The Open Database of Buildings (ODB) is a collection of open data on buildings made available under the Open Government License - Canada. The ODB brings together 530 datasets originating from 107 government sources of open data. The database aims to enhance access to a harmonized collection of building features across Canada.

This dataset contains a list of infrastructure projects across Canada that have been approved by Infrastructure Canada. The project information listed is based on current information.

Data here contain and describe an open-source structured query language (SQLite) portable database containing high resolution mass spectrometry data (MS1 and MS2) for per- and polyfluorinated alykl substances (PFAS) and associated metadata regarding their measurement techniques, quality assurance metrics, and the samples from which they were produced. These data are stored in a format adhering to the Database Infrastructure for Mass Spectrometry (DIMSpec) project. That project produces and uses databases like this one, providing a complete toolkit for non-targeted analysis. See more information about the full DIMSpec code base - as well as these data for demonstration purposes - at GitHub (https://github.com/usnistgov/dimspec) or view the full User Guide for DIMSpec (https://pages.nist.gov/dimspec/docs).Files of most interest contained here include the database file itself (dimspec_nist_pfas.sqlite) as well as an entity relationship diagram (ERD.png) and data dictionary (DIMSpec for PFAS_1.0.1.20230615_data_dictionary.json) to elucidate the database structure and assist in interpretation and use.

The database of the national open access infrastructure consists of metadata and data on authors of final works (diploma, master’s degree and doctorate) and research publications of Slovenian universities and other Slovenian collections (dLib, Videolectures.NET, DKMORS, SciVie repository...). The national portal (you can find it at http://www.openscience.si/) aggregates content from university repositories and other Slovenian collections for the purposes of a common search engine, recommender system and detector of similar content. The data is available in CSV, RDF/XML and n-triples formats. The ontology used by the national open access infrastructure is also added. You can also query the openscience database via the web interface. Each query returns the JSON object with a variable amount of properties (depending on the available data and the type of request).

This submission contains a technical report describing the development process and visual graphics for the Global Oil and Gas Infrastructure database. Access the GOGI database using the following link: https://edx.netl.doe.gov/dataset/global-oil-gas-features-database There is a web-mapping tool that allows you to visualize and interact with this data also available here: https://edxspatial.arcgis.netl.doe.gov/maps/edxspatial-gogi-index.html Acknowledgement: This work was performed under a CRADA between NETL and EDF, and was funded under the Climate and Clean Air Coalition (CCAC) Oil and Gas Methane Science Studies. The studies are managed by United Nations Environment in collaboration with the Office of the Chief Scientist, Steven Hamburg of the Environmental Defense Fund. Funding was provided by the Environmental Defense Fund, OGCI Companies (Shell, BP, ENI, Petrobras, Repsol, Total, Equinor, CNPC, Saudi Aramco, Exxon, Oxy, Chevron, Pemex) and CCAC.

Description: - This dataset provides detailed information on several urban parking lots, including their basic characteristics and location.

Field details: - ID: Unique identifier for each parking lot. - Name: Car park name - Location: Geographical coordinates (latitude, longitude) indicating the position of the parking lot. - Capacity: Total number of spaces (spacesTotal).

Data update: Data is updated daily.

Data usage: - Open Data Commons Open Database License (ODbL)

Open Data Handbook Curation Detailed Diagram. DC’s data submission process involves four steps as depicted in this diagram. Overall, the data analysts guide the data owner and other analysts as needed to run the data through the submission process, with different groups leading each part (see all caps in diagram above). Their application occurs in a unified database infrastructure consisting of a data warehouse and geospatial database. While there are specific processes and guidelines for each database, they share an overall setting where consistency and standardization are promoted and supported for their individual data curation processes.

Historically, access to the Homeland Infrastructure Foundation-Level Data (HIFLD) has been restricted to applicants meeting a variety of criteria, such as working for a federal government agency, or state emergency management agency. With the release of their new ArcGIS Online Open Data website, the HIFLD has made data previously contained within the Homeland Security Infrastructure Program (HSIP) databases available, and open, to the public. Currently, there are over 270 datasets available that can be downloaded in a variety of proprietary and open data formats, such as a Shapefile, CSV, and KML. All datasets are also available as APIs, such as GeoJSON and GeoServices which allows data to be easily added to web applications. All data are separated into a variety of useful categories such as agriculture, emergency services, natural hazards, and ground transportation, to name a few. Once a dataset is selected, users can read a detailed description of the data, preview the data in the map window, preview the attribute table, and select to download data by map area, or filtered attributes. Once the data has been filtered, or once a focus area has been selected by the user, the data can either be downloaded or opened in ArcGIS Online.

