---
# System prepended metadata

title: Course outline
tags: [Key-Documents]

---

---
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
