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dataModel.Transportation

These data models describe the main entities involved with smart applications that deal with transportation issues. This set of entities is primarily associated with the Automotive and Smart City vertical segments and related IoT applications. When feasible, references to existing schema.org entity types and attributes are included. These models have been devised to be as generic as possible, thus allowing to deal with different scenarios

  • Traffic flow monitoring - Private Vehicles. - Public Vehicles (Buses, Trains, etc.). - Municipal Vehicles (pick up lorries, cleaning units, ...) - Special Vehicles (ambulances, fire brigades, ...)

List of data models

The following entity types are available:

  • AnonymousCommuterId. Anonymized identifier for flow monitoring. Includes an origin and destiny property to map its path.

  • AnprFlowObserved. The data model represents an observation linked to the passing of a vehicle at a certain location and at a given time. This Data Model is based on the [dataModel.Transportation/ItemFlowObserved], extended with ANPR specific properties and links to the observation images.

  • APDSObservation. This entity models a particular observation of a set of ANPR camera. The Observation might be done with several ANPR cameras, but is limited to the observation of ONE vehicle. It implements the APDS data model https://www.allianceforparkingdatastandards.org/

  • BikeHireDockingStation. Bike Hire Docking Station

  • BikeLane. A generic bike lane schema

  • CityWork. The Data Model is a contextual description of urban works carried out on a road axis and which can impact individual (Cars, motorcycle, bicycles, .…) or common transport (Tram, Bus, subway). It contains a geographic representation making it possible to locate its work from a specific JSON Object and at a more global level (Road segment, Road, District, ...) in order to assess the potential impacts on the circulation. A GeoJSON object may represent a region of space (a Geometry), a spatially-bounded entity (a Feature), or a list of features (a Feature Collection). refer to the document geojson for more information about the modeling and the possible value.

  • CrowdFlowObserved. CrowdFlowObserved

  • EVChargingStation. EV Charging Station

  • FareCollectionSystem. A public transit fare collection system Data Model

  • FleetVehicle. This entity contains a harmonised description of a generic fleet vehicle such as a delivery vehicle, an ambulance or a postal vehicle. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • FleetVehicleOperation. This entity contains a harmonised description of a generic fleet vehicle operation such as a delivery, or a postal collection. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • FleetVehicleStatus. This entity contains a harmonised description of the status of a generic fleet vehicle. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • ItemFlowObserved. The data model intended to measure an observation linked to the movement of an item at a certain location and over a given period. This Data Model proposes an evolution of two Data Model by merging them and integrating all the attributes of the initial version of [TrafficFlowObserved] and [CrowFlowObserved] and by extension any type of item that we want to analyze the movements. Attributes vehicleType and vehicleSubType are removed from the initial data Model in order to become generic itemType and itemSubType of possible values. (people, Type of vehicle, Type of boat, Type of plane, ...).

  • RestrictedTrafficArea. An area of a city in which the traffic generated by cars or any other kind of vehicles is subjected to limitation.

  • RestrictionException. A Restriction Exception represents a particular case that specialise restriction reported in a Restricted Traffic Areas; for instance it could describe particular permissions applied to specific kind vehicles

  • Road. This entity contains a harmonised geographic and contextual description of a road.

  • RoadAccident. A road accident description with causes and aftermath. First version developed in Synchronicity project

  • RoadSegment. This entity contains a harmonised geographic and contextual description of a road segment. A collection of road segments are used to describe a Road.

  • SpecialRestriction. A Special Restriction represents a particular case that specialise restriction reported in a Restricted Traffic Areas; for instance it could describe particular restrictions applied to specific kind vehicles

  • TrafficFlowObserved. An observation of traffic flow conditions at a certain place and time.

  • TrafficViolation. A Data Model for Traffic Violations registered and E-Challans generated in Cities.

  • TransportStation. The data model is a general description of urban stations (Metro, Bus, Tram, Heliport, ...) according to the GFTS standard https://developers.google.com/transit/gtfs/reference/#stopstxt, as well the detailed description of these (means of access, platform, assistance, ...).

  • Vehicle. This entity models a particular vehicle model, including all properties which are common to multiple vehicle instances belonging to such model.

  • VehicleFault. This entity contains a harmonised description of a Vehicle Fault. This entity is primarily associated with the Automotive vertical segment but might also be relevant to Industry, Smart City, Agriculture and related IoT applications.

  • VehicleModel. This entity models a particular vehicle model, including all properties which are common to multiple vehicle instances belonging to such model.

Contributors

Link to the 20 current contributors of the data models of this Subject.

Contribution

You can raise an issue or submit your PR on existing data models

About

Transportation Data Model

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GitHub - vgonzalez7/dataModel.Transportation: Transportation Data Model · GitHub
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dataModel.Transportation

These data models describe the main entities involved with smart applications that deal with transportation issues. This set of entities is primarily associated with the Automotive and Smart City vertical segments and related IoT applications. When feasible, references to existing schema.org entity types and attributes are included. These models have been devised to be as generic as possible, thus allowing to deal with different scenarios

  • Traffic flow monitoring - Private Vehicles. - Public Vehicles (Buses, Trains, etc.). - Municipal Vehicles (pick up lorries, cleaning units, ...) - Special Vehicles (ambulances, fire brigades, ...)

List of data models

The following entity types are available:

  • AnonymousCommuterId. Anonymized identifier for flow monitoring. Includes an origin and destiny property to map its path.

