The Voter Participation indicator presents voter turnout in Champaign County as a percentage, calculated using two different methods.

In the first method, the voter turnout percentage is calculated using the number of ballots cast compared to the total population in the county that is eligible to vote. In the second method, the voter turnout percentage is calculated using the number of ballots cast compared to the number of registered voters in the county.

Since both methods are in use by other agencies, and since there are real differences in the figures that both methods return, we have provided the voter participation rate for Champaign County using each method.

Voter participation is a solid illustration of a community’s engagement in the political process at the federal and state levels. One can infer a high level of political engagement from high voter participation rates.

The voter participation rate calculated using the total eligible population is consistently lower than the voter participation rate calculated using the number of registered voters, since the number of registered voters is smaller than the total eligible population.

There are consistent trends in both sets of data: the voter participation rate, no matter how it is calculated, shows large spikes in presidential election years (e.g., 2008, 2012, 2016, 2020) and smaller spikes in intermediary even years (e.g., 2010, 2014, 2018, 2022). The lowest levels of voter participation can be seen in odd years (e.g., 2015, 2017, 2019, 2021, 2023).

This data primarily comes from the election results resources on the Champaign County Clerk website. Election results resources from Champaign County include the number of ballots cast and the number of registered voters. The results are published frequently, following each election.

Data on the total eligible population for Champaign County was sourced from the U.S. Census Bureau, using American Community Survey (ACS) 1-Year Estimates for each year starting in 2005, when the American Community Survey was created. The estimates are released annually by the Census Bureau.

Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because this data is not available for Champaign County, the eligible voting population for 2020 is not included in this Indicator.

For interested data users, the 2020 ACS 1-Year Experimental data release includes datasets on Population by Sex and Population Under 18 Years by Age.

Sources: Champaign County Clerk Historical Election Data; U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using data.census.gov; (10 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using data.census.gov; (5 October 2023).; Champaign County Clerk Historical Election Data; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using data.census.gov; (7 October 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using data.census.gov; (8 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using data.census.gov; (8 June 2021).; Champaign County Clerk Election History; U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (13 May 2019).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (13 May 2019).; U.S. Census Bureau; American Community Survey, American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (6 March 2017).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey 2012 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).

The 119th Congressional Districts dataset reflects boundaries from January 03, 2025 from the United States Census Bureau (USCB), and the attributes are updated every Sunday from the United States House of Representatives and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Information for each member of Congress is appended to the Census Congressional District shapefile using information from the Office of the Clerk, U.S. House of Representatives' website https://clerk.house.gov/xml/lists/MemberData.xml and its corresponding XML file. Congressional districts are the 435 areas from which people are elected to the U.S. House of Representatives. This dataset also includes 9 geographies for non-voting at large delegate districts, resident commissioner districts, and congressional districts that are not defined. After the apportionment of congressional seats among the states based on census population counts, each state is responsible for establishing congressional districts for the purpose of electing representatives. Each congressional district is to be as equal in population to all other congressional districts in a state as practicable. The 119th Congress is seated from January 3, 2025 through January 3, 2027. In Connecticut, Illinois, and New Hampshire, the Redistricting Data Program (RDP) participant did not define the CDs to cover all of the state or state equivalent area. In these areas with no CDs defined, the code "ZZ" has been assigned, which is treated as a single CD for purposes of data presentation. The TIGER/Line shapefiles for the District of Columbia, Puerto Rico, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands) each contain a single record for the non-voting delegate district in these areas. The boundaries of all other congressional districts reflect information provided to the Census Bureau by the states by May 31, 2024. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529006

Abstract

The 2000 Republic of Palau Census of Population and Housing was the second census collected and processed entirely by the republic itself. This monograph provides analyses of data from the most recent census of Palau for decision makers in the United States and Palau to understand current socioeconomic conditions. The 2005 Census of Population and Housing collected a wide range of information on the characteristics of the population including demographics, educational attainments, employment status, fertility, housing characteristics, housing characteristics and many others.

