Maybe Ambiguous Pronoun is a dataset similar to GAP dataset, but without binary gender constraints.

MAP-CC

🌐 Homepage | 🤗 MAP-CC | 🤗 CHC-Bench | 🤗 CT-LLM | 📖 arXiv | GitHub An open-source Chinese pretraining dataset with a scale of 800 billion tokens, offering the NLP community high-quality Chinese pretraining data.

  Disclaimer

This model, developed for academic purposes, employs rigorously compliance-checked training data to uphold the highest standards of integrity and compliance. Despite our efforts, the inherent complexities of data and the broad spectrum of… See the full description on the dataset page: https://huggingface.co/datasets/m-a-p/MAP-CC.

The USGS Topo base map service from The National Map is a combination of contours, shaded relief, woodland and urban tint, along with vector layers, such as geographic names, governmental unit boundaries, hydrography, structures, and transportation, to provide a composite topographic base map. Data sources are the National Atlas for small scales, and The National Map for medium to large scales.

The Digital Geologic-GIS Map of Mount Rainier National Park, Washington 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 (mora_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 and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (mora_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 (mora_geology.gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (mora_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 (mora_geology_metadata_faq.pdf). Please read the mora_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: http://www.google.com/earth/index.html. 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: 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 (mora_geology_metadata.txt or mora_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 1:62,500 and United States National Map Accuracy Standards features are within (horizontally) 31.8 meters or 104.2 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). The GIS data projection is NAD83, UTM Zone 10N, however, for the KML/KMZ format the data is projected upon export to WGS84 Geographic, the native coordinate system used by Google Earth.

Streetview Pothole Map Dataset

## Overview

Streetview Pothole Map Dataset is a dataset for object detection tasks - it contains Pothole annotations for 528 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

📊 Dataset Overview

The emoji-map dataset, created by omarkamali, contains text data in parquet format. It consists of 10K-100K entries, specifically 5.03k rows. The dataset is available in the train split.

  📁 Data Structure

The dataset includes two main columns: emoji and unicode_description. The emoji column contains various emoji characters, while the unicode_description column provides a textual description of each emoji.

  🔍 Sample Data

Examples from the… See the full description on the dataset page: https://huggingface.co/datasets/omarkamali/emoji-map.

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, ...

Leaflet Map

## Overview

Leaflet Map is a dataset for object detection tasks - it contains Places Maps annotations for 278 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

3D Map System Market Outlook

The global 3D map system market size was valued at approximately $4.2 billion in 2023 and is projected to reach around $11.3 billion by 2032, growing at a robust CAGR of 11.5% during the forecast period. The increasing demand for advanced mapping solutions across various sectors such as automotive, urban planning, and infrastructure development is a significant growth factor propelling this market. The adoption of 3D maps, driven by technological advancements and the need for precise spatial data, is transforming how industries manage and utilize geospatial information.

One of the primary growth factors of the 3D map system market is the burgeoning demand within the automotive industry. The rise of autonomous and connected vehicles relies heavily on high-precision 3D mapping systems to ensure safety and efficiency. As vehicles become increasingly sophisticated, the need for accurate terrain and environmental data becomes paramount, driving the integration of these systems into modern automobiles. Additionally, the evolution of smart cities and infrastructure projects around the globe has necessitated the use of 3D maps for planning and management, further fueling market growth.

The aerospace and defense sectors are also major proponents of 3D map systems, utilizing them for navigation, simulation, and mission planning. The accuracy and detailed visualization provided by these maps are indispensable in military applications, where precise terrain understanding can critically impact operations and strategy development. Furthermore, the expansion of drone technology has increased the demand for 3D mapping solutions, as these aerial vehicles increasingly rely on detailed geospatial data to perform a variety of tasks ranging from surveillance to environmental monitoring.

In urban planning, the use of 3D mapping systems has gained significant traction due to their ability to provide a comprehensive view of urban landscapes, aiding in efficient planning and decision-making. These systems enable planners to visualize and simulate different developmental scenarios, assessing their impact on the environment and city infrastructure. Such capabilities are invaluable in developing sustainable urban areas that can accommodate growing populations while minimizing ecological footprints. Moreover, as environmental concerns and regulatory pressures increase, the use of 3D maps is becoming more prevalent in infrastructure planning and development.

Regionally, North America dominates the 3D map system market, driven by technological innovation and high adoption rates across various industries. The presence of key market players and substantial investment in research and development further bolster the region's dominance. Meanwhile, the Asia Pacific is experiencing the fastest growth, attributed to rapid urbanization and infrastructure development, particularly in countries like China and India. The implementation of smart city initiatives and the expansion of automotive and defense sectors are significant factors contributing to the region's market expansion.

Component Analysis

The component segment of the 3D map system market is subdivided into software, hardware, and services, each playing a pivotal role in the overall functionality and utilization of 3D mapping technologies. Software components are at the core of the 3D map system market, offering essential functionalities for creating, editing, and managing 3D spatial data. The demand for sophisticated software solutions is rising as users seek advanced features such as real-time data processing, analytics, and augmented reality integration. These software solutions enable various applications, from navigation and simulation to geospatial data analysis, making them indispensable across multiple industries.

Hardware components include the physical devices and infrastructure required to capture, store, and process 3D mapping data. This includes GPS devices, LiDAR systems, and high-resolution cameras, which are critical for accurate data acquisition. The hardware segment is experiencing growth due to technological advances that enhance data capture accuracy and efficiency. The integration of artificial intelligence and machine learning with hardware components further improves the capability of 3D mapping systems, enabling automated data processing and real-time applications.