This submission offers a link to a web mapping application hosted instance of the Global Oil & Gas Features Database (GOGI), via EDX Spatial. This offers users with the ability to visualize, interact, and create maps with data of their choice, as well as download specific attributes or fields of view from the database. This data can also be downloaded as a File Geodatabse from EDX at https://edx.netl.doe.gov/dataset/global-oil-gas-features-database. Access the technical report describing how this database was produced using the following link: https://edx.netl.doe.gov/dataset/development-of-an-open-global-oil-and-gas-infrastructure-inventory-and-geodatabase” This data was developed using a combination of big data computing, custom search and data integration algorithms, and expert driven search to collect open oil and gas data resources worldwide. This approach identified over 380 data sets and integrated more than 4.8 million features into the GOGI database. Acknowledgements: This work was funded under the Climate and Clean Air Coalition (CCAC) Oil and Gas Methane Science Studies. The studies are managed by United Nations Environment in collaboration with the Office of the Chief Scientist, Steven Hamburg of the Environmental Defense Fund. Funding was provided by the Environmental Defense Fund, OGCI Companies (Shell, BP, ENI, Petrobras, Repsol, Total, Equinor, CNPC, Saudi Aramco, Exxon, Oxy, Chevron, Pemex) and CCAC.

Summary: This map shows the locations of critical services and lifeline using infrastructure data from OpenStreetMap for Abaco Islands and part of Grand Bahama Island in the Bahamas.Suggested Use:This product can be used to highlight and identify certain critical infrastructure that was exposed to hazard from Hurricane Dorian. This data is best used with additional data that shows where flooding, power outages, or other hazards have occurred. The infrastructure data is derived from pre-event imagery, so may not reflect current situations.Credits: OpenStreetMap Contributors; data available under Open Database Licence (www.openstreetmap.org/copyright)

Construction materials are associated with significant environmental and resources impacts. The circular use of materials already in-use as stocks may provide an opportunity to reduce these impacts. We provide a dataset describing the potential global urban mine consisting of transportation infrastructure in an open database based on geospatial data from OpenStreetMaps. We reveal the significant opportunities of the embedded materials in this huge stock. With this Total Resources in Physical Infrastructure, or TRIPI, database we provide easy access to a global dataset covering 175 countries and sub-regions, allowing researchers to select an area of study, and find the location as well as material composition of the physical infrastructure. Material stocks are reported on a national level and commonly used regional aggregations. Material stocks are reported per kg, kg per capita, and kg per area; and for the physical type of infrastructure that is available in kilometer and area (km²). This dataset can be used in various research applications such as Material Flow Analysis, Material stock inventories, Country level comparisons of infrastructure density, and others, and inform policy on harnessing the opportunities of the urban mine.

The Oil and Gas Infrastructure Mapping (OGIM) database is a global, spatially explicit, and granular database of oil and gas infrastructure, developed at Environmental Defense Fund (EDF) (www.edf.org). The OGIM database is developed to support the quantification and source characterization of oil and gas methane emissions. The database development is based on the acquisition, analysis, curation, integration, and quality-assurance, performed at EDF, of public-domain datasets reported by official government sources, industry, academic, and other non-government entities.

The OGIM database includes locations and facility attributes of oil and gas infrastructure types that are important sources of methane emissions, including oil and gas production wells, offshore production platforms, natural gas compressor stations, processing facilities, liquefied natural gas facilities, crude oil refineries, pipelines, etc.

The OGIM_v1 database includes approximately six million features, including 2.6 million point locations of oil and gas facility types and over 2.6 million kilometers of oil and gas pipelines. This work and the OGIM database, which we anticipate updating on a regular cadence, helps fill a crucial oil and gas geospatial data need, in support of the quantification and attribution of global oil and gas methane emissions at high resolution.

Full details for database development and related analytics can be found in the following journal paper, which is under review at Earth System Science Data journal.

