Freebase is amongst the largest public cross-domain knowledge graphs. It possesses three main data modeling idiosyncrasies. It has a strong type system; its properties are purposefully represented in reverse pairs; and it uses mediator objects to represent multiary relationships. These design choices are important in modeling the real-world. But they also pose nontrivial challenges in research of embedding models for knowledge graph completion, especially when models are developed and evaluated agnostically of these idiosyncrasies. We make available several variants of the Freebase dataset by inclusion and exclusion of these data modeling idiosyncrasies. This is the first-ever publicly available full-scale Freebase dataset that has gone through proper preparation.

Dataset Details

The dataset consists of the four variants of Freebase dataset as well as related mapping/support files. For each variant, we made three kinds of files available:

• Subject matter triples file
  • fb+/-CVT+/-REV One folder for each variant. In each folder there are 5 files: train.txt, valid.txt, test.txt, entity2id.txt, relation2id.txt Subject matter triples are the triples belong to subject matters domains—domains describing real-world facts.
    • Example of a row in train.txt, valid.txt, and test.txt:
      • 2, 192, 0
    • Example of a row in entity2id.txt:
      • /g/112yfy2xr, 2
    • Example of a row in relation2id.txt:
      • /music/album/release_type, 192
    • Explaination
      • "/g/112yfy2xr" and "/m/02lx2r" are the MID of the subject entity and object entity, respectively. "/music/album/release_type" is the realtionship between the two entities. 2, 192, and 0 are the IDs assigned by the authors to the objects.
• Type system file
  • freebase_endtypes: Each row maps an edge type to its required subject type and object type.
    • Example
      • 92, 47178872, 90
    • Explanation
      • "92" and "90" are the type id of the subject and object which has the relationship id "47178872".
• Metadata files
  • object_types: Each row maps the MID of a Freebase object to a type it belongs to.
    • Example
      • /g/11b41c22g, /type/object/type, /people/person
    • Explanation
      • The entity with MID "/g/11b41c22g" has a type "/people/person"
  • object_names: Each row maps the MID of a Freebase object to its textual label.
    • Example
      • /g/11b78qtr5m, /type/object/name, "Viroliano Tries Jazz"@en
    • Explanation
      • The entity with MID "/g/11b78qtr5m" has name "Viroliano Tries Jazz" in English.
  • object_ids: Each row maps the MID of a Freebase object to its user-friendly identifier.
    • Example
      • /m/05v3y9r, /type/object/id, "/music/live_album/concert"
    • Explanation
      • The entity with MID "/m/05v3y9r" can be interpreted by human as a music concert live album.
  • domains_id_label: Each row maps the MID of a Freebase domain to its label.
    • Example
      • /m/05v4pmy, geology, 77
    • Explanation
      • The object with MID "/m/05v4pmy" in Freebase is the domain "geology", and has id "77" in our dataset.
  • types_id_label: Each row maps the MID of a Freebase type to its label.
    • Example
      • /m/01xljxh, /government/political_party, 147
    • Explanation
      • The object with MID "/m/01xljxh" in Freebase is the type "/government/political_party", and has id "147" in our dataset.
  • entities_id_label: Each row maps the MID of a Freebase entity to its label.
    • Example
      • /g/11b78qtr5m, Viroliano Tries Jazz, 2234
    • Explanation
      • The entity with MID "/g/11b78qtr5m" in Freebase is "Viroliano Tries Jazz", and has id "2234" in our dataset.
    • properties_id_label: Each row maps the MID of a Freebase property to its label.
      • Example
        • /m/010h8tp2, /comedy/comedy_group/members, 47178867
      • Explanation
        • The object with MID "/m/010h8tp2" in Freebase is a property(relation/edge), it has label "/comedy/comedy_group/members" and has id "47178867" in our dataset.
    • uri_original2simplified and uri_simplified2original: The mapping between original URI and simplified URI and the mapping between simplified URI and original URI repectively.
      • Example
        • uri_original2simplified
          • "http://rdf.freebase.com/ns/type.property.unique": "/type/property/unique"
        • uri_simplified2original
          • "/type/property/unique": "http://rdf.freebase.com/ns/type.property.unique"
      • Explanation
        • The URI "http://rdf.freebase.com/ns/type.property.unique" in the original Freebase RDF dataset is simplified into "/type/property/unique" in our dataset.
        • The identifier "/type/property/unique" in our dataset has URI http://rdf.freebase.com/ns/type.property.unique in the original Freebase RDF dataset.