  • AnprFlowObserved. The data model represents an observation linked to the passing of a vehicle at a certain location and at a given time. This Data Model is based on the [dataModel.Transportation/ItemFlowObserved], extended with ANPR specific properties and links to the observation images.

  • APDSObservation. This entity models a particular observation of a set of ANPR camera. The Observation might be done with several ANPR cameras, but is limited to the observation of ONE vehicle. It implements the APDS data model https://www.allianceforparkingdatastandards.org/

  • BikeHireDockingStation. Bike Hire Docking Station

  • BikeLane. A generic bike lane schema

  • CityWork. The Data Model is a contextual description of urban works carried out on a road axis and which can impact individual (Cars, motorcycle, bicycles, .…) or common transport (Tram, Bus, subway). It contains a geographic representation making it possible to locate its work from a specific JSON Object and at a more global level (Road segment, Road, District, ...) in order to assess the potential impacts on the circulation. A GeoJSON object may represent a region of space (a Geometry), a spatially-bounded entity (a Feature), or a list of features (a Feature Collection). refer to the document geojson for more information about the modeling and the possible value.

  • CrowdFlowObserved. CrowdFlowObserved

  • EVChargingStation. EV Charging Station

  • FareCollectionSystem. A public transit fare collection system Data Model

  • FleetVehicle. This entity contains a harmonised description of a generic fleet vehicle such as a delivery vehicle, an ambulance or a postal vehicle. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • FleetVehicleOperation. This entity contains a harmonised description of a generic fleet vehicle operation such as a delivery, or a postal collection. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • FleetVehicleStatus. This entity contains a harmonised description of the status of a generic fleet vehicle. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • ItemFlowObserved. The data model intended to measure an observation linked to the movement of an item at a certain location and over a given period. This Data Model proposes an evolution of two Data Model by merging them and integrating all the attributes of the initial version of [TrafficFlowObserved] and [CrowFlowObserved] and by extension any type of item that we want to analyze the movements. Attributes vehicleType and vehicleSubType are removed from the initial data Model in order to become generic itemType and itemSubType of possible values. (people, Type of vehicle, Type of boat, Type of plane, ...).

  • RestrictedTrafficArea. An area of a city in which the traffic generated by cars or any other kind of vehicles is subjected to limitation.

  • RestrictionException. A Restriction Exception represents a particular case that specialise restriction reported in a Restricted Traffic Areas; for instance it could describe particular permissions applied to specific kind vehicles

  • Road. This entity contains a harmonised geographic and contextual description of a road.

  • RoadAccident. A road accident description with causes and aftermath. First version developed in Synchronicity project

  • RoadSegment. This entity contains a harmonised geographic and contextual description of a road segment. A collection of road segments are used to describe a Road.

  • SpecialRestriction. A Special Restriction represents a particular case that specialise restriction reported in a Restricted Traffic Areas; for instance it could describe particular restrictions applied to specific kind vehicles

  • TrafficFlowObserved. An observation of traffic flow conditions at a certain place and time.

  • TrafficViolation. A Data Model for Traffic Violations registered and E-Challans generated in Cities.

  • TransportStation. The data model is a general description of urban stations (Metro, Bus, Tram, Heliport, ...) according to the GFTS standard https://developers.google.com/transit/gtfs/reference/#stopstxt, as well the detailed description of these (means of access, platform, assistance, ...).

  • Vehicle. This entity models a particular vehicle model, including all properties which are common to multiple vehicle instances belonging to such model.

  • VehicleFault. This entity contains a harmonised description of a Vehicle Fault. This entity is primarily associated with the Automotive vertical segment but might also be relevant to Industry, Smart City, Agriculture and related IoT applications.

  • VehicleModel. This entity models a particular vehicle model, including all properties which are common to multiple vehicle instances belonging to such model.

Contributors

Link to the 20 current contributors of the data models of this Subject.

Contribution

You can raise an issue or submit your PR on existing data models

About

Transportation Data Model

Resources

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Force GitHub README to respect dark mode (function() { var style = document.createElement('style'); style.textContent = ' .markdown-body { color-scheme: dark light; } .markdown-body pre { background: #161b22 !important; } .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; } .markdown-body table th, .markdown-body table td { border-color: #30363d !important; } .markdown-body img { background: #0d1117; } .markdown-body blockquote { border-left-color: #8b949e; } .markdown-body hr { border-color: #30363d; } '; document.head.appendChild(style); })(); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - vgonzalez7/dataModel.Transportation: Transportation Data Model · GitHub
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dataModel.Transportation

These data models describe the main entities involved with smart applications that deal with transportation issues. This set of entities is primarily associated with the Automotive and Smart City vertical segments and related IoT applications. When feasible, references to existing schema.org entity types and attributes are included. These models have been devised to be as generic as possible, thus allowing to deal with different scenarios

  • Traffic flow monitoring - Private Vehicles. - Public Vehicles (Buses, Trains, etc.). - Municipal Vehicles (pick up lorries, cleaning units, ...) - Special Vehicles (ambulances, fire brigades, ...)

List of data models

The following entity types are available:

  • AnonymousCommuterId. Anonymized identifier for flow monitoring. Includes an origin and destiny property to map its path.

  • AnprFlowObserved. The data model represents an observation linked to the passing of a vehicle at a certain location and at a given time. This Data Model is based on the [dataModel.Transportation/ItemFlowObserved], extended with ANPR specific properties and links to the observation images.

