The Intelligent Road Network dataset provided by the Transport Department includes traffic directions, turning restrictions at road junctions, stopping restrictions, on-street parking spaces and other road traffic data for supporting the development of intelligent transport system, fleet management system and car navigation etc. by the public.

Esri China (HK) has prepared this File Geodatabase containing a Network Dataset for the Intelligent Road Network to support Esri GIS users to use the dataset in ArcGIS Pro without going through long configuration steps. Please refer to this guideline to use the Road Network Dataset in ArcGIS Pro for routing analysis. This network dataset has been configured and deployed the following restrictions:

Speed LimitTurnIntersectionTraffic FeaturesPedestrian ZoneTraffic Sign of ProhibitionVehicle RestrictionThe coordinate system of this dataset is Hong Kong 1980 Grid.The objectives of uploading the network dataset to ArcGIS Online platform are to facilitate our Hong Kong ArcGIS users to utilize the data in a spatial ready format and save their data conversion effort.For details about the schema and information about the content and relationship of the data, please refer to the data dictionary provided by Transport Department at https://data.gov.hk/en-data/dataset/hk-td-tis_15-road-network-v2.For details about the data, source format and terms of conditions of usage, please refer to the website of DATA.GOV.HK at https://data.gov.hk.Dataset last updated on: 2021 July

This data contains general information about Pedestrian Network in Hong Kong. Pedestrian Network is a set of 3D line features derived from road features and road furniture from Lands Department and Transport Department. A number of attributes are associated with the pedestrian network such as spatially related street names. Besides, the pedestrian network includes information like wheelchair accessibility and obstacles to facilitate the digital inclusion for the needy. Please refer to this video to learn how to use 3D Pedestrian Network Dataset in ArcGIS Pro to facilitate your transportation analysis.The data was provided in the formats of JSON, GML and GDB by Lands Department and downloaded via GEODATA.GOV.HK website.

The original data files were processed and converted into an Esri file geodatabase. Wheelchair accessibility, escalator/lift, staircase walking speed and street gradient were used to create and build a network dataset in order to demonstrate basic functions for pedestrian network and routing analysis in ArcMap and ArcGIS Pro. There are other tables and feature classes in the file geodatabase but they are not included in the network dataset, users have to consider the use of information based on their requirements and make necessary configurations. The coordinate system of this dataset is Hong Kong 1980 Grid.

The objectives of uploading the network dataset to ArcGIS Online platform are to facilitate our Hong Kong ArcGIS users to utilize the data in a spatial ready format and save their data conversion effort.

For details about the schema and information about the content and relationship of the data, please refer to the data dictionary provided by Lands Department at https://geodata.gov.hk/gs/download-datadict/201eaaee-47d6-42d0-ac81-19a430f63952.

For details about the data, source format and terms of conditions of usage, please refer to the website of GEODATA STORE at https://geodata.gov.hk.Dataset last updated on: 2022 Oct

In 2020, with generous funding from the National Lottery Heritage Fund, Ulster Wildlife, National Trust NI, RSPB NI and Woodland Trust NI came together to start building capacity to deliver Nature Recovery Networks in Northern Ireland. As part of the project, habitat networks maps were produced for all terrestrial and intertidal priority habitats, based on the Natural England (Edwards et al., 2020) methodology. The habitat networks comprise vector datasets that map areas of land into different network categories, based on how favourable the land is for restoration to, or creation of the priority habitat, and how effective actions in each area would be at enhancing connectivity of the priority habitat, based on proximity to existing habitat patches. A description of these network categories is provided in Table 1 in the methodology report, available at https://www.ulsterwildlife.org/sites/default/files/2022-10/EnvSys%20NI%20NRN%20mapping%20report.pdf. The habitat network maps do not represent a fully comprehensive depiction of land cover, nor do they provide specific land management options and do not therefore replace the need for an on-site ecological surveys/appraisals. The maps are intended to function as a decision-support tool alongside other pieces of information, both from on-site surveys and data from other sources.

