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This dashboard depicts the status of NG9-1-1 data submitted to Datmark VEP, a data validation software solution.

Data producers or those who maintain parcel data can use this tool to validate their data against the state Geospatial Advisory Committee (GAC) Parcel Data Standard. The validations within the tool were originally created as part of a MetroGIS Regional Parcel Dataset workflow.

Counties using this tool can obtain a schema geodatabase from Parcel Data Standard page hosted by MnGeo (link below). All counties, cities or those maintaining authoritative data on a local jurisdiction's behalf, are encouraged to use and modify the tool as needed to support local workflows.

Parcel Data Standard Page
http://www.mngeo.state.mn.us/committee/standards/parcel_attrib/parcel_attrib.html

Specific validation information and tool requirements can be found in the following documents included within this resource.
Readme_HowTo.pdf
Readme_Validations.pdf

MAP Data Authoring and Validation Market Outlook

According to our latest research, the global MAP Data Authoring and Validation market size reached USD 2.47 billion in 2024, propelled by the increasing demand for accurate geospatial data across numerous industries. The market is experiencing robust growth, with a CAGR of 13.2% anticipated from 2025 to 2033, projecting the market to reach USD 7.23 billion by 2033. This surge is primarily driven by the proliferation of smart city projects, autonomous vehicle development, and the integration of advanced mapping solutions in various sectors, as per our most recent analysis.

One of the most significant growth factors for the MAP Data Authoring and Validation market is the escalating adoption of location-based services and real-time navigation systems. Industries such as automotive, telecommunications, and urban planning are increasingly reliant on precise mapping data to enable advanced functionalities, including autonomous driving, network planning, and infrastructure development. The evolution of smart transportation and the need for enhanced situational awareness in both civilian and defense sectors further amplify the demand for high-quality map data. Additionally, the integration of artificial intelligence and machine learning algorithms in map data authoring processes has significantly improved the accuracy and speed of data validation, making these solutions indispensable for organizations aiming to maintain a competitive edge in a data-driven landscape.

Another prominent driver is the growing importance of geographic information systems (GIS) in decision-making processes across multiple verticals. As businesses and governments increasingly leverage spatial data analytics for strategic planning, the need for robust map data authoring and validation tools has surged. The expansion of 5G networks and the Internet of Things (IoT) ecosystem has also necessitated the deployment of detailed and up-to-date geospatial datasets to optimize network performance and resource allocation. Furthermore, regulatory frameworks mandating the use of accurate geospatial data for safety and compliance purposes in sectors such as aviation and maritime are fueling the adoption of advanced map data validation solutions.

The market is also witnessing substantial investments in research and development aimed at enhancing the capabilities of map data authoring platforms. Technological advancements, such as cloud-based geospatial data management and the incorporation of real-time data feeds from satellites, drones, and sensors, are transforming the landscape of map data creation and validation. These innovations facilitate the generation of high-resolution, dynamic maps that are critical for applications ranging from urban mobility to environmental monitoring. As the complexity and volume of geospatial data continue to grow, the demand for scalable and automated map data authoring and validation solutions is expected to escalate, further accelerating market expansion.

Regionally, North America continues to dominate the MAP Data Authoring and Validation market, accounting for the largest share in 2024, followed closely by Europe and Asia Pacific. The presence of leading technology providers, high adoption rates of advanced mapping solutions, and substantial investments in smart infrastructure projects are key factors driving regional growth. Asia Pacific, in particular, is emerging as a high-growth region, fueled by rapid urbanization, government initiatives to digitize infrastructure, and the expansion of automotive and telecommunications sectors. Meanwhile, Europe’s focus on sustainable urban development and stringent regulatory standards for geospatial data accuracy further bolster market prospects in the region. Latin America and the Middle East & Africa, while currently accounting for smaller shares, are expected to witness increased adoption of map data solutions as digital transformation initiatives gain momentum.

Component Analysis

The MAP Data Authoring and Validation market is segmented by component into Software and Services, each playing a pivotal role in the ecosystem. Software solutions form the backbone of map data authoring and validation, offering robust platforms for data creation, editing, and verification. These tools leverage advanced algorithms, machine learning, and artificial intelligence to streamline the proce

Data producers or those who maintain park and trail data can use this tool to validate their data against the MetroGIS Park and Trail data standard. The validations within the tool were created to support the Metro Park and Trail datasets (see associated datasets below).

