The Geographic Information Systems (GIS) Platform market is experiencing robust growth, projected to reach a market size of $4078.2 million in 2025. While the provided CAGR is missing, considering the widespread adoption of GIS across various sectors like government, utilities, and commercial businesses, coupled with advancements in cloud-based GIS and increasing demand for spatial analytics, a conservative estimate of the Compound Annual Growth Rate (CAGR) between 2025 and 2033 would be around 7-9%. This suggests a significant expansion of the market over the forecast period. Key drivers include the rising need for efficient resource management, improved infrastructure planning, precise location-based services, and the growing adoption of big data analytics combined with location intelligence. The market is segmented by type (Desktop GIS, Web Map Service GIS, Others) and application (Government & Utilities, Commercial Use), reflecting the diverse applications of GIS technology. Leading players like Environmental Systems Research Institute (Esri), Hexagon, Pitney Bowes, and SuperMap are shaping the market landscape through continuous innovation and strategic partnerships. The North American market currently holds a significant share due to high technology adoption and substantial investments in GIS infrastructure, but rapid growth is anticipated in Asia Pacific regions like China and India driven by urbanization and infrastructure development. The increasing availability of affordable high-resolution imagery and data fuels further expansion. The continued integration of GIS with other technologies like AI and IoT is expected to unlock new applications and further drive market growth. Challenges include the high initial investment costs for sophisticated GIS solutions, the need for skilled professionals to manage and interpret data, and ensuring data security and privacy. However, the benefits of improved decision-making, optimized resource allocation, and enhanced operational efficiency are expected to outweigh these challenges, contributing to the sustained expansion of the GIS Platform market throughout the forecast period. The market's future trajectory remains positive, fueled by technological advancements and the increasing reliance on location intelligence across various industries.