Geographic coverage

National

Analysis unit

• Household;
• Individual.

Universe

The 1990, 1995 and 2000 censuses were all modified de jure censuses, counting people and recording selected characteristics of each individual according to his or her usual place of residence as of census day. Data were collected for each enumeration district - the households and population in each enumerator assignment - and these enumeration districts were then collected into hamlets in Koror, and the 16 States of Palau.

Kind of data

Census/enumeration data [cen]

Sampling procedure

No sampling - whole universe covered

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2000 censuses of Palau employed a modified list-enumerate procedure, also known as door-to-door enumeration. Beginning in mid-April 2000, enumerators began visiting each housing unit and conducted personal interviews, recording the information collected on the single questionnaire that contained all census questions. Follow-up enumerators visited all addresses for which questionnaires were missing to obtain the information required for the census.

Cleaning operations

The completed questionnaires were checked for completeness and consistency of responses, and then brought to OPS for processing. After checking in the questionnaires, OPS staff coded write-in responses (e.g., ethnicity or race, relationship, language). Then data entry clerks keyed all the questionnaire responses. The OPS brought the keyed data to the U.S. Census Bureau headquarters near Washington, DC, where OPS and Bureau staff edited the data using the Consistency and Correction (CONCOR) software package prior to generating tabulations using the Census Tabulation System (CENTS) package. Both packages were developed at the Census Bureau's International Programs Center (IPC) as part of the Integrated Microcomputer Processing System (IMPS).

The goal of census data processing is to produce a set of data that described the population as clearly and accurately as possible. To meet this objective, crew leaders reviewed and edited questionnaires during field data collection to ensure consistency, completeness, and acceptability. Census clerks also reviewed questionnaires for omissions, certain inconsistencies, and population coverage. Census personnel conducted a telephone or personal visit follow-up to obtain missing information. The follow-ups considered potential coverage errors as well as questionnaires with omissions or inconsistencies beyond the completeness and quality tolerances specified in the review procedures.

Following field operations, census staff assigned remaining incomplete information and corrected inconsistent information on the questionnaires using imputation procedures during the final automated edit of the data. The use of allocations, or computer assignments of acceptable data, occurred most often when an entry for a given item was lacking or when the information reported for a person or housing unit on an item was inconsistent with other information for that same person or housing unit. In all of Palau’s censuses, the general procedure for changing unacceptable entries was to assign an entry for a person or housing unit that was consistent with entries for persons or housing units with similar characteristics. The assignment of acceptable data in place of blanks or unacceptable entries enhanced the usefulness of the data.

Sampling error estimates

Human and machine-related errors occur in any large-scale statistical operation. Researchers generally refer to these problems as non-sampling errors. These errors include the failure to enumerate every household or every person in a population, failure to obtain all required information from residents, collection of incorrect or inconsistent information, and incorrect recording of information. In addition, errors can occur during the field review of the enumerators' work, during clerical handling of the census questionnaires, or during the electronic processing of the questionnaires. To reduce various types of non-sampling errors, Census office personnel used several techniques during planning, data collection, and data processing activities. Quality assurance methods were used throughout the data collection and processing phases of the census to improve the quality of the data.

Census staff implemented several coverage improvement programs during the development of census enumeration and processing strategies to minimize under-coverage of the population and housing units. A quality assurance program improved coverage in each census. Telephone and personal visit follow-ups also helped improve coverage. Computer and clerical edits emphasized improving the quality and consistency of the data. Local officials participated in post-census local reviews. Census enumerators conducted additional re-canvassing where appropriate.

The purpose of this dataset is to indicate the boundary of each US Congressional District within Cook County, Illinois. These boundaries are based off of Census 2000 geographies.Created for all users to view and understand jurisdictional boundaries within Cook County. US Congressional Districts are redrawn every 10 years based on the decennial census. Clerk Elections maintains the US Congressional District feature.