MetroGIS Park and Trail Data Page
https://www.metrogis.org/projects/park-and-trail.aspx

Specific validation information and tool requirements can be found in the following documents included within this resource.
Readme_HowTo.pdf
Readme_Validations.pdf

Our location data powers the most advanced address validation solutions for enterprise backend and frontend systems.

A global, standardized, self-hosted location dataset containing all administrative divisions, cities, and zip codes for 247 countries.

All geospatial data for address data validation is updated weekly to maintain the highest data quality, including challenging countries such as China, Brazil, Russia, and the United Kingdom.

Use cases for the Address Validation at Zip Code Level Database (Geospatial data)

• Address capture and address validation

• Address autocomplete

• Address verification

• Reporting and Business Intelligence (BI)

• Master Data Mangement

• Logistics and Supply Chain Management

• Sales and Marketing

Product Features

• Dedicated features to deliver best-in-class user experience

• Multi-language support including address names in local and foreign languages

• Comprehensive city definitions across countries

Data export methodology

Our location data packages are offered in variable formats, including .csv. All geospatial data for address validation are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

Why do companies choose our location databases

• Enterprise-grade service

• Full control over security, speed, and latency

• Reduce integration time and cost by 30%

• Weekly updates for the highest quality

• Seamlessly integrated into your software

Note: Custom address validation packages are available. Please submit a request via the above contact button for more details.

BIEN data validation and standardization tools.

Utility GIS Data Quality Services Market Outlook

According to our latest research, the global Utility GIS Data Quality Services market size reached USD 1.37 billion in 2024 and is projected to grow at a robust CAGR of 12.8% from 2025 to 2033, reaching an estimated USD 4.08 billion by 2033. The primary growth factor driving this market is the increasing demand for accurate, real-time geospatial data to optimize utility operations and comply with stringent regulatory requirements. The surge in smart grid deployments and digital transformation initiatives across the utility sector is significantly boosting the adoption of specialized GIS data quality services.

One of the core growth drivers for the Utility GIS Data Quality Services market is the accelerating shift toward digital infrastructure in the utilities sector. Utilities, including electric, water, and gas providers, are increasingly relying on Geographic Information Systems (GIS) for asset management, network optimization, and outage management. However, the effectiveness of these systems is heavily dependent on the accuracy and integrity of the underlying data. As utilities modernize their grids and expand their service offerings, the need for comprehensive data cleansing, validation, and enrichment becomes paramount. This trend is further amplified by the proliferation of IoT devices and smart meters, which generate vast volumes of spatial and operational data, necessitating advanced GIS data quality services to ensure consistency and reliability across platforms.

Another significant factor propelling market growth is the evolving regulatory landscape. Governments and regulatory bodies worldwide are imposing stricter requirements on utilities to maintain high-quality, up-to-date geospatial records for compliance, safety, and disaster response. Inaccurate or outdated GIS data can lead to costly penalties, service interruptions, and reputational damage. As a result, utility companies are investing heavily in data quality services to achieve regulatory compliance and mitigate operational risks. The integration of artificial intelligence and machine learning technologies into GIS data quality processes is also enhancing the efficiency and accuracy of data validation, migration, and integration, further supporting market expansion.

Moreover, the increasing complexity of utility networks and the growing emphasis on sustainability and resilience are driving utilities to adopt advanced GIS data quality services. Utilities are under pressure to optimize resource allocation, minimize losses, and enhance customer service, all of which require high-quality geospatial data. The rise of distributed energy resources, such as solar and wind, and the need to manage bi-directional power flows are adding new layers of complexity to utility networks. GIS data quality services enable utilities to maintain a comprehensive, accurate digital twin of their infrastructure, supporting better planning, predictive maintenance, and rapid response to outages or emergencies. These factors collectively contribute to the sustained growth of the Utility GIS Data Quality Services market.

From a regional perspective, North America currently dominates the Utility GIS Data Quality Services market, driven by large-scale investments in smart grid projects and the presence of major utility companies adopting advanced GIS solutions. However, Asia Pacific is expected to witness the fastest growth over the forecast period, fueled by rapid urbanization, infrastructure development, and government initiatives to modernize utility networks. Europe also presents significant opportunities, with increasing focus on sustainability, regulatory compliance, and cross-border energy integration. The Middle East & Africa and Latin America are gradually catching up, with investments in utility infrastructure and digital transformation initiatives gaining momentum. Overall, the global market is poised for substantial growth, underpinned by technological advancements, regulatory mandates, and the evolving needs of the utility sector.

