The Google Maps dataset is ideal for getting extensive information on businesses anywhere in the world. Easily filter by location, business type, and other factors to get the exact data you need. The Google Maps dataset includes all major data points: timestamp, name, category, address, description, open website, phone number, open_hours, open_hours_updated, reviews_count, rating, main_image, reviews, url, lat, lon, place_id, country, and more.

The MAPS dataset is one of the most used benchmark dataset for automatic music transcription. We propose here an updated version of the ground truth MIDI files, containing, on top of the original pitch, onset and offsets, additional annotations.

The annotations include:

• Tempo curve

• Time signature

• Durations of notes in fraction of a quarter note (some of them are approximate)

• Key signature (always written as the major relative)

• Sustain pedal activation

• Separate left and right hand staff

• Text annotations from the score (tempo indications, coda...).

If you use these annotations in a published research project, please cite:
Adrien Ycart and Emmanouil Benetos. “A-MAPS: Augmented MAPS Dataset with Rhythm and Key Annotations” 19th International Society for Music Information Retrieval Conference Late Breaking and Demo Papers, September 2018, Paris, France.

More information is available at: http://c4dm.eecs.qmul.ac.uk/ycart/a-maps.html

It’s a crisp fall morning in Portland. A local barista opens her shop and pulls out her phone to check delivery routes for fresh beans. She taps the familiar red-and-white pin icon, Google Maps. Across the globe in Tokyo, a student uses Street View to navigate to his university. Meanwhile,...

The Perry-Castañeda Library Map Collection (PCL 1.306) is a general collection of more than 250,000 maps covering all areas of the world. Many of the maps are included in the University of Texas Library Catalog. More than 11,000 map images from the collection are also available online via this link. Maps were produced by the U.S. Central Intelligence Agency, unless otherwise indicated. Maps dated 1976 were taken from The Indian Ocean Atlas, published by the Central Intelligence Agency.

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.

This web map presents a vector basemap of OpenStreetMap (OSM) data hosted by Esri. Esri created this vector tile basemap from the Daylight map distribution of OSM data, which is supported by Facebook and supplemented with additional data from Microsoft. This version of the map is rendered using OSM cartography. The OSM Daylight map will be updated every month with the latest version of OSM Daylight data.OpenStreetMap is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap site:www.OpenStreetMap.org. Esri is a supporter of the OSM project and is excited to make this enhanced vector basemap available to the ArcGIS user and developer communities.

The Community Map (World Edition) web map provides a customized world basemap that is uniquely symbolized and optimized to display special areas of interest (AOIs) that have been created and edited by Community Maps contributors. These special areas of interest include landscaping features such as grass, trees, and sports amenities like tennis courts, football and baseball field lines, and more. This basemap, included in the ArcGIS Living Atlas of the World, uses the Community vector tile layer. The vector tile layer in this web map is 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.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 layer items referenced in this map.

The feature class indicates the specific types of motorized vehicles allowed on the designated routes and their seasons of use. The feature class is designed to be consistent with the MVUM (Motor Vehicle Use Map). It is compiled from the GIS Data Dictionary data and NRM Infra tabular data that the administrative units have prepared for the creation of their MVUMs. Only roads with a SYMBOL attribute value of 1, 2, 3, 4, 11, and 12 are Forest Service System roads and contain data concerning their availability for OHV (Off Highway Vehicle) use. This data is published and refreshed on a unit by unit basis as needed. Data for each individual unit must be verified and proved consistent with the published MVUMs prior to publication.The Forest Service's Natural Resource Manager (NRM) Infrastructure (Infra) is the agency standard for managing and reporting information about inventory of constructed features and land units as well as the permits sold to the general public and to partners. Metadata

The Human Geography Map (World Edition) web map provides a detailed vector basemap with a monochromatic style and content adjusted to support Human Geography information. Where possible, the map content has been adjusted so that it observes WCAG contrast criteria.This basemap, included in the ArcGIS Living Atlas of the World, uses 3 vector tile layers:Human Geography Label, a label reference layer including cities and communities, countries, administrative units, and at larger scales street names.Human Geography Detail, a detail reference layer including administrative boundaries, roads and highways, and larger bodies of water. This layer is designed to be used with a high degree of transparency so that the detail does not compete with your information. It is set at approximately 50% in this web map, but can be adjusted.Human Geography Base, a simple basemap consisting of land areas in a very light gray only.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 Introducing a Human Geography Basemap.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.

