100+ datasets found
  1. CrowdMag Visualization Web Map

    • noaa.hub.arcgis.com
    Updated May 15, 2023
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    NOAA GeoPlatform (2023). CrowdMag Visualization Web Map [Dataset]. https://noaa.hub.arcgis.com/maps/f8e24dd400c94d4e8275417f2e8a2070
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    Dataset updated
    May 15, 2023
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Authors
    NOAA GeoPlatform
    Area covered
    Description

    This web map is a component of the CrowdMag Visualization App.NOAA's CrowdMag is a crowdsourced data collection project that uses a mobile app to collect geomagnetic data from the magnetometers that modern smartphones use as part of their navigation systems. NCEI collects these data from citizen scientists around the world and provides quality control services before making them available through a series of aggregated maps and charts. These data have the potential to provide a high resolution alternative to geomagnetic satellite data, as well as near real-time information about changes in the magnetic field.This map shows data collected from phones around the world! Displayed are the Crowdsourced magnetic data within a tolerance level of prediction by World Magnetic Model. We have added some uncertainty to each data point shown to ensure the privacy of our contributors. The data points are grouped together (or "aggregated") into small areas , and we display the median data value across all the readings for each point.

    This map is updated every day. Layers are available for Median Intensity, Median Horizontal Component (Y), and Median Vertical Component (Z).
    
    
    Use the time slider to select the date range. Select the different layers under the "Crowdmag Observations" menu. View a color scale using the legend tool. Zoom to your location using the "Find my Location" tool. Click or tap on a data point to view a popup containing more information.
    
  2. d

    Data from: California State Waters Map Series--Offshore of Santa Cruz Web...

    • datasets.ai
    • data.usgs.gov
    • +2more
    55
    Updated Sep 21, 2024
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    Department of the Interior (2024). California State Waters Map Series--Offshore of Santa Cruz Web Services [Dataset]. https://datasets.ai/datasets/california-state-waters-map-series-offshore-of-santa-cruz-web-services
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    55Available download formats
    Dataset updated
    Sep 21, 2024
    Dataset authored and provided by
    Department of the Interior
    Area covered
    Santa Cruz, California
    Description

    In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Santa Cruz map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Santa Cruz map area data layers. Data layers are symbolized as shown on the associated map sheets.

  3. D

    Data Asset Map System Report

    • marketreportanalytics.com
    doc, pdf, ppt
    Updated Apr 3, 2025
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    Market Report Analytics (2025). Data Asset Map System Report [Dataset]. https://www.marketreportanalytics.com/reports/data-asset-map-system-57042
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    ppt, pdf, docAvailable download formats
    Dataset updated
    Apr 3, 2025
    Dataset authored and provided by
    Market Report Analytics
    License

    https://www.marketreportanalytics.com/privacy-policyhttps://www.marketreportanalytics.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The Data Asset Map System market is experiencing robust growth, driven by the increasing need for organizations to gain a comprehensive understanding of their data assets. This allows for better data governance, improved data quality, and more efficient utilization of data for informed decision-making. The market is segmented by application (Data Governance and Intelligent Analytics Engine) and deployment type (Cloud-based and Local Deployment). The cloud-based segment is witnessing faster adoption due to its scalability, cost-effectiveness, and ease of access. Intelligent analytics engines are becoming increasingly important as organizations seek to derive actionable insights from their data assets, driving demand for sophisticated mapping systems. Key players in the market include Primeton, Bynder, and WoodWing, along with several other prominent vendors. The market's growth is fueled by the rising volume and complexity of data, coupled with stricter data regulations and the growing adoption of digital transformation initiatives. The North American market currently holds a significant share due to the region's advanced technological infrastructure and high adoption rates, followed by Europe and Asia Pacific. The market's expansion is projected to continue at a healthy CAGR (let's assume a conservative 15% based on typical growth rates in the data management sector) throughout the forecast period (2025-2033). However, challenges remain, including the initial investment costs associated with implementing such systems and the need for skilled professionals to manage and interpret the generated data maps. Despite these restraints, the long-term outlook for the Data Asset Map System market remains positive, driven by ongoing technological advancements and the increasing strategic importance of data within organizations. This includes the development of more user-friendly interfaces and integration with existing business intelligence tools, making the systems more accessible and valuable to a wider range of businesses.