Access National Hydrography ProductsThe National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.The NHD is a national framework for assigning reach addresses to water-related entities, such as industrial discharges, drinking water supplies, fish habitat areas, wild and scenic rivers. Reach addresses establish the locations of these entities relative to one another within the NHD surface water drainage network, much like addresses on streets. Once linked to the NHD by their reach addresses, the upstream/downstream relationships of these water-related entities--and any associated information about them--can be analyzed using software tools ranging from spreadsheets to geographic information systems (GIS). GIS can also be used to combine NHD-based network analysis with other data layers, such as soils, land use and population, to help understand and display their respective effects upon one another. Furthermore, because the NHD provides a nationally consistent framework for addressing and analysis, water-related information linked to reach addresses by one organization (national, state, local) can be shared with other organizations and easily integrated into many different types of applications to the benefit of all.Statements of attribute accuracy are based on accuracy statements made for U.S. Geological Survey Digital Line Graph (DLG) data, which is estimated to be 98.5 percent. One or more of the following methods were used to test attribute accuracy: manual comparison of the source with hardcopy plots; symbolized display of the DLG on an interactive computer graphic system; selected attributes that could not be visually verified on plots or on screen were interactively queried and verified on screen. In addition, software validated feature types and characteristics against a master set of types and characteristics, checked that combinations of types and characteristics were valid, and that types and characteristics were valid for the delineation of the feature. Feature types, characteristics, and other attributes conform to the Standards for National Hydrography Dataset (USGS, 1999) as of the date they were loaded into the database. All names were validated against a current extract from the Geographic Names Information System (GNIS). The entry and identifier for the names match those in the GNIS. The association of each name to reaches has been interactively checked, however, operator error could in some cases apply a name to a wrong reach.Points, nodes, lines, and areas conform to topological rules. Lines intersect only at nodes, and all nodes anchor the ends of lines. Lines do not overshoot or undershoot other lines where they are supposed to meet. There are no duplicate lines. Lines bound areas and lines identify the areas to the left and right of the lines. Gaps and overlaps among areas do not exist. All areas close.The completeness of the data reflects the content of the sources, which most often are the published USGS topographic quadrangle and/or the USDA Forest Service Primary Base Series (PBS) map. The USGS topographic quadrangle is usually supplemented by Digital Orthophoto Quadrangles (DOQs). Features found on the ground may have been eliminated or generalized on the source map because of scale and legibility constraints. In general, streams longer than one mile (approximately 1.6 kilometers) were collected. Most streams that flow from a lake were collected regardless of their length. Only definite channels were collected so not all swamp/marsh features have stream/rivers delineated through them. Lake/ponds having an area greater than 6 acres were collected. Note, however, that these general rules were applied unevenly among maps during compilation. Reach codes are defined on all features of type stream/river, canal/ditch, artificial path, coastline, and connector. Waterbody reach codes are defined on all lake/pond and most reservoir features. Names were applied from the GNIS database. Detailed capture conditions are provided for every feature type in the Standards for National Hydrography Dataset available online through https://prd-wret.s3-us-west-2.amazonaws.com/assets/palladium/production/atoms/files/NHD%201999%20Draft%20Standards%20-%20Capture%20conditions.PDF.Statements of horizontal positional accuracy are based on accuracy statements made for U.S. Geological Survey topographic quadrangle maps. These maps were compiled to meet National Map Accuracy Standards. For horizontal accuracy, this standard is met if at least 90 percent of points tested are within 0.02 inch (at map scale) of the true position. Additional offsets to positions may have been introduced where feature density is high to improve the legibility of map symbols. In addition, the digitizing of maps is estimated to contain a horizontal positional error of less than or equal to 0.003 inch standard error (at map scale) in the two component directions relative to the source maps. Visual comparison between the map graphic (including digital scans of the graphic) and plots or digital displays of points, lines, and areas, is used as control to assess the positional accuracy of digital data. Digital map elements along the adjoining edges of data sets are aligned if they are within a 0.02 inch tolerance (at map scale). Features with like dimensionality (for example, features that all are delineated with lines), with or without like characteristics, that are within the tolerance are aligned by moving the features equally to a common point. Features outside the tolerance are not moved; instead, a feature of type connector is added to join the features.Statements of vertical positional accuracy for elevation of water surfaces are based on accuracy statements made for U.S. Geological Survey topographic quadrangle maps. These maps were compiled to meet National Map Accuracy Standards. For vertical accuracy, this standard is met if at least 90 percent of well-defined points tested are within one-half contour interval of the correct value. Elevations of water surface printed on the published map meet this standard; the contour intervals of the maps vary. These elevations were transcribed into the digital data; the accuracy of this transcription was checked by visual comparison between the data and the map.

