusivity may be achieved through academic accomodations and/or student resources for learning and research. Accomodations and correspondence about them are confidential.
- Academic Honesty: Open source and open science have a different ethos about intellectual property and its value than most of us are accustomed to. In the first two weeks of class, we will discuss and update our expectations for the honor code and academic honesty in a course focused on open science.
- Deadlines: You must always commit the progress that you have made on assignments by the assignment deadline. In case unforseen challenges or delays have prevented full completion of an assignment, you are required to record the progress that you have made, describe the barrier(s) encountered and anything you have learned about it/them, and propose a solution.
- End of Semester: With many seniors in a spring course, it is not possible to accept late assignment submissions during or after finals week. Incomplete grades can only be considered if extreme/unexpected circumstances arise in the final weeks of the semester and if the the majority of assignments have already been satisfactorily completed.
Student Work & Evaluation
- Blog Posts & Active Participation
0.2 (routine)
- Maintain GitHub site & repositories
- Review or react to readings in a personal blog post.
- Collaboratively take notes on discussions or while studying papers, software, or data sources.
- Friday in-person discussions will be as lively as you make them as a group.
- Working with an open science ethos means openly sharing your challenges and discoveries in person during lab and online using the course Issues and Wiki.
- Peer review of GitHub portfolios
- Periodic self-reflection on your learning and participation
- GIScience Analyses
0.5 (each analysis will be our primary focus for one to two weeks)
- QGIS Spatial Interaction
0.08
- GRASS Hydrology
0.08
- PostGIS Urban Resiliency
0.08
- RStudio/PostGIS Climate Vulnerability
0.08
- RStudio Twitter Disasters
0.08
- Python COVID-19 Access to Healthcare Resources
0.08
Independent Project 0.08 (equivalent in duration, difficulty, and deliverables to any of the directed analyses; due with final GitHub Profile)- Bonus Credit
0.02
- Final GitHub Profile
0.3
- As the course concludes, you have a final opportunity to revise your GitHub portfolio content.
- Final revisions due to GitHub by May 25 (any time).
Typical Rhythm
- Monday Lecture: Learn and practice new GIScience techniques or review/revise techniques from previous challenges.
- Wednesday Lecture/Discussion: Set up a lab problem by discussing the problem and its context, significance, implications, etc. This may include assigned reading or research tasks in preparation of a lab problem.
- Wednesday Evening Lab: Work together on GIScience analyses.
- Friday Discussion: Read and discuss GIScience research/literature and discuss findings from lab problems.
Materials & Resources
There is no required textbook.
Digital materials will be provided on this site and in other repositories of the GIS4DEV GitHub Organization, including a private repository for literature.
Due to health and safety restrictions this spring, you will need your own personal laptop computer to participate in the class. You will need Windows or MacOS 10.13 (High Sierra) or better. You must be willing to install a variety of free software and apply for/subscribe to a variety of free internet-based services, listed below. We will not install or sign up for all of these programs/services at once, but please attempt to get each one running quickly as you are prompted throughout the semester, so that we have ample time to troubleshoot or find alternative solutions.
General Expectations for GIScience Analyses
Expectations applying to all seven analyses:
- Write up a summary and interpretation of the analysis.
- Include methods documentation to support full reproducibility. This is most easily achieved by having a model and/or code with good comments.
- Visualize results with maps and/or graphs.
- Publish the full package (write-up, methods documentation and visualization of results) to your GitHub pages by Monday at noon.
Main Page