Deprecation notice: This tool is deprecated because this functionality is now available with out-of-the-box tools in ArcGIS Pro. The tool author will no longer be making further enhancements or fixing major bugs.Use Add GTFS to a Network Dataset to incorporate transit data into a network dataset so you can perform schedule-aware analyses using the Network Analyst tools in ArcMap.After creating your network dataset, you can use the ArcGIS Network Analyst tools, like Service Area and OD Cost Matrix, to perform transit/pedestrian accessibility analyses, make decisions about where to locate new facilities, find populations underserved by transit or particular types of facilities, or visualize the areas reachable from your business at different times of day. You can also publish services in ArcGIS Server that use your network dataset.The Add GTFS to a Network Dataset tool suite consists of a toolbox to pre-process the GTFS data to prepare it for use in the network dataset and a custom GTFS transit evaluator you must install that helps the network dataset read the GTFS schedules. A user's guide is included to help you set up your network dataset and run analyses.Instructions:Download the tool. It will be a zip file.Unzip the file and put it in a permanent location on your machine where you won't lose it. Do not save the unzipped tool folder on a network drive, the Desktop, or any other special reserved Windows folders (like C:\Program Files) because this could cause problems later.The unzipped file contains an installer, AddGTFStoaNetworkDataset_Installer.exe. Double-click this to run it. The installation should proceed quickly, and it should say "Completed" when finished.Read the User's Guide for instructions on creating and using your network dataset.System requirements:ArcMap 10.1 or higher with a Desktop Standard (ArcEditor) license. (You can still use it if you have a Desktop Basic license, but you will have to find an alternate method for one of the pre-processing tools.) ArcMap 10.6 or higher is recommended because you will be able to construct your network dataset much more easily using a template rather than having to do it manually step by step. This tool does not work in ArcGIS Pro. See the User's Guide for more information.Network Analyst extensionThe necessary permissions to install something on your computer.Data requirements:Street data for the area covered by your transit system, preferably data including pedestrian attributes. If you need help preparing high-quality street data for your network, please review this tutorial.A valid GTFS dataset. If your GTFS dataset has blank values for arrival_time and departure_time in stop_times.txt, you will not be able to run this tool. You can download and use the Interpolate Blank Stop Times tool to estimate blank arrival_time and departure_time values for your dataset if you still want to use it.Help forum

This dataset contains point features representing the approximate location of tax parcels contained in County Assessor tax rolls. Individual county data was integrated into this statewide publication by the Arkansas Geographic Information Office (AGIO). The Computer Aided Mass Appraisal (CAMA) systems maintained in each county are used to populate the database attributes for each centroid feature. The entity attribute structure conforms to the Arkansas Cadastral Mapping Standard. The digital cadastral data is provided as a publication version that only represents a snapshot of the production data at the time it was received from the county. Published updates may be made to counties throughout the year. These will occur after new data is digitized or updates to existing data are finished. Production versions of the data exist in the various counties where daily and weekly updates occur. Users should consult the BEGIN_DATE attribute column to determine the age of the data for a given county. This column reflects the date when AGIO received the data from the county. Only parcels with an associated Computer Assisted Mass Appraisal (CAMA) record are provided. This means a CAMA record may exist, but no point geometry or vice-versa. Cadastral data is dynamic by its nature; therefore it is impossible for any county to ever be considered complete. The data is NOT topologically enforced. As a statewide integrator, AGIO publishes the data but does not make judgment calls about where points or polygon lines are meant to be located. Therefore each county data set is published without topology rules being enforced. GIS Technicians use best practices such as polygon closure and vertex snapping, however, topology is not built for each county. Users should be aware, by Arkansas Law (15-21-504 2 B) digital cadastral data does not represent legal property boundary descriptions, nor is it suitable for boundary determination of the individual parcels included in the cadastre. Users requiring a boundary determination should consult an Arkansas Registered Land Surveyor (http://www.arkansas.gov/pels/search/search.php) on boundary questions. The digital cadastral data is intended to be a graphical representation of the tax parcel only. Just because a county is listed does NOT imply the data represents county wide coverage. AGIO worked with each county to determine a level of production that warranted the data was ready to be published. For example, in some counties only the north part of the county was covered or in other cases only rural parcels are covered and yet in others only urban parcels. The approach is to begin incremental publishing as production blocks are ready, even though a county may not have county wide coverage. Each case represents a significant amount of data that will be useful immediately. Users should consult the BEGIN_DATE attribute column to determine the age of the data for a given county. This date reflects when the data was received from the county. Digital cadastral data users should be aware the County Assessor Mapping Program adopted a phased approach for developing cadastral data. Phase One includes the production of a parcel centroid for each parcel that bears the attributes prescribed by the state cadastral mapping standard. Phase Two includes the production of parcel polygon geometry and bears the standard attributes. The Arkansas standard closely mirrors the federal Cadastral Core Data Standard established by the Federal Geographic Data Committee, Subcommittee for Cadastral Data. Counties within this file include: Arkansas, Ashley, Baxter, Boone, Carroll, Chicot, Clark, Clay, Columbia, Conway, Craighead, Crawford, Cross, Desha, Faulkner, Franklin, Hot Spring, Howard, Izard, Jackson, Jefferson, Lafayette, Lincoln, Little River, Logan, Lonoke, Madison, Mississippi, Montgomery, Nevada, Newton, Perry, Pike, Poinsett, Polk, Pope, Pulaski, Randolph, Saline, Sebastian, Stone, Van Buren, Washington and White.