Please Note: Community Reporting Areas (CRA) have been updated to follow the 2020 census tract lines which resulted in minor changes to some boundary conditions. They have also been extended into water areas to allow the assignment of CRAs to overwater housing and businesses. To exclude the water polygons from a map choose the filter, water=0.Community reporting areas (CRAs) are designed to address a gap that existed in city geography. The task of reporting citywide information at a "community-like level" across all departments was either not undertaken or it was handled in inconsistent ways across departments. The CRA geography provides a "common language" for geographic description of the city for reporting purposes. Therefore, this geography may be used by departments for geographic reporting and tracking purposes, as appropriate. The U.S. Census Bureau census tract geography was chosen as the basis of the CRA geography due to their stability through time and link to widely-used demographic data.The following criteria for a CRA geography were defined for this effort:no overlapping areascomplete coverage of the citysuitable scale to represent neighborhood areas/conditionsreasonably stable over timeconsistent with census geographyrelatively easy to use in a data contextfamiliar system of common place namesrespects neighborhood district geography to the extent possibleThe following existing geographies were reviewed during this effort:neighborhood planning areas (DON)neighborhood districts (DON/CNC/Neighborhood District Councils)city sectors/neighborhood plan implementation areas (DON)urban centers/urban villages (DPD)population sub-areas (DPD)Neighborhood Map Atlas (City Clerk)Census tract geographytopographyvarious other geographic information sources related to neighborhood areas and common place namesThis is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.

Abstract

The 2005 Census of Population and Housing was the third comprehensive data collection of population and housing characteristics taken by the Republic since Compact Implementation in October 1994. The 2005 Census of Palau had two volumes. This first volume contained the basic tables, which can be used instantly for planning and policy determination. A second volume, the Census monograph, contained analyses of trends and comparisons of the States.

Geographic coverage

National

Analysis unit

Individuals Families Households General Population

Universe

The Census covered all the households and respective residents in the entire country.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Not applicable to a full enumeration census. For details please refer to the attached Basic Tables and Monograph.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Full scale processing and editing activiities comprised eight separate sessions either with or separately but with remote guidance of the U.S. Census Bureau experts to finalize all datasets for publishing stage.

Response rate

In any large-scale statistical operation, such as the 2005 Census of the Republic of Palau, human- and machine-related errors do occur. These errors are commonly referred to as nonsampling errors. Such errors include not enumerating every household or every person in the population, not obtaining all required information form the respondents, obtaining incorrect or inconsistent information, and recording information incorrectly. In addition, errors can occur during the field review of the enumerators' work, during clerical handling of the census questionnaires, or during the electronic processing of the questionnaires.

To reduce various types of nonsampling errors, a number of techniques were implemented during the planning, data collection, and data processing activities. Quality assurance methods were used throughout the data collection and processing phases of the census to improve the quality of the data.

Sampling error estimates

Sampling Error is not applicable to censuses; however, a processing operation was handled with care to produce a set of data that describes the population as clearly and accurately as possible. To meet this objective, questionnaires were reviewed and edited during field data collection operations by crew leaders for consistency, completeness, and acceptability. Questionnaires were also reviewed by census clerks in the census office for omissions, certain inconsistencies, and population coverage. For example, write-in entries such as “Don't know” or “NA” were considered unacceptable in certain quantities and/or in conjunction with other data omissions.

As a result of this review operation, a telephone or personal visit follow-up was made to obtain missing information. Potential coverage errors were included in the follow-up, as well as questionnaires with omissions or inconsistencies beyond the completeness and quality tolerances specified in the review procedures.