  4. h

    ARCHITRAVE [map visualization : data & software]

    • heidata.uni-heidelberg.de
    application/gzip, pdf
    Updated Oct 22, 2021
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    Hendrik Ziegler; Hendrik Ziegler; Alexandra Pioch; Alexandra Pioch (2021). ARCHITRAVE [map visualization : data & software] [Dataset]. http://doi.org/10.11588/DATA/AT1QUR
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    pdf(241144), application/gzip(914689)Available download formats
    Dataset updated
    Oct 22, 2021
    Dataset provided by
    heiDATA
    Authors
    Hendrik Ziegler; Hendrik Ziegler; Alexandra Pioch; Alexandra Pioch
    License

    https://heidata.uni-heidelberg.de/api/datasets/:persistentId/versions/2.0/customlicense?persistentId=doi:10.11588/DATA/AT1QURhttps://heidata.uni-heidelberg.de/api/datasets/:persistentId/versions/2.0/customlicense?persistentId=doi:10.11588/DATA/AT1QUR

    Time period covered
    1685 - 1723
    Area covered
    Italy, Versailles, France, Netherlands, Paris, France, Poland, Germany, Belgium, Spain, France
    Dataset funded by
    DFG-ANR
    Description

    The dataset includes cartographic visualization data and software designed, implemented, and published for the ARCHITRAVE research project website. The research focused on the edition, executed in German and French, of six travelogues by German travelers of the Baroque period who visited Paris and Versailles. The edited texts are published in the Textgrid repository. For all further information on the content and objectives of the research, please refer to the website (https://architrave.eu/) and given literature. Three visualizations were created for the website: the travel stops of five of the travelers on their way to Paris and Versailles the sites in Europe mentioned in the six travelogues the sites in Paris described by the six travelers The visualizations were implemented with Leaflet.js. The dataset contains scripts for data crunching processed geodata scripts for leaflet.js License README

  5. I

    Interactive Map Creation Tools Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated Jun 28, 2025
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    Data Insights Market (2025). Interactive Map Creation Tools Report [Dataset]. https://www.datainsightsmarket.com/reports/interactive-map-creation-tools-1418201
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    pdf, doc, pptAvailable download formats
    Dataset updated
    Jun 28, 2025
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The interactive map creation tools market is experiencing robust growth, driven by increasing demand for visually engaging data representation across diverse sectors. The market, estimated at $2.5 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $7.8 billion by 2033. This expansion is fueled by several key factors. The rising adoption of location-based services (LBS) and geographic information systems (GIS) across industries like real estate, tourism, logistics, and urban planning is a major catalyst. Businesses are increasingly leveraging interactive maps to enhance customer engagement, improve operational efficiency, and gain valuable insights from geospatial data. Furthermore, advancements in mapping technologies, including the integration of AI and machine learning for improved data analysis and visualization, are contributing to market growth. The accessibility of user-friendly tools, coupled with the decreasing cost of cloud-based solutions, is also making interactive map creation more accessible to a wider range of users, from individuals to large corporations. However, the market also faces certain challenges. Data security and privacy concerns surrounding the use of location data are paramount. The need for specialized skills and expertise to effectively utilize advanced mapping technologies may also hinder broader adoption, particularly among smaller businesses. Competition among established players like Mapbox, ArcGIS StoryMaps, and Google, alongside emerging innovative solutions, necessitates constant innovation and differentiation. Nevertheless, the overall market outlook remains positive, with continued technological advancements and rising demand for data visualization expected to propel growth in the coming years. Specific market segmentation data, while unavailable, can be reasonably inferred from existing market trends, suggesting a strong dominance of enterprise-grade solutions, but with substantial growth expected from simpler, more user-friendly tools designed for individuals and small businesses.

  6. a

    Multibeam Sonar Data Visualization Map

    • noaa.hub.arcgis.com
    Updated Mar 15, 2022
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    NOAA GeoPlatform (2022). Multibeam Sonar Data Visualization Map [Dataset]. https://noaa.hub.arcgis.com/maps/6795496737cf451d8fa4d5306b60889e
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    Dataset updated
    Mar 15, 2022
    Dataset authored and provided by
    NOAA GeoPlatform
    Area covered
    Description

    This map contains multibeam sonar survey data collected during the 2021 field project. This file supports the New Technology and the Search for Historic Shipwrecks StoryMap created by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) and Office of National Marine Sanctuaries (ONMS). The StoryMap can be viewed here. The StoryMap was funded through NOAA's Office of Ocean Exploration and Research. More information on the project can be found here. All project files are stored in the NOAA National Centers for Environmental Information.

