--- tags: Session1-Reverse-Engineer-a-Map --- # Session 1 Teacher Notes #### Key learning goals * Be able to look at a map and think about what kinds of sources were required to create it * Understand what we mean by “geospatial data,” and the difference between the data and the map itself * Critically evaluate what happens when observations of the world are encoded into computer data *Stuff we’ll also be trying to communicate* * Insights of Harley, “Deconstructing the Map” and critical cartography * “Raw” data versus visual frames around the data * Data ontologies ### Before Session 1 * ask participants to bring in a map they find (if they want to/have time) - go into breakout rooms to discuss at some point in the sesssion (maybe at the end to bring everything together?) ### Exercise 1 outline * work through exercise, emphasizing and discussing the following: * BLS Map: * Where did these boundaries come from? How does the computer know where they are? * Why is data for Puerto Rico missing for the map from Arpil 2020? * City Health Dashboard: * Why do you think the cartographers chose to include a basemap? * Discuss census tracts vs. census block groups? * Sleep Maps: * Which map makes a stronger/more effective argument? * What is the purpose of each map? Are both trying to make an argument? More discussion questions * What does making a map interactive do for the argument it makes and the way the viewer interprets the data? When might we want to choose not to make maps interactive? * What might be particularly dangerous about considering and presenting maps as objective representations of the world? * Questions/thoughts from participants? ### Exercise 2 outline * What is a map? * Walk thorugh exercise as written * A bit of background about critical cartography maybe? * In-class map-making exercise * Denver heat temp vs. income maps: * Is there a spatial pattern with these two attributes? * Key terms: reference maps vs. thematic maps * What is data? * Giorgial Lupi Dear Data project * Non-geospatial data; observations of the world recorded and visualized * Geospatial data * John Snow map of Broad Street pump * Geospatial data allow us to see patterns of occurances across space. * Recall the Denver maps here! * Mention GIS software that reads this type of data * Key terms: features and attributes * BLS map callback: have participants identify features and attributes data * Key terms: vector data and raster data * Minor terms to mention continuous and discrete * Key terms: point, line, polygon * Breakout rooms * Discuss types of data that are on the hand-drawn maps; how would the information you drew be transformed into data? * Discuss maps that participants brought in * Quizlet * Participants can do this after the class ends if we don't have time ### Exercise 1 Outline After Rework (1 hour session) | Section | Time| Format| | -------- | -------- | -------- | | Intro to Course + What is Map | 10 min | Verbal | | Activity - Draw Map | 10 min (5 min draw, 5 min discuss) | Breakout Rooms | | How to Look at Maps | 15 min | Verbal | Critical Thinking about Data + Deep Dive + How to Approach Data| 20 min | Verbal | | Wrap Up + HW for Next Session | 5 min | Verbal | * What is a Map? * grammar analogy * Lewis Carroll * Draw Your Own Map * coordinate sharing of maps - breakout rooms? * discuss what kinds of knowledge participants have through personal connection to the places they are depicting * the algorithm behind the map - automatic creation of buckets * How Should We Look at Maps? * BLS Map: * Where did these boundaries come from? How does the computer know where they are? * Why is data for Puerto Rico missing for the map from April 2020? * Diving Deep into Data * How did the steps shown in the diagram play into your own mapmaking? What about in the BLS maps? * How do you decide what information to keep track of in your own life? * What data exists about you - health data, sleep data, food data etc. allude to making your own dataset * Identify Types of Data (moved to session 2?) * Data: What Gets Lost in Translation? * How might you want to use the LMEC Public Data Portal? * What Questions Should We Ask of Data? * What are some potential harms of failing to ask these questions of data? * Data is like any other written source - has author, purpose, context etc which you shouldn't overlook * Exercise: Find Your Own Data Set * List some examples of places participants can look for a dataset? * How Do We Approach Data? * City Health Dashboard: * Why do you think the cartographers chose to include a basemap? * Discuss census tracts vs. census block groups? * Sleep Maps: * Which map makes a stronger/more effective argument? * What is the purpose of each map? Do they make the same argument? * Conclusion * How might you use and view maps in the future? * Session 2 Preview * Answer any logistical and content questions * Assign the find a dataset homework More discussion questions * What does making a map interactive do for the argument it makes and the way the viewer interprets the data? When might we want to choose not to make maps interactive? * What might be particularly dangerous about considering and presenting maps as objective representations of the world? * Questions/thoughts from participants?