Service Type Analysis

The Utility GIS Data Quality Services market is segmented by service type into data cleansing, data validation, data integration, data migration, data enrichment, and others. Data cleansing services form the backbone of this segment, as they address the critical need to remove inaccuracies, inconsistencies, and redundancies from utility GIS databases. Wit

MAP Data Authoring and Validation Market Outlook

According to our latest research, the global MAP Data Authoring and Validation market size in 2024 is valued at USD 4.28 billion, reflecting the rapidly increasing demand for accurate mapping data across multiple industries. The market is experiencing a robust growth trajectory, with a recorded CAGR of 13.2% from 2025 to 2033. By 2033, the MAP Data Authoring and Validation market is forecasted to reach an impressive USD 12.42 billion. This growth is primarily driven by the proliferation of autonomous vehicles, smart city initiatives, and the critical importance of precise geospatial data in modern applications, as per our latest research findings.

The MAP Data Authoring and Validation market is witnessing exponential expansion due to the escalating integration of advanced mapping solutions in the automotive and transportation sectors. The surge in demand for autonomous vehicles and connected mobility solutions necessitates highly accurate and real-time map data, which, in turn, propels the adoption of authoring and validation tools. Furthermore, the evolution of smart cities and IoT-enabled urban infrastructure is generating an unprecedented need for reliable geospatial data to optimize city planning, utility management, and emergency response systems. These factors collectively contribute to the sustained growth of the market, as organizations increasingly prioritize data accuracy, consistency, and validation to enhance operational efficiency and decision-making processes.

Another significant growth factor for the MAP Data Authoring and Validation market is the rapid digital transformation across industries, particularly in logistics, utilities, and government sectors. The shift towards digital workflows and automation, coupled with regulatory mandates for accurate geospatial information, is compelling enterprises to invest in sophisticated software and services for map data creation and validation. Additionally, the rise of location-based services, mobile mapping applications, and real-time navigation solutions is accelerating the market’s momentum. The growing adoption of cloud-based platforms further amplifies accessibility and scalability, enabling organizations to manage large volumes of spatial data efficiently while ensuring compliance with evolving data standards.

Technological advancements are also playing a pivotal role in driving the MAP Data Authoring and Validation market. The integration of artificial intelligence, machine learning, and big data analytics into mapping solutions is enhancing the precision, automation, and speed of data authoring and validation processes. These technologies facilitate the rapid detection and correction of errors, automate data enrichment, and enable predictive analytics for proactive decision-making. Moreover, the increasing interoperability of mapping platforms with other enterprise systems, such as ERP and GIS, is unlocking new opportunities for cross-functional data utilization and business intelligence. As industries continue to embrace digital innovation, the demand for advanced MAP Data Authoring and Validation solutions is expected to accelerate further.

From a regional perspective, the MAP Data Authoring and Validation market exhibits robust growth across North America, Europe, and Asia Pacific, with North America currently holding the largest market share. The region’s dominance is attributed to the early adoption of advanced mapping technologies, strong presence of automotive and technology giants, and significant investments in smart infrastructure projects. Europe follows closely, driven by stringent regulatory frameworks and a thriving automotive sector. Meanwhile, Asia Pacific is emerging as the fastest-growing region, fueled by rapid urbanization, expanding transportation networks, and government-led digitalization initiatives. Latin America and the Middle East & Africa are also witnessing steady growth, albeit at a more measured pace, as regional players increase their focus on geospatial data management and smart city development.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. Our final map product is a geographic information system (GIS) database of vegetation structure and composition across the Crater Lake National Park terrestrial landscape, including wetlands. The database includes photos we took at all relevé, validation, and accuracy assessment plots, as well as the plots that were done in the previous wetlands inventory. We conducted an accuracy assessment of the map by evaluating 698 stratified random accuracy assessment plots throughout the project area. We intersected these field data with the vegetation map, resulting in an overall thematic accuracy of 86.2 %. The accuracy of the Cliff, Scree & Rock Vegetation map unit was difficult to assess, as only 9% of this vegetation type was available for sampling due to lack of access. In addition, fires that occurred during the 2017 accuracy assessment field season affected our sample design and may have had a small influence on the accuracy. Our geodatabase contains the locations where particular associations are found at 600 relevé plots, 698 accuracy assessment plots, and 803 validation plots.