Access National Hydrography ProductsThe National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.The NHD is a national framework for assigning reach addresses to water-related entities, such as industrial discharges, drinking water supplies, fish habitat areas, wild and scenic rivers. Reach addresses establish the locations of these entities relative to one another within the NHD surface water drainage network, much like addresses on streets. Once linked to the NHD by their reach addresses, the upstream/downstream relationships of these water-related entities--and any associated information about them--can be analyzed using software tools ranging from spreadsheets to geographic information systems (GIS). GIS can also be used to combine NHD-based network analysis with other data layers, such as soils, land use and population, to help understand and display their respective effects upon one another. Furthermore, because the NHD provides a nationally consistent framework for addressing and analysis, water-related information linked to reach addresses by one organization (national, state, local) can be shared with other organizations and easily integrated into many different types of applications to the benefit of all.Statements of attribute accuracy are based on accuracy statements made for U.S. Geological Survey Digital Line Graph (DLG) data, which is estimated to be 98.5 percent. One or more of the following methods were used to test attribute accuracy: manual comparison of the source with hardcopy plots; symbolized display of the DLG on an interactive computer graphic system; selected attributes that could not be visually verified on plots or on screen were interactively queried and verified on screen. In addition, software validated feature types and characteristics against a master set of types and characteristics, checked that combinations of types and characteristics were valid, and that types and characteristics were valid for the delineation of the feature. Feature types, characteristics, and other attributes conform to the Standards for National Hydrography Dataset (USGS, 1999) as of the date they were loaded into the database. All names were validated against a current extract from the Geographic Names Information System (GNIS). The entry and identifier for the names match those in the GNIS. The association of each name to reaches has been interactively checked, however, operator error could in some cases apply a name to a wrong reach.Points, nodes, lines, and areas conform to topological rules. Lines intersect only at nodes, and all nodes anchor the ends of lines. Lines do not overshoot or undershoot other lines where they are supposed to meet. There are no duplicate lines. Lines bound areas and lines identify the areas to the left and right of the lines. Gaps and overlaps among areas do not exist. All areas close.The completeness of the data reflects the content of the sources, which most often are the published USGS topographic quadrangle and/or the USDA Forest Service Primary Base Series (PBS) map. The USGS topographic quadrangle is usually supplemented by Digital Orthophoto Quadrangles (DOQs). Features found on the ground may have been eliminated or generalized on the source map because of scale and legibility constraints. In general, streams longer than one mile (approximately 1.6 kilometers) were collected. Most streams that flow from a lake were collected regardless of their length. Only definite channels were collected so not all swamp/marsh features have stream/rivers delineated through them. Lake/ponds having an area greater than 6 acres were collected. Note, however, that these general rules were applied unevenly among maps during compilation. Reach codes are defined on all features of type stream/river, canal/ditch, artificial path, coastline, and connector. Waterbody reach codes are defined on all lake/pond and most reservoir features. Names were applied from the GNIS database. Detailed capture conditions are provided for every feature type in the Standards for National Hydrography Dataset available online through https://prd-wret.s3-us-west-2.amazonaws.com/assets/palladium/production/atoms/files/NHD%201999%20Draft%20Standards%20-%20Capture%20conditions.PDF.Statements of horizontal positional accuracy are based on accuracy statements made for U.S. Geological Survey topographic quadrangle maps. These maps were compiled to meet National Map Accuracy Standards. For horizontal accuracy, this standard is met if at least 90 percent of points tested are within 0.02 inch (at map scale) of the true position. Additional offsets to positions may have been introduced where feature density is high to improve the legibility of map symbols. In addition, the digitizing of maps is estimated to contain a horizontal positional error of less than or equal to 0.003 inch standard error (at map scale) in the two component directions relative to the source maps. Visual comparison between the map graphic (including digital scans of the graphic) and plots or digital displays of points, lines, and areas, is used as control to assess the positional accuracy of digital data. Digital map elements along the adjoining edges of data sets are aligned if they are within a 0.02 inch tolerance (at map scale). Features with like dimensionality (for example, features that all are delineated with lines), with or without like characteristics, that are within the tolerance are aligned by moving the features equally to a common point. Features outside the tolerance are not moved; instead, a feature of type connector is added to join the features.Statements of vertical positional accuracy for elevation of water surfaces are based on accuracy statements made for U.S. Geological Survey topographic quadrangle maps. These maps were compiled to meet National Map Accuracy Standards. For vertical accuracy, this standard is met if at least 90 percent of well-defined points tested are within one-half contour interval of the correct value. Elevations of water surface printed on the published map meet this standard; the contour intervals of the maps vary. These elevations were transcribed into the digital data; the accuracy of this transcription was checked by visual comparison between the data and the map.