Contains:World HillshadeWorld Street Map (with Relief) - Base LayerLarge Scale International Boundaries (v11.3)World Street Map (with Relief) - LabelsDoS Country Labels DoS Country LabelsCountry (admin 0) labels that have been vetted for compliance with foreign policy and legal requirements. These labels are part of the US Federal Government Basemap, which contains the borders and place names that have been vetted for compliance with foreign policy and legal requirements.Source: DoS Country Labels - Overview (arcgis.com)Large Scale International BoundariesVersion 11.3Release Date: December 19, 2023DownloadFor more information on the LSIB click here: https://geodata.state.gov/ A direct link to the data is available here: https://data.geodata.state.gov/LSIB.zipAn ISO-compliant version of the LSIB metadata (in ISO 19139 format) is here: https://geodata.state.gov/geonetwork/srv/eng/catalog.search#/metadata/3bdb81a0-c1b9-439a-a0b1-85dac30c59b2 Direct inquiries to internationalboundaries@state.govOverviewThe Office of the Geographer and Global Issues at the U.S. Department of State produces the Large Scale International Boundaries (LSIB) dataset. The current edition is version 11.3 (published 19 December 2023). The 11.3 release contains updates to boundary lines and data refinements enabling reuse of the dataset. These data and generalized derivatives are the only international boundary lines approved for U.S. Government use. The contents of this dataset reflect U.S. Government policy on international boundary alignment, political recognition, and dispute status. They do not necessarily reflect de facto limits of control.National Geospatial Data AssetThis dataset is a National Geospatial Data Asset managed by the Department of State on behalf of the Federal Geographic Data Committee's International Boundaries Theme.DetailsSources for these data include treaties, relevant maps, and data from boundary commissions and national mapping agencies. Where available and applicable, the dataset incorporates information from courts, tribunals, and international arbitrations. The research and recovery process involves analysis of satellite imagery and elevation data. Due to the limitations of source materials and processing techniques, most lines are within 100 meters of their true position on the ground.Attribute StructureThe dataset uses thefollowing attributes:Attribute NameCC1COUNTRY1CC2COUNTRY2RANKSTATUSLABELNOTES These attributes are logically linked:Linked AttributesCC1COUNTRY1CC2COUNTRY2RANKSTATUS These attributes have external sources:Attribute NameExternal Data SourceCC1GENCCOUNTRY1DoS ListsCC2GENCCOUNTRY2DoS ListsThe eight attributes listed above describe the boundary lines contained within the LSIB dataset in both a human and machine-readable fashion. Other attributes in the release include "FID", "Shape", and "Shape_Leng" are components of the shapefile format and do not form an intrinsic part of the LSIB."CC1" and "CC2" fields are machine readable fields which contain political entity codes. These codes are derived from the Geopolitical Entities, Names, and Codes Standard (GENC) Edition 3 Update 18. The dataset uses the GENC two-character codes. The code ‘Q2’, which is not in GENC, denotes a line in the LSIB representing a boundary associated with an area not contained within the GENC standard.The "COUNTRY1" and "COUNTRY2" fields contain human-readable text corresponding to the name of the political entity. These names are names approved by the U.S. Board on Geographic Names (BGN) as incorporated in the list of Independent States in the World and the list of Dependencies and Areas of Special Sovereignty maintained by the Department of State. To ensure the greatest compatibility, names are presented without diacritics and certain names are rendered using commonly accepted cartographic abbreviations. Names for lines associated with the code ‘Q2’ are descriptive and are not necessarily BGN-approved. Names rendered in all CAPITAL LETTERS are names of independent states. Other names are those associated with dependencies, areas of special sovereignty, or are otherwise presented for the convenience of the user.The following fields are an intrinsic part of the LSIB dataset and do not rely on external sources:Attribute NameMandatoryContains NullsRANKYesNoSTATUSYesNoLABELNoYesNOTESNoYesNeither the "RANK" nor "STATUS" field contains null values; the "LABEL" and "NOTES" fields do.The "RANK" field is a numeric, machine-readable expression of the "STATUS" field. Collectively, these fields encode the views of the United States Government on the political status of the boundary line.Attribute NameValueRANK123STATUSInternational BoundaryOther Line of International Separation Special Line A value of "1" in the "RANK" field corresponds to an "International Boundary" value in the "STATUS" field. Values of "2" and "3" correspond to "Other Line of International Separation" and "Special Line", respectively.The "LABEL" field contains required text necessarily to describe the line segment. The "LABEL" field is used when the line segment is displayed on maps or other forms of cartographic visualizations. This includes most interactive products. The requirement to incorporate the contents of the "LABEL" field on these products is scale dependent. If a label is legible at the scale of a given static product a proper use of this dataset would encourage the application of that label. Using the contents of the "COUNTRY1" and "COUNTRY2" fields in the generation of a line segment label is not required. The "STATUS" field is not a line labeling field but does contain the preferred description for the three LSIB line types when lines are incorporated into a map legend. Using the "CC1", "CC2", or "RANK" fields for labeling purposes is prohibited.The "NOTES" field contains an explanation of any applicable special circumstances modifying the lines. This information can pertain to the origins of the boundary lines, any limitations regarding the purpose of the lines, or the original source of the line. Use of the "NOTES" field for labeling purposes is prohibited.External Data SourcesGeopolitical Entities, Names, and Codes Registry: https://nsgreg.nga.mil/GENC-overview.jspU.S. Department of State List of Independent States in the World: https://www.state.gov/independent-states-in-the-world/U.S. Department of State List of Dependencies and Areas of Special Sovereignty: https://www.state.gov/dependencies-and-areas-of-special-sovereignty/The source for the U.S.—Canada international boundary (NGDAID97) is the International Boundary Commission: https://www.internationalboundarycommission.org/en/maps-coordinates/coordinates.phpThe source for the “International Boundary between the United States of America and the United States of Mexico” (NGDAID82) is the International Boundary and Water Commission: https://catalog.data.gov/dataset?q=usibwcCartographic UsageCartographic usage of the LSIB requires a visual differentiation between the three categories of boundaries. Specifically, this differentiation must be between:- International Boundaries (Rank 1);- Other Lines of International Separation (Rank 2); and- Special Lines (Rank 3).Rank 1 lines must be the most visually prominent. Rank 2 lines must be less visually prominent than Rank 1 lines. Rank 3 lines must be shown in a manner visually subordinate to Ranks 1 and 2. Where scale permits, Rank 2 and 3 lines must be labeled in accordance with the “Label” field. Data marked with a Rank 2 or 3 designation does not necessarily correspond to a disputed boundary.Additional cartographic information can be found in Guidance Bulletins (https://hiu.state.gov/data/cartographic_guidance_bulletins/) published by the Office of the Geographer and Global Issues.ContactDirect inquiries to internationalboundaries@state.gov.CreditsThe lines in the LSIB dataset are the product of decades of collaboration between geographers at the Department of State and the National Geospatial-Intelligence Agency with contributions from the Central Intelligence Agency and the UK Defence Geographic Centre.Attribution is welcome: U.S. Department of State, Office of the Geographer and Global Issues.Changes from Prior ReleaseThe 11.3 release is the third update in the version 11 series.This version of the LSIB contains changes and accuracy refinements for the following line segments. These changes reflect improvements in spatial accuracy derived from newly available source materials, an ongoing review process, or the publication of new treaties or agreements. Notable changes to lines include:• AFGHANISTAN / IRAN• ALBANIA / GREECE• ALBANIA / KOSOVO• ALBANIA/MONTENEGRO• ALBANIA / NORTH MACEDONIA• ALGERIA / MOROCCO• ARGENTINA / BOLIVIA• ARGENTINA / CHILE• BELARUS / POLAND• BOLIVIA / PARAGUAY• BRAZIL / GUYANA• BRAZIL / VENEZUELA• BRAZIL / French Guiana (FR.)• BRAZIL / SURINAME• CAMBODIA / LAOS• CAMBODIA / VIETNAM• CAMEROON / CHAD• CAMEROON / NIGERIA• CHINA / INDIA• CHINA / NORTH KOREA• CHINA / Aksai Chin• COLOMBIA / VENEZUELA• CONGO, DEM. REP. OF THE / UGANDA• CZECHIA / GERMANY• EGYPT / LIBYA• ESTONIA / RUSSIA• French Guiana (FR.) / SURINAME• GREECE / NORTH MACEDONIA• GUYANA / VENEZUELA• INDIA / Aksai Chin• KAZAKHSTAN / RUSSIA• KOSOVO / MONTENEGRO• KOSOVO / SERBIA• LAOS / VIETNAM• LATVIA / LITHUANIA• MEXICO / UNITED STATES• MONTENEGRO / SERBIA• MOROCCO / SPAIN• POLAND / RUSSIA• ROMANIA / UKRAINEVersions 11.0 and 11.1 were updates to boundary lines. Like this version, they also contained topology fixes, land boundary terminus refinements, and tripoint adjustments. Version 11.2 corrected a few errors in the attribute data and ensured that CC1 and CC2 attributes are in alignment with an updated version of the Geopolitical Entities, Names, and Codes (GENC) Standard, specifically Edition 3 Update 17.LayersLarge_Scale_International_BoundariesTerms of