The pathway representation consists of segments and intersection elements. A segment is a linear graphic element that represents a continuous physical travel path terminated by path end (dead end) or physical intersection with other travel paths. Segments have one street name, one address range and one set of segment characteristics. A segment may have none or multiple alias street names. Segment types included are Freeways, Highways, Streets, Alleys (named only), Railroads, Walkways, and Bike lanes. SNDSEG_PV is a linear feature class representing the SND Segment Feature, with attributes for Street name, Address Range, Alias Street name and segment Characteristics objects. Part of the Address Range and all of Street name objects are logically shared with the Discrete Address Point-Master Address File layer. Appropriate uses include: Cartography - Used to depict the City's transportation network _location and connections, typically on smaller scaled maps or images where a single line representation is appropriate. Used to depict specific classifications of roadway use, also typically at smaller scales. Used to label transportation network feature names typically on larger scaled maps. Used to label address ranges with associated transportation network features typically on larger scaled maps. Geocode reference - Used as a source for derived reference data for address validation and theoretical address _location Address Range data repository - This data store is the City's address range repository defining address ranges in association with transportation network features. Polygon boundary reference - Used to define various area boundaries is other feature classes where coincident with the transportation network. Does not contain polygon features. Address based extracts - Used to create flat-file extracts typically indexed by address with reference to business data typically associated with transportation network features. Thematic linear _location reference - By providing unique, stable identifiers for each linear feature, thematic data is associated to specific transportation network features via these identifiers. Thematic intersection _location reference - By providing unique, stable identifiers for each intersection feature, thematic data is associated to specific transportation network features via these identifiers. Network route tracing - Used as source for derived reference data used to determine point to point travel paths or determine optimal stop allocation along a travel path. Topological connections with segments - Used to provide a specific definition of _location for each transportation network feature. Also provides a specific definition of connection between each transportation network feature. (defines where the streets are and the relationship between them ie. 4th Ave is west of 5th Ave and 4th Ave does intersect with Cherry St) Event _location reference - Used as source for derived reference data used to locate event and linear referencing.Data source is TRANSPO.SNDSEG_PV. Updated weekly.

This Bitcoin transaction network data as extracted with the bitcoind client. Due to the nature of Bitcoin, all transactions are published to a P2P network. These can be downloaded and extracted with any of the available client programs. This dataset includes the data used in our papers: Kondor, D., Pósfai, M., Csabai, I., & Vattay, G. (2014). Do the rich get richer? An empirical analysis of the BitCoin transaction network. PLoS ONE, 9(2), e86197. https://doi.org/10.1371/journal.pone.0086197 Kondor, D., Csabai, I., Szüle, J., Pósfai, M., & Vattay, G. (2014). Inferring the interplay between network structure and market effects in Bitcoin. New Journal of Physics, 16(12), 125003. https://doi.org/10.1088/1367-2630/16/12/125003

This dataset has been produced during a small sub-project of APIS (https://apis.acdh.oeaw.ac.at). It contains data from 151 annotated biographies of the Austrian Biographical Dictionary. These selection of biographical articles describe the life and career steps of historians, librarians, teachers etc. These particular texts have been manually annotated through the webapplication APIS. Through these annotations relations between different kinds of entities were established. The result are biographical data which can be used for network visualization or statistical queries.

The Global Historical Climatology Network - Daily (GHCN-Daily/GHCNd) dataset integrates daily climate observations from approximately 30 different data sources. Version 3 was released in September 2012 with the addition of data from two additional station networks. Changes to the processing system associated with the version 3 release also allowed for updates to occur 7 days a week rather than only on most weekdays. Version 3 contains station-based measurements from well over 90,000 land-based stations worldwide, about two thirds of which are for precipitation measurement only. Other meteorological elements include, but are not limited to, daily maximum and minimum temperature, temperature at the time of observation, snowfall and snow depth. Over 25,000 stations are regularly updated with observations from within roughly the last month. The dataset is also routinely reconstructed (usually every week) from its roughly 30 data sources to ensure that GHCNd is generally in sync with its growing list of constituent sources. During this process, quality assurance checks are applied to the full dataset. Where possible, GHCNd station data are also updated daily from a variety of data streams. Station values for each daily update also undergo a suite of quality checks.

In 2020, with generous funding from the National Lottery Heritage Fund, Ulster Wildlife, National Trust NI, RSPB NI and Woodland Trust NI came together to start building capacity to deliver Nature Recovery Networks in Northern Ireland. As part of the project, habitat networks maps were produced for all terrestrial and intertidal priority habitats, based on the Natural England (Edwards et al., 2020) methodology. The habitat networks comprise vector datasets that map areas of land into different network categories, based on how favourable the land is for restoration to, or creation of the priority habitat, and how effective actions in each area would be at enhancing connectivity of the priority habitat, based on proximity to existing habitat patches. A description of these network categories is provided in Table 1 in the methodology report, available at https://www.ulsterwildlife.org/sites/default/files/2022-10/EnvSys%20NI%20NRN%20mapping%20report.pdf. The habitat network maps do not represent a fully comprehensive depiction of land cover, nor do they provide specific land management options and do not therefore replace the need for an on-site ecological surveys/appraisals. The maps are intended to function as a decision-support tool alongside other pieces of information, both from on-site surveys and data from other sources.

A Togo subset of this dataset: ECOWAS region - Existing and Planned Transmission Grid (2017) Existing and planned transmission grid network (medium and high voltage lines) in the ECOWAS Region. Also covers other regions of West Africa. The source of the dataset is the West African Power Pool (WAPP) GIS database January 2017. WAPP collects and validates spatial information on transmission lines in a yearly basis.