The surface requirements of the local planning plan (LDP) are digitised in accordance with the national requirements of the CNIG. The requirements of a PLU are defined in Article R123-11 of the Urban Planning Code and are presented in the form of information which appears on the graphic documents of the PLU. A requirement which superimposes on an area of the planning document generally imposes an additional constraint on the settlement of the area. In this dataset are the surface requirements of TYPE 01 (classified wooded spaces) and 05 (reserved spaces) if they appear on the graphic documents of the PLU.

The Digital Geomorphic-GIS Map of Cape Lookout National Seashore, North Carolina (1:24,000 scale 2008 mapping) is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (calo_geomorphology.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 3.X map file (.mapx) file (calo_geomorphology.mapx) and individual Pro 3.X layer (.lyrx) 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 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (calo_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (calo_geomorphology.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 (calo_geomorphology_metadata_faq.pdf). Please read the calo_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: 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: North Carolina 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 (calo_geomorphology_metadata.txt or calo_geomorphology_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 Pro, 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).

Reconstruction maps of cryo-electron microscopy (cryo-EM) exhibit distortion when the cryo-EM dataset is incomplete, usually caused by unevenly distributed orientations. Prior efforts had been attempted to address this preferred orientation problem using tilt-collection strategy, modifications to grids or to air-water-interfaces. However, these approaches often require time-consuming experiments and the effect was always protein dependent. Here, we developed a procedure containing removing mis-aligned particles and an iterative reconstruction method based on signal-to-noise ratio of Fourier component to correct such distortion by recovering missing data using a purely computational algorithm. This procedure called Signal-to-Noise Ratio Iterative Reconstruction Method (SIRM) was applied on incomplete datasets of various proteins to fix distortion in cryo-EM maps and to a more isotropic resolution. In addition, SIRM provides a better reference map for further reconstruction refinements, resulting in an improved alignment, which ultimately improves map quality and benefits model building.

The Digital Surficial Geologic-GIS Map of the Stroudsburg Quadrangle, New Jersey and Pennsylvania 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 (stro_surficial_geology.gdb), and a 2.) Open Geospatial Consortium (OGC) geopackage. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (stro_surficial_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 (stro_surficial_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (dewa_surficial_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (dewa_surficial_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 (stro_surficial_geology_metadata_faq.pdf). Please read the dewa_surficial_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. QGIS software is available for free at: https://www.qgis.org/en/site/. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Pennsylvania 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 (stro_surficial_geology_metadata.txt or stro_surficial_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

This is a MD iMAP hosted service layer. Find more information at http://imap.maryland.gov. This layer contains the boundaries and IDs of the Maryland tax maps produced by Maryland Department of Planning. Tax maps - also known as assessment maps - property maps or parcel maps - are a graphic representation of real property showing and defining individual property boundaries in relationship to contiguous real property. Last Updated: Feature Service Layer Link: http://geodata.md.gov/imap/rest/services/PlanningCadastre/MD_PropertyData/MapServer/2 ADDITIONAL LICENSE TERMS: The Spatial Data and the information therein (collectively "the Data") is provided "as is" without warranty of any kind either expressed implied or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct indirect incidental consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