The dataset contains locations and attributes of GSA owned or leased buildings, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. A database provided by GSA identified Federal locations and DC GIS staff geo-processed the data.

The North Carolina state and local government metadata profile as adopted by the NC Geographic Information Coordinating Council. The document and other information can be found at: https://it.nc.gov/documents/files/gicc-smac-state-local-gov-metadata-profile.

A listing of web services published from the authoritative East Baton Rouge Parish Geographic Information System (EBRGIS) data repository. Services are offered in Esri REST, and the Open Geospatial Consortium (OGC) Web Mapping Service (WMS) or Web Feature Service (WFS) formats.

Landmarks and Government BuildingsThis feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Geological Survey, displays Cemeteries, Post Offices, City/Town Halls, Courthouses, State Capitols, State Supreme Courts, The White House, U.S. Capitol, U.S. Supreme Court, Historic Sites/Points of Interest, and National Symbols/Monuments in the U.S. Per the USGS, "Structures data are designed to be used in general mapping and in the analysis of structure related activities using geographic information system technology. The National Map structures data is commonly combined with other data themes, such as boundaries, elevation, hydrography, and transportation, to produce general reference base maps. The types of structures collected are largely determined by the needs of disaster planning and emergency response, and homeland security organizations."Supreme Court of WyomingData currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (Landmarks & Government Buildings) and will support mapping, analysis, data exports and OGC API – Feature access.NGDAID: 135 (USGS National Structures Dataset - USGS National Map Downloadable Data Collection)OGC API Features Link: (Landmark Structures - OGC Features) copy this link to embed it in OGC Compliant viewersFor more information, please visit: The National MapFor feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Real Property Theme Community. Per the Federal Geospatial Data Committee (FGDC), Real Property is defined as "the spatial representation (location) of real property entities, typically consisting of one or more of the following: unimproved land, a building, a structure, site improvements and the underlying land. Complex real property entities (that is "facilities") are used for a broad spectrum of functions or missions. This theme focuses on spatial representation of real property assets only and does not seek to describe special purpose functions of real property such as those found in the Cultural Resources, Transportation, or Utilities themes."For other NGDA Content: Esri Federal Datasets

1. US Census Bureau Cartographic Boundary File of county boundaries for each state in the Unites States.

From the US Census Bureau: "The cartographic boundary files are simplified representations of selected geographic areas from the Census Bureau’s MAF/TIGER geographic database. These boundary files are specifically designed for small scale thematic mapping."

