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tags: Key-Documents
---

# Course outline

## Session 1

Intro to maps and data

1. Intro
2. What is a map?
* Reference maps vs. thematic maps
3. In-class exercise: draw a map
4. How should we look at maps?
* BLS maps: choropleth, buckets
5. Diving deep into data
* Features vs. attribues
6. Quiz: Identify types of data
7. Data: What gets lost in translation?
* LMEC public data portal
8. In-class exercise: find your own dataset
9. What questions should we ask of data?
10. How do we approach data?
* City health dashboard / sleep deprivation maps
11. Discussion questions
12. Conclusion
13. Session 2 preview and "homework"

**Add projections into Session 1?**

## Session 2

Where do you find data, let's make it less scary

1. Review from last time: features and attributes
* Types of features data: raster, vector, point, line, and polygon
* Types of attribute data: strings and numbers
2. In-class exercise: Review datasets participants bring to class
3. Metadata
4. Common file types in mapping projects
5. Joins
6. Closer look at Cartinal / LMEC Public Data Portal

If there's time?
* Scale
* Projection
* Symbolization
* Introduce concept of coordinate system

## Session 3

How can you make a project, how can you help fill in the blanks.

1. Review:
* joins
* Cartinal/LMEC Public Data Portal
* Segue: metadata to missing data
3. What is missing data? What is data transparency?
4. What if I can't find data for my project?
5. Helpful techniques in Excel and/or Google Sheets
6. When should we use maps/other types of visualizations/both working together?
7. Geocoding: What if I have some information but no coordinates?
8. Discussion: what are some ways participants hope to apply takeaways from the course into their work/lives?
10. Resources for continuing with geospatial data

#
###### notes
Exercise 1
* Key Terms
* Choropleth Map
* Census Block vs Census Tract
* Buckets
* Interval
* Critical Questions
* What decisions must a mapmaker make when creating a map? What kind of biases can be passed in to maps
* What data makes up a map?

Exercise 2
* Key Terms
* Line
* Point
* Polygon
* Raster
* Vector
* Data (Feature vs Attribute)
* Critical Questions
* What is data and what forms can it take?
*

Exercise 3
* Key Terms
* Critical Questions