  • APDSObservation. This entity models a particular observation of a set of ANPR camera. The Observation might be done with several ANPR cameras, but is limited to the observation of ONE vehicle. It implements the APDS data model https://www.allianceforparkingdatastandards.org/

  • BikeHireDockingStation. Bike Hire Docking Station

  • BikeLane. A generic bike lane schema

  • CityWork. The Data Model is a contextual description of urban works carried out on a road axis and which can impact individual (Cars, motorcycle, bicycles, .…) or common transport (Tram, Bus, subway). It contains a geographic representation making it possible to locate its work from a specific JSON Object and at a more global level (Road segment, Road, District, ...) in order to assess the potential impacts on the circulation. A GeoJSON object may represent a region of space (a Geometry), a spatially-bounded entity (a Feature), or a list of features (a Feature Collection). refer to the document geojson for more information about the modeling and the possible value.

  • CrowdFlowObserved. CrowdFlowObserved

  • EVChargingStation. EV Charging Station

  • FareCollectionSystem. A public transit fare collection system Data Model

  • FleetVehicle. This entity contains a harmonised description of a generic fleet vehicle such as a delivery vehicle, an ambulance or a postal vehicle. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • FleetVehicleOperation. This entity contains a harmonised description of a generic fleet vehicle operation such as a delivery, or a postal collection. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • FleetVehicleStatus. This entity contains a harmonised description of the status of a generic fleet vehicle. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • ItemFlowObserved. The data model intended to measure an observation linked to the movement of an item at a certain location and over a given period. This Data Model proposes an evolution of two Data Model by merging them and integrating all the attributes of the initial version of [TrafficFlowObserved] and [CrowFlowObserved] and by extension any type of item that we want to analyze the movements. Attributes vehicleType and vehicleSubType are removed from the initial data Model in order to become generic itemType and itemSubType of possible values. (people, Type of vehicle, Type of boat, Type of plane, ...).

  • RestrictedTrafficArea. An area of a city in which the traffic generated by cars or any other kind of vehicles is subjected to limitation.

  • RestrictionException. A Restriction Exception represents a particular case that specialise restriction reported in a Restricted Traffic Areas; for instance it could describe particular permissions applied to specific kind vehicles

  • Road. This entity contains a harmonised geographic and contextual description of a road.

  • RoadAccident. A road accident description with causes and aftermath. First version developed in Synchronicity project

  • RoadSegment. This entity contains a harmonised geographic and contextual description of a road segment. A collection of road segments are used to describe a Road.

  • SpecialRestriction. A Special Restriction represents a particular case that specialise restriction reported in a Restricted Traffic Areas; for instance it could describe particular restrictions applied to specific kind vehicles

  • TrafficFlowObserved. An observation of traffic flow conditions at a certain place and time.

  • TrafficViolation. A Data Model for Traffic Violations registered and E-Challans generated in Cities.

  • TransportStation. The data model is a general description of urban stations (Metro, Bus, Tram, Heliport, ...) according to the GFTS standard https://developers.google.com/transit/gtfs/reference/#stopstxt, as well the detailed description of these (means of access, platform, assistance, ...).

  • Vehicle. This entity models a particular vehicle model, including all properties which are common to multiple vehicle instances belonging to such model.

  • VehicleFault. This entity contains a harmonised description of a Vehicle Fault. This entity is primarily associated with the Automotive vertical segment but might also be relevant to Industry, Smart City, Agriculture and related IoT applications.

  • VehicleModel. This entity models a particular vehicle model, including all properties which are common to multiple vehicle instances belonging to such model.

Contributors

Link to the 20 current contributors of the data models of this Subject.

Contribution

You can raise an issue or submit your PR on existing data models

About

Transportation Data Model

Resources

Stars

0 stars

Watchers

0 watching

Forks

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Highlight search terms from Google/DuckDuckGo/Bing referrer (function() { var ref = document.referrer; var terms = []; if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) { var url = new URL(ref); var q = url.searchParams.get('q') || url.searchParams.get('p'); if (q) { terms = q.split(/\s+/).filter(function(t) { return t.length > 2; }); } } if (terms.length === 0) return; var style = document.createElement('style'); style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }'; document.head.appendChild(style); function highlight(node) { if (node.nodeType === 3) { // text node var text = node.textContent; var found = false; terms.forEach(function(term) { var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\]\\]/g, '\\') + ')', 'gi'); if (regex.test(text)) { found = true; var frag = document.createDocumentFragment(); var parts = text.split(regex); parts.forEach(function(part, i) { if (i % 2 === 0) { frag.appendChild(document.createTextNode(part)); } else { var span = document.createElement('span'); span.className = 'userscript-highlight'; span.textContent = part; frag.appendChild(span); } }); node.parentNode.replaceChild(frag, node); } }); } else if (node.nodeType === 1 && node.childNodes) { // element var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT']; if (!skipTags.includes(node.tagName)) { Array.from(node.childNodes).forEach(highlight); } } } highlight(document.body); // Re-highlight on dynamic content var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1 || node.nodeType === 3) highlight(node); }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - vgonzalez7/dataModel.Transportation: Transportation Data Model · GitHub
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dataModel.Transportation

These data models describe the main entities involved with smart applications that deal with transportation issues. This set of entities is primarily associated with the Automotive and Smart City vertical segments and related IoT applications. When feasible, references to existing schema.org entity types and attributes are included. These models have been devised to be as generic as possible, thus allowing to deal with different scenarios

  • Traffic flow monitoring - Private Vehicles. - Public Vehicles (Buses, Trains, etc.). - Municipal Vehicles (pick up lorries, cleaning units, ...) - Special Vehicles (ambulances, fire brigades, ...)

