ArcGIS REST Services Directory Login | Get Token
JSON | SOAP

Election_Data/2000_1990_Election_Data_with_2011_Wards (FeatureServer)

View In:   ArcGIS Online Map Viewer

View Footprint In:   ArcGIS Online Map Viewer

Service Description: Election Data Overview: Election data that is included in this file was collected by LTSB from the Government Accountability Board (GAB)/Wisconsin Elections Commission (WEC) after each general election. A disaggregation process was performed on this election data based on the municipal ward layer that was available at the time of the election. The ward data that is collected after each decennial census is made up of collections of whole and split census blocks. (Note: Split census blocks occur during local redistricting when municipalities include recently annexed property in their ward submissions to the legislature). Disaggregation of Election Data: Election data is first disaggregated from reporting units to wards, and then to census blocks. Next, the election data is aggregated back up to wards, municipalities, and counties. The disaggregation of election data to census blocks is done based on total population. Detailed Methodology: Data is disaggregated first from reporting unit (i.e. multiple wards) to the ward level proportionate to the population of that ward. The data then is distributed down to the block level, again based on total population. When data is disaggregated to block or ward, we restrain vote totals not to exceed population 18 numbers, unless absolutely required. This methodology results in the following: Election data totals reported to the GAB/WEC at the state, county, municipal and reporting unit level should match the disaggregated election data total at the same levels. Election data totals reported to the GAB at ward level may not match the ward totals in the disaggregated election data file. Some wards may have more election data allocated than voter age population. This will occur if a change to the geography results in more voters than the 2010 historical population limits. Other things of note… We use a static, official ward layer (in this case created in 2011) to disaggregate election data to blocks. Using this ward layer creates some challenges. New wards are created every year due to annexations and incorporations. When these new wards are reported with election data, an issue arises wherein election data is being reported for wards that do not exist in our official ward layer. For example, if Cityville has four wards in the official ward layer, the election data may be reported for five wards, including a new ward from an annexation. There are two different scenarios and courses of action to these issues: When a single new ward is present in the election data but there is no ward geometry present in the official ward layer, the votes attributed to this new ward are distributed to all the other wards in the municipality based on population percentage. Distributing based on population percentage means that the proportion of the population of the municipality will receive that same proportion of votes from the new ward. In the example of Cityville explained above, the fifth ward may have five votes reported, but since there is no corresponding fifth ward in the official layer, these five votes will be assigned to each of the other wards in Cityville according the percentage of population. Another case is when a new ward is reported, but its votes are part of reporting unit. In this case, the votes for the new ward are assigned to the other wards in the reporting unit by population percentage; and not to wards in the municipality as a whole. For example, Cityville’s ward five was given as a reporting unit together with wards 1, 4, and 5. In this case, the votes in ward five are assigned to wards one and four according to population percentage. Outline Ward-by-Ward Election Results: The process of collecting election data and disaggregating to municipal wards occurs after a general election, so disaggregation has occurred with different ward layers and different population totals. We have outlined (to the best of our knowledge) what layer and population totals were used to produce these ward-by-ward election results. Election data disaggregates from GAB/WEC Reporting Unit -> Ward [Variant year outlined below]; Elections 1990 – 2000: Wards 1991 (Census 1990 totals used for disaggregation); Elections 2002 – 2010: Wards 2001 (Census 2000 totals used for disaggregation); Elections 2012: Wards 2011 (Census 2010 totals used for disaggregation); Elections 2014 – 2016: Wards spring 2017 (Census 2010 totals used for disaggregation); Blocks 2011 -> Centroid geometry and spatially joined with Wards [All Versions]; Each Block has an assignment to each of the ward versions outlined above. In the event that a ward exists now in which no block exists (Occurred with spring 2017) due to annexations, a block centroid was created with a population 0, and encoded with the proper Census IDs. Wards [All Versions] disaggregate -> Blocks 2011; This yields a block centroid layer that contains all elections from 1990 to 2016; Blocks 2011 [with all election data] -> Wards 2011 (then MCD 2011, and County 2011). All election data (including later elections such as 2016) is aggregated to the Wards 2011 assignment of the blocks. Notes: Population of municipal wards 1991, 2001 and 2011 used for disaggregation were determined by their respective Census. Population and Election data will be contained within a county boundary. This means that even though MCD and ward boundaries vary greatly between versions of the wards, county boundaries have stayed the same, so data should total within a county the same between wards 2011 and wards 2017 Election data may be different for the same legislative district, for the same election, due to changes in the wards from 2011 and 2017. This is due to boundary corrections in the data from 2011 to 2017, and annexations, where a block may have been reassigned. Ward Data Overview: These municipal wards were created by grouping Census 2010 population collection blocks into municipal wards. This project started with the release of Census 2010 geography and population totals to all 72 Wisconsin counties on March 21st, 2011, and were made available via LTSB's GIS website and the WISE-LR web application. The 180 day statutory timeline for local redistricting ended on September 19th, 2011. Wisconsin Legislative and Congressional redistricting plans were enacted in the fall of 2011 by Wisconsin Act 43 and Act 44. These new districts were created using Census 2010 block geography. Some municipal wards, created before the passing of Act 43 and 44, were required to be split between assembly, senate and congressional district boundaries. 2011 Wisconsin Act 39 allowed communities to divide wards, along census block boundaries, if they were divided by newly enacted boundaries. A number of wards created under Wisconsin Act 39 were named using alpha-numeric labels. An example would be where ward 1 divided by an assembly district would become ward 1A and ward 1B, and in other municipalities the next sequential ward number was used: ward 1 and ward 2. The process of dividing wards under Act 39 ended on April 10th, 2012. This link provides more information on Act 39. The United States Eastern District Federal Court on April 11th, 2012 ordered Assembly Districts 8 and 9 (both in the City of Milwaukee) be changed to follow the court’s description. On September 19th, 2012 the Legislative Technology Services Bureau (LTSB) divided the few remaining municipal wards that were split by a 2011 Wisconsin Act 43 or 44 district line.

All Layers and Tables

Has Versioned Data: false

MaxRecordCount: 1000

Supported Query Formats: JSON

Supports Query Data Elements: true

Layers: Description:

Copyright Text: LTSB, WEC

Spatial Reference: 102100  (3857)


Initial Extent: Full Extent: Units: esriMeters

Document Info: Enable Z Defaults: false

Supports ApplyEdits With Global Ids: false

Support True Curves : true

Only Allow TrueCurve Updates By TrueCurveClients : false

Supports Dynamic Layers: false

Child Resources:   Info   Query Data Elements   Relationships

Supported Operations:   Query   QueryDomains   Query Contingent Values   Create Replica