Tax Maps and other affiliated layers. The comprehensive point theme incorporates parcel ownership and address information, parcel valuation information and basic information about the land and structure(s) associated with a given tax assessment account. Data for the Parcel point theme are obtained from the State Department of Assessments and Taxation with added data from Maryland Department of Planning. The date the point was most recently published in Planning's data products MdProperty View and FINDER Quantum is contained in the mdpvdate field. The date of the most recent Assessments data linkage to MdProperty View/FINDER Quantum points is contained in the sdatdate field. Accounts deleted between those two dates are no longer represented as points. For more information on the attribute definitions, please see the MdProperty View User's Guide, available for download at https://planning.maryland.gov/Pages/OurProducts/DownloadFiles.aspx . Tax maps, also known as assessments, property or parcel maps, are a graphic representation of real property showing and defining individual property boundaries in relationship to contiguous real property. The primary purpose of these maps is to help State tax assessors locate properties for assessments and taxation purposes. The maps contained herein are NOT to be construed or used as a "legal description". It is not a survey product and not to be used for the design, modification or construction of improvements to real property or for flood plain determination. Planning does not provide any guarantee of accuracy or completeness regarding the map information. Any errors or omissions should be reported to the Maryland Department of Planning Property Mapping Unit. In no event will Planning or the State of Maryland be liable for any damages, including but not limited to loss of data, lost profits, business interruption, loss of business information or any other pecuniary loss that might arise from the use of this map or information it contains. This is a MD iMAP hosted service layer. Find more information at https://imap.maryland.gov

The dataset contains metadata records for 50,600 maps from the Sanborn Fire Insurance Maps collection and their corresponding 440,048 JPEG images. The Sanborn collection at Library of Congress includes over fifty thousand editions of fire insurance maps comprising almost seven hundred thousand individual sheets. The Library of Congress holdings represent the largest extant collection of maps produced by the Sanborn Map Company.

This dataset contains 82 annotated map samples from diverse historical city maps of Jerusalem and Paris, suitable for map text detection, recognition, and sequencing.

Organization of the data

The data in maptext_format.json is organized in the same way as in the General Data from the David Rumsey Collection from ICDAR 2024 Competition on Historical Map Text Detection, Recognition, and Linking [1].

The data is structured by image, and list of sequences (groups). The boolean attributes illegible and truncated are used to provide additional insight on the data quality.

Our interpretation of the truncated and illegible tags is the following:

• truncated refers to the case where part of a word is located outside the image crop, and is thus missing. In that case, the transcription stops at the image border, focusing only on the visible part of the word
• illegible is a subjective indication of (un)certainty in the transcription provided. Whenever possible, a best guess transcription is provided. Otherwise, the illegible letters are filled with blank spaces

The text corresponds to the diplomatic transcription, i.e. as it appears on the document. Text are transcribes with all latin characters, with cases, diacritics (e.g. ö, ḡ) and diagraphs (e.g. Œ).

Each word polygon consists of an even number of vertices arranged in clockwise order starting from the initial point to the top left. The first n/2 vertices represent the upper boundary line following the reading direction, while the second half represents the lower boundary line in the reverse direction. Here is an illustration:

Example structure

[
{
"image": "map_image_1.jpg",

# Here groups are what we call sequences.
"groups": [
{
"vertices": [[x1, y1], [x2, y2], ...],
"text": "Champs",
"illegible": "false",
"truncated": "false"
},
{
"vertices": [[x1, y1], [x2, y2], ...],
"text": "Elysées",
"illegible": "false",
"truncated": "false"
}
]
}
]


The file pandas_format.pkl contains the same data. It is only provided for convenience.

Image documents

The maps of Paris were taken from the Historical City Maps Semantic Segmentation Dataset [2]. The original documents were digitized by the Bibliothèque nationale de France (BnF), and the Bibliothèque Historique de la Ville de Paris (BHVP).

The maps of Jerusalem were curated from the collections of the National Library of Israel (NLI), and Wikimedia Commons.