Please cite the paper when using the database:

Omara, M., Gautam, R., O'Brien, M., Himmelberger, A., Franco, A., Meisenhelder, K., Hauser, G., Lyon, D., Chulakadaba, A., Miller, C., Franklin, J., Wofsy, S., and Hamburg, S.: Developing a spatially explicit global oil and gas infrastructure database for characterizing methane emission sources at high resolution, Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-452, 2023.

Important note: While we describe these datasets in detail in the manuscript above, and include maps for all acquired datasets, this open-access version of the OGIM database does not include the locations of about 300 natural gas compressor stations in Russia. Future updates may include these datasets when appropriate permissions to make them publicly accessible are obtained.

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OGIM_v1.1.gpkg. May-10-2023 update:

• This update includes the addition of natural gas flaring detections for the year 2021 based on the VIIRS dataset, available from the Earth Observation Group at Colorado School of Mines, as described in the manuscript text.
  
  
• The current version of the OGIM (OGIM_v1.1) is based on public-domain datasets reported on or prior to January 2023. Each record in OGIM includes a source date when the data was last updated. Some records may have out-of-date information, for example, if facility status has changed since we last acquired the data. We are continuing to update the OGIM database as new public-domain datasets become available.

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Point of Contact at Environmental Defense Fund: Ritesh Gautam (rgautam@edf.org).

London’s Cycling Infrastructure Database (CID) is the world’s largest and most comprehensive database of cycling infrastructure, containing comprehensive details of cycling infrastructure in the Capital. The CID is intended to address barriers to cycling by providing Londoners with clear and accurate information about cycling infrastructure, helping them plan cycle journeys with confidence. The CID is a core part of our Cycling Action Plan , which sets out how TfL, boroughs and others will work together to make London the world’s best big city for cycling. To create the database, TfL have surveyed every street in every London borough to collect information on over 240,000 pieces of infrastructure, covering an area of 1,595 square kilometres. The database also contains 480,000 photographs of cycling infrastructure, allowing users to see exactly what can be found on street. For example, cycle parking users will be able to see what type of parking is available. TfL collected data of 146,000 cycle parking spaces across London, as well as gathering information on 2,000km of cycle routes and 58,000 wayfinding signs. An update to TfL's own Journey Planner means that people using the planner for cycle journeys can now see the nearest and most convenient place to park for every journey. Third party developers will be able to use the data for their own journey planning tools, which will make it simpler for Londoners to plan cycle journeys using their preferred apps. We’re excited to see how developers can use the data to help make cycling in the Capital easier, and to kick-start this we will invite app developers to a hackathon this autumn to see how this data can be maximised to benefit people cycling. As well as making it easier for Londoners to plan cycle journeys, the database will help TfL and boroughs to plan future cycling investment. For example, the database has already been used to develop TfL's Cycle Parking Implementation Plan, which sets out how TfL will work with partners across the capital to deliver 50,000 cycle parking spaces over the next six years where they are needed most, to meet the growing demand for safe places to park cycles. The following types of asset are included in the database: Cycle lanes and tracks – including whether they are segregated or painted lanes Cycle parking, including the type and capacity of parking Signalised crossings for cycles Restricted route - Modal filters and traffic gates which allow cycles to pass but restrict car traffic Traffic calming, including the location of all speed humps in Greater London Advanced stop lines – boxes at junctions for people cycling Signals - early-release signals at junctions Signage - Signed cycle routes and other wayfinding Restricted Points – points where people cycling will have to dismount Paths through parks and other green spaces that can, and cannot, be cycled on

Data here contain and describe an open-source structured query language (SQLite) portable database containing high resolution mass spectrometry data (MS1 and MS2) for pyrrolizidine alkaloids (PAs) and associated metadata regarding their measurement techniques, quality assurance metrics, and the samples from which they were produced. These data are stored in a format adhering to the Database Infrastructure for Mass Spectrometry (DIMSpec) project. That project produces and uses databases like this one, providing a complete toolkit for non-targeted analysis. See more information about the full DIMSpec code base - as well as these data for demonstration purposes - at GitHub (https://github.com/usnistgov/dimspec) or view the full User Guide for DIMSpec (https://pages.nist.gov/dimspec/docs). Files of most interest contained here include the database file itself (pa_database.sqlite) as well as an entity relationship diagram (ERD.png) and data dictionary (DIMSpec for PAs_1.0.1.20230615_data_dictionary.json) to elucidate the database structure and assist in interpretation and use.