This document explains the purpose, logic, and results of Minnesota’s Next Generation 9-1-1 (NG9-1-1) Street Name Validation found on the Minnesota NG9-1-1 GIS Data Validation and Aggregation Portal.

GIS quality control checks are intended to identify issues in the source data that may impact a variety of9-1-1 end use systems.The primary goal of the initial CalOES NG9-1-1 implementation is to facilitate 9-1-1 call routing. Thesecondary goal is to use the data for telephone record validation through the LVF and the GIS-derivedMSAG.With these goals in mind, the GIS QC checks, and the impact of errors found by them are categorized asfollows in this document:Provisioning Failure Errors: GIS data issues resulting in ingest failures (results in no provisioning of one or more layers)Tier 1 Critical errors: Impact on initial 9-1-1 call routing and discrepancy reportingTier 2 Critical errors: Transition to GIS derived MSAGTier 3 Warning-level errors: Impact on routing of call transfersTier 4 Other errors: Impact on PSAP mapping and CAD systemsGeoComm's GIS Data Hub is configurable to stop GIS data that exceeds certain quality control check error thresholdsfrom provisioning to the SI (Spatial Interface) and ultimately to the ECRFs, LVFs and the GIS derivedMSAG.

Mapping of environmental variables often relies on map accuracy assessment through cross-validation with the data used for calibrating the underlying mapping model. When the data points are spatially clustered, conventional cross-validation leads to optimistically biased estimates of map accuracy. Several papers have promoted spatial cross-validation as a means to tackle this over-optimism. Many of these papers blame spatial autocorrelation as the cause of the bias and propagate the widespread misconception that spatial proximity of calibration points to validation points invalidates classical statistical validation of maps. In the paper related to these data, we present and evaluate alternative cross-validation approaches for assessing map accuracy from clustered sample data.

The study area is western Europe, constrained in the north at 52° latitude and at -10° and 24° longitude The projection is IGNF:ETRS89LAEA (Lambert azimuthal equal area projection).

Files:

agb.tif = above ground biomass (AGB) map from version 3 of the 2017 CCI-Biomass product (https://catalogue.ceda.ac.uk/uuid/5f331c418e9f4935b8eb1b836f8a91b8) AGBstack.tif = covariates used for predicting AGB aggArea.tif = coarse grid used for simulation in the model-based methods ocs.tif = soil organic carbon stock (OCS) map (0-30 cm) from Soilgrids (https://www.isric.org/explore/soilgrids) OCSstack.tif = covariates used for predicting OCS strata.xxx = 100 compact geo-strata (ESRI shape) created with the spcosa package; used for generating clustered samples TOTmask.tif = mask of the area covered by the covariates

Details and data sources of the covariates in AGBstack.tif and OCSstack.tif:

Name

Description

Source

Note

ai

Aridity Index

https://chelsa-climate.org/downloads/

    Version 2.1

bio1

Mean annual air temperature [°C]

    https://chelsa-climate.org/downloads/
    Version 2.1

bio5

Mean daily maximum air temperature of the warmest month [°C]

    https://chelsa-climate.org/downloads/
    Version 2.1

bio7

Annual range of air temperature [°C]

    https://chelsa-climate.org/downloads/
    Version 2.1

bio12

Annual precipitation [kg/m2]

    https://chelsa-climate.org/downloads/
    Version 2.1

bio15

Precipitation seasonality [kg/m2]

    https://chelsa-climate.org/downloads/
    Version 2.1

gdd10

Growing degree days heat sum above 10°C

    https://chelsa-climate.org/downloads/
    Version 2.1

clay

Clay content [g/kg] of the 0-5cm layer

https://soilgrids.org/

Only used for AGB

sand

Sand content [g/kg] of the 0-5cm layer

    https://soilgrids.org/
    as above

pH

Acidity (Ph(water)) of the 0-5cm layer

    https://soilgrids.org/
    as above

glc2017

Landcover 2017

https://land.copernicus.eu/global/products/lc, reclassified to: closed forest, open forest, natural non-forest veg., bare & sparse veg. cropland, built-up, water