The cladding elements are entries in relation to a regulatory provision (way width, odds, names of neighbouring municipalities.) or geometrical surface, linear or point indicative elements, dressing the graphic documents of the PLU or the POS. They are necessary for the paper edition of the applicable graphic documents. This may be, for example, a hold of a detail plan, a frame, a cartridge, a reminder for a writing, a draw to draw a rating, an equipment identification label

Geoform is a configurable app template for form based data editing of a Feature Service. This application allows users to enter data through a form instead of a map's pop-up while leveraging the power of the Web Map and editable Feature Services. This app geo-enables data and workflows by lowering the barrier of entry for completing simple tasks. Use CasesProvides a form-based experience for entering data through a form instead of a map pop-up. This is a good choice for users who find forms a more intuitive format than pop-ups for entering data.Useful to collect new point data from a large audience of non technical staff or members of the community.Configurable OptionsGeoform has an interactive builder used to configure the app in a step-by-step process. Use Geoform to collect new point data and configure it using the following options:Choose a web map and the editable layer(s) to be used for collection.Provide a title, logo image, and form instructions/details.Control and choose what attribute fields will be present in the form. Customize how they appear in the form, the order they appear in, and add hint text.Select from over 15 different layout themes.Choose the display field that will be used for sorting when viewing submitted entries.Enable offline support, social media sharing, default map extent, locate on load, and a basemap toggle button.Choose which locate methods are available in the form, including: current location, search, latitude and longitude, USNG coordinates, MGRS coordinates, and UTM coordinates.Supported DevicesThis application is responsively designed to support use in browsers on desktops, mobile phones, and tablets.Data RequirementsThis web app includes the capability to edit a hosted feature service or an ArcGIS Server feature service. Creating hosted feature services requires an ArcGIS Online organizational subscription or an ArcGIS Developer account. Get Started This application can be created in the following ways:Click the Create a Web App button on this pageShare a map and choose to Create a Web AppOn the Content page, click Create - App - From Template Click the Download button to access the source code. Do this if you want to host the app on your own server and optionally customize it to add features or change styling.

The dataset

The dataset is produced within the SafeLog project and it is used for benchmarking of multi-agent path planning algorithms. Specifically, the dataset consists of a set of 21 maps with increasing density and a set of 500 random assignments, each for a group of 100 agents for planning on each of the maps.

All of the maps, in the form of a graph G = {V, E}, are built on the same set of 400 vertices V. The sets of edges Ej, where j ∈ (0; 20), in the maps then form a set ranging from a spanning tree to a mostly 4-connected graph. These maps were created by generating a complete square graph with the size of 20*20 vertices. The graph was then simplified to a spanning tree, and, finally, approximately 50 random edges from the complete graph were added 20 times, to create the set of 21 maps of density ranging from 800 to 1500 edges in the graph.

Content and format

The following files are included in the dataset

test_nodes.txt - 400 nodes of a 20*20 square map in the form "id x y"
testAssignment.txt - 50499 random pairs of nodes ids from test_nodes.txt
test_edgesX.txt - pairs of adjacent nodes ids from test_nodes.txt forming edges
- X = 0 - tree
- X = 20 - full graph
- created starting at a full graph and repeatedly erasing edges until a tree remains

To illustrate the maps in the dataset, we provide three images (1008.png, 1190.png, and 1350.png) showing maps with 1008 (1190, 1350) edges.

Citation

If you use the dataset, please cite:

[1] Hvězda, J., Rybecký, T., Kulich, M., and Přeučil, L. (2018). Context-Aware Route Planning for Automated Warehouses. Proceedings of 2018 21st International Conference on Intelligent Transportation Systems (ITSC).