Descriptive statistics

Number of words: 7528
Number of single-word sequences: 1757
Number of multi-word sequences: 1969
Statistics of multi-word sequences length:
mean: 2.93 words
std: 1.25 words
min: 2.00 words
med: 3.00 words
max: 15.00 words

Future updates

The transcribed text, corresponds to the diplomatic transcription, suitable for text recognition tasks. In future updates, we hope to complement it with an additional normalization attribute, which could extend abbreviations (e.g. "bvd." => "boulevard") and normalize transcriptions (e.g. "QVARTER" => "QUARTER").

Use and Citation

For any mention of this dataset, please cite :

@misc{paris_jerusalem_dataset_2025,
author = {Dai, Tianhao and Johnson, Kaede and Petitpierre, R{\'{e}}mi and Vaienti, Beatrice and di Lenardo, Isabella},
title = {{Paris and Jerusalem City Maps Text Dataset}},
year = {2025},
publisher = {Zenodo},
url = {https://doi.org/10.5281/zenodo.14982662}}

@article{recognizing_sequencing_2025,
author = {Zou, Mengjie and Dai, Tianhao and Petitpierre, R{\'{e}}mi and Vaienti, Beatrice and di Lenardo, Isabella},
title = {{Recognizing and Sequencing Multi-word Texts in Maps Using an Attentive Pointer}},
year = {2025}}

Corresponding author

Rémi PETITPIERRE - remi.petitpierre@epfl.ch - ORCID - Github - Scholar - ResearchGate

Work ethics

The data were annotated by two master's students from EPFL, Switzerland. The students were paid for their work using public funding, and were offered the possibility to be associated with the publication of the data.

License

This project is licensed under the CC BY 4.0 License.

Liability

We do not assume any liability for the use of this dataset.

References

1. Li Z., Lin Y., Chiang Y.-Y., Weinman J., Tual S., Chazalon J., Perret J., Duménieu B., Abadie N. (2024). ICDAR 2024 competition on historical map text detection, recognition, and linking. In Document Analysis and Recognition - ICDAR 2024: 18th International Conference, Athens, Greece, August 30–September 4, 2024, Proceedings, Part VI. Springer-Verlag, Berlin, Heidelberg, 363–380. https://doi.org/10.1007/978-3-031-70552-6_22
2. Petitpierre, R. (2021). Historical City Maps Semantic Segmentation Dataset. V1.0. https://doi.org/10.5281/zenodo.5513639

Are you looking to identify B2B leads to promote your business, product, or service? Outscraper Google Maps Scraper might just be the tool you've been searching for. This powerful software enables you to extract business data directly from Google's extensive database, which spans millions of businesses across countless industries worldwide.

Outscraper Google Maps Scraper is a tool built with advanced technology that lets you scrape a myriad of valuable information about businesses from Google's database. This information includes but is not limited to, business names, addresses, contact information, website URLs, reviews, ratings, and operational hours.

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In a world that's growing increasingly data-driven, utilizing a tool like Outscraper Google Maps Scraper could be instrumental to your business' success. If you're looking to get ahead in your market and find B2B leads in a more efficient and precise manner, Outscraper is worth considering. It streamlines the data collection process, allowing you to focus on what truly matters – using the data to grow your business.

https://outscraper.com/google-maps-scraper/

As a result of the Google Maps scraping, your data file will contain the following details:

Query Name Site Type Subtypes Category Phone Full Address Borough Street City Postal Code State Us State Country Country Code Latitude Longitude Time Zone Plus Code Rating Reviews Reviews Link Reviews Per Scores Photos Count Photo Street View Working Hours Working Hours Old Format Popular Times Business Status About Range Posts Verified Owner ID Owner Title Owner Link Reservation Links Booking Appointment Link Menu Link Order Links Location Link Place ID Google ID Reviews ID

If you want to enrich your datasets with social media accounts and many more details you could combine Google Maps Scraper with Domain Contact Scraper.

Domain Contact Scraper can scrape these details:

Email Facebook Github Instagram Linkedin Phone Twitter Youtube

This dataset contains old maps of Hong Kong, including “Plan of the City of Victoria Hong Kong (1889)”, “Victoria Hong Kong (1897)”, “Kowloon Peninsula (1892, 1947, 1963 & 1970)”, “Hong Kong (1927 & 1957)”, “Sha Tin (1904)”, “Tsuen Wan (1958)”, “Central (1938)” and “Wan Chai (1947)”. The map images scanned from paper maps are geo-referenced to the Hong Kong 1980 Grid coordinate system.