Subsequent to field operations, remaining incomplete or inconsistent information on the questionnaires was assigned using imputation procedures during the final automated edit of the collected data. Allocations, or computer assignments of acceptable data in place of unacceptable entries or blanks, were needed most often when an entry for a given item was lacking or when the information reported for a person or housing unit on that item was inconsistent with other information for that same person or housing unit. As in previous censuses, the general procedure for changing unacceptable entries was to assign an entry for a person or housing unit that was consistent with entries for persons or housing units with similar characteristics. The assignment of acceptable data in lace of blanks or unacceptable entries enhanced the usefulness of the data.

Another way to make corrections during the computer editing process is substitution. Substitution is the assignment of a full set of characteristics for a person or housing unit. Because of the detailed field operations, substitution was not needed for the 2005 Census.

Data appraisal

In any large-scale statistical operation, such as the 2005 Census of the Republic of Palau, human- and machine-related errors were anticipated. These errors are commonly referred to as nonsampling errors. Such errors include not enumerating every household or every person in the population, not obtaining all required information form the respondents, obtaining incorrect or inconsistent information, and recording information incorrectly. In addition, errors can occur during the field review of the enumerators' work, during clerical handling of the census questionnaires, or during the electronic processing of the questionnaires.

To reduce various types of nonsampling errors, a number of techniques were implemented during the planning, data collection, and data processing activities. Quality assurance methods were used throughout the data collection and processing phases of the census to improve the quality of the data.

Abstract

The 2005 Republic of Palau Census of Population and Housing will be used to give a snapshot of Republic of Palau's population and housing at the mid-point of the decade. This Census is also important because it measures the population at the beginning of the implementation of the Compact of Free Association. The information collected in the census is needed to plan for the needs of the population. The government uses the census figures to allocate funds for public services in a wide variety of areas, such as education, housing, and job training. The figures also are used by private businesses, academic institutions, local organizations, and the public in general to understand who we are and what our situation is, in order to prepare better for our future needs.

The fundamental purpose of a census is to provide information on the size, distribution and characteristics of a country's population. The census data are used for policymaking, planning and administration, as well as in management and evaluation of programmes in education, labour force, family planning, housing, health, transportation and rural development. A basic administrative use is in the demarcation of constituencies and allocation of representation to governing bodies. The census is also an invaluable resource for research, providing data for scientific analysis of the composition and distribution of the population and for statistical models to forecast its future growth. The census provides business and industry with the basic data they need to appraise the demand for housing, schools, furnishings, food, clothing, recreational facilities, medical supplies and other goods and services.

Geographic coverage

A hierarchical geographic presentation shows the geographic entities in a superior/subordinate structure in census products. This structure is derived from the legal, administrative, or areal relationships of the entities. The hierarchical structure is depicted in report tables by means of indentation. The following structure is used for the 2005 Census of the Republic of Palau:

Republic of Palau State Hamlet/Village Enumeration District Block

Analysis unit

Individuals Families Households General Population

Universe

The Census covered all the households and respective residents in the entire country.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Not applicable to a full enumeration census.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2005 Palau Census of Population and Housing comprises three parts: 1. Housing - one form for each household 2. Population - one for for each member of the household 3. People who have left home - one form for each household.

Cleaning operations

Full scale processing and editing activiities comprised eight separate sessions either with or separately but with remote guidance of the U.S. Census Bureau experts to finalize all datasets for publishing stage.

Processing operation was handled with care to produce a set of data that describes the population as clearly and accurately as possible. To meet this objective, questionnaires were reviewed and edited during field data collection operations by crew leaders for consistency, completeness, and acceptability. Questionnaires were also reviewed by census clerks in the census office for omissions, certain inconsistencies, and population coverage. For example, write-in entries such as "Don't know" or "NA" were considered unacceptable in certain quantities and/or in conjunction with other data omissions.

As a result of this review operation, a telephone or personal visit follow-up was made to obtain missing information. Potential coverage errors were included in the follow-up, as well as questionnaires with omissions or inconsistencies beyond the completeness and quality tolerances specified in the review procedures.