List of data models

The following entity types are available:

  • AnonymousCommuterId. Anonymized identifier for flow monitoring. Includes an origin and destiny property to map its path.

  • AnprFlowObserved. The data model represents an observation linked to the passing of a vehicle at a certain location and at a given time. This Data Model is based on the [dataModel.Transportation/ItemFlowObserved], extended with ANPR specific properties and links to the observation images.

  • APDSObservation. This entity models a particular observation of a set of ANPR camera. The Observation might be done with several ANPR cameras, but is limited to the observation of ONE vehicle. It implements the APDS data model https://www.allianceforparkingdatastandards.org/

  • BikeHireDockingStation. Bike Hire Docking Station

  • BikeLane. A generic bike lane schema

  • CityWork. The Data Model is a contextual description of urban works carried out on a road axis and which can impact individual (Cars, motorcycle, bicycles, .…) or common transport (Tram, Bus, subway). It contains a geographic representation making it possible to locate its work from a specific JSON Object and at a more global level (Road segment, Road, District, ...) in order to assess the potential impacts on the circulation. A GeoJSON object may represent a region of space (a Geometry), a spatially-bounded entity (a Feature), or a list of features (a Feature Collection). refer to the document geojson for more information about the modeling and the possible value.

  • CrowdFlowObserved. CrowdFlowObserved

  • EVChargingStation. EV Charging Station

  • FareCollectionSystem. A public transit fare collection system Data Model

  • FleetVehicle. This entity contains a harmonised description of a generic fleet vehicle such as a delivery vehicle, an ambulance or a postal vehicle. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • FleetVehicleOperation. This entity contains a harmonised description of a generic fleet vehicle operation such as a delivery, or a postal collection. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • FleetVehicleStatus. This entity contains a harmonised description of the status of a generic fleet vehicle. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • ItemFlowObserved. The data model intended to measure an observation linked to the movement of an item at a certain location and over a given period. This Data Model proposes an evolution of two Data Model by merging them and integrating all the attributes of the initial version of [TrafficFlowObserved] and [CrowFlowObserved] and by extension any type of item that we want to analyze the movements. Attributes vehicleType and vehicleSubType are removed from the initial data Model in order to become generic itemType and itemSubType of possible values. (people, Type of vehicle, Type of boat, Type of plane, ...).

  • RestrictedTrafficArea. An area of a city in which the traffic generated by cars or any other kind of vehicles is subjected to limitation.

  • RestrictionException. A Restriction Exception represents a particular case that specialise restriction reported in a Restricted Traffic Areas; for instance it could describe particular permissions applied to specific kind vehicles

  • Road. This entity contains a harmonised geographic and contextual description of a road.

  • RoadAccident. A road accident description with causes and aftermath. First version developed in Synchronicity project

  • RoadSegment. This entity contains a harmonised geographic and contextual description of a road segment. A collection of road segments are used to describe a Road.

  • SpecialRestriction. A Special Restriction represents a particular case that specialise restriction reported in a Restricted Traffic Areas; for instance it could describe particular restrictions applied to specific kind vehicles

  • TrafficFlowObserved. An observation of traffic flow conditions at a certain place and time.

  • TrafficViolation. A Data Model for Traffic Violations registered and E-Challans generated in Cities.

  • TransportStation. The data model is a general description of urban stations (Metro, Bus, Tram, Heliport, ...) according to the GFTS standard https://developers.google.com/transit/gtfs/reference/#stopstxt, as well the detailed description of these (means of access, platform, assistance, ...).

  • Vehicle. This entity models a particular vehicle model, including all properties which are common to multiple vehicle instances belonging to such model.

  • VehicleFault. This entity contains a harmonised description of a Vehicle Fault. This entity is primarily associated with the Automotive vertical segment but might also be relevant to Industry, Smart City, Agriculture and related IoT applications.

  • VehicleModel. This entity models a particular vehicle model, including all properties which are common to multiple vehicle instances belonging to such model.

Contributors

Link to the 20 current contributors of the data models of this Subject.

Contribution

You can raise an issue or submit your PR on existing data models

About

Transportation Data Model

Resources

Stars

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Forks

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Strip utm_, fbclid, gclid, etc. from all links on page (function() { var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content', 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid', 'ref', 'ref_src', 'source', 'medium', 'campaign']; function cleanUrl(url) { try { var u = new URL(url, window.location.origin); var changed = false; trackingParams.forEach(function(p) { if (u.searchParams.has(p)) { u.searchParams.delete(p); changed = true; } }); return changed ? u.toString() : url; } catch (e) { return url; } } function cleanLinks() { document.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } cleanLinks(); var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1) { if (node.tagName === 'A') cleanLinks(); node.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + ' GitHub - vgonzalez7/dataModel.Transportation: Transportation Data Model · GitHub
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dataModel.Transportation

These data models describe the main entities involved with smart applications that deal with transportation issues. This set of entities is primarily associated with the Automotive and Smart City vertical segments and related IoT applications. When feasible, references to existing schema.org entity types and attributes are included. These models have been devised to be as generic as possible, thus allowing to deal with different scenarios

  • Traffic flow monitoring - Private Vehicles. - Public Vehicles (Buses, Trains, etc.). - Municipal Vehicles (pick up lorries, cleaning units, ...) - Special Vehicles (ambulances, fire brigades, ...)