The services component encompasses the various support and maintenance services essential for the optimal functioning of 3D map systems. These services include system integration,

A web map used to visualize available digital parcel data for Organized Towns and Unorganized Territories throughout the state of Maine. Individual towns submit parcel data on a voluntary basis; the data are compiled by the Maine Office of GIS for dissemination by the Maine GeoLibrary, and where available, the web map also includes assessor data contained in the Parcels_ADB related table.This web map is intended for use within the Maine Geoparcel Viewer Application; it is not intended for use as a standalone web map.Within Maine, real property data is maintained by the government organization responsible for assessing and collecting property tax for a given location. Organized towns and townships maintain authoritative data for their communities and may voluntarily submit these data to the Maine GeoLibrary Parcel Project. Maine Parcels Organized Towns and Maine Parcels Organized Towns ADB are the product of these voluntary submissions. Communities provide updates to the Maine GeoLibrary on a non-regular basis, sometimes many years apart, which affects the currency of Maine GeoLibrary parcels data. Another resource for real property transaction data is the County Registry of Deeds, although organized town data should very closely match registry information, except in the case of in-process property conveyance transactions.

The Enhanced Contrast Map (World Edition) web map provides a detailed vector basemap for the world symbolized using enhanced contrast and a color-vision-deficient-safe palette. It is designed for use as part of a presentation that aims to meet the WCAG (Web Content Accessibility Guidelines) AA standard, and US Government Section 508 compliance. The base layer includes highways, major roads, minor roads, railways, water features, cities, parks, landmarks, and building footprints. The reference layer includes all labels and administrative boundary lines. Label size has been increased where possible, but not to the point where it conceals the map detail. The 'Ubuntu' font is used throughout, to be clear and legible while maintaining some character.This basemap, included in the ArcGIS Living Atlas of the World, uses the Enhanced Contrast Reference and Enhanced Contrast Base vector tile layers.The vector tile layers in this web map are built using the same data sources used for other Esri Vector Basemaps. For details on data sources contributed by the GIS community, view the map of Community Maps Basemap Contributors. Esri Vector Basemaps are updated monthly.Learn more about this basemap from the cartographic designer in Working with Enhanced Contrast basemaps to improve accessibility.Use this MapThis map is designed to be used as a basemap for overlaying other layers of information or as a stand-alone reference map. You can add layers to this web map and save as your own map. If you like, you can add this web map to a custom basemap gallery for others in your organization to use in creating web maps. If you would like to add this map as a layer in other maps you are creating, you may use the tile layer item referenced in this map.

NOAA's National Geodetic Survey (NGS) Map - Web Map is the map used by the Web Map Application. It allows users to view geodetic control across the United States and its territories. This application includes three different data sets (CORS, OPUS, Datasheets) as layers with Datasheets having 2 layers and CORS having 3 layers (2 for scale based symbology). This map provides access to control mark information including latitude, longitude, elevation and more. National Geodetic Survey Map - Web Map Application

The ArcGIS Online US Geological Survey (USGS) topographic map collection now contains over 177,000 historical quadrangle maps dating from 1882 to 2006. The USGS Historical Topographic Map Explorer app brings these maps to life through an interface that guides users through the steps for exploring the map collection:

Finding the maps of interest is simple. Users can see a footprint of the map in the map view before they decide to add it to the display, and thumbnails of the maps are shown in pop-ups on the timeline. The timeline also helps users find maps because they can zoom and pan, and maps at select scales can be turned on or off by using the legend boxes to the left of the timeline. Once maps have been added to the display, users can reorder them by dragging them. Users can also download maps as zipped GeoTIFF images. Users can also share the current state of the app through a hyperlink or social media. This ArcWatch article guides you through each of these steps: https://www.esri.com/esri-news/arcwatch/1014/envisioning-the-past.

MAP Test

## Overview

MAP Test is a dataset for object detection tasks - it contains Animal annotations for 476 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

This map is just one of the many data visualizations on the Global Midwives Hub, a digital resource with open data, maps, and mapping applications (among other things), to support advocacy for improved maternal and newborn services, supported by the International Confederation of Midwives (ICM), UNFPA, WHO, and Direct Relief.

The 3D Visualisation Map (Tile-based models) are based on the mesh model made from the oblique aerial images. The dataset covers the whole territory of Hong Kong. You can click the link below to access the 3D Visualisation Map (https://3d.map.gov.hk/).

This map feeds into a web app that allows a user to examine the known status of structures damaged by the wildfire. If a structure point does not appear on the map it may still have been impacted by the fire. Specific addresses can be searched for in the search bar. Use the imagery and topographic basemaps and photos to positively identify a structure. Photos may only be available for damaged and destroyed structures

For more information about the wildfire response efforts, visit the CAL FIRE incident page.

This part of DS 781 presents data for the bathymetric contours for several seafloor maps of the Offshore of Point Reyes map area, California. The vector data file is included in "Contours_PointReyes.zip," which is accessible from http://pubs.usgs.gov/ds/781/OffshorePointReyes/data_catalog_PointReyes.html.

10-m interval contours of the Offshore of Point Reyes map area, California, were generated from bathymetry data collected by California State University, Monterey Bay (CSUMB) and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Bathymetric contours at 10-m intervals were generated from a bathymetric surface model. The most continuous contour segments were preserved while smaller segments and isolated island polygons were excluded from the final output. Contours were smoothed via a polynomial approximation with exponential kernel (PAEK) algorithm using a tolerance value of 60 m. The contours were then clipped to the boundary of the map area. These data are not intended for navigational purposes.

Comprehensive dataset of 466 Map stores in United States as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

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 ...