  7. H

    Mapping the Milky Way, from the Inside Out, in Color

    • dataverse.harvard.edu
    Updated Jan 23, 2020
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    Harvard Dataverse (2020). Mapping the Milky Way, from the Inside Out, in Color [Dataset]. http://doi.org/10.7910/DVN/7IO69A
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    pdf(31350987), application/x-iwork-keynote-sffkey(753864503)Available download formats
    Dataset updated
    Jan 23, 2020
    Dataset provided by
    Harvard Dataverse
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Presentation Date: Friday, March 15, 2019. Location: Barnstable, MA. Abstract: A presentation to a crowd of Barnstable High "AstroJunkies," about how we use physics, statistics, and visualizations to turn information from large, public, astronomical data sets, across many wavelengths into a better understanding of the structure of the Milky Way.

  8. d

    Development of Interactive Data Visualization Tool for the Predictive...

    • search.dataone.org
    • borealisdata.ca
    Updated Dec 28, 2023
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    Chan, Wai Chung Wilson (2023). Development of Interactive Data Visualization Tool for the Predictive Ecosystem Mapping Project [Dataset]. http://doi.org/10.5683/SP3/7RVB70
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    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Borealis
    Authors
    Chan, Wai Chung Wilson
    Description

    Biogeoclimatic Ecosystem Classification (BEC) system is the ecosystem classification adopted in the forest management within British Columbia based on vegetation, soil, and climate characteristics whereas Site Series is the smallest unit of the system. The Ministry of Forests, Lands, Natural Resource Operations and Rural Development held under the Government of British Columbia (“the Ministry”) developed a web-based tool known as BEC Map for maintaining and sharing the information of the BEC system, but the Site Series information was not included in the tool due to its quantity and complexity. In order to allow users to explore and interact with the information, this project aimed to develop a web-based tool with high data quality and flexibility to users for the Site Series classes using the “Shiny” and “Leaflet” packages in R. The project started with data classification and pre-processing of the raster images and attribute tables through identification of client requirements, spatial database design and data cleaning. After data transformation was conducted, spatial relationships among these data were developed for code development. The code development included the setting-up of web map and interactive tools for facilitating user friendliness and flexibility. The codes were further tested and enhanced to meet the requirements of the Ministry. The web-based tool provided an efficient and effective platform to present the complicated Site Series features with the use of Web Mapping System (WMS) in map rendering. Four interactive tools were developed to allow users to examine and interact with the information. The study also found that the mode filter performed well in data preservation and noise minimization but suffered from long processing time and creation of tiny sliver polygons.

  9. D

    Data from: The Categorical Data Map - Replication Data

    • darus.uni-stuttgart.de
    Updated Jan 26, 2024
    + more versions
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    Frederik L. Dennig; Lucas Joos; Patrick Paetzold; Daniela Blumberg; Oliver Deussen; Daniel Keim; Maximilian T. Fischer (2024). The Categorical Data Map - Replication Data [Dataset]. http://doi.org/10.18419/DARUS-3372
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 26, 2024
    Dataset provided by
    DaRUS
    Authors
    Frederik L. Dennig; Lucas Joos; Patrick Paetzold; Daniela Blumberg; Oliver Deussen; Daniel Keim; Maximilian T. Fischer
    License

    https://darus.uni-stuttgart.de/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.18419/DARUS-3372https://darus.uni-stuttgart.de/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.18419/DARUS-3372

    Dataset funded by
    DFG
    Description

    Source code and datasets used for our experiments are shared for replication purposes along our publication "The Categorical Data Map". We describe each of the six datasets individually on a per-file basis. All datasets are purely nominal datasets.