List of data models

The following entity types are available:

  • AnonymousCommuterId. Anonymized identifier for flow monitoring. Includes an origin and destiny property to map its path.

  • AnprFlowObserved. The data model represents an observation linked to the passing of a vehicle at a certain location and at a given time. This Data Model is based on the [dataModel.Transportation/ItemFlowObserved], extended with ANPR specific properties and links to the observation images.

  • APDSObservation. This entity models a particular observation of a set of ANPR camera. The Observation might be done with several ANPR cameras, but is limited to the observation of ONE vehicle. It implements the APDS data model https://www.allianceforparkingdatastandards.org/

  • BikeHireDockingStation. Bike Hire Docking Station

  • BikeLane. A generic bike lane schema

  • CityWork. The Data Model is a contextual description of urban works carried out on a road axis and which can impact individual (Cars, motorcycle, bicycles, .…) or common transport (Tram, Bus, subway). It contains a geographic representation making it possible to locate its work from a specific JSON Object and at a more global level (Road segment, Road, District, ...) in order to assess the potential impacts on the circulation. A GeoJSON object may represent a region of space (a Geometry), a spatially-bounded entity (a Feature), or a list of features (a Feature Collection). refer to the document geojson for more information about the modeling and the possible value.

  • CrowdFlowObserved. CrowdFlowObserved

  • EVChargingStation. EV Charging Station

  • FareCollectionSystem. A public transit fare collection system Data Model

  • FleetVehicle. This entity contains a harmonised description of a generic fleet vehicle such as a delivery vehicle, an ambulance or a postal vehicle. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • FleetVehicleOperation. This entity contains a harmonised description of a generic fleet vehicle operation such as a delivery, or a postal collection. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • FleetVehicleStatus. This entity contains a harmonised description of the status of a generic fleet vehicle. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • ItemFlowObserved. The data model intended to measure an observation linked to the movement of an item at a certain location and over a given period. This Data Model proposes an evolution of two Data Model by merging them and integrating all the attributes of the initial version of [TrafficFlowObserved] and [CrowFlowObserved] and by extension any type of item that we want to analyze the movements. Attributes vehicleType and vehicleSubType are removed from the initial data Model in order to become generic itemType and itemSubType of possible values. (people, Type of vehicle, Type of boat, Type of plane, ...).

  • RestrictedTrafficArea. An area of a city in which the traffic generated by cars or any other kind of vehicles is subjected to limitation.

  • RestrictionException. A Restriction Exception represents a particular case that specialise restriction reported in a Restricted Traffic Areas; for instance it could describe particular permissions applied to specific kind vehicles

  • Road. This entity contains a harmonised geographic and contextual description of a road.

  • RoadAccident. A road accident description with causes and aftermath. First version developed in Synchronicity project

  • RoadSegment. This entity contains a harmonised geographic and contextual description of a road segment. A collection of road segments are used to describe a Road.

  • SpecialRestriction. A Special Restriction represents a particular case that specialise restriction reported in a Restricted Traffic Areas; for instance it could describe particular restrictions applied to specific kind vehicles

  • TrafficFlowObserved. An observation of traffic flow conditions at a certain place and time.

  • TrafficViolation. A Data Model for Traffic Violations registered and E-Challans generated in Cities.

  • TransportStation. The data model is a general description of urban stations (Metro, Bus, Tram, Heliport, ...) according to the GFTS standard https://developers.google.com/transit/gtfs/reference/#stopstxt, as well the detailed description of these (means of access, platform, assistance, ...).

  • Vehicle. This entity models a particular vehicle model, including all properties which are common to multiple vehicle instances belonging to such model.

  • VehicleFault. This entity contains a harmonised description of a Vehicle Fault. This entity is primarily associated with the Automotive vertical segment but might also be relevant to Industry, Smart City, Agriculture and related IoT applications.

  • VehicleModel. This entity models a particular vehicle model, including all properties which are common to multiple vehicle instances belonging to such model.

Contributors

Link to the 20 current contributors of the data models of this Subject.

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Auto-enable theater mode on YouTube (function() { function tryTheater() { var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]'); if (btn && !btn.classList.contains('activated')) { btn.click(); } } // Try immediately tryTheater(); // Try after navigation (SPA) var lastUrl = location.href; setInterval(function() { if (location.href !== lastUrl) { lastUrl = location.href; setTimeout(tryTheater, 500); } }, 1000); // Also try on player load var observer = new MutationObserver(tryTheater); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - vgonzalez7/dataModel.Transportation: Transportation Data Model · GitHub
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dataModel.Transportation

These data models describe the main entities involved with smart applications that deal with transportation issues. This set of entities is primarily associated with the Automotive and Smart City vertical segments and related IoT applications. When feasible, references to existing schema.org entity types and attributes are included. These models have been devised to be as generic as possible, thus allowing to deal with different scenarios

  • Traffic flow monitoring - Private Vehicles. - Public Vehicles (Buses, Trains, etc.). - Municipal Vehicles (pick up lorries, cleaning units, ...) - Special Vehicles (ambulances, fire brigades, ...)

List of data models

The following entity types are available:

  • AnonymousCommuterId. Anonymized identifier for flow monitoring. Includes an origin and destiny property to map its path.