Categorical variable

dem

Elevation

https://www.eea.europa.eu/data-and-maps/data/copernicus-land-monitoring-service-eu-dem

cosasp

Cosine of slope aspect

Computed with the terra package from elevation

    Computed @25m resolution; next aggregated to 0.5km

sinasp

Sine of slope aspect

    Computed with the terra package from elevation
    as above

slope

Slope

    Computed with the terra package from elevation
    as above

TPI

Topographic position index

    Computed with the terra package from elevation
    as above

TRI

Terrain ruggedness index

    Computed with the terra package from elevation
    as above

TWI

Topographic wetness index

Computed with SAGA from 500m resolution (aggregated) dem

gedi

Forest height

https://glad.umd.edu/dataset/gedi

Zone: NAFR

xcoord

X coordinate

Using a mask created from the other covariates

ycoord

Y coordinate

    Using a mask created from the other covariates

Dcoast

Distance from coast

Using a land mask created from the other covariates

Utility GIS Data Quality Services Market Outlook

According to our latest research, the global Utility GIS Data Quality Services market size reached USD 1.29 billion in 2024, with a robust growth trajectory marked by a CAGR of 10.7% from 2025 to 2033. By the end of the forecast period, the market is projected to attain a value of USD 3.13 billion by 2033. This growth is primarily driven by the increasing need for accurate spatial data, the expansion of smart grid initiatives, and the rising complexity of utility network infrastructures worldwide.

The primary growth factor propelling the Utility GIS Data Quality Services market is the surging adoption of Geographic Information Systems (GIS) for utility asset management and network optimization. Utilities are increasingly relying on GIS platforms to ensure seamless operations, improved decision-making, and regulatory compliance. However, the effectiveness of these platforms is directly linked to the quality and integrity of the underlying data. With the proliferation of IoT devices and the integration of real-time data sources, the risk of data inconsistencies and inaccuracies has risen, making robust data quality services indispensable. Utilities are investing heavily in data cleansing, validation, and enrichment to mitigate operational risks, reduce outages, and enhance customer satisfaction. This trend is expected to continue, as utilities recognize the strategic importance of data-driven operations in an increasingly digital landscape.

Another significant driver is the global movement towards smart grids and digital transformation across the utility sector. As utilities modernize their infrastructure, they are deploying advanced metering infrastructure (AMI) and integrating distributed energy resources (DERs), which generate vast volumes of spatial and non-spatial data. Ensuring the accuracy, consistency, and completeness of this data is crucial for optimizing grid performance, minimizing losses, and enabling predictive maintenance. The need for real-time analytics and advanced network management further amplifies the demand for high-quality GIS data. Additionally, regulatory mandates for accurate reporting and asset traceability are compelling utilities to prioritize data quality initiatives. These factors collectively create a fertile environment for the growth of Utility GIS Data Quality Services, as utilities strive to achieve operational excellence and regulatory compliance.

Technological advancements and the rise of cloud-based GIS solutions are also fueling market expansion. Cloud deployment offers utilities the flexibility to scale data quality services, access advanced analytics, and collaborate across geographies. This has democratized access to sophisticated GIS data quality tools, particularly for mid-sized and smaller utilities that previously faced budgetary constraints. Moreover, the integration of artificial intelligence (AI) and machine learning (ML) in data quality solutions is enabling automated data cleansing, anomaly detection, and predictive analytics. These innovations are not only reducing manual intervention but also enhancing the accuracy and reliability of utility GIS data. As utilities continue to embrace digital transformation, the demand for cutting-edge data quality services is expected to surge, driving sustained market growth throughout the forecast period.

Utility GIS plays a pivotal role in supporting the digital transformation of the utility sector. By leveraging Geographic Information Systems, utilities can achieve a comprehensive understanding of their network infrastructures, enabling more efficient asset management and network optimization. The integration of Utility GIS with advanced data quality services ensures that utilities can maintain high standards of data accuracy and integrity, which are essential for effective decision-making and regulatory compliance. As utilities continue to modernize their operations and embrace digital technologies, the role of Utility GIS in facilitating seamless data integration and real-time analytics becomes increasingly critical. This not only enhances operational efficiency but also supports the strategic goals of sustainability and resilience in utility management.

