A new complete course in Data, GIS, and Society
I have created a new course linked here, with a focus on geospatial data, GIS, and society. This course invites learners to work with real data to solve problems and foster skills through a set of readings, hands-on activities, discussions, quizzes, and a final project. I also invite instructors who seek to incorporate meaningful data and discussion about data in their courses to use all or part of this course in their own courses and programs.
Course Description:
Geospatial data are the foundation upon which GIS and spatial analysis rests. As GIS has matured, the challenge has evolved from generating data to managing the enormous volume of data from government agencies, nonprofit organizations, and industry, and increasingly, from ordinary citizens through citizen science and volunteered geographic information efforts. Key to working with this volume of data are essential issues such as privacy, copyright, public domain, cost recovery, metadata standards, and data quality that GIS professionals must grapple with to be effective in the 21st Century. This class discusses and applies these issues and works with a rich array of data sources to enable effective decision-making in a Geographic Information System. The prerequisite for this course is an introductory GIS course or similar GIS course and/or work experience.
Course Questions:
The course is focused on three questions:
1. How can I find geospatial data for my projects? ✔️
2. How do I know if I can trust the geospatial data that I find? In other words, how can I assess geospatial data quality? ✔️
3. How can I consider societal issues surrounding geospatial data and tools, including copyright, location privacy, ethics, symbology, classification methods, map projections, and others? ✔️
Course Philosophy:
Four philosophies run through the course:
✏️1. Data is the foundation for all mapping, analysis, and decision-making that stems from that mapping and analysis. Thus, data and data quality are vitally important to continually ask questions about, to seek, and to assess.
✏️2. Scale matters. Patterns and relationships may exist at one scale and not another, and vice versa. The scale at which you are conducting your analysis and the scale at which your data has been collected and published have great influences on the patterns that you will see, and the patterns that will remain hidden.
✏️3. You will encounter data that is understandable, and data that is confusing. You will encounter data portals that are easy-to-use, and others that are difficult. This is intentional: The course instructor is not cleaning up any of the data or the data sites. You will encounter the exact same thing in the workplace, and learning how to deal with geo-data challenges is central to the objectives of this course.
✏️4. Today's GIS tools and open data portals are easier to use than ever before. However, learning GIS is not just learning software interfaces and where data are located. Central to successful use of GIS and to this course is cultivating a healthy critical view of data and of GIS tools--recognizing their benefits, and also their limitations.
Course Themes:
Weekly themes of this course include:
Week 1: Spatial data and the public domain. GIS in our everyday lives. 📖
Week 2: Vector data model and data, portals, data quality. 📖
Week 3: Raster data model and data, portals, location privacy. 📖
Week 4: Data costs, local data access. 📖
Week 5: Metadata and standards. National and state data portals. 📖
Week 6: National and international data infrastructures and initiatives. 📖
Week 7: Data policies. 📖
Week 8: Crowdsourced data. Data disclaimers. 📖
Week 9: Cloud computing and GIS. Software as a service. 📖
Week 10: The future of public domain spatial data. 📖
Course Prerequisites and History:
This 10 week online course was created for a graduate program inside a university GIS program. This course is meant to follow an introductory course covering basic GIS skills. I have taught, assessed, and improved this course each year over the span of over 20 years and am happy to share it with the community. The course was originally taught face-to-face, then taught online via a Learning Management System (LMS), and then moved into a space so that you can access it, above.
Course Issues, Skills, Data Sets, and Portals:
Major issues addressed include: Data sources, data representation and models, data quality, metadata, spatial data input and output, spatial analysis, location privacy, copyright, streaming vs. downloading data, on premises servers vs. open access, spatial data serving policy. 🌍
Major skills addressed include: spatial data management, analyzing tabular information, data input and querying, locating spatial data, assessing spatial data, formatting spatial data, projecting, georeferencing, geocoding, overlay and proximity, merging, raster data analysis, preparing 3D visualizations, making decisions with GIS and data. 🌍
Major data sets used in this course: World Resources Institute (WRI), USGS vector and raster data, US Census Bureau demographic data, historical images and maps, UAV imagery, soils and hydrography data, WWF ecoregions data, land cover data, real-time data feeds, xy coordinate data, satellite imagery, and more. 🌍
Data portals included: ArcGIS Hub sites, ArcGIS Living Atlas of the World, USGS National Earthquake Information Center, USGS National Map, local government sources, UNEP, data.gov, state GIS portals, and others. 🌍
Course Delivery Formats:
The course contents are served as an Experience Builder app. Each tile in the graphic above links to a story map. The introduction "row" in the Experience Builder app contains 4 elements, or tiles. Week 1, reading across, contains 3 elements; Week 2 contains 2 elements, and so on. Toggle to the other two pages in app to see the rest of the course.
