A Geographic Analysis of Homeless Management Information System (HMIS) Data for North GA Tim Branscomb Geog 596A Capstone Proposal Penn State MGIS Program May

Outline Background Goals Project Phases Potential Focus Areas Project Status Schedule Beyond Final Project 2

Background Homelessness in Atlanta Multiple homeless organizations in Atlanta Desire to utilize GIS for homeless purposes Arrival at the Pathways Organization What is Pathways? Discussions lead to using GIS with Homeless Management Information Systems (HMIS) data What is HMIS? 3

Project Goals 4 Apply skills learned in MGIS program to aid homelessness Provide customer focused geographic analysis Create template of GIS procedures for other HMIS providers to follow Create ‘path’ for data sharing between Pathways and other requesting organizations

Project Phases Phase 1-DataPhase 2-AnalysisPhase 3-Presentation 5

Phase 1 – Data Research HMIS data Investigate available census data estimates and entities Locate tools for pre-processing (Excel, Access, ArcMap) Execute required training and agreements Establish accounts needed for data access 6

Data Dictionary Data Model Data Standards Manual 7 HMIS: Homeless Management Information System Phase 1 – Data

Basic review of Census Bureau geographic entities, their relationships, and available datasets Non-alignment between zip code boundaries and traditional census entities (tracts, block groups, etc.) Close alignment between zip code boundaries and Zip Code Tabulation Areas (ZCTAs) 8 U.S. Census Bureau Information Phase 1 – Data

Use Iterative workflow to answer general questions: What areas have the highest concentration of clients? What types of clients are from which areas? What types of service do the clients use the most? What distances do clients have to travel for services? Which areas have an increasing/decreasing rate of clients? Phase 2 – Analysis 9

Original HMIS Report Data Excel Pivot Table to Summarize Data Imported and Linked to ZCTAs Resulting Geographic Visualization(s) 10 Phase 2 – Analysis Data Pre-Processing Steps

Phase 2 - Analysis Thematic Map of Clients with Children Rates per Zip Code Proportional Symbol Map of Client Totals per Zip Code 11

Phase 2 - Analysis Pie Chart Symbol Map of Client Race Proportions per Zip Code Drive-Time Polygon Map from Family Focused Shelters 12

Phase 2 - Analysis Hotspot Analysis of Veteran Rate per Zip Code Grouping Analysis Map of Homeless Client Rates per Zip Code 13

Most ‘telling’ results are selected by Pathways Storyboard created by Pathways for the selected results Publish appropriate feature services to support storyboard Story Map created and published after iterative process Appendix documentation created for selected data and maps Phase 3 - Presentation 14

Initial Inquiry Outcome (map) HMIS entities used Required SQL Census data used Pre-processing steps GIS workflow 15 Report Documentation Phase 3 - Presentation

Regression modelling Custom modification of Story Maps (using JavaScript) Significant focus on template for other HMIS organizations Windows utility application creation for pulling and aggregating data as needed (via ODBC connection) ArcMap Python scripts and/or models for pre-processing needs Excel VBA scripts for converting data and/or producing necessary pivot tables Potential Focus Areas 16

Project Status 17

February – May 2015 Phase 1 – Data Research and Coordination April – July 2015 Phase 2 – Analysis June – September 2015 Phase 3 – Presentation (Templates and Story Maps ) September 2015 Draft final paper and conference presentation October 2015 Present Results at National HMIS Users Conference (Washington, DC) Project Schedule 18

Continued involvement/analysis for Pathways Obtain non-profit ArcGIS software for Pathways GIS Training for Pathways Take basic approach to one of several non-profit organizations I would like to work GIS for Adapt methods to open source products Beyond Capstone Project 2016 … 19 Ref: ESRI 2015

Dr. Douglas Miller – Project Advisor Dr. Josie Parker – Pathway’s Research Project Manager Dr. Jack Barile– Pathway’s Data Researcher Dr. Justine Blanford – Future geo-statistical consultant Meghan Branscomb – Supporting Wife! Acknowledgements 20

Census.gov (2015a). Zip code Tabulation Areas (ZCTAs). Retrieved April 2, 2015 from Census.gov (2015b). American Community Survey: When to use 1-year, 3-year, or 5-year estimates. Retrieved April 2, 2015 from Department of Housing and Urban Development (2005). Making the Most of HMIS Data: A Guide to Understanding Homelessness and Improving Programs in Your Community. Retrieved March 20, 2015 from programs/ programs/ HudExchange.info (2014a). Homeless Management Information System. Retrieved March 20, 2015 from HudExchange.info (2014b). HMIS Data Dictionary. Retrieved March 20, 2015 from Loubert, Linda (2010). Mapping Urban Inequalities with GIS. Retrieved March 20, 2015, from urban.htmlhttp:// urban.html Olivia, Jon-Paul (2006). Using Geographic Information Systems (GIS) as a tool for HMIS decision making. Retrieved March 20, 2015 from PCNI.org (n.d.) Pathways Community Network Institute. Retrieved March 20, 2015, from Storymaps.argis.com (n.d.) Use StoryMaps to Inform and Inspire Your Audience. Retrieved March 20, 2015, from Wong, Yin-Ling I, Hiller, Amy E. (2001). Evaluating a Community Based Homelessness Prevention Program: A Geographic Information System Approach. Administration in Social Work 25:4, pp References 21