Analysis of ‘PLACES: Census Tract Data (GIS Friendly Format), 2020 release’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/36454ff3-3bd6-4626-8607-ed62ff3f4619 on 12 February 2022.

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

This dataset contains model-based census tract level estimates for the PLACES project 2020 release in GIS-friendly format. The PLACES project is the expansion of the original 500 Cities project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code tabulation Areas (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2018 or 2017 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2014-2018 or 2013-2017 estimates. The 2020 release uses 2018 BRFSS data for 23 measures and 2017 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening). Four measures are based on the 2017 BRFSS data because the relevant questions are only asked every other year in the BRFSS. These data can be joined with the census tract 2015 boundary file in a GIS system to produce maps for 27 measures at the census tract level. An ArcGIS Online feature service is also available at https://www.arcgis.com/home/item.html?id=8eca985039464f4d83467b8f6aeb1320 for users to make maps online or to add data to desktop GIS software.

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

This dataset is refreshed on a weekly basis from the datasets the team works on daily.Last update date: 11 July 2025.National Highways Operational Highway Boundary (RedLine) maps out the land belonging to the highway for the whole Strategic Road Network (SRN). It comprises two layers; one being the an outline and another showing the registration status / category of land of land that makes up the boundary. Due to the process involved in creating junctions with local highway authority (LHA) roads, land in this dataset may represent LHA highway (owned by National Highways but the responsibility of the LHA to maintain). Surplus land or land held for future projects does not form part of this dataset.The highway boundary is derived from:Ordnance Survey Mastermap Topography,HM Land Registry National Polygon Service (National Highway titles only), andplots researched and digitised during the course of the RedLine Boundary Project.The boundary is split into categories describing the decisions made for particular plots of land. These categories are as follows:Auto-RedLine category is for plots created from an automated process using Ordnance Survey MasterMap Topography as a base. Land is not registered under National Highways' name. For example, but not limited to, unregistered ‘ancient’ highway vested in Highways England, or bridge carrying highways over a rail line.NH Title within RedLine category is for plots created from Land Registry Cadastral parcels whose proprietor is National Highways or a predecessor. Land in this category is within the highway boundary (audited) or meets a certain threshold by the algorithm.NH Title outside RedLine category is for plots created in the same way as above but these areas are thought to be outside the highway boundary. Where the Confidence is Low, land in this category is yet to be audited. Where the Confidence is High, land in this category has been reviewed and audited as outside our operational boundary.National Highways (Technician) Data category is for plots created by National Highways, digitised land parcels relating to highway land that is not registered, not yet registered or un-registerable.Road in Tunnel category, created using tunnel outlines from Ordnance Survey MasterMap Topography data. These represent tunnels on Highways England’s network. Land is not registered under National Highways' name, but land above the tunnel may be in National Highways’ title. Please refer to the definitive land ownership records held at HM Land Registry.The process attribute details how the decision was made for the particular plot of land. These are as follows:Automated category denotes data produced by an automated process. These areas are yet to be audited by the company.Audited category denotes data that has been audited by the company.Technician Data (Awaiting Audit) category denotes data that was created by National Highways but is yet to be audited and confirmed as final.The confidence attribute details how confident you can be in the decision. This attribute is derived from both the decisions made during the building of the underlying automated dataset as well as whether the section has been researched and/or audited by National Highways staff. These are as follows:High category denotes land that has a high probability of being within the RedLine boundary. These areas typically are audited or are features that are close to or on the highway.Moderate category denotes land that is likely to be within the highway boundary but is subject to change once the area has been audited.Low category denotes land that is less likely to be within the highway boundary. These plots typically represent Highways England registered land that the automated process has marked as outside the highway boundary.Please note that this dataset is indicative only. For queries about this dataset please contact the GIS and Research Team.