Subsequent to field operations, remaining incomplete or inconsistent information on the questionnaires was assigned using imputation procedures during the final automated edit of the collected data. Allocations, or computer assignments of acceptable data in place of unacceptable entries or blanks, were needed most often when an entry for a given item was lacking or when the information reported for a person or housing unit on that item was inconsistent with other information for that same person or housing unit. As in previous censuses, the general procedure for changing unacceptable entries was to assign an entry for a person or housing unit that was consistent with entries for persons or housing units with similar characteristics. The assignment of acceptable data in lace of blanks or unacceptable entries enhanced the usefulness of the data.

Another way to make corrections during the computer editing process is substitution. Substitution is the assignment of a full set of characteristics for a person or housing unit. Because of the detailed field operations, substitution was not needed for the 2005 Census.

Sampling error estimates

Sampling Error is not applicable to full enumeration censuses.

Data appraisal

In any large-scale statistical operation, such as the 2005 Census of the Republic of Palau, human- and machine-related errors were anticipated. These errors are commonly referred to as nonsampling errors. Such errors include not enumerating every household or every person in the population, not obtaining all required information form the respondents, obtaining incorrect or inconsistent information, and recording information incorrectly. In addition, errors can occur during the field review of the enumerators' work, during clerical handling of the census questionnaires, or during the electronic processing of the questionnaires.

To reduce various types of nonsampling errors, a number of techniques were implemented during the planning, data collection, and data processing activities. Quality assurance methods were used throughout the data collection and processing phases of the census to improve the quality of the data.

Data from: American Community Survey, 5-year Series 2006-2010City of Seattle Council District boundaries with American Community Survey data and attachments of census reports. There are seven council districts in the City of Seattle, positions 1-7, and two positions elected "at-large" (city-wide) in positions 8 and 9.For more information about the Council Districts see the Office of the City Clerk.Neighborhood aggregations of American Community Survey tract-based data derived from the U.S. Census Bureau's demographic profiles (DP02-DP05). The geo service includes over 50 attributes of the most frequently requested data.Also includes custom reports in pdf format as attachments to each neighborhood.When downloading the data, please select "GDB Download" under "Additional Resources" to preserve long field names and attachments. The associated file geodatabase contains a separate feature class for three levels of neighborhood geography - council districts, community reporting areas, and urban village demographic areas that includes these 50+ attributes.

Wisconsin County Supervisory districts collected in January 2025. [Attribute Definitions]. This data has been collected in regards to state statute 15(4)(br)1. County clerks will transmit municipal, municipal ward, and county supervisory districts in GIS format to LTSB by January 15th and July 15th* per statute 5.15(4)(br)1: "...no later than January 15 and July 15 of each year*, the county clerk shall transmit to the Legislative Technology Services Bureau a report confirming the boundaries of each municipality, ward, and supervisory district in the county together with a map of the county, in an electronic format approved by the Legislative Technology Services Bureau. Each report shall be current to the nearest January 1 or July 1* preceding the date of the report”.Municipal clerks need to notify the county clerk within 5 days of any boundary change per statute 5.15(4)(b): "Within 5 days after adoption or enactment of an ordinance or resolution under this section or any amendment thereto, the municipal clerk shall transmit one copy of the ordinance or resolution or the amendment to the county clerk of each county in which the municipality is contained, accompanied by the list and map specified in par. (a). Each copy shall identify the name of the municipality and the county or counties in which it is located."Municipal data collected in the January collections will be used by LTSB to update municipal boundaries the U.S. Census Bureau’s TIGER database via the Boundary Annexation Survey (BAS). Counties and municipalities are no longer required to submit boundary changes directly to the Census Bureau. LTSB will submit data to the Census Bureau for the state as a whole.Section 13.96(1)(b) of the Wisconsin Statutes requires LTSB to “upon receipt of municipal boundary information at each reporting interval, reconcile and compile the information received to produce a statewide data base consisting of municipal boundary information for the entire state”.Section 13.96(1)(c) states that LTSB shall “Participate, on behalf of this state, in geographic boundary information programs when offered by the U.S. bureau of the census”.LTSB will publish Municipal Wards, Municipal Boundaries (cities, towns, villages), and County Supervisory Districts to the LTSB GIS Hub website.This data has been collected with the LTSB GeoData Collector.*with the exception of years ending in “01” where data collection will align closer to typical redistricting timelines of March and October 15