  10. I

    Interactive Map Creation Tools Report

    • marketreportanalytics.com
    doc, pdf, ppt
    Updated Apr 3, 2025
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    Market Report Analytics (2025). Interactive Map Creation Tools Report [Dataset]. https://www.marketreportanalytics.com/reports/interactive-map-creation-tools-55534
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    doc, pdf, pptAvailable download formats
    Dataset updated
    Apr 3, 2025
    Dataset authored and provided by
    Market Report Analytics
    License

    https://www.marketreportanalytics.com/privacy-policyhttps://www.marketreportanalytics.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The interactive map creation tools market is experiencing robust growth, driven by increasing demand for visually engaging data representation across diverse sectors. The market's value is estimated at $2 billion in 2025, exhibiting a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This growth is fueled by several factors, including the rising adoption of location-based services, the proliferation of readily available geographic data, and the growing need for effective data visualization in business intelligence and marketing. The individual user segment currently holds a significant share, but corporate adoption is rapidly expanding, propelled by the need for sophisticated map-based analytics and internal communication. Furthermore, the paid use segment is anticipated to grow more quickly than the free use segment, reflecting the willingness of businesses and organizations to invest in advanced features and functionalities. This trend is further amplified by the increasing integration of interactive maps into various platforms, such as business intelligence dashboards and website content. Geographic expansion is also a significant growth driver. North America and Europe currently dominate the market, but the Asia-Pacific region is showing significant promise due to rapid technological advancements and increasing internet penetration. Competitive pressures remain high, with established players such as Google, Mapbox, and ArcGIS StoryMaps vying for market share alongside innovative startups offering specialized solutions. The market's restraints are primarily focused on the complexities of data integration and the technical expertise required for effective map creation. However, ongoing developments in user-friendly interfaces and readily available data integration tools are mitigating these challenges. The future of the interactive map creation tools market promises even greater innovation, fueled by developments in augmented reality (AR), virtual reality (VR), and 3D visualization technologies. We expect to see the emergence of more sophisticated tools catering to niche requirements, further driving market segmentation and specialization. Continued investment in research and development will also play a crucial role in pushing the boundaries of what's possible with interactive map creation. The market presents opportunities for companies to develop tools which combine data analytics and interactive map design.

  11. Digital Geologic-GIS Map of San Miguel Island, California (NPS, GRD, GRI,...

    • catalog.data.gov
    Updated Jun 4, 2024
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    National Park Service (2024). Digital Geologic-GIS Map of San Miguel Island, California (NPS, GRD, GRI, CHIS, SMIS digital map) adapted from a American Association of Petroleum Geologists Field Trip Guidebook map by Weaver and Doerner (1969) [Dataset]. https://catalog.data.gov/dataset/digital-geologic-gis-map-of-san-miguel-island-california-nps-grd-gri-chis-smis-digital-map
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    Dataset updated
    Jun 4, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    San Miguel Island, California
    Description

    The Digital Geologic-GIS Map of San Miguel Island, California 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 (smis_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (smis_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 (smis_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. 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.) this file (chis_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (chis_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 (smis_geology_metadata_faq.pdf). Please read the chis_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. 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: American Association of Petroleum Geologists. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (smis_geology_metadata.txt or smis_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 Google Earth, 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).

  12. B

    Business Mapping Software Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated May 5, 2025
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    Data Insights Market (2025). Business Mapping Software Report [Dataset]. https://www.datainsightsmarket.com/reports/business-mapping-software-1969709
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    ppt, pdf, docAvailable download formats
    Dataset updated
    May 5, 2025
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The global Business Mapping Software market is experiencing robust growth, driven by the increasing need for data visualization and spatial analysis across diverse sectors. The market, estimated at $15 billion in 2025, is projected to achieve a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching approximately $45 billion by 2033. This expansion is fueled by several key factors. The escalating adoption of cloud-based solutions offers scalability and cost-effectiveness, attracting businesses of all sizes. Furthermore, the growing demand for location intelligence in industries such as healthcare (optimizing resource allocation), automotive (supply chain management), and finance (risk assessment) significantly contributes to market growth. The integration of advanced analytics and AI capabilities within business mapping software further enhances its value proposition, enabling better decision-making and strategic planning. While data security concerns and the complexity of implementing such solutions pose some restraints, the overall market outlook remains positive, particularly with the rising adoption of GIS (Geographic Information System) technologies and the increasing availability of high-quality geospatial data. The market segmentation reveals significant opportunities across various applications and deployment types. The healthcare sector is anticipated to be a major driver, followed closely by automotive and financial services. Cloud-based solutions are experiencing faster growth compared to on-premise deployments due to their flexibility and accessibility. Geographically, North America currently holds a substantial market share, benefiting from technological advancements and early adoption. However, the Asia-Pacific region is expected to witness rapid growth in the coming years, fueled by increasing digitalization and infrastructure development in countries like China and India. Key players in the market, including Caliper, Microsoft, IBM, and others, are actively engaged in innovation and strategic partnerships to consolidate their market positions and capitalize on emerging opportunities. This competitive landscape is further characterized by the emergence of specialized solutions catering to niche industry needs.