  • AnprFlowObserved. The data model represents an observation linked to the passing of a vehicle at a certain location and at a given time. This Data Model is based on the [dataModel.Transportation/ItemFlowObserved], extended with ANPR specific properties and links to the observation images.

  • APDSObservation. This entity models a particular observation of a set of ANPR camera. The Observation might be done with several ANPR cameras, but is limited to the observation of ONE vehicle. It implements the APDS data model https://www.allianceforparkingdatastandards.org/

  • BikeHireDockingStation. Bike Hire Docking Station

  • BikeLane. A generic bike lane schema

  • CityWork. The Data Model is a contextual description of urban works carried out on a road axis and which can impact individual (Cars, motorcycle, bicycles, .…) or common transport (Tram, Bus, subway). It contains a geographic representation making it possible to locate its work from a specific JSON Object and at a more global level (Road segment, Road, District, ...) in order to assess the potential impacts on the circulation. A GeoJSON object may represent a region of space (a Geometry), a spatially-bounded entity (a Feature), or a list of features (a Feature Collection). refer to the document geojson for more information about the modeling and the possible value.

  • CrowdFlowObserved. CrowdFlowObserved

  • EVChargingStation. EV Charging Station

  • FareCollectionSystem. A public transit fare collection system Data Model

  • FleetVehicle. This entity contains a harmonised description of a generic fleet vehicle such as a delivery vehicle, an ambulance or a postal vehicle. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • FleetVehicleOperation. This entity contains a harmonised description of a generic fleet vehicle operation such as a delivery, or a postal collection. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • FleetVehicleStatus. This entity contains a harmonised description of the status of a generic fleet vehicle. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • ItemFlowObserved. The data model intended to measure an observation linked to the movement of an item at a certain location and over a given period. This Data Model proposes an evolution of two Data Model by merging them and integrating all the attributes of the initial version of [TrafficFlowObserved] and [CrowFlowObserved] and by extension any type of item that we want to analyze the movements. Attributes vehicleType and vehicleSubType are removed from the initial data Model in order to become generic itemType and itemSubType of possible values. (people, Type of vehicle, Type of boat, Type of plane, ...).

  • RestrictedTrafficArea. An area of a city in which the traffic generated by cars or any other kind of vehicles is subjected to limitation.

  • RestrictionException. A Restriction Exception represents a particular case that specialise restriction reported in a Restricted Traffic Areas; for instance it could describe particular permissions applied to specific kind vehicles

  • Road. This entity contains a harmonised geographic and contextual description of a road.

  • RoadAccident. A road accident description with causes and aftermath. First version developed in Synchronicity project

  • RoadSegment. This entity contains a harmonised geographic and contextual description of a road segment. A collection of road segments are used to describe a Road.

  • SpecialRestriction. A Special Restriction represents a particular case that specialise restriction reported in a Restricted Traffic Areas; for instance it could describe particular restrictions applied to specific kind vehicles

  • TrafficFlowObserved. An observation of traffic flow conditions at a certain place and time.

  • TrafficViolation. A Data Model for Traffic Violations registered and E-Challans generated in Cities.

  • TransportStation. The data model is a general description of urban stations (Metro, Bus, Tram, Heliport, ...) according to the GFTS standard https://developers.google.com/transit/gtfs/reference/#stopstxt, as well the detailed description of these (means of access, platform, assistance, ...).

  • Vehicle. This entity models a particular vehicle model, including all properties which are common to multiple vehicle instances belonging to such model.

  • VehicleFault. This entity contains a harmonised description of a Vehicle Fault. This entity is primarily associated with the Automotive vertical segment but might also be relevant to Industry, Smart City, Agriculture and related IoT applications.

  • VehicleModel. This entity models a particular vehicle model, including all properties which are common to multiple vehicle instances belonging to such model.

Contributors

Link to the 20 current contributors of the data models of this Subject.

Contribution

You can raise an issue or submit your PR on existing data models

About

Transportation Data Model

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Remove or un-stick sticky/fixed headers that block content (function() { function unstick() { document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) { if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') { el.style.position = 'static'; el.style.top = 'auto'; el.style.zIndex = 'auto'; } }); } unstick(); var observer = new MutationObserver(unstick); observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] }); })(); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - vgonzalez7/dataModel.Transportation: Transportation Data Model · GitHub
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dataModel.Transportation

These data models describe the main entities involved with smart applications that deal with transportation issues. This set of entities is primarily associated with the Automotive and Smart City vertical segments and related IoT applications. When feasible, references to existing schema.org entity types and attributes are included. These models have been devised to be as generic as possible, thus allowing to deal with different scenarios

  • Traffic flow monitoring - Private Vehicles. - Public Vehicles (Buses, Trains, etc.). - Municipal Vehicles (pick up lorries, cleaning units, ...) - Special Vehicles (ambulances, fire brigades, ...)

List of data models

The following entity types are available:

  • AnonymousCommuterId. Anonymized identifier for flow monitoring. Includes an origin and destiny property to map its path.

  • AnprFlowObserved. The data model represents an observation linked to the passing of a vehicle at a certain location and at a given time. This Data Model is based on the [dataModel.Transportation/ItemFlowObserved], extended with ANPR specific properties and links to the observation images.