Regionally, North America leads the Utility GIS Data Quality Services market, accounting for the largest share in 2024, followed closely by

Links to recordings of the Integrated Services Program and 9-1-1 & Geospatial Services Bureau webinar series, including NG9-1-1 GIS topics such as: data preparation; data provisioning and maintenance; boundary best practices; and extract, transform, and load (ETL). Offerings include:Topic: Virginia Next Generation 9-1-1 Dashboard and Resources Update Description: Virginia recently updated the NG9-1-1 Dashboard with some new tabs and information sources and continues to develop new resources to assist the GIS data work. This webinar provides an overview of changes, a demonstration of new functionality, and a guide to finding and using new resources that will benefit Virginia public safety and GIS personnel with roles in their NG9-1-1 projects. Wednesday 16 June 2021. Recording available at: https://vimeo.com/566133775Topic: Emergency Service Boundary GIS Data Layers and Functions in your NG9-1-1 PSAP Description: Law, Fire, and Emergency Medical Service (EMS) Emergency Service Boundary (ESB) polygons are required elements of the NENA NG9-1-1 GIS data model stack that indicate which agency is responsible for primary response. While this requirement must be met in your Virginia NG9-1-1 deployment with AT&T and Intrado, there are quite a few ways you could choose to implement these polygons. PSAPs and their GIS support must work together to understand how this information will come into a NG9-1-1 i3 PSAP and how it will replace traditional ESN information in order to make good choices while implementing these layers. This webinar discusses:the function of ESNs in your legacy 9-1-1 environment, the role of ESBs in NG9-1-1, and how ESB information appears in your NG9-1-1 PSAP. Wednesday, 22 July 2020. Recording available at: https://vimeo.com/441073056#t=360sTopic: "The GIS Folks Handle That": What PSAP Professionals Need to Know about the GIS Project Phase of Next Generation 9-1-1 DeploymentDescription: Next Generation 9-1-1 (NG9-1-1) brings together the worlds of emergency communication and spatial data and mapping. While it may be tempting for PSAPs to outsource cares and concerns about road centerlines and GIS data provisioning to 'the GIS folks', GIS staff are crucial to the future of emergency call routing and location validation. Data required by NG9-1-1 usually builds on data that GIS staff already know and use for other purposes, so the transition requires them to learn more about PSAP operations and uses of core data. The goal of this webinar is to help the PSAP and GIS worlds come together by explaining the role of the GIS Project in the Virginia NG9-1-1 Deployment Steps, exploring how GIS professionals view NG9-1-1 deployment as a project, and fostering a mutual understanding of how GIS will drive NG9-1-1. 29 January 2020. Recording available at: https://vimeo.com/showcase/9791882/video/761225474Topic: Getting Your GIS Data from Here to There: Processes and Best Practices for Extract, Transform and Load (ETL) Description: During the fall of 2019, VITA-ISP staff delivered workshops on "Tools and Techniques for Managing the Growing Role of GIS in Enterprise Software." This session presents information from the workshops related to the process of extracting, transforming, and loading data (ETL), best practices for ETL, and methods for data schema comparison and field mapping as a webinar. These techniques and skills assist GIS staff with their growing role in Next Generation 9-1-1 but also apply to many other projects involving the integration and maintenance of GIS data. 19 February 2020. Recording available at: https://vimeo.com/showcase/9791882/video/761225007Topic: NG9-1-1 GIS Data Provisioning and MaintenanceDescription: VITA ISP pleased to announce an upcoming webinar about the NG9-1-1 GIS Data Provisioning and Maintenance document provided by Judy Doldorf, GISP with the Fairfax County Department of Information Technology and RAC member. This document was developed by members of the NG9-1-1 GIS workgroup within the VITA Regional Advisory Council (RAC) and is intended to provide guidance to local GIS and PSAP authorities on the GIS datasets and associated GIS to MSAG/ALI validation and synchronization required for NG9-1-1 services. The document also provides guidance on geospatial call routing readiness and the short- and long-term GIS data maintenance workflow procedures. In addition, some perspective and insight from the Fairfax County experience in GIS data preparation for the AT&T and West solution will be discussed in this webinar. 31 July 2019. Recording available at: https://vimeo.com/showcase/9791882/video/761224774Topic: NG9-1-1 Deployment DashboardDescription: I invite you to join us for a webinar that will provide an overview of our NG9-1-1 Deployment Dashboard and information about other online ISP resources. The ISP website has been long criticized for being difficult to use and find information. The addition of the Dashboard and other changes to the website are our attempt to address some of these concerns and provide an easier way to find information especially as we undertake NG9-1-1 deployment. The Dashboard includes a status map of all Virginia PSAPs as it relates to the deployment of NG9-1-1, including the total amount of funding requested by the localities and awards approved by the 9-1-1 Services Board. During this webinar, Lyle Hornbaker, Regional Coordinator for Region 5, will navigate through the dashboard and provide tips on how to more effectively utilize the ISP website. 12 June 2019. Recording not currently available. Please see the Virginia Next Generation 9-1-1 Dashboard and Resources Update webinar recording from 16 June 2021. Topic: PSAP Boundary Development Tools and Process RecommendationDescription: This webinar will be presented by Geospatial Program Manager Matt Gerike and VGIN Coordinator Joe Sewash. With the release of the PSAP boundary development tools and PSAP boundary segment compilation guidelines on the VGIN Clearinghouse in March, this webinar demonstrates the development tools, explains the process model, and discusses methods, tools, and resources available for you as you work to complete PSAP boundary segments with your neighbors. 15 May 2019. Recording available at: https://www.youtube.com/watch?v=kI-1DkUQF9Q&feature=youtu.beTopic: NG9-1-1 Data Preparation - Utilizing VITA's GIS Data Report Card ToolDescription: This webinar, presented by VGIN Coordinator Joe Sewash, Geospatial Program Manager Matt Gerike, and Geospatial Analyst Kenny Brevard will provide an overview of the first version of the tools that were released on March 25, 2019. These tools will allow localities to validate their GIS data against the report card rules, the MSAG and ALI checks used in previous report cards, and the analysis listed in the NG9-1-1 migration proposal document. We will also discuss the purpose of the tools, input requirements, initial configuration, how to run them, and how to make sense of your results. 10 April 2019. Recording available at: https://vimeo.com/showcase/9791882/video/761224495Topic: NG9-1-1 PSAP Boundary Best Practice WebinarDescription: During the months of November and December, VITA ISP staff hosted regional training sessions about best practices for PSAP boundaries as they relate to NG9-1-1. These sessions were well attended and very interactive, therefore we feel the need to do a recap and allow those that may have missed the training to attend a makeup session. 30 January 2019. Recording not currently available. Please see the PSAP Boundary Development Tools and Process Recommendation webinar recording from 15 May 2019.Topic: NG9-1-1 GIS Overview for ContractorsDescription: The Commonwealth of Virginia has started its migration to next generation 9-1-1 (NG9-1-1). This migration means that there will be a much greater reliance on geographic information (GIS) to locate and route 9-1-1 calls. VITA ISP has conducted an assessment of current local GIS data and provided each locality with a report. Some of the data from this report has also been included in the localities migration proposal, which identifies what data issues need to be resolved before the locality can migrate to NG9-1-1. Several localities in Virginia utilize a contractor to maintain their GIS data. This webinar is intended for those contractors to review the data in the report, what is included in the migration proposal and how they may be called on to assist the localities they serve. It will still ultimately be up to each locality to determine whether they engage a contractor for assistance, but it is important for the contractor community to understand what is happening and have an opportunity to ask questions about the intent and goals. This webinar will provide such an opportunity. 22 August 2018. Recording not currently available. Please contact us at NG911GIS@vdem.virginia.gov if you are interested in this content.