@inproceedings{Hvezda18itsc,
author = {Hvězda, Jakub and Rybecký, Tomáš and Kulich, Miroslav and Přeučil, Libor},
title = {Context-Aware Route Planning for Automated Warehouses},
booktitle = {Proceedings of 2018 21st International Conference on Intelligent Transportation Systems (ITSC)},
publisher = {IEEE Intelligent Transportation Systems Society},
address = {Maui},
year = {2018},
doi = {10.1109/ITSC.2018.8569712},
}

[2] Hvězda, J., Kulich, M., and Přeučil, L. (2019). On Randomized Searching for Multi-robot Coordination. In: Gusikhin O., Madani K. (eds) Informatics in Control, Automation and Robotics. ICINCO 2018. Lecture Notes in Electrical Engineering, vol 613. Springer, Cham.

@inbook{Hvezda19springer,
author = {Hvězda, Jakub and Kulich, Miroslav and Přeučil, Libor},
title = {On Randomized Searching for Multi-robot Coordination},
booktitle = {Informatics in Control, Automation and Robotics},
publisher = {Springer},
address = {Cham, CH},
year = {2019},
series = {Lecture Notes in Electrical Engineering},
language = {English},
url = {https://link.springer.com/chapter/10.1007/978-3-030-31993-9_18},
doi = {10.1007/978-3-030-31993-9},
}

[3] Hvězda, J., Kulich, M., and Přeučil, L. (2018). Improved Discrete RRT for Coordinated Multi-robot Planning. Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - (Volume 2).

@inproceedings{Hvezda18icinco,
author = {Hvězda, Jakub and Kulich, Miroslav and Přeučil, Libor},
title = {Improved Discrete RRT for Coordinated Multi-robot Planning},
booktitle = {Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - (Volume 2)},
publisher = {SciTePress},
address = {Madeira, PT},
year = {2018},
language = {English},
url = {http://www.scitepress.org/PublicationsDetail.aspx?ID=ppwUqsGaX18=\&t=1},
doi = {10.5220/0006865901710179},
access = {full}
}

The surface requirements of the local planning plan (LDP) are digitised in accordance with the national requirements of the CNIG. The requirements of a PLU are defined in Article R123-11 of the Urban Planning Code and are presented in the form of information which appears on the graphic documents of the PLU. A requirement which superimposes on an area of the planning document generally imposes an additional constraint on the settlement of the area. In this dataset are the surface requirements of TYPE 01 (classified wooded spaces) and 05 (reserved spaces) if they appear on the graphic documents of the PLU.

The Digital Geohazards-GIS Map of Everglades National Park and Vicinity (2005 Mapping), Florida 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 (ever_geohazard.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 (ever_geohazard.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (ever_geohazard.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.) A GIS readme file (ever_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (ever_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 (ever_geohazard_metadata_faq.pdf). Please read the ever_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: Florida 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 (ever_geohazard_metadata.txt or ever_geohazard_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).

The information contained in graphic documents of a PLU or POS urban planning document shall be added either for regulatory reasons or for information purposes: — the information which is to be annexed to the planning documents in accordance with Articles R123-13 and R123-14 of the Planning Code,- the information reported on the graphic documents for information purposes.

The surface requirements of the local planning plan (LDP) are digitised in accordance with the national requirements of the CNIG. The requirements of a PLU are defined in Article R123-11 of the Urban Planning Code and are presented in the form of information which appears on the graphic documents of the PLU. A requirement which superimposes on an area of the planning document generally imposes an additional constraint on the settlement of the area. In this dataset are the surface requirements of TYPE 01 (classified wooded spaces) and 05 (reserved spaces) if they appear on the graphic documents of the PLU.

The Digital Geologic-GIS Map of Everglades National Park and Vicinity, Florida 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 (ever_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 (ever_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 (ever_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.) A GIS readme file (ever_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (ever_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 (ever_geology_metadata_faq.pdf). Please read the ever_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: Florida Geological Survey and 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 (ever_geology_metadata.txt or ever_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 1:675,000 and United States National Map Accuracy Standards features are within (horizontally) 342.9 meters or 1125 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).

Great Smoky Mountains National Park 1949 Park Topographic Map

How should this data set be cited?

United States Geologic Survey, 1949 , Topographic Map. Great Smoky Mountains National Park. Tennessee and North Carolina. Online Links:

http://science.nature.nps.gov/nrdata

What geographic area does the data set cover?

West_Bounding_Coordinate: -84.007769 East_Bounding_Coordinate: -83.037582 North_Bounding_Coordinate: 35.790660 South_Bounding_Coordinate: 35.418718

What does it look like?

