Projects¶

Overview¶

The course project provides the opportunity to blend your newly acquired computational skills with the theories, methods, and models of regional and spatial analysis. The initial weeks of the quarter will provide a primer in open source tools. After that, the focus of the course switches to project work. Course meetings will then be dedicated to concentrated collaboration on the group project, which should supplement work being done outside the class meetings.

Project Grading¶

Each student’s project grade constitutes 50 percent of their overall grade for the course. The project grade for a student will be determined using the following weighting:

Component	Weight	Notes
Documentation	35	Group
Presentation	15	Group
Individual commits/PRs	30	Individual
Peer evaluation	15	Individual
Self evaluation	5	Individual

Documentation¶

For each group, final documentation for the course project will be required. This documentation will consist of the following components

Project proposal (5 points, Due May 5 5pm)
1. identification of the team
2. identification of data sets that will be used
3. at least 5 references from academic literature related to the topic
4. draft list of tasks and two milestones on GitHub Project Repository
Final paper that reports on the research findings (20 points Due June 4 5pm)
Project reproducibility documentation (10 points Due June 4 5pm)

The final paper should take the form of a manuscript that could be submitted for publication. The project reproducibility documentation will is to be contained on the project repository and allow an interested user (like the instructor) to reproduce the analysis presented in final paper.

Presentation¶

Each group will be required to present their findings on the date of the final examination.

Individual commits/PRs¶

Based on analysis of the git logs for the project, the instructor will evaluate the contributions of each individual to the project. Contributions can be of the following forms:

accepted commits
pull requests
issues reported
issues closed
commenting on issues/pull requests

Peer evaluation¶

Each student will be required to complete a confidential evaluation of their team members.

Self evaluation¶

Each student will be required to complete a self evaluation.

Project Portfolio¶

The list of potential projects follows. Students will submit a ranked preference for working on these, and project assignments will be made to optimize matching.

Neighborhood Change and Schools¶

Components (Initial Ideas)¶

Enhance GeoSNAP to integrate schools into neighborhood clustering algorithms
Develop analytics to measure neighborhood change
Develop analytics to measure school change
Integrative analysis of neighborhood and school change

Team¶

jchen  
nnasr  
erami
druck
sstac
hwelc
calfa

Spatial Inequality Dynamics¶

Components (Initial Ideas)¶

Implement a web-based version of STARS: Space-Time Analysis of Regional Systems
Rely on PySAL for existing analytics
Use CGS Quilt as data infrastructure
Evaluate alternative web-based visualization tool kits
Deliver a prototype
Test on a new spatial inequality data set

Team¶

pcarl
rpena
bpham
bpich
arang
mrodr
mshee

Environmental Justice & Primary Education¶

Components (Initial Ideas)¶

Analyze the spatial relationship between school demography,
Combine data from the EPA and the NCES from CGS’s quilt bucket, along with SEDA to create a school-level analysis
Examine whether schools with different demographic characteristics are exposed to different levels of environmental quality, and whether a relationship exists between educational opportunity and healthy environments
Develop an interactive notebook structured as a article/narrative that describes your findings to a general audience

Team¶

pjutu
wnoor
jolgu
lsala
evill
afire