Data collected and prepared for a project of the World Bank Group Energy Community of South East Europe APL 3 Montenegro Project in Montenegro. This data is based on a digitized PDF map, and so is intended as a schematic of rough locations of the power network. It is not suitable for applications requiring high accuracy. The PDF map can be viewed on the last page of report attached. To learn more, please visit http://projects.worldbank.org/P106899/energy-community-south-east-europe...

Dataset

This dataset was created by Miguel Tomás

Contents

A tissue-specific gene regulatory network (GRN) was generated for the lung tissue using,1) Hi-C dataset from lung cells2) GTEx eQTL dataset from lung tissue.

The National Network dataset is as of December 22, 2020 and is from the Bureau of Transportation Statistics (BTS) along with the Federal Highway Administration (FHWA), and part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The National Network was authorized by the Surface Transportation Assistance Act of 1982 (P.L. 97-424) and specified in the U.S. Code of Federal Regulations (23 CFR 658) to require states to allow conventional combinations on "the Interstate System and those portions of the Federal-aid Primary System serving to link principal cities and densely developed portions of the states on high volume routes utilized extensively by large vehicles for interstate commerce which do not have any unusual characteristics causing current or anticipated safety problems. “The National Network (NN) includes almost all of the Interstate Highway System and other, specified non-Interstate highways. The network comprises more than 200,000 miles of highways. The National Network supports interstate commerce by regulating the size of trucks. This file is a geospatial representation of the National Network as described in 23 CFR 658 Appendix A and should not be interpreted as the official National Network and should not be used for truck size and weight enforcement purposes or for navigation.

This dataset contains a geodatabase that includes network dataset junctions, network dataset edges, roads network and restriction network files. It can be used for network analysis purpose.

Additional tables and supporting documentation are available in the Data Dictionary and User Manual.

In 2020, with generous funding from the National Lottery Heritage Fund, Ulster Wildlife, National Trust NI, RSPB NI and Woodland Trust NI came together to start building capacity to deliver Nature Recovery Networks in Northern Ireland. As part of the project, habitat networks maps were produced for all terrestrial and intertidal priority habitats, based on the Natural England (Edwards et al., 2020) methodology. The habitat networks comprise vector datasets that map areas of land into different network categories, based on how favourable the land is for restoration to, or creation of the priority habitat, and how effective actions in each area would be at enhancing connectivity of the priority habitat, based on proximity to existing habitat patches. A description of these network categories is provided in Table 1 in the methodology report, available at https://www.ulsterwildlife.org/sites/default/files/2022-10/EnvSys%20NI%20NRN%20mapping%20report.pdf. The habitat network maps do not represent a fully comprehensive depiction of land cover, nor do they provide specific land management options and do not therefore replace the need for an on-site ecological surveys/appraisals. The maps are intended to function as a decision-support tool alongside other pieces of information, both from on-site surveys and data from other sources.

This file includes the locations and nature of street closures, one-way conversions and reversals, and two-way conversions within the five boroughs of New York City. It does NOT contain information on closures or temporary re-routing due to construction or special events. NYCDOT estimates these changes occur less than once a month. The New York City Department of Transportation makes no warranty of accuracy or completeness of this data. Drivers should always comply with signals, signs and other existing regulations.

The Navigable Waterway Network Lines dataset is periodically updated by the United States Army Corp of Engineers (USACE) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The National Waterway Network (Lines) is a comprehensive network database of the Nation's navigable waterways. The dataset covers the 48 contiguous states plus the District of Columbia, Hawaii, Alaska, Puerto Rico and water links between. It consists of a line feature class of the National Waterway Network (NWN), which is based on a route feature class for the NWN update regions (“1†through “7†, as well as the open ocean region “0†) and route event table with linear referencing system measures for NWN links. This dataset is a feature class with associated measures (in miles) that are used for finding distances, locating features, and displaying route event layers. It was exported from this route event layer. The nominal scale of the dataset varies with the source material. The majority of the information is at 1:100,000 with larger scales used in harbor/bay/port areas and smaller scales used in open waters. These data could be used for analytical studies of waterway performance, for compiling commodity flow statistics, and for mapping purposes.

A tissue-specific gene regulatory network (GRN) was generated for brain cortex tissue using1) Hi-C dataset from dorsolateral prefrontal cortex cells2) GTEx eQTL dataset from brain cortex tissue.

The dataset used in the paper is the U.S. airport network.

The National Highway Planning Network (NHPN) dataset was compiled on May 01, 2014 from the Federal Highway Administration (FHWA) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). This dataset is a comprehensive network database of the nation's major highway system. It consists of the nation's highways comprised of Rural Arterials, Urban Principal Arterials and all National Highway System routes. The data set covers the 48 contiguous States plus the District of Columbia, Alaska, Hawaii, and Puerto Rico. The nominal scale of the data set is 1:100,000 with a maximal positional error of 80 meters.