Does the data set describe conditions during a particular time period?

Calendar_Date: 09-Mar-2015Currentness_Reference: publication date

What is the general form of this data set?

Geospatial_Data_Presentation_Form: raster digital data

How does the data set represent geographic features?

How are geographic features stored in the data set? This is a Raster data set.

What coordinate system is used to represent geographic features? Horizontal positions are specified in geographic coordinates, that is, latitude and longitude. Latitudes are given to the nearest 0.000000. Longitudes are given to the nearest 0.000000. Latitude and longitude values are specified in Decimal degrees.

The horizontal datum used is North American Datum of 1983. The ellipsoid used is Geodetic Reference System 80. The semi-major axis of the ellipsoid used is 6378137.000000. The flattening of the ellipsoid used is 1/298.257222.

Vertical_Coordinate_System_Definition:

Altitude_System_Definition:

Altitude_Datum_Name: North American Vertical Datum of 1988 Altitude_Resolution: 0.000025 Altitude_Distance_Units: feet Altitude_Encoding_Method:

Explicit elevation coordinate included with horizontal coordinates

How does the data set describe geographic features?

Entity_and_Attribute_Overview:

Where possible entity attribute population is completed automatically by the GIS/SQL database software. Enclosed herein are Attribute Domains and lists of legal values (LOV) where attributes are populated by "Picklists".

Who produced the data set?

Who are the originators of the data set? (may include formal authors, digital compilers, and editors)

United States Geologic Survey

Who also contributed to the data set?

To whom should users address questions about the data?

National Park Service Attn: Thomas Colson GIS Specialist 107 Park Headquarters Road Gatlinburg, Tennessee 37738 United States

(865)436-1701 (voice) GRSM_Resource_Management@nps.gov

Hours_of_Service: 0800-1730

Why was the data set created?

For the display, query, and analysis of spatial and tabular data.

How was the data set created?

From what previous works were the data drawn?

How were the data generated, processed, and modified?

Date: 28-Mar-2015 (process 1 of 1)

These data contain location values from numerous resource research, inventory, and monitoring projects spanning over many decades. The National Park Service is unable to determin the process steps used to depict many locations, citing lack of reliable data. When known, map source is given as a range of values.

What similar or related data should the user be aware of?

How reliable are the data; what problems remain in the data set?

How well have the observations been checked? Attribute accuracy is tested by manual comparison of the source with hard copy plots and/or symbolized display of the map data on an interactive computer graphic system. Selected attributes that cannot be visually verified on plots or on screen are interactively queried and verified on screen. In addition, the attributes are tested against a master set of valid attributes. All attribute data conform to the attribute codes in the signed classification and correlation document and amendment(s).

How accurate are the geographic locations? These data contain location values from numerous resource research, inventory, and monitoring projects spanning over many decades. The National Park Service is unable to asses the positional accuracy of many locations, citing lack of reliable data. When known, estimated horizontal precision is given as a range of possible values.

Statements of horizontal positional accuracy are based on accuracy statements made for U.S. Geological Survey topographic quadrangle maps. These maps were compiled to meet National Map Accuracy Standards. For horizontal accuracy, this standard is met if at least 90 percent of points tested are within 0.02 inch (at map scale) of the true position. Additional offsets to positions may have been introduced where feature density is high to improve the legibility of map symbols. In addition, the digitizing of maps is estimated to contain a horizontal positional error of less than or equal to 0.003 inch standard error (at map scale) in the two component directions relative to the source maps. Visual comparison between the map graphic (including digital scans of the graphic) and plots or digital displays of points, lines, and areas, is used as control to assess the positional accuracy of digital data. Digital map elements along the adjoining edges of data sets are aligned if they are within a 0.02 inch tolerance (at map scale). Features with like dimensionality (for example, features that all are delineated with lines), with or without like characteristics, that are within the tolerance are aligned by moving the features equally to a common point. Features outside the tolerance are not moved; instead, a feature of type connector is added to join the features.

This hardcopy map was scanned and georectified using current USGS 1:24k-scale topographic maps. This map is for reference purpose only, and there are likey several gross horizontal errors committed during rectification.