The Government Information Construction Service market is experiencing robust growth, driven by increasing government initiatives to modernize infrastructure, enhance citizen services, and improve data management capabilities. The market's expansion is fueled by a rising need for efficient and secure data handling, particularly in the context of smart city development and the increasing adoption of cloud-based solutions. This shift towards cloud-based services offers scalability, cost-effectiveness, and improved accessibility, surpassing traditional on-premises systems. While the initial investment for cloud migration can be substantial, the long-term benefits in terms of reduced maintenance costs and enhanced agility are compelling government agencies to embrace this technology. Furthermore, the growing adoption of data analytics and artificial intelligence (AI) within government operations is further fueling market growth, enabling better decision-making and enhanced service delivery. However, challenges remain, including concerns about data security, interoperability issues across different systems, and the need for skilled professionals to manage and maintain these complex systems. Regional variations exist within the market, with North America and Europe currently holding the largest market share, due to advanced digital infrastructure and high government spending on IT initiatives. However, Asia-Pacific is emerging as a region with significant growth potential, driven by substantial investments in digital transformation across various governments within the region. The market is segmented by application (city and rural) and deployment type (cloud-based and on-premises). Cloud-based solutions are witnessing rapid adoption, while on-premises deployments remain relevant, particularly in sectors with stringent security requirements. Key players like IBM, Microsoft, SAP, Oracle, and Accenture are actively involved in providing solutions, fostering competition and innovation within the sector. The forecast period (2025-2033) anticipates sustained growth, propelled by continued digital transformation efforts and the increasing importance of data-driven governance. Let's assume a 2025 market size of $15 billion, with a CAGR of 12% for the forecast period. This implies a substantial market expansion by 2033.

The global Government Information Construction Service market is experiencing robust growth, driven by increasing government investments in digital infrastructure, the rising adoption of cloud-based solutions for enhanced data security and accessibility, and the growing need for efficient and streamlined information management systems. The market's expansion is further fueled by the imperative to improve citizen services through digital channels and the ongoing development of smart city initiatives. While on-premises solutions still hold a significant share, the cloud-based segment is witnessing accelerated growth, projected to dominate the market in the coming years due to its scalability, cost-effectiveness, and enhanced accessibility. Regional variations exist, with North America and Europe currently leading the market due to advanced technological infrastructure and high government spending on digital transformation projects. However, Asia-Pacific is poised for substantial growth, driven by rapid urbanization and increasing government initiatives focused on digitalization and e-governance. Challenges include data security concerns, the need for robust cybersecurity measures, and the complexities associated with integrating legacy systems with new cloud-based solutions. This requires significant investment in training and skilled personnel to manage and maintain these systems effectively. The market is highly competitive, with established players like IBM, Microsoft, and SAP competing with specialized service providers and consulting firms such as Accenture and Deloitte. The forecast period (2025-2033) anticipates continued expansion, propelled by ongoing technological advancements and increasing government focus on data-driven decision-making. The shift towards advanced analytics and artificial intelligence (AI) in government operations is another key growth driver, enabling more efficient resource allocation, improved public services, and better citizen engagement. Furthermore, the increasing adoption of big data technologies and the Internet of Things (IoT) within government infrastructure will further drive the demand for robust information construction services. However, potential restraints include budgetary constraints in some regions, concerns regarding data privacy and compliance, and the need for seamless interoperability across different government agencies and systems. The market will witness a dynamic landscape with ongoing mergers and acquisitions, strategic partnerships, and the emergence of innovative solutions catering to specific government needs. Competitive differentiation will increasingly rely on the ability to provide secure, scalable, and user-friendly solutions that address the evolving challenges of public sector information management.

Hospitals. This dataset contains points representing hospital locations, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. Hospital locations were identified from public records and heads-up digitized from the snapbase.

District addresses for the District Land. The dataset contains of addresses for the District land (Owned, Operated, and Maintained), created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. Databases researched by the DC Office of the Chief Technology Officer (OCTO) identified DC Agency locations and DC GIS staff geo-processed the data.