  • APDSObservation. This entity models a particular observation of a set of ANPR camera. The Observation might be done with several ANPR cameras, but is limited to the observation of ONE vehicle. It implements the APDS data model https://www.allianceforparkingdatastandards.org/

  • BikeHireDockingStation. Bike Hire Docking Station

  • BikeLane. A generic bike lane schema

  • CityWork. The Data Model is a contextual description of urban works carried out on a road axis and which can impact individual (Cars, motorcycle, bicycles, .…) or common transport (Tram, Bus, subway). It contains a geographic representation making it possible to locate its work from a specific JSON Object and at a more global level (Road segment, Road, District, ...) in order to assess the potential impacts on the circulation. A GeoJSON object may represent a region of space (a Geometry), a spatially-bounded entity (a Feature), or a list of features (a Feature Collection). refer to the document geojson for more information about the modeling and the possible value.

  • CrowdFlowObserved. CrowdFlowObserved

  • EVChargingStation. EV Charging Station

  • FareCollectionSystem. A public transit fare collection system Data Model

  • FleetVehicle. This entity contains a harmonised description of a generic fleet vehicle such as a delivery vehicle, an ambulance or a postal vehicle. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • FleetVehicleOperation. This entity contains a harmonised description of a generic fleet vehicle operation such as a delivery, or a postal collection. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • FleetVehicleStatus. This entity contains a harmonised description of the status of a generic fleet vehicle. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • ItemFlowObserved. The data model intended to measure an observation linked to the movement of an item at a certain location and over a given period. This Data Model proposes an evolution of two Data Model by merging them and integrating all the attributes of the initial version of [TrafficFlowObserved] and [CrowFlowObserved] and by extension any type of item that we want to analyze the movements. Attributes vehicleType and vehicleSubType are removed from the initial data Model in order to become generic itemType and itemSubType of possible values. (people, Type of vehicle, Type of boat, Type of plane, ...).

  • RestrictedTrafficArea. An area of a city in which the traffic generated by cars or any other kind of vehicles is subjected to limitation.

  • RestrictionException. A Restriction Exception represents a particular case that specialise restriction reported in a Restricted Traffic Areas; for instance it could describe particular permissions applied to specific kind vehicles

  • Road. This entity contains a harmonised geographic and contextual description of a road.

  • RoadAccident. A road accident description with causes and aftermath. First version developed in Synchronicity project

  • RoadSegment. This entity contains a harmonised geographic and contextual description of a road segment. A collection of road segments are used to describe a Road.

  • SpecialRestriction. A Special Restriction represents a particular case that specialise restriction reported in a Restricted Traffic Areas; for instance it could describe particular restrictions applied to specific kind vehicles

  • TrafficFlowObserved. An observation of traffic flow conditions at a certain place and time.

  • TrafficViolation. A Data Model for Traffic Violations registered and E-Challans generated in Cities.

  • TransportStation. The data model is a general description of urban stations (Metro, Bus, Tram, Heliport, ...) according to the GFTS standard https://developers.google.com/transit/gtfs/reference/#stopstxt, as well the detailed description of these (means of access, platform, assistance, ...).

  • Vehicle. This entity models a particular vehicle model, including all properties which are common to multiple vehicle instances belonging to such model.

  • VehicleFault. This entity contains a harmonised description of a Vehicle Fault. This entity is primarily associated with the Automotive vertical segment but might also be relevant to Industry, Smart City, Agriculture and related IoT applications.

  • VehicleModel. This entity models a particular vehicle model, including all properties which are common to multiple vehicle instances belonging to such model.

Contributors

Link to the 20 current contributors of the data models of this Subject.

Contribution

You can raise an issue or submit your PR on existing data models

About

Transportation Data Model

Resources

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

, 'i'); if (__m === '*' || __re.test(location.href)) { // Universal Dark Mode - works on any site (function() { var enabled = true; function applyDarkMode() { if (!enabled) return; // Create style element if it doesn't exist var style = document.getElementById('universal-dark-mode-style'); if (!style) { style = document.createElement('style'); style.id = 'universal-dark-mode-style'; document.head.appendChild(style); } // Dark mode CSS - inverts colors but preserves images/video style.textContent = ' /* Invert everything except media */ html { filter: invert(1) hue-rotate(180deg) !important; background: #1a1a2e !important; } /* Restore images, videos, iframes, canvas */ img, video, iframe, canvas, svg, picture, [style*="background-image"] { filter: invert(1) hue-rotate(180deg) !important; } /* Preserve specific elements that should not be inverted */ .no-dark-mode, .no-dark-mode *, [data-theme="light"], [data-theme="light"], .ace_editor, .ace_editor *, .CodeMirror, .CodeMirror *, .monaco-editor, .monaco-editor *, .markdown-body pre, .markdown-body pre *, .highlight, .highlight *, pre code, pre code * { filter: none !important; } /* Fix common UI elements */ .modal, .popup, .dropdown-menu, .tooltip, .popover { filter: invert(1) hue-rotate(180deg) !important; background: #2d2d44 !important; border-color: #444 !important; } /* Scrollbars */ ::-webkit-scrollbar { background: #1a1a2e !important; } ::-webkit-scrollbar-thumb { background: #444 !important; } ::-webkit-scrollbar-thumb:hover { background: #555 !important; } /* Selection */ ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; } ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; } '; } function removeDarkMode() { var style = document.getElementById('universal-dark-mode-style'); if (style) style.remove(); } // Toggle with Alt+Shift+D document.addEventListener('keydown', function(e) { if (e.altKey && e.shiftKey && e.key === 'D') { e.preventDefault(); enabled = !enabled; if (enabled) { applyDarkMode(); console.log('[Universal Dark Mode] Enabled'); } else { removeDarkMode(); console.log('[Universal Dark Mode] Disabled'); } } }); // Apply on load applyDarkMode(); // Re-apply on dynamic content var observer = new MutationObserver(function(mutations) { if (enabled && !document.getElementById('universal-dark-mode-style')) { applyDarkMode(); } }); observer.observe(document.head, { childList: true }); console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle'); })(); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })(); GitHub - vgonzalez7/dataModel.Transportation: Transportation Data Model · GitHub
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dataModel.Transportation