Analysis of ‘A Council Districts Profile ACS 5-year 2013-2017’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/f041fcfa-c22a-41ef-887c-08661c181447 on 27 January 2022.

--- Dataset description provided by original source is as follows ---

Data from: American Community Survey, 5-year Series 2013-2017

--- Original source retains full ownership of the source dataset ---

Analysis of ‘Council Districts Profile ACS 5-year 2006-2010’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/9e79a8db-d8f9-4fe0-a95c-58508b01efa4 on 27 January 2022.

--- Dataset description provided by original source is as follows ---

Data from: American Community Survey, 5-year Series 2006-2010

--- Original source retains full ownership of the source dataset ---

Wisconsin municipal ward data collected in January 2025 by LTSB. [Attribute Definitions]. This data has been collected in regards to state statute 15(4)(br)1. County clerks will transmit municipal, municipal ward, and county supervisory districts in GIS format to LTSB by January 15th and July 15th* per statute 5.15(4)(br)1: "...no later than January 15 and July 15 of each year*, the county clerk shall transmit to the Legislative Technology Services Bureau a report confirming the boundaries of each municipality, ward, and supervisory district in the county together with a map of the county, in an electronic format approved by the Legislative Technology Services Bureau. Each report shall be current to the nearest January 1 or July 1* preceding the date of the report”. (*with the exception of years ending in “01” where data collection will align closer to typical redistricting timelines of March and October 15)Municipal clerks need to notify the county clerk within 5 days of any boundary change per statute 5.15(4)(b): "Within 5 days after adoption or enactment of an ordinance or resolution under this section or any amendment thereto, the municipal clerk shall transmit one copy of the ordinance or resolution or the amendment to the county clerk of each county in which the municipality is contained, accompanied by the list and map specified in par. (a). Each copy shall identify the name of the municipality and the county or counties in which it is located."Municipal data collected in the January collections will be used by LTSB to update municipal boundaries the U.S. Census Bureau’s TIGER database via the Boundary Annexation Survey (BAS). Counties and municipalities are no longer required to submit boundary changes directly to the Census Bureau. LTSB will submit data to the Census Bureau for the state as a whole.Section 13.96(1)(b) of the Wisconsin Statutes requires LTSB to “upon receipt of municipal boundary information at each reporting interval, reconcile and compile the information received to produce a statewide data base consisting of municipal boundary information for the entire state”.Section 13.96(1)(c) states that LTSB shall “Participate, on behalf of this state, in geographic boundary information programs when offered by the U.S. bureau of the census”.LTSB will publish Municipal Wards, Municipal Boundaries (cities, towns, villages), and County Supervisory Districts to the LTSB GIS HUB website.This data has been collected with the LTSB GeoData Collector.*with the exception of years ending in “01” where data collection will align closer to typical redistricting timelines of March and October 15.

Data from: American Community Survey, 5-year Series 2013-2017

Analysis of ‘Council Districts Profile ACS 5-year 2009-2013’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/d7ab67ea-2d87-4b52-b6d6-559559f15c05 on 27 January 2022.