Analysis of ‘PLACES: County Data (GIS Friendly Format), 2021 release’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/e128e2f2-02af-4605-81aa-97ebdb8b2fc8 on 12 February 2022.

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

This dataset contains model-based county-level estimates for the PLACES 2021 release in GIS-friendly format. PLACES is the expansion of the original 500 Cities Project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. Project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2019 or 2018 data, Census Bureau 2019 or 2018 county population estimates, and American Community Survey (ACS) 2015–2019 or 2014–2018 estimates. The 2021 release uses 2019 BRFSS data for 22 measures and 2018 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours a night). Seven measures are based on the 2018 BRFSS data because the relevant questions are only asked every other year in the BRFSS. These data can be joined with the census 2015 county boundary file in a GIS system to produce maps for 29 measures at the county level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

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

Analysis of ‘Zoning by Address’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/6f2f7b6d-d824-4286-92f0-7118c25b7c21 on 13 February 2022.

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

Do not use this data to make zoning determinations. This data does not show all zoning regulations for an address, including overlays and situations where an address has more than one zoning. Also, the data may be out of date. Use the interactive mapping application http://www.austintexas.gov/GIS/PropertyProfile/ to make zoning determinations, and call 311 if you have questions about zoning. Zoning only applies to addresses within the City of Austin city limits.

This dataset is a list of addresses with their zoning provided to answer questions such as "what property addresses have CS zoning." This data is derived from GIS layer for address and zoning. The place_id field is provided for linking to the addresses GIS layer.

This product is produced by the City of Austin for informational purposes. No warranty is made they City of Austin regarding specific accuracy or completeness.

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

Analysis of ‘PLACES: ZCTA Data (GIS Friendly Format), 2020 release’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/3f03eb36-0c56-4347-9054-257176c84559 on 12 February 2022.

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

This dataset contains model-based ZIP Code tabulation Areas (ZCTA) level estimates for the PLACES project 2020 release in GIS-friendly format. The PLACES project is the expansion of the original 500 Cities project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code tabulation Areas (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2018 or 2017 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2014-2018 or 2013-2017 estimates. The 2020 release uses 2018 BRFSS data for 23 measures and 2017 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening). Four measures are based on the 2017 BRFSS data because the relevant questions are only asked every other year in the BRFSS. These data can be joined with the census 2010 ZCTA boundary file in a GIS system to produce maps for 27 measures at the ZCTA level. An ArcGIS Online feature service is also available at https://www.arcgis.com/home/item.html?id=8eca985039464f4d83467b8f6aeb1320 for users to make maps online or to add data to desktop GIS software.

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

Analysis of ‘HURDLES ’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/https-mon-saint-quentin-hub-arcgis-com-datasets-24237487e38a4831a82ff6bc26a8f7e6_0 on 13 January 2022.