Policy-makers are looking to promote the uptake of bicycling as a healthy mode of travel that reduces the negative effects of traditional motorised transport (physical inactivity, air pollution, traffic congestion) and achieves sustainability goals. As an active form of mobility, bicycling improves physical and mental health and has long-term public health benefits. However, there are a number of barriers that prevent people from riding a bike, including fears about riding alongside motor vehicle traffic and the lack of safe and appropriate bicycling infrastructure. For the strategic installation of safer bicycling infrastructure or the improvement of existing infrastructure, rigorous evidence-informed scientific studies are necessary, which in turn rely on high-quality bicycling data, which is scarce. In this regard, one of the prerequisites is understanding the different types of bicycling infrastructure that exist in an urban area and create an inventory dataset that can form the basis of future bicycling-related research. OpenStreetMap (OSM) is a valuable open-source map database that contains transport infrastructure data among other things and has spatial coverage for almost the entire planet. Hence, it is used extensively by researchers and planners and it helps develop methods that are transferable and thus can be replicated irrespective of the study area. We, the Sustainable Mobility and Safety Research Group (SMSR) at Monash University, Australia, have developed a classification process to classify existing bicycling infrastructure across Greater Melbourne, Australia. We have derived knowledge from existing studies and calibrated our classification system to suit local tagging practices.

The purpose of Canada’s Core Infrastructure Cost Dataset is to assign estimated costs to core infrastructure throughout Canada. Using the Replacement Cost and Inventory Count estimates from the Canada’s Core Public Infrastructure (CCPI) survey, and publicly available national infrastructure location data, a variety of core public infrastructure assets were assigned costs according to their location and asset type. The map and related database are set to include, though not limited to: Roads, Waste/Drinking Water facilities, Recreation and Sports facilities, and Transit facilities. For further information on the methods used for specific assets and definitions, please refer to the Asset Methodology Documents. Note: This data does not include Quebec Completed Assets: • Roads • Non-Linear Wastewater Facilities

Natural Resources Canada’s Major Projects Inventory published annually, provides a snapshot of major natural resource projects in Canada that are either currently under construction or are planned within the next 10 years. The inventory includes major projects that increase, extend or improve natural resource production in Canada, including new extraction projects, infrastructure projects, major processing facilities and large expansion projects. In addition, the inventory includes information on the value, timing and geographic location of projects. To be included in the inventory, projects in the energy and mining sectors must meet a minimum capital worth threshold of $50 million and electricity and forest sector projects must meet a threshold of $20 million. Also included in the inventory are clean energy and clean technology projects, which must meet a minimum capital worth threshold of $10 million. DISCLAIMER: Data is sourced from federal, provincial, and territorial databases, publicly accessible websites, and other sources, including CANOILS. Data and maps are for illustrative purposes only. Users understand that, although all efforts have been made to accurately and exhaustively compile, locate and classify projects, the authors do not guarantee the accuracy and/or the comprehensiveness of the data and assume no responsibility for errors or omissions. The routes of the proposed transmission lines and pipelines are approximations, often using only start and end points. In support of this initiative, proponents and partners are encouraged to contact Natural Resources Canada should they identify any significant errors or omissions.

Number of provincially, territorially, regionally and municipally owned bridges, culverts and tunnels for all provinces and territories.

This dataset displays the approximate location of US Forest Service, Great American Outdoors Act (GAOA) projects. The data is refreshed on a nightly basis from the US Forest Service database of infrastructure projects which is stewarded by the individual National Forests and Grasslands. This dataset is a spatial data layer of points representing the approximate or general location where the project takes place. The point location is intended for use in small scale maps to indicate the general location of the projects across the country. The location data is maintained by staff on the individual National Forest or Grassland using the database of record. Because a project can be made up of many assets distributed across a land area, a single project location point will not always reflect the specific location and extent of the work in the project. The project detail data can be used to display the individual assets that make up the project. For more information about Forest Service GAOA projects visit our website: https://www.fs.usda.gov/managing-land/gaoaMetadata and DownloadsThis record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService OGC WMS CSV Shapefile GeoJSON KML For complete information, please visit https://data.gov.