  13. e

    ARCHITRAVE [map visualization : data & software] - Dataset - B2FIND

    • b2find.eudat.eu
    Updated Jul 30, 2025
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    (2025). ARCHITRAVE [map visualization : data & software] - Dataset - B2FIND [Dataset]. https://b2find.eudat.eu/dataset/6d6dc9a3-4144-5fca-b68f-8fa9de27d2e3
    Explore at:
    Dataset updated
    Jul 30, 2025
    Description

    The dataset includes cartographic visualization data and software designed, implemented, and published for the ARCHITRAVE research project website. The research focused on the edition, executed in German and French, of six travelogues by German travelers of the Baroque period who visited Paris and Versailles. The edited texts are published in the Textgrid repository. For all further information on the content and objectives of the research, please refer to the website (https://architrave.eu/) and given literature. Three visualizations were created for the website:

  14. d

    Data from: California State Waters Map Series--Offshore of Tomales Point Web...

    • datasets.ai
    • data.usgs.gov
    • +5more
    55
    Updated Sep 10, 2024
    + more versions
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    Department of the Interior (2024). California State Waters Map Series--Offshore of Tomales Point Web Services [Dataset]. https://datasets.ai/datasets/california-state-waters-map-series-offshore-of-tomales-point-web-services
    Explore at:
    55Available download formats
    Dataset updated
    Sep 10, 2024
    Dataset authored and provided by
    Department of the Interior
    Area covered
    California
    Description

    In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Tomales Point map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Tomales Point map area data layers. Data layers are symbolized as shown on the associated map sheets.

  15. f

    MOESM1 of GrapHi-C: graph-based visualization of Hi-C datasets

    • springernature.figshare.com
    text/x-perl
    Updated Jun 4, 2023
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    Kimberly MacKay; Anthony Kusalik; Christopher Eskiw (2023). MOESM1 of GrapHi-C: graph-based visualization of Hi-C datasets [Dataset]. http://doi.org/10.6084/m9.figshare.6726713.v1
    Explore at:
    text/x-perlAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    figshare
    Authors
    Kimberly MacKay; Anthony Kusalik; Christopher Eskiw
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Additional file 1. Perl script used for converting a contact map into an adjacency matrix based on the graphrepresentation in Fig. 1a.