The Digital Geologic Map of the U.S. Geological Survey Mapping in the Western Portion of Amistad National Recreation Area, Texas is composed of GIS data layers complete with ArcMap 9.3 layer (.LYR) files, two ancillary GIS tables, a Map PDF document with ancillary map text, figures and tables, a FGDC metadata record and a 9.3 ArcMap (.MXD) Document that displays the digital map in 9.3 ArcGIS. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Eddie Collins, Amanda Masterson and Tom Tremblay (Texas Bureau of Economic Geology); Rick Page (U.S. Geological Survey); Gilbert Anaya (International Boundary and Water Commission). Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation sections(s) of this metadata record (wpam_metadata.txt; available at http://nrdata.nps.gov/amis/nrdata/geology/gis/wpam_metadata.xml). All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.1. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.3 personal geodatabase (wpam_geology.mdb), and as shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 14N. The data is within the area of interest of Amistad National Recreation Area.

Mature Support Notice: This item is in mature support as of June 2021. A replacement item has not been identified at this time.This map presents land cover and detailed topographic maps for the United States. It uses the USA Topographic Map service. The map includes the National Park Service (NPS) Natural Earth physical map at 1.24km per pixel for the world at small scales, i-cubed eTOPO 1:250,000-scale maps for the contiguous United States at medium scales, and National Geographic TOPO! 1:100,000 and 1:24,000-scale maps (1:250,000 and 1:63,000 in Alaska) for the United States at large scales. The TOPO! maps are seamless, scanned images of United States Geological Survey (USGS) paper topographic maps.The maps provide a very useful basemap for a variety of applications, particularly in rural areas where the topographic maps provide unique detail and features from other basemaps.To add this map service into a desktop application directly, go to the entry for the USA Topo Maps map service. Tip: Here are some famous locations as they appear in this web map, accessed by including their location in the URL that launches the map:Grand Canyon, ArizonaGolden Gate, CaliforniaThe Statue of Liberty, New YorkWashington DCCanyon De Chelly, ArizonaYellowstone National Park, WyomingArea 51, Nevada

Number of markers, and map size and density of each parent map and of the two consensus maps (BT×K) and (R×L).

Stanislaus County Recorded Maps

Important Note: This item is in mature support as of June 2021 and is no longer updated. This map presents land cover and detailed topographic maps for the United States. It uses the USA Topographic Map service. The map includes the National Park Service (NPS) Natural Earth physical map at 1.24km per pixel for the world at small scales, i-cubed eTOPO 1:250,000-scale maps for the contiguous United States at medium scales, and National Geographic TOPO! 1:100,000 and 1:24,000-scale maps (1:250,000 and 1:63,000 in Alaska) for the United States at large scales. The TOPO! maps are seamless, scanned images of United States Geological Survey (USGS) paper topographic maps.The maps provide a very useful basemap for a variety of applications, particularly in rural areas where the topographic maps provide unique detail and features from other basemaps.To add this map service into a desktop application directly, go to the entry for the USA Topo Maps map service. Tip: Here are some famous locations as they appear in this web map, accessed by including their location in the URL that launches the map:Grand Canyon, ArizonaGolden Gate, CaliforniaThe Statue of Liberty, New YorkWashington DCCanyon De Chelly, ArizonaYellowstone National Park, WyomingArea 51, Nevada

Alquist-Priolo Earthquake Fault Zoning Act (1972) and the Seismic Hazards Mapping Act (1990) direct the State Geologist to delineate regulatory "Zones of Required Investigation" to reduce the threat to public health and safety and to minimize the loss of life and property posed by earthquake-triggered ground failures. Cities and counties affected by the zones must regulate certain development "projects" within them. These Acts also require sellers of real property (and their agents) within a mapped hazard zone to disclose at the time of sale that the property lies within such a zone. NOTE: Fault Evaluation Reports are available for those areas covered by a Regulatory Map however there are reports available for areas outside the Regulatory map boundary. For a complete set of maps available for purchase on CD please contact the CGS Library.