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TwitterThe Ministry for Primary Industries (MPI) generates and acquires geospatial data. To maintain trust and confidence in the accuracy of this data, and the ability to reuse MPI has developed standards for both internal staff and external contractors. At the conclusion of any project or contract involving MPI, all data created should be provided to MPI. All data supplied to MPI must be well structured and managed to a high standard. The data must be in a format compatible with ESRI software, with all datasets named logically and clearly. If a deviation is required from the data standards please contact the contract manager.
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TwitterBuilding information modeling (BIM) allows representation of detailed information regarding building elements while geographic information system (GIS) allows representation of spatial information about buildings and their surroundings. Overlapping these domains will combine their individual features and provide support to important activities such as building emergency response, construction site safety, construction supply chain management, and sustainable urban design. Interoperability through open data standards is one method of connecting software tools from BIM and GIS domains. However, no single open data standard available today can support all information from the two domains. As a result, many researchers have been working to overlap or connect different open data standards to enhance interoperability. An overview of these studies will help identify the different approaches used and determine the approach with the most potential to enhance interoperability. This paper adopted a strong definition of interoperability using information technology (IT) based standard documents. Based on this definition, previous approaches towards improving interoperability between BIM and GIS applications through open data standards were studied. The result shows previous approaches have implemented data conversion, data integration, and linked data approaches. Between these methods, linked data emerged as having the most potential to connect open data standards and expand interoperability between BIM and GIS applications because it allows information exchange without editing the original data. The paper also identifies the main challenges in implementing linked data technologies for interoperability and provides directions for future research.
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TwitterThe Oregon Framework Program encourages the development of standardized data. All statewide standards are developed through the process outlined in Oregon's Geospatial Standards Development Guidelines.
All geospatial data standards have been endorsed by Oregon's Geographic Information Council.
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TwitterThe Getting Started section is your go-to guide for figuring out how to meet the minimum metadata requirements for sharing your geospatial data. These examples are designed for use with ArcGIS software, as it is the most widely used across the agency. However, they should also serve as a framework for sharing geospatial data in any format. Having good metadata makes your data easier to find, understand, and trust, ensuring effective content sharing. The usability and accessibility of our data will ultimately be enhanced by adhering to these guidelines.CalEPA’s Minimum Metadata requirements are based on the FAIR data principles and California Open Data Policy Requirements, California Open Data Publishers Handbook.
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TwitterThe Vegetation Technical Working Group (VTWG) of the Alaska Geospatial Council developed the Minimum Standards for Field Observation of Vegetation and Related Properties Version 1.1 (August 2022) to help ensure that vegetation data collected as part of independent vegetation survey, mapping, monitoring, and classification projects can support the production of a statewide vegetation map from quantitative data and the continued development of the U.S. National Vegetation Classification.
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TwitterOverview of the Water Development GIS Standards.
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TwitterDemographic dataset of individual recipients served by City of Portland Rescue Plan projects using Homeless Management Information System (HMIS) to collect and manage data. Demographic data follows the US Department of Housing and Development (HUD) HMIS data standards.-- Additional Information: Category: ARPA Update Frequency: As Necessary-- Metadata Link: https://www.portlandmaps.com/metadata/index.cfm?&action=DisplayLayer&LayerID=60951
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TwitterThis dataset represents the cadastral maps created by the Geomatics branch in support of real property acquisitions within the Department of Water Resources. The geographic extent of each map frame was created after using all the spatial attributes available in each map to appropriately georeference it and create the extents from the outer frame of the map. The maps were digitally scanned from the original paper format that were archived after moving to the new resources building. As new maps are created by the branch for real property acquisition services, they will be georeference, attributed and updated into this dataset. The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standard version 3.6, dated September 27, 2023. DWR makes no warranties or guarantees either expressed or implied as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. Original internal source projection for this dataset was Teale Albers/NAD83. For copies of data in the original projection, please contact DWR. Comments, problems, improvements, updates, or suggestions should be forwarded to gis@water.ca.gov as available and appropriate.
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TwitterThe Digital Geologic-GIS Map of the Rhoda Quadrangle, Kentucky is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (rhod_geology.gdb), and a 2.) Open Geospatial Consortium (OGC) geopackage. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (rhod_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (rhod_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (maca_abli_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (maca_abli_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (rhod_geology_metadata_faq.pdf). Please read the maca_abli_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. QGIS software is available for free at: https://www.qgis.org/en/site/. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (rhod_geology_metadata.txt or rhod_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).
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TwitterBear River Data Model GIS Standards Training Webinar (Nov. 15, 2017)
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TwitterThe purpose of the Virginia Public Safety Answering Point (PSAP) and Emergency Service Boundary Geospatial Data Standard is to implement, as a Commonwealth ITRM Standard, the data file naming conventions, geometry, map projection system, common set of attributes, dataset type and specifications, and level of precision for the Virginia Public Safety Answering Point (PSAP) and Emergency Service Boundary Datasets, which will be the data source of record at the state level for these types of spatial features within the Commonwealth of Virginia.