--- Dataset description provided by original source is as follows ---

Data from: American Community Survey, 5-year Series 2009-2013

--- Original source retains full ownership of the source dataset ---

LTSB dissolves municipal ward data into county supervisory districts. Wisconsin municipal ward data was collected in July 2024. [Attribute Definitions]. This data has been collected in regards to state statute 15(4)(br)1. County clerks will transmit municipal, municipal ward, and county supervisory districts in GIS format to LTSB by January 15th and July 15th* per statute 5.15(4)(br)1: "...no later than January 15 and July 15 of each year*, the county clerk shall transmit to the Legislative Technology Services Bureau a report confirming the boundaries of each municipality, ward, and supervisory district in the county together with a map of the county, in an electronic format approved by the Legislative Technology Services Bureau. Each report shall be current to the nearest January 1 or July 1* preceding the date of the report”. (*with the exception of years ending in “01” where data collection will align closer to typical redistricting timelines of March and October 15)Municipal clerks need to notify the county clerk within 5 days of any boundary change per statute 5.15(4)(b): "Within 5 days after adoption or enactment of an ordinance or resolution under this section or any amendment thereto, the municipal clerk shall transmit one copy of the ordinance or resolution or the amendment to the county clerk of each county in which the municipality is contained, accompanied by the list and map specified in par. (a). Each copy shall identify the name of the municipality and the county or counties in which it is located."Municipal data collected in the January collections will be used by LTSB to update municipal boundaries the U.S. Census Bureau’s TIGER database via the Boundary Annexation Survey (BAS). Counties and municipalities are no longer required to submit boundary changes directly to the Census Bureau. LTSB will submit data to the Census Bureau for the state as a whole.Section 13.96(1)(b) of the Wisconsin Statutes requires LTSB to “upon receipt of municipal boundary information at each reporting interval, reconcile and compile the information received to produce a statewide data base consisting of municipal boundary information for the entire state”.Section 13.96(1)(c) states that LTSB shall “Participate, on behalf of this state, in geographic boundary information programs when offered by the U.S. bureau of the census”.LTSB will publish Municipal Wards, Municipal Boundaries (cities, towns, villages), and County Supervisory Districts to the LTSB HUB Data Portal.This data has been collected with the LTSB GeoData Collector.

This data has been collected in regards state statute 5.15(4)(br)1. Municipal clerks within 5 days of any boundary change need to notify the county clerk.5.15(4)(b)Within 5 days after adoption or enactment of an ordinance or resolution under this section or any amendment thereto, the municipal clerk shall transmit one copy of the ordinance or resolution or the amendment to the county clerk of each county in which the municipality is contained, accompanied by the list and map specified in par. (a). Each copy shall identify the name of the municipality and the county or counties in which it is located.County clerks will transmit municipal, municipal ward and county supervisory districts in GIS format to LTSB by January 15thand July 15th. ”no later than January 15 and July 15 of each year, the county clerk shall transmit to the legislative technology services bureau a report confirming the boundaries of each municipality, ward, and supervisory district in the county together with a map of the county, in an electronic format approved by the legislative technology services bureau. Each report shall be current to the nearest January 1 or July 1 preceding the date of the report”.Municipal data collected in January will be used by LTSB to update municipal boundaries the U.S. Census Bureau’s TIGER database via the Boundary Annexation Survey (BAS). Counties and municipalities are no longer required to submit boundary changes directly to the Census Bureau. LTSB will submit data to the Census Bureau for the state as a whole.Section 13.96(1)(b)of the Wisconsin Statutes requires LTSB to “upon receipt of municipal boundary information at each reporting interval under s. 5.15 (4) (bg), reconcile and compile the information received to produce a statewide data base consisting of municipal boundary information for the entire state”.13.96(1)(c)LTSB shall “Participate, on behalf of this state, in geographic boundary information programs when offered by the U.S. bureau of the census”.LTSB will publish Municipal Ward, Municipal Boundaries and County Supervisory Districts to the LTSB Open Data Portal located at http://data.ltsb.opendata.arcgis.com/.This data has been collected with the WISE-Decade software platform. For more information on this system please visit http://legis.wisconsin.gov/ltsb/gis/wise-decade/.