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

The accessibility policy aims to achieve a number of objectives:

progressively adapt the living environment to the whole population, including persons with disabilities or reduced mobility, in order to: Enable them to participate fully in social, educational, cultural and professional life in order to combat all forms of discrimination, even those who are most unconscious in combating exclusion, isolation and marginalisation, enabling people to choose their place and way of life freely;

ensure that the travel chain (i.e. the existing built environment, roads, public spaces, transport and their inter-modality) is continuously accessible to persons with disabilities or reduced mobility and, in particular, at the interface of the various links;

promote mobility, including the use of the walking of older people and active modes of travel, for reasons of public health and maintenance of autonomy. Accessibility policy is based on two complementary and indispensable types of action:

take advantage of all the opportunities offered by new buildings, new infrastructure and redevelopment of public spaces to make them accessible from the outset;

review the existing living environment to identify the work needed to adapt it to persons with disabilities or reduced mobility. To this end, planning and programming tools aimed at making the city more accessible must be developed by many actors:

plans for the accessibility of roads and public spaces (PAVE) by municipalities (or possibly public establishments for inter-municipal cooperation);

master plans for accessibility of public transport services by transport organising authorities;

accessibility diagnostics of establishments receiving the public by the administrations or operators of such establishments.

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

Analysis of ‘TRUNKING ’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/https-mon-saint-quentin-hub-arcgis-com-datasets-24237487e38a4831a82ff6bc26a8f7e6_1 on 12 January 2022.

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

The accessibility policy aims to achieve a number of objectives:

progressively adapt the living environment to the whole population, including persons with disabilities or reduced mobility, in order to: Enable them to participate fully in social, educational, cultural and professional life in order to combat all forms of discrimination, even those who are most unconscious in combating exclusion, isolation and marginalisation, enabling people to choose their place and way of life freely;

ensure that the travel chain (i.e. the existing built environment, roads, public spaces, transport and their inter-modality) is continuously accessible to persons with disabilities or reduced mobility and, in particular, at the interface of the various links;

promote mobility, including the use of the walking of older people and active modes of travel, for reasons of public health and maintenance of autonomy. Accessibility policy is based on two complementary and indispensable types of action:

take advantage of all the opportunities offered by new buildings, new infrastructure and redevelopment of public spaces to make them accessible from the outset;

review the existing living environment to identify the work needed to adapt it to persons with disabilities or reduced mobility. To this end, planning and programming tools aimed at making the city more accessible must be developed by many actors:

plans for the accessibility of roads and public spaces (PAVE) by municipalities (or possibly public establishments for inter-municipal cooperation);

master plans for accessibility of public transport services by transport organising authorities;

accessibility diagnostics of establishments receiving the public by the administrations or operators of such establishments.

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

Analysis of ‘Code Complaints’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/415c72cd-2f1b-4953-b781-4e68561ade02 on 11 February 2022.

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

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

Analysis of ‘2.16 311 Caller Wait Time (summary)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/fcde5e92-b76e-4f8d-ae5d-050282748c09 on 11 February 2022.

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

The Customer Relations Center (CRC) or Tempe 311 is often the first and possibly only contact a resident has with the City. Our goal is to make each interaction as smooth and efficient as possible. The 311 Customer Relations Center strives to achieve an average caller wait time of less than or equal to sixty seconds for 90% of phone calls to Tempe 311.

This page provides data for the 311 Caller Wait Time performance measure.

The performance measure dashboard is available at 2.16 Caller Wait Time.

Additional Information

Source: Cisco Unified Intelligence Center

Contact: Moncayo, Kim

Contact E-Mail: Kim_Moncayo@tempe.gov

Data Source Type: Excel

Preparation Method: Contact Service Queue Call Distribution Summary Report will be pulled from Cisco Unified Intelligence Center. The total/percentage calls handled with queue time of 60 seconds will be extracted from this report.

Publish Frequency: Quarterly

Publish Method: Manual

Data Dictionary

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