  16. D

    Data Visualization Industry Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated Mar 3, 2025
    + more versions
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    Data Insights Market (2025). Data Visualization Industry Report [Dataset]. https://www.datainsightsmarket.com/reports/data-visualization-industry-14160
    Explore at:
    doc, pdf, pptAvailable download formats
    Dataset updated
    Mar 3, 2025
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The global data visualization market, valued at $9.84 billion in 2025, is experiencing robust growth, projected to expand at a Compound Annual Growth Rate (CAGR) of 10.95% from 2025 to 2033. This expansion is fueled by several key drivers. The increasing volume and complexity of data generated across various industries necessitates effective visualization tools for insightful analysis and decision-making. Furthermore, the rising adoption of cloud-based solutions offers scalability, accessibility, and cost-effectiveness, driving market growth. Advances in artificial intelligence (AI) and machine learning (ML) are integrating seamlessly with data visualization platforms, enhancing automation and predictive capabilities, further stimulating market demand. The BFSI (Banking, Financial Services, and Insurance) sector, along with IT and Telecommunications, are major adopters, leveraging data visualization for risk management, fraud detection, customer relationship management, and network optimization. However, challenges remain, including the need for skilled professionals to effectively utilize these tools and concerns regarding data security and privacy. The market segmentation reveals a strong presence of executive management and marketing departments across organizations, highlighting the strategic importance of data visualization in business operations. The market's competitive landscape is characterized by established players like SAS Institute, IBM, Microsoft, and Salesforce (Tableau), along with emerging innovative companies. This competition fosters innovation and drives down costs, making data visualization solutions more accessible to a broader range of businesses and organizations. Regional variations in market penetration are expected, with North America and Europe currently holding significant shares, but Asia Pacific is poised for substantial growth, driven by rapid digitalization and technological advancements in the region. The on-premise deployment mode still holds a considerable market share, though the cloud/on-demand segment is experiencing faster growth due to its inherent advantages. The ongoing trend towards self-service business intelligence (BI) tools is empowering end-users to access and analyze data independently, increasing the overall market demand for user-friendly and intuitive data visualization platforms. Future growth will depend on continued technological advancements, expanding applications across diverse industries, and addressing the existing challenges related to data skills gaps and security concerns. This report provides a comprehensive analysis of the Data Visualization Market, projecting robust growth from $XX Billion in 2025 to $YY Billion by 2033. It covers the period from 2019 to 2033, with a focus on the forecast period 2025-2033 and a base year of 2025. This in-depth study examines key market segments, competitive landscapes, and emerging trends influencing this rapidly evolving industry. The report is designed for executives, investors, and market analysts seeking actionable insights into the future of data visualization. Recent developments include: September 2022: KPI 360, an AI-driven solution that uses real-time data monitoring and prediction to assist manufacturing organizations in seeing various operational data sources through a single, comprehensive industrial intelligence dashboard that sets up in hours, was recently unveiled by SymphonyAI Industrial., January 2022: The most recent version of the IVAAP platform for ubiquitous subsurface visualization and analytics applications was released by INT, a top supplier of data visualization software. IVAAP allows exploring, visualizing, and computing energy data by providing full OSDU Data Platform compatibility. With the new edition, IVAAP's map-based search, data discovery, and data selection are expanded to include 3D seismic volume intersection, 2D seismic overlays, reservoir, and base map widgets for cloud-based visualization of all forms of energy data.. Key drivers for this market are: Cloud Deployment of Data Visualization Solutions, Increasing Need for Quick Decision Making. Potential restraints include: Lack of Tech Savvy and Skilled Workforce/Inability. Notable trends are: Retail Segment to Witness Significant Growth.

  17. d

    Zoning Map in 3D

    • catalog.data.gov
    • opendata.dc.gov
    Updated Feb 5, 2025
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    City of Washington, DC (2025). Zoning Map in 3D [Dataset]. https://catalog.data.gov/dataset/zoning-map-in-3d
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    Dataset updated
    Feb 5, 2025
    Dataset provided by
    City of Washington, DC
    Description

    The DC Office of Zoning (OZ) proudly announces an expansion of its online mapping services with the release of the DCOZ 3D Zoning Map. This new mapping application builds off existing DC Open Datasets and new OZ Zoning data to visualize the District in 3D, providing greater context for proposed development projects and helping enhance Board of Zoning Adjustment and Zoning Commission decisions throughout the District. The 3D Zoning Map was developed to enhance District resident’s understanding, knowledge, and participation in Zoning matters, and help increase transparency in the Zoning process.

  18. B

    Business Mapping Software Report

    • archivemarketresearch.com
    doc, pdf, ppt
    Updated Mar 14, 2025
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    Archive Market Research (2025). Business Mapping Software Report [Dataset]. https://www.archivemarketresearch.com/reports/business-mapping-software-56923
    Explore at:
    doc, pdf, pptAvailable download formats
    Dataset updated
    Mar 14, 2025
    Dataset authored and provided by
    Archive Market Research
    License

