eVA is used by more than 245 state agencies and institutes of higher education, and 900+ local governments and public bodies, to announce bidding opportunities, receive quotes, order placement & approvals, contract management and more. Since its inception in 2001, eVA has transformed the way the Commonwealth buys goods and services from a decentralized, paper based process to a centralized, electronic platform. Providing industry leading procurement solutions for all public bodies, the marketplace includes nearly 100,000 businesses competing to provide the Commonwealth with quality goods and services, resulting in more than $25 million in savings annually. This dataset contains the purchase orders for the goods and services.

Point shapefiles for the 2023 Virginia Telecommunication Initiative (VATI) grant application submitted by Shenandoah County Public Schools in partnership with Shentel.

2013-2021 Virginia Disability Characteristics by Census Tract. Contains estimates and margins of error.

Special data considerations: Large negative values do exist (more detail below) and should be addressed prior to graphing or aggregating the data. A null value in the estimate means there is no data available for the requested geography.

A value of -888,888,888 indicates that the estimate or margin of error is not applicable or not available.

U.S. Census Bureau; American Community Survey, American Community Survey 5-Year Estimates, Table S1810
Data accessed from: Census Bureau's API for American Community Survey (https://www.census.gov/data/developers/data-sets.html)

The United States Census Bureau's American Community Survey (ACS):
-What is the American Community Survey? (https://www.census.gov/programs-surveys/acs/about.html)
-Geography & ACS (https://www.census.gov/programs-surveys/acs/geography-acs.html)
-Technical Documentation (https://www.census.gov/programs-surveys/acs/technical-documentation.html)

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section. (https://www.census.gov/programs-surveys/acs/technical-documentation/code-lists.html)

Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section. (https://www.census.gov/acs/www/methodology/sample_size_and_data_quality/)

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties.

Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation https://www.census.gov/programs-surveys/acs/technical-documentation.html). The effect of nonsampling error is not represented in these tables.

Point shapefiles for the 2023 Virginia Telecommunication Initiative (VATI) grant application submitted by the West Piedmont PDC in partnership with RiverStreet Networks for its Pittsylvania project area.

2013-2021 Virginia Ratio of Income to Poverty Level in the Past 12 Months by Census Block Group. Contains estimates and margins of error.

U.S. Census Bureau; American Community Survey, American Community Survey 5-Year Estimates, Table C17002
Data accessed from: Census Bureau's API for American Community Survey (https://www.census.gov/data/developers/data-sets.html)

The United States Census Bureau's American Community Survey (ACS):
-What is the American Community Survey? (https://www.census.gov/programs-surveys/acs/about.html)
-Geography & ACS (https://www.census.gov/programs-surveys/acs/geography-acs.html)
-Technical Documentation (https://www.census.gov/programs-surveys/acs/technical-documentation.html)

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section. (https://www.census.gov/programs-surveys/acs/technical-documentation/code-lists.html)

Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section. (https://www.census.gov/acs/www/methodology/sample_size_and_data_quality/)

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties.

Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation https://www.census.gov/programs-surveys/acs/technical-documentation.html). The effect of nonsampling error is not represented in these tables.

Point shapefiles for the 2023 Virginia Telecommunication Initiative (VATI) grant application submitted by Caroline County in partnership with Breezeline.

Point shapefiles for the 2023 Virginia Telecommunication Initiative (VATI) grant application submitted by Greensville County in partnership with Verizon.

Point shapefiles for the 2023 Virginia Telecommunication Initiative (VATI) grant application submitted by New Kent County in partnership with Cox.

Point shapefiles for the 2023 Virginia Telecommunication Initiative (VATI) grant application submitted by Giles County in partnership with Gigabeam.

Point shapefiles for the 2023 Virginia Telecommunication Initiative (VATI) grant application submitted by the Roanoke Valley Broadband Authority for their Catawba project.