Here is an overview of our current projects. If you’d like to join a project, contact Eric Busboom, eric@sandiegodata.org.

Homelessness Counts. Digitize and analyze 5 years of monthly counts of the homeless in Downtown San Diego. The San Diego Downtown Partnership counts the homeless downtown every month, and now has about 5 years of paper maps recording the positions of where homeless individuals were sleeping. This project will digitize these maps, extracting the position information, to create a detailed dataset. Then we will analyze the data, by linking homelessness to land use, business location and traffic patterns. The project can be done with manual GIS work, but would be best done with image recognition to geo-reference the maps and extract handwritten marks.

Needs:

  • GIS
  • Image Recognition, to geo-reference maps and extract data.
  • Descriptive analytics, linking homeless locations to land use.
  • Predicative analytics, to asses the impact of change in the built environment
  • Geographic data viz.

Improving student grades with Reality Changers. Reality Changers’ Challenge Assembles challenge low performing students to improve their grades, with successful students being accepted into Reality Changers programs that put students on a path to college. In this project, we are collecting, cleaning and analyzing two years of student performance records to characterize the success of the program and suggest improvements.

Needs:

  • Data wrangling, primarily cleaning manually recorded administrative records.
  • Descriptive statistics and regressions.
  • Data viz and reporting findings.

Analyze Free and Reduced Price Meals Programs. The San Diego Hunger Coalition is an advocacy and research programs that seeks data wrangling support for their Hunger Free Kids program. In this project, we are collecting public datasets, primarily from the California Department of Education, packing the data with Metatab, and deploying the datasets to databases to support the SDHC’s researchers.

Needs:

  • Data wrangling, to locate and process public datasets
  • Data Engineering, linking datasets and loading into databases ( Primarily Redshift. )
  • Statistical analysis, descriptive statistics, regressionData viz, Tableau preferred.