    https://www.archivemarketresearch.com/privacy-policyhttps://www.archivemarketresearch.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The global Business Mapping Software market is experiencing robust growth, driven by the increasing adoption of cloud-based solutions and the expanding need for data visualization across diverse industries. Our analysis projects a market size of $15 billion in 2025, expanding at a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033. This significant growth is fueled by several key factors. The rise of digital transformation initiatives across sectors like healthcare, finance, and manufacturing is creating a heightened demand for efficient data visualization tools. Businesses are increasingly relying on business mapping software to understand geographical patterns, optimize supply chains, analyze market trends, and improve operational efficiency. Furthermore, advancements in Artificial Intelligence (AI) and Machine Learning (ML) are enhancing the capabilities of these platforms, making them more insightful and user-friendly. The prevalence of cloud-based solutions offers scalability, accessibility, and cost-effectiveness, contributing significantly to market expansion. While data security concerns and the need for specialized training can act as restraints, the overall market outlook remains highly positive. The market segmentation highlights the strong demand across various application sectors. Healthcare is a particularly lucrative segment, leveraging the software for efficient resource allocation, patient management, and epidemiological studies. The automotive industry uses it for supply chain optimization and logistics management. Similarly, banking, financial services, and manufacturing benefit from improved risk assessment, market analysis, and operational optimization. The competitive landscape is dynamic, featuring both established tech giants like Microsoft and IBM, and specialized providers like Caliper and eSpatial. Geographic expansion, particularly in rapidly developing economies in Asia-Pacific, presents significant growth opportunities. This suggests the market will continue its upward trajectory, driven by technological advancements, increasing digitalization across industries, and a global demand for enhanced data visualization and analysis capabilities.

  19. d

    California State Waters Map Series--Point Sur to Point Arguello Web Services...

    • catalog.data.gov
    • s.cnmilf.com
    Updated Jul 6, 2024
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    U.S. Geological Survey (2024). California State Waters Map Series--Point Sur to Point Arguello Web Services [Dataset]. https://catalog.data.gov/dataset/california-state-waters-map-series-point-sur-to-point-arguello-web-services
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Point Arguello, California
    Description

    In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Point Sur to Point Arguello map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Point Sur to Point Arguello map area data layers. Data layers are symbolized as shown on the associated map sheets.

  20. d

    Tutorial: How to use Google Data Studio and ArcGIS Online to create an...

    • search.dataone.org
    • hydroshare.org
    • +1more
    Updated Apr 15, 2022
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    Sarah Beganskas (2022). Tutorial: How to use Google Data Studio and ArcGIS Online to create an interactive data portal [Dataset]. http://doi.org/10.4211/hs.9edae0ef99224e0b85303c6d45797d56
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    Dataset updated
    Apr 15, 2022
    Dataset provided by
    Hydroshare
    Authors
    Sarah Beganskas
    Description

    This tutorial will teach you how to take time-series data from many field sites and create a shareable online map, where clicking on a field location brings you to a page with interactive graph(s).

    The tutorial can be completed with a sample dataset (provided via a Google Drive link within the document) or with your own time-series data from multiple field sites.

    Part 1 covers how to make interactive graphs in Google Data Studio and Part 2 covers how to link data pages to an interactive map with ArcGIS Online. The tutorial will take 1-2 hours to complete.

    An example interactive map and data portal can be found at: https://temple.maps.arcgis.com/apps/View/index.html?appid=a259e4ec88c94ddfbf3528dc8a5d77e8

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NOAA GeoPlatform (2023). CrowdMag Visualization Web Map [Dataset]. https://noaa.hub.arcgis.com/maps/f8e24dd400c94d4e8275417f2e8a2070
Organization logo

CrowdMag Visualization Web Map

Explore at:
Dataset updated
May 15, 2023
Dataset provided by
National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
Authors
NOAA GeoPlatform
Area covered
Description

This web map is a component of the CrowdMag Visualization App.NOAA's CrowdMag is a crowdsourced data collection project that uses a mobile app to collect geomagnetic data from the magnetometers that modern smartphones use as part of their navigation systems. NCEI collects these data from citizen scientists around the world and provides quality control services before making them available through a series of aggregated maps and charts. These data have the potential to provide a high resolution alternative to geomagnetic satellite data, as well as near real-time information about changes in the magnetic field.This map shows data collected from phones around the world! Displayed are the Crowdsourced magnetic data within a tolerance level of prediction by World Magnetic Model. We have added some uncertainty to each data point shown to ensure the privacy of our contributors. The data points are grouped together (or "aggregated") into small areas , and we display the median data value across all the readings for each point.

This map is updated every day. Layers are available for Median Intensity, Median Horizontal Component (Y), and Median Vertical Component (Z).


Use the time slider to select the date range. Select the different layers under the "Crowdmag Observations" menu. View a color scale using the legend tool. Zoom to your location using the "Find my Location" tool. Click or tap on a data point to view a popup containing more information.
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