This layer contains the most current locations and up-to-date non-spatial attributes for Kentucky's Public, K-12 Schools. The Front Door project implemented by the Kentucky Department of Education allowed school teams to capture the geographic coordinates digitally using The Commonwealth Map. Following data validation, the Kentucky Division of Geographic Information utilizes this layer in the mapping services it provides to the communities.Download: Ky Open GIS Data

This is the static test data from the study "Global Geolocated Realtime Data of Interfleet Urban Transit Bus Iding" collected by GRD-TRT-BUF-4I. Updated versions are available here.test-data-a.csv was collected from December 31, 2023 00:01:30 UTC to January 1, 2024 00:01:30 UTC.test-data-b.csv was collected from January 4, 2024 01:30:30 UTC to January 5, 2024 01:30:30 UTC.test-data-c.csv was collected from January 10, 2024 16:05:30 UTC to January 11, 2024 16:05:30 UTC.test-data-d.csv was collected from January 15, 2024 22:30:21 UTC to January 16, 2024 22:30:17 UTC.test-data-e.csv was collected from February 16, 2024 22:30:21 UTC to February 17, 2024 22:30:20 UTC.test-data-f.csv was collected from February 21, 2024 22:30:21 UTC to February 22, 2024 22:30:20 UTC.

Minnesota Geospatial Commons Metadata ValidatorWelcome to the Minnesota Geospatial Commons Metadata Validator! This notebook helps you check the metadata for your ArcGIS Online item or group items.InstructionsRun All Cells: Click on "Run All Cells" or Click "Run" for each cell.Input Your ArcGIS ID: When prompted, enter your ArcGIS Item ID or Group ID.What This Notebook DoesParses the metadata for the provided ArcGIS Online item or items in the provided group.Prints out any missing required attributes.Additional RequirementsPlease ensure your item also meets the following criteria:Publicly Accessible: The item must be accessible to the public.ISO Topic Category: The item should have an ISO Topic Category.Relevant Tags: The item should include relevant tags.