How accurate are the heights or depths? Statements of vertical positional accuracy for elevation of these points are based on accuracy statements made for U.S. Geological Survey topographic quadrangle maps. These maps were compiled to meet National Map Accuracy Standards. For vertical accuracy, this standard is met if at least 90 percent of well-defined points tested are within one-half contour interval of the correct value. Elevations of points printed on the published map meet this standard; the contour intervals of the maps vary. These elevations were transcribed into the digital data; the accuracy of this transcription was checked by visual comparison between the data and the map. This statement is generally true for the most common sources of these data. Other sources and methods may have been used to create or update these data. In some cases, additional information may be found in the feature-level metadata report.

Where are the gaps in the data? What is missing? Data completeness for these data reflect content of the source data. Features may have been eliminated or generalized on the source data due to scale and legibility constraints. For information on collection and inclusion criteria, see U.S. Geological Survey, 1994, Standards for 1:24,000-Scale Digital Line Graphs and Quadrangle Maps: National Mapping Program Technical Instructions and U.S. Geological Survey, 1994, Standards for Digital Line Graphs: National Mapping Program Technical Instructions.

How consistent are the relationships among the observations, including topology? No duplicate features exist nor duplicate points in a data string. Point data are represented by two sets of coordinate pairs, each with the same coordinate values, contained in the "Shape" Column, and "X_COORD, Y_COORD" Columns.

Database engine scripts automatically populate many of the possible "List of Values" for those columns that derive their attrtibute from other source data (see Entity Attribute Section of this document for details), thereby enforcing Attribute Accuracy. Database engine scripts also prevent the entry of duplication location coordinates, ensure the consistency and format of binary data representing geographic coordinates, and spatial and attribute index integrity.

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?

Who distributes the data set? (Distributor 1 of 1)

Thomas Colson National Park Service GIS Specialist 107 Park Headquarters Rd. Gatlinburg, Tennessee 37738 United States

(865)436-1701 (voice) GRSM_Resource_Management@nps.gov

Hours_of_Service: 0800-1730 EST

What's the catalog number I need to order this data set? Downloadable Data

What legal disclaimers am I supposed to read?

The National Park Service shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics (i.e. GIF or JPG format files) are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time. The data are not better than the original sources from which they were derived. It is the responsibility of the data user to use the data appropriately and consistent within the limitations of geospatial data in general and these data in particular. The related graphics are intended to aid the data user in acquiring relevant data; it is not appropriate to use the related graphics as data. The National Park Service gives no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data. It is strongly recommended that these data are directly acquired from an NPS server and not indirectly through other sources which may have changed the data in some way. Although these data have been processed successfully on computer systems at the National Park Service, no warranty expressed or implied is made regarding the utility of the data on other

Aggregation of generic tables describing the noise zones, for an infrastructure, type of infrastructure concerned ROUTE (R), type C map according to the Lden indicator (day/evening/night).

This map is a graphic representation of the areas where the Lden noise level exceeds the limit value of 68 dB for the 3 rd deadline.

Noise level zones describe a noise exposure situation based on a noise indicator or area affected by noise. They are used primarily for the preparation of strategic noise maps pursuant to Article R.572-5 of the Environmental Code.

The Digital Geologic-GIS Map of Ocmulgee Mounds National Historical Park and Vicinity, Georgia 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 (ocmu_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 (ocmu_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 (ocmu_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.) A GIS readme file (ocmu_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (ocmu_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 (ocmu_geology_metadata_faq.pdf). Please read the ocmu_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: Georgia Department of Natural Resources and 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 (ocmu_geology_metadata.txt or ocmu_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 1:181,000 and United States National Map Accuracy Standards features are within (horizontally) 91.9 meters or 301.7 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).

Post rendered obsolete (Article L 174-3 of the Urban Planning Code). Back to the RNU since 27/03/2017. The surface requirements of the land use plan (POS) are digitised in accordance with the national requirements of the CNIG. The requirements of a POS are defined in Article R123-11 of the Urban Planning Code and are presented in the form of information which appears on the graphic documents of the POS. A requirement which superimposes on an area of the planning document generally imposes an additional constraint on the regulation of the area. This dataset contains the surface requirements of TYPE 01 (classified wooded spaces) and 05 (reserved spaces) if they appear on the POS graphic documents.