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In May, 2012, the U.S. Department of Education (ED) published approximately 300 2009–2010 school boundaries from the Public School Boundary Geodatabase (PSBG) on the School District Demographic Data System (SDDS) Map Viewer (http://nces.ed.gov/surveys/sdds). Using the previous process as a spring board, ED created a new data model for the boundaries covering the 2010–2011 through 2012–2013 school years using Esri ArcGIS 10.1 for Server and Desktop in addition to custom built Python tools. Improvements included data storage and sharing on the GeoCloud as well as replication and versioning for QA/QC purposes. Having implemented the new data model, we will reflect on work flow issues that arose and helpful tool automation. We will also discuss the future plans for the project.
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CREATING A CLOUD BASED DATA MODEL FOR SCHOOL BOUNDARY
COLLECTION
2013 ESRI Federal GIS Conference
Presented by Tai Phan, Andrea Conver, & Amy Ramsdell
NCES, Sanametrix & Blue Raster
2/27/2013
School Boundary Geodatabase History
Continuation of the SABINS project Headed by Prof. Salvatore Saporito, The College of William & Mary David Van Riper, Minnesota Population Center www.sabinsdata.org
First release in the SDDS Map Viewer in May 2012 2009-2010 school boundaries for the top 350 districts
School Boundaries Collection Initiative
Collection of school attendance areas for all 13,000+ U.S. school districts
Combination of data collection by Census and a “group-sourced” mapping effort
The 2013-2014 school year will serve as a trial year
Census Bureau is summarizing the data by school boundary
Contact and Data Tracking Application
Tracks all contact between the district and the Census collection team
Stores original data type (PDF, jpeg, Shapefile, etc.)
Records the date completed and user name for each processing step
Generates a variety of reports
Contact and Data Tracking Application
School Boundary Technologies
Using ArcSDE 10.1sp1 Centralized Data Repository on Cloud Data Replication
Using ArcGIS Server 10.1 on the Cloud Data visualization Data dissemination
Python (Arcpy)
Data Model
Data Processing & Custom Toolbox
Collect boundaries Dissolve boundaries into a 1 to 1 format Associate boundaries with an unique ID Perform QA/QC Sync data to the Cloud
School Boundary Collection Workflow
Public School Boundary Collection and Verification Tool
Workflow Issues
Working with different teams in a variety of locations
No shared network Data collection from a variety of sources Data collection for multiple years Determining what to collect Refactoring QA/ QC based on
requirements and deliverables
Conclusions
A simplified data model decreases file size and streamlines QA/QC
Custom tools have minimized human error, improved overall data quality, and reduced processing time
Network speeds can be a hindrance when working with SDE and data replication
Collecting data from the source Using servers in the cloud increases
accessibility