To see the course contents as a story map collection, click here. Both Experience Builder and Story Map collections have advantages. Consider content that you would like to host, or you want your students to host, and think about serving that content through Experience Builder, Story Map Collections, ArcGIS Hub sites, or via the ArcGIS APIs and SDKs. By exposing your students to these many options, you foster their skills across the web GIS platform as they gain even more capability and empowerment.
Course Text and Relevance:
The course uses The GIS Guide to Public Domain Data as its text, that I co-authored with Jill Clark, and readings and activities from the book's associated data blog, Spatial Reserves. The course was originally conceived by the University of Denver, and I salute Steve Hick there for his foresight in establishing and keeping this course on the DU University College GIS roster. I changed the course over the years from a focus on a survey of spatial data types and portals to a solving problems with spatial data course with a heavy infusion of societal implications.
I would argue that this course is more relevant now than ever before, now that everyone can easily access, use, create, and share geospatial data, and societal issues surrounding location and mapping, including AI, become ever more simultaneously personal and global. I encourage other universities and college to consider offering a "data and society" focused course. If you do not have one at your institution, perhaps this course can provide some ideas and inspiration.
The textbook, exercises, and everything a student needs to take the course are included in the Experience Builder app. Everything a faculty member needs to incorporate the course into your own program and courses is there as well. The only things that did not completely port from the LMS are the interactive discussion boards and the self-assessment capabilities of the quizzes.
Course Structure and Sequence:
Each week of the course, a set of readings provides background, and a short activity fosters skills. During selected weeks, a longer hands-on lab activity is included, and a short quiz for the learner to assess their progress is included. Leading up to the last weeks of the course, a final project proposal involving GIS and public domain data is also included, to be turned in during the last week of the course.
The short hands-on activities each week using ArcGIS Online and ArcGIS Pro cover the following themes:
Week 1: Filling out a crowdsourced survey and visualizing the results in a map and dashboard. ✔️
Week 2: Analyzing real-time x-y formatted data (earthquakes). ✔️
Week 3: Using NREL renewable energy data to choose the optimal site for a wind farm. ✔️
Week 4: Analyzing floodplains in Boulder County Colorado. ✔️
Week 5: Analyzing risk to reservoirs from hurricanes in Texas. ✔️
Week 6: Comparing national data portals in the USA and New Zealand. ✔️
Week 7: Examining metadata and standards. ✔️
Week 8: Examining data disclaimers, add data to crowdsourced project. ✔️
Week 9: Using a map package to examine ecoregions in Brazil, save to the cloud. ✔️
Week 10: Final project presentation. ✔️
The longer lab hands-on activities using ArcGIS Pro cover the following themes:
1. Examining the temporal and spatial pattern of zebra mussels invasive species in the USA and Canada.
2. Assessing the optimal locations for expanding tea cultivation in Kenya.
3. Siting a fire tower in the Loess Hills, Nebraska.
4. Creating an ecotourism map of New Zealand.
Because of the course's short (10-week) duration, time did not permit me to include all of the lab exercises that we created for the public domain data and book. However, the additional 6 lab exercises are here. These additional labs cover the following themes:
- Climate Change (Coastal issues)
- Locating A High Speed Internet Cafe
- Flood Risk Analysis
- Land Use Suitability
- 3 hazards: Natural and Human-Caused
- Hurricane hazards assessment
The syllabus, objectives, software, discussion, quizzes, and final projects are all included, and the course is meant to be taught and learned in the following sequence:
Week "O": (before the course begins and during Week 1): Goals, instructor information, syllabus, software, announcements.
➡️ Week 1: Discussion 1, Lab 1.
➡️ Week 2: Discussion 2, Quiz 1.
➡️ Week 3: Discussion 3, Lab 2.
➡️Week 4: Discussion 4, Quiz 2.
➡️Week 5: Discussion 5, Lab 3, Quiz 3.
➡️ Week 6: Discussion 6
➡️Week 7: Discussion 7, Lab 4, Quiz 4.
➡️Week 8: Discussion 8
➡️Week 9: Discussion 9, Quiz 5.
➡️Week 10: Discussion 10, Final Project.
I look forward to hearing your reactions to this course and how you are making use of it.