GIS (Geographic Information System) data, which includes spatial data such as maps, satellite imagery, and other geospatial data, is typically created using various techniques and methods to ensure its accuracy, completeness, and reliability. The process of creating GIS data for use in metadata involves several key steps, which may include: Data Collection: The first step in creating GIS data for metadata is data collection. This may involve gathering data from various sources, such as field surveys, remote sensing, aerial photography, or existing datasets. Data can be collected using GPS (Global Positioning System) receivers, satellite imagery, LiDAR (Light Detection and Ranging) technology, or other data acquisition methods.Data Validation and Quality Control: Once data is collected, it goes through validation and quality control processes to ensure its accuracy and reliability. This may involve comparing data against known standards or specifications, checking for data errors or inconsistencies, and validating data attributes to ensure they meet the desired accuracy requirements.Data Processing and Analysis: After validation and quality control, data may be processed and analyzed to create meaningful information. This may involve data integration, data transformation, spatial analysis, and other geoprocessing techniques to derive new datasets or generate metadata.Metadata Creation: Metadata, which is descriptive information about the GIS data, is created based on established standards or guidelines. This may include information such as data source, data quality, data format, spatial extent, projection information, and other relevant details that provide context and documentation about the GIS data.Metadata Documentation: Once metadata is created, it needs to be documented in a standardized format. This may involve using metadata standards such as ISO 19115, FGDC (Federal Geographic Data Committee), or other industry-specific standards. Metadata documentation typically includes information about the data source, data lineage, data quality, spatial reference system, attributes, and other relevant information that describes the GIS data and its characteristics.Data Publishing: Finally, GIS data and its associated metadata may be published or made accessible to users through various means, such as online data portals, web services, or other data dissemination methods. Metadata is often used to facilitate data discovery, evaluation, and use, providing users with the necessary information to understand and utilize the GIS data effectively.Overall, the process of creating GIS data for use in metadata involves data collection, validation, processing, analysis, metadata creation, documentation, and data publishing, following established standards or guidelines to ensure accuracy, reliability, and interoperability of the GIS data.

GapMaps Live is an easy-to-use location intelligence platform available across 25 countries globally that allows you to visualise your own store data, combined with the latest demographic, economic and population movement intel right down to the micro level so you can make faster, smarter and surer decisions when planning your network growth strategy.

With one single login, you can access the latest estimates on resident and worker populations, census metrics (eg. age, income, ethnicity), consuming class, retail spend insights and point-of-interest data across a range of categories including fast food, cafe, fitness, supermarket/grocery and more.

Some of the world's biggest brands including McDonalds, Subway, Burger King, Anytime Fitness and Dominos use GapMaps Live as a vital strategic tool where business success relies on up-to-date, easy to understand, location intel that can power business case validation and drive rapid decision making.

Primary Use Cases for GapMaps Live includes:

1. Retail Site Selection - Identify optimal locations for future expansion and benchmark performance across existing locations.
2. Customer Profiling: get a detailed understanding of the demographic profile of your customers and where to find more of them.
3. Analyse your catchment areas at a granular grid levels using all the key metrics
4. Target Marketing: Develop effective marketing strategies to acquire more customers.
5. Marketing / Advertising (Billboards/OOH, Marketing Agencies, Indoor Screens)
6. Customer Profiling
7. Target Marketing
8. Market Share Analysis

Some of features our clients love about GapMaps Live include: - View business locations, competitor locations, demographic, economic and social data around your business or selected location - Understand consumer visitation patterns (“where from” and “where to”), frequency of visits, dwell time of visits, profiles of consumers and much more. - Save searched locations and drop pins - Turn on/off all location listings by category - View and filter data by metadata tags, for example hours of operation, contact details, services provided - Combine public data in GapMaps with views of private data Layers - View data in layers to understand impact of different data Sources - Share maps with teams - Generate demographic reports and comparative analyses on different locations based on drive time, walk time or radius. - Access multiple countries and brands with a single logon - Access multiple brands under a parent login - Capture field data such as photos, notes and documents using GapMaps Connect and integrate with GapMaps Live to get detailed insights on existing and proposed store locations.