Scott Hilkert, Managing Principal NIST Workshop on a Common Data Format for Electronic Voting Systems. Oct , 2009

 Background of Illinois Election Data Collection project.  Primer on Election Systems and Data Paths Between.  Challenges Faced in EDC Project.  Inconsistency in Contest Naming  Inconsistency in Precinct Naming  Suitability of Raw Machine Data for Reporting  Relevance to Common Data Workshop

 Sponsored by EAC Grant awarded to 5 states.  Objective: Devise a means of automatic election data reporting for the 2008 General Election  Objective: Report election results data at the precinct level.  Applied to the 2008 General Election  Illinois Project Started late, Limited functionality in place for March 2009 reporting deadline  Grant extended, final software to serve as proof-of- concept for Electronic Canvass.  Focused on Data Paths 1 & 2 on the following slide.

1Data exports from vote tabulation systems. (VTS) All 4 major Vendor systems represented in Illinois 2Data exported from VR or election management systems (EMS) Typically the Statewide VR System 3Data used to configure vote tabulation systems for each election. Lack of consistent naming and usage was a challenge 9EMS / VTS System Boundary Inconsistency across boundary was a challenge

 Accepts Standard Export Files from each county tabulation system.  Separate Translaction Plugin developed for each of 4 major vendor systems (Hart, ES&S, Sequoia, Premier)  Accepts Data Export from Statewide Voter Registration System.  In “bottom up” states, Statewide VR data is derived from separate county systems.  Local survey data is also combined.  Data must be mapped and merged as it moves up the reporting hierarchy on following slide

 Data from separate county systems must be correlated and merged.  Requires mapping of contest and choice names to state standard conventions:  For example, Illinois 17th Congressional District spans 12 whole counties and portions of 2 more counties. Example names for this contest:  “US House of Representatives”  “Representative in the United States Congress,”  or simply “Congress.”  Note that none of these identified this as the 17 th.

 A name mapping feature had to be developed (See screen shot on following slide)  Also required for Party name and Choice names.  This required significant staff hours to manually analyze and configure the data mapping.  Had the naming conventions used to program the systems (Data Flow #3) been standardized, the manual mapping process could have been avoided.

 Establish standard codes or short names for major contests (Replace old FIPS codes)  Train and educate local election jurisdictions on VTS programming and usage conventions  Incorporate standards and guidelines into VTS Vendor products and documentation.

 Caused by the EMS / VTS system boundary discussed earlier.  Limits ability to correlate voter registration data, ballot request data with votes cast data.  A similar name mapping interface had to be developed.  Very ineffective for 1000’s of Precincts.  Remedies similar to that of previous mentioned challenge.

 Small discrepancies encountered between VTS export files and official canvass reports.  Provisional and other ballot types added to Canvass in external process.  Date of export uncertain  Some adjustments are inevitable.  Remedies?:  Establish standard VTS usage guidelines for ballot types.  Encourage use of VTS exports with Official Canvass  Data standards must track manual adjustments separatly from original machine counts.

 Small discrepancies encountered between VTS export files and official canvass reports.  Provisional and other ballot types added to Canvass in external process.  Date of export uncertain  Some adjustments are inevitable.  Remedies?:  Establish standard VTS usage guidelines for ballot types.  Encourage use of VTS exports with Official Canvass  Data standards must track manual adjustments separatly from original machine counts.

 Inconsistent Data Format between the 4 systems was actually the least of the challenges faced.  Data usage and naming conventions should be promoted along with any emerging data standard.  EAC Sponsored Technology initiatives can help.