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TwitterGender categories for US Department of Housing and Development (HUD) data standards. These standards apply for projects using the Homeless Management Information System (HMIS) for data collection and management. HMIS is a local information technology system used to collect client-level data and data on the provision of housing and services to individuals and families experiencing or at risk of houselessness. The Federal HUD HMIS standards preempt the City of Portland Rescue Plan Data Standards.-- Additional Information: Category: ARPA Update Frequency: As Necessary-- Metadata Link: https://www.portlandmaps.com/metadata/index.cfm?&action=DisplayLayer&LayerID=60944
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TwitterThe purpose of the Virginia Administrative Boundary Geospatial Data Standard is to implement, as a Commonwealth ITRM Standard, the data file naming conventions, geometry, map projection system, common set of attributes, dataset type and specifications, and level of precision for the Virginia Administrative Boundaries Dataset, which will be the data source of record at the state level for administrative boundary spatial features within the Commonwealth of Virginia.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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The Network Adequacy Standards data is divided out by Provider Type, Adult and Pediatric separately, so that the Time or Distance analysis can be performed with greater detail. These standards differ by County due to the County "type" which is based on the population density of the county. There are 5 county categories within California; Rural (<50 people/sq mile), Small (51-200 people/sq mile), Medium (201-599 people/sq mile), and Dense (>600 people/sq mile).
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TwitterThe Vegetation Technical Working Group (VTWG) of the Alaska Geospatial Council developed the Standards for Mapping Vegetation in Alaska Version 1.1 (August 2022) to promote consistency among independently produced local, regional, and statewide vegetation maps for Alaska.
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TwitterThe Vegetation Technical Working Group (VTWG) of the Alaska Geospatial Council developed Standards for Production of Alaska Vegetation Map Version 1.1 (August 2022) to set technical goals for the production of a vegetation map that consistently covers all of Alaska with high spatial and ecological resolution. We compared vegetation maps and mapping frameworks with statewide coverage to the standards to determine the most appropriate map to select as the implementation of a statewide map and found that the AKVEG Map is the only map or mapping framework that fulfills all VTWG goals.
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TwitterThis dataset represents a water shortage vulnerability analysis performed by DWR using Small Water System boundaries pulled from the SWRCB (State Water Resource Control Board) water system boundary layer (SABL). The water systems were then restricted to only active water systems with under 3000 connections that had SDWIS (Safe Drinking Water Information System) data. This data is from the 2024 analysis.The spatial data of these feature classes is used as units of analysis for the spatial analysis performed by DWR. These datasets are intended to be authoritative datasets of the scoring tools required from DWR according to Senate Bill 552. Please refer to the source metadata for more information on completeness.The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standard version 3.4, dated September 14, 2022. DWR makes no warranties or guarantees — either expressed or implied— as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. Comments, problems, improvements, updates, or suggestions should be forwarded to GIS@water.ca.gov.
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TwitterThis polygon feature class is a data set compiled by DWR employees in 2013 and represents the statewide Groundwater Management Plan (Plan) boundaries predating the Sustainable Groundwater Management Act (SGMA) requirements. Each polygon represents the area in which a Plan is to be implemented. The boundaries were provided to DWR by the affiliated public agency and compiled into a single statewide data set. Spatial plan boundaries were provided by agencies to DWR either via shapefiles or PDFs. PDFs were georeferenced and turned into GIS layers by DWR employees. This feature class is for legacy purposes only and will not be changed nor updated. It needs to be memorialized for spatial coverage of Groundwater Management Plans prior to SGMA and because SGMA only requires medium and high priority basins to have a Groundwater Sustainability Plan. The Plans outlined in this shapefile by medium and high priority basins are in effect until SGMA goes into effect. Some low and very low priority basins will likely use the existing plans to get funding for future basin management (since it is only voluntary for them to provide a Plan under SGMA, but they already have one in place). The data set is considered complete because of its legacy status. However, anyone using the data set will notice boundary inconsistencies, agency plan overlaps, mismatches, and other topology errors. The data set is based on boundary estimations and in the cases of medium and high priority basins will be outdated with in implementation of SGMA.The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standard version 3.1, dated September 11, 2019. This data set was not produced by DWR. Data were originally developed and supplied by each individual plan agency and compiled by DWR. DWR makes no warranties or guarantees — either expressed or implied— as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. Comments, problems, improvements, updates, or suggestions should be forwarded to GIS@water.ca.gov.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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This dataset is a compilation of ownership rights represented as parcels owned by the State of California, Department of Water Resources. The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standard version 3.6, dated September 27, 2023.DWR makes no warranties or guarantees —either expressed or implied — as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. Comments, problems, improvements or suggestions should be forwarded to gis@water.ca.gov. This version is considered current as of 5/29/2025.
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TwitterThe Ministry for Primary Industries (MPI) generates and acquires geospatial data. To maintain trust and confidence in the accuracy of this data, and the ability to reuse MPI has developed standards for both internal staff and external contractors. At the conclusion of any project or contract involving MPI, all data created should be provided to MPI. All data supplied to MPI must be well structured and managed to a high standard. The data must be in a format compatible with ESRI software, with all datasets named logically and clearly. If a deviation is required from the data standards please contact the contract manager.