The COVID-19 Guidance Questionnaire The COVID-19 Guidance Questionnaire is published on Government website. The opinion he provides has no medical value: its goal is to direct the respondent according to his or her health and symptoms towards the right behavior to adopt. The algorithm used to propose guidance is in line with documentation published by the Ministry of Solidarity and Health, which reference also other solutions that comply with it. ### Data from the COVID-19 Guidance Questionnaire This data is published in open data to inform about the number of times the questionnaire has been completed to the end as well as the guidance messages sent. Data are grouped by week, department and age group. For each week/department/age class are indicated the number of responses obtained, the number of referrals to the UAS, the number of referrals to a consultation, and the number of messages indicating that the respondent should stay at home and monitor their health. The published ‘csv’ file will be updated weekly by adding the new data. The questionnaire was offline on 27 January 2021, so data runs until 26 January 2021.

The dataset contains locations and attributes of Post Offices, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. Information provided by the United States Postal Service (USPS) and DC GIS staff geo-processed the data.

Minnesota interpretation of the boundaries of the federal recognized tribes within Minnesota.

Check other metadata records in this package for more information on Tribal Government Information.


Link to ESRI Feature Service:

Tribal Government in Minnesota: Tribal Government

Analysis of ‘2019 CT Data Catalog (GIS)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/168eaac6-5f52-4015-be99-93031db2fd0d on 26 January 2022.

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

Catalog of high value data inventories produced by Connecticut executive branch agencies and compiled by the Office of Policy and Management, updated in 2019. This catalog contains information on high value GIS data only. A catalog of high value non-GIS data may be found at the following link: https://data.ct.gov/Government/2019-CT-Data-Catalog-Non-GIS-/f6rf-n3ke

As required by Public Act 18-175, executive branch agencies must annually conduct a high value data inventory to capture information about the high value data that they collect.

High value data is defined as any data that the department head determines (A) is critical to the operation of an executive branch agency; (B) can increase executive branch agency accountability and responsiveness; (C) can improve public knowledge of the executive branch agency and its operations; (D) can further the core mission of the executive branch agency; (E) can create economic opportunity; (F) is frequently requested by the public; (G) responds to a need and demand as identified by the agency through public consultation; or (H) is used to satisfy any legislative or other reporting requirements.

This dataset was last updated 2/3/2020 and will continue to be updated as high value data inventories are submitted to OPM.

The 2018 high value data inventories for Non-GIS and GIS data can be found at the following links: CT Data Catalog (Non GIS): https://data.ct.gov/Government/CT-Data-Catalog-Non-GIS-/ghmx-93jn/ CT Data Catalog (GIS): https://data.ct.gov/Government/CT-Data-Catalog-GIS-/p7we-na27 Less

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

Government Facilities in Frederick County, Maryland

[Metadata] Description: Detailed Government Landownership in the State of Hawaii as of 2022: County, Federal, State, and State DHHL Lands (by TMK parcel)

This dataset includes United States government facilities located within Montgomery County. It was developed and is maintained by TEBS-GIS. This dataset satisfies County basemap accuracy requirements (1:2400) and is included in the Places of Interest Guide. This data is used both by Government and the public. The Places of Interest Guide can be used to find a Place of Interest within Montgomery County, Maryland by address, by title, by place name or city, or by category. Once you've located the place of interest, then you can generate travel directions, time estimates, maps and distances.

The dataset contains locations and attributes of Hotels, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. A database provided by the DC Taxi Commission (DCTC) and research at various commercial websites identified Hotels and DC GIS staff geo-processed the data.

Various telecommunication datasets such as cellphone towers and service areas, land mobile station locations, AM, FM, and TV communication can be downloaded on an FCC page. Additionally, data files can be individually downloaded from the FCC Universal Licensing System data site. This data resource is intended to guide users toward the authoritative data source and to demonstrate at least one translation of that data into a spatial format.

The metadata for this translated dataset is here:

Antenna Structure Registration: antenna_structure_registration_mn.html

In addition, the Department of Homeland Security's Homeland Infrastructure Foundation - Level Data (HIFLD) program has an "Open Data" site, which includes a nationwide dataset on Cellular Towers derived from the FCC Universal Licensing System Database: https://hifld-geoplatform.opendata.arcgis.com/datasets/cellular-towers