These data models describe the main entities involved with smart applications that deal with transportation issues. This set of entities is primarily associated with the Automotive and Smart City vertical segments and related IoT applications. When feasible, references to existing schema.org entity types and attributes are included. These models have been devised to be as generic as possible, thus allowing to deal with different scenarios

  • Traffic flow monitoring - Private Vehicles. - Public Vehicles (Buses, Trains, etc.). - Municipal Vehicles (pick up lorries, cleaning units, ...) - Special Vehicles (ambulances, fire brigades, ...)

List of data models

The following entity types are available:

  • AnonymousCommuterId. Anonymized identifier for flow monitoring. Includes an origin and destiny property to map its path.

  • AnprFlowObserved. The data model represents an observation linked to the passing of a vehicle at a certain location and at a given time. This Data Model is based on the [dataModel.Transportation/ItemFlowObserved], extended with ANPR specific properties and links to the observation images.

  • APDSObservation. This entity models a particular observation of a set of ANPR camera. The Observation might be done with several ANPR cameras, but is limited to the observation of ONE vehicle. It implements the APDS data model https://www.allianceforparkingdatastandards.org/

  • BikeHireDockingStation. Bike Hire Docking Station

  • BikeLane. A generic bike lane schema

  • CityWork. The Data Model is a contextual description of urban works carried out on a road axis and which can impact individual (Cars, motorcycle, bicycles, .…) or common transport (Tram, Bus, subway). It contains a geographic representation making it possible to locate its work from a specific JSON Object and at a more global level (Road segment, Road, District, ...) in order to assess the potential impacts on the circulation. A GeoJSON object may represent a region of space (a Geometry), a spatially-bounded entity (a Feature), or a list of features (a Feature Collection). refer to the document geojson for more information about the modeling and the possible value.

  • CrowdFlowObserved. CrowdFlowObserved

  • EVChargingStation. EV Charging Station

  • FareCollectionSystem. A public transit fare collection system Data Model

  • FleetVehicle. This entity contains a harmonised description of a generic fleet vehicle such as a delivery vehicle, an ambulance or a postal vehicle. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • FleetVehicleOperation. This entity contains a harmonised description of a generic fleet vehicle operation such as a delivery, or a postal collection. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • FleetVehicleStatus. This entity contains a harmonised description of the status of a generic fleet vehicle. This entity is primarily associated with the vertical segment of the transport and logistics but may also be used many other related IoT applications.

  • ItemFlowObserved. The data model intended to measure an observation linked to the movement of an item at a certain location and over a given period. This Data Model proposes an evolution of two Data Model by merging them and integrating all the attributes of the initial version of [TrafficFlowObserved] and [CrowFlowObserved] and by extension any type of item that we want to analyze the movements. Attributes vehicleType and vehicleSubType are removed from the initial data Model in order to become generic itemType and itemSubType of possible values. (people, Type of vehicle, Type of boat, Type of plane, ...).

  • RestrictedTrafficArea. An area of a city in which the traffic generated by cars or any other kind of vehicles is subjected to limitation.

  • RestrictionException. A Restriction Exception represents a particular case that specialise restriction reported in a Restricted Traffic Areas; for instance it could describe particular permissions applied to specific kind vehicles

  • Road. This entity contains a harmonised geographic and contextual description of a road.

  • RoadAccident. A road accident description with causes and aftermath. First version developed in Synchronicity project

  • RoadSegment. This entity contains a harmonised geographic and contextual description of a road segment. A collection of road segments are used to describe a Road.

  • SpecialRestriction. A Special Restriction represents a particular case that specialise restriction reported in a Restricted Traffic Areas; for instance it could describe particular restrictions applied to specific kind vehicles

  • TrafficFlowObserved. An observation of traffic flow conditions at a certain place and time.

  • TrafficViolation. A Data Model for Traffic Violations registered and E-Challans generated in Cities.

  • TransportStation. The data model is a general description of urban stations (Metro, Bus, Tram, Heliport, ...) according to the GFTS standard https://developers.google.com/transit/gtfs/reference/#stopstxt, as well the detailed description of these (means of access, platform, assistance, ...).

  • Vehicle. This entity models a particular vehicle model, including all properties which are common to multiple vehicle instances belonging to such model.

  • VehicleFault. This entity contains a harmonised description of a Vehicle Fault. This entity is primarily associated with the Automotive vertical segment but might also be relevant to Industry, Smart City, Agriculture and related IoT applications.

  • VehicleModel. This entity models a particular vehicle model, including all properties which are common to multiple vehicle instances belonging to such model.

Contributors

Link to the 20 current contributors of the data models of this Subject.

Contribution

You can raise an issue or submit your PR on existing data models

About

Transportation Data Model

Resources

Stars

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Watchers

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Forks

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