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Phone"},{"category_id":"e77d9098-5fa0-4953-9681-6652a229f600","description":"","image_url":"ec95c6db-28f1-46ff-8f42-43236dff1b53.png","id":"7f5aa308-4716-48f4-9dea-898ffdde806a","name":"[Eco-Movement] EV Charging Station Location & Tariffs Data - real-time API","type_id":"8e8f5094-8df7-4479-b9d5-de236bb3d5fd","url_id":"global-ev-charge-point-data","published_step":2,"data_specs":{"params":[{"name":"Complete overview: https://www.eco-movement.com/attribute-definition/?swcfpc=1 ","frequency":""},{"name":"Location","frequency":"Daily"},{"name":"Operator","frequency":"Daily"},{"name":"Pricing","frequency":"Daily"},{"name":"(Derived) Opening times","frequency":"Daily"},{"name":"Power","frequency":"Daily"},{"name":"Power type (AC, DC)","frequency":"Daily"},{"name":"Connector","frequency":"Daily"},{"name":"Location access type","frequency":"Daily"},{"name":"Location facilities","frequency":"Daily"}],"sources":["Connected cars","Charge Point Operators"," Verified Sources","Mobility Service Providers"," In-house market research","Machine Learning"],"language":["English"],"data_volume":"Over 550.000 connectors","availability":{"real_time":"","historical":""},"geo_coverage":["ASIA","AFRICA","EUROPE","NORTH_AMERICA","SOUTH_AMERICA","OCEANIA","Europe","North America"]},"project_data_category.name":"EV Charging","category_name":"EV Charging"},{"category_id":"1be67912-4f98-4a65-84ff-84cc120a048b","description":"","image_url":"9028ba05-463b-42fc-b918-ac9a17024923.jpg","id":"676018dc-e6de-4d4c-aec1-da2d58142081","name":"Mobile signal strength","type_id":"13bbf0af-8c8f-4554-8247-8de6643fa25c","url_id":"mobile-signal-strength","published_step":3,"data_specs":{"params":[{"name":"Average signal strength value","frequency":""},{"name":"Network technology (2G, 3G, 4G)","frequency":""},{"name":"Mobile Country Code (MCC)","frequency":""},{"name":"Mobile Network Code (MNC)","frequency":""},{"name":"H3-11 hexgrid","frequency":""},{"name":"Longitude","frequency":""},{"name":"Latitude","frequency":""},{"name":"Confidence interval","frequency":""},{"name":"Value generation method (measured or calculated)","frequency":""},{"name":"Qualitative description of signal strength","frequency":""}],"sources":["Mobile apps"],"language":["English"],"data_volume":"120 million hexagons","availability":{"historical":"6 months"},"geo_coverage":["Europe"]},"project_data_category.name":"Mobile Phone","category_name":"Mobile Phone"},{"category_id":"d13fbdee-8f71-4e16-ab8c-24a5bb884304","description":"","image_url":"3ce1bde4-9e83-470f-924b-8c9178b11da2.png","id":"e15e12bc-4cff-438c-9e2e-16d366a45924","name":"HERE Traffic Patterns","type_id":"13bbf0af-8c8f-4554-8247-8de6643fa25c","url_id":"here-traffic-patterns","published_step":3,"data_specs":{"params":[{"name":"TMC (Traffic Message Channel) Location Code info","frequency":"In 15 minutes intervals, for each day of the week"},{"name":"Average speed (mph/kph) in 15-minute or 60-minute time intervals","frequency":"In 15 minutes intervals, for each day of the week"}],"sources":["Vehicle probe data"],"language":["English"],"data_volume":"Trillions of vehicle speed observations","availability":{"historical":"3 years of historical observations"},"geo_coverage":["Andorra","Argentina","Australia","Austria","Belgium","Bosnia and Herzegovina","Brazil","Bulgaria","Canada","Chile","Colombia","Croatia","Czech Republic","Denmark","Egypt","Estonia","Finland","France","Germany","Greece","Hungary","Iceland","India","Indonesia","Ireland","Israel","Italy","Jordan","Kosovo","Latvia","Lebanon","Lithuania","Luxembourg","North Macedonia","Malaysia","Mexico","Monaco","Montenegro","Netherlands","New Zealand","Norway","Philippines","Peru","Poland","Portugal","Qatar","Romania","Russia","San Marino","Saudi Arabia","Serbia","Singapore","Slovakia","Slovenia","South Africa","Spain","Sweden","Switzerland","Turkey","Ukraine","United Arab Emirates","United Kingdom","USA","Vatican City","Vietnam","Cyprus"]},"project_data_category.name":"Road Conditions","category_name":"Road Conditions"},{"category_id":"d13fbdee-8f71-4e16-ab8c-24a5bb884304","description":"","image_url":"5d2575f7-f1b8-4419-88ac-416eba224767.png","id":"762e5247-5057-4e72-9e9f-b62ddb85a361","name":"HERE Traffic Analytics","type_id":"13bbf0af-8c8f-4554-8247-8de6643fa25c","url_id":"here-traffic-analytics","published_step":3,"data_specs":{"params":[{"name":"Timestamp","frequency":""},{"name":"Location reference (e.g. TMC-Traffic Message Channel location code)","frequency":""},{"name":"Epoch (data broken into 5-minute, 15-minute or 60-minute epochs across the day)","frequency":""},{"name":"Length (the length of the road segment being reported on, in meters)","frequency":""},{"name":"Free Flow speed","frequency":""},{"name":"Mean speed","frequency":""},{"name":"Standard deviation (of all speed observations)","frequency":""},{"name":"Min & Max Speeds","frequency":""},{"name":"Confidence (the number of observations in the epoch, and the variance of those observations)","frequency":""}],"sources":["Vehicle probe data"],"language":["English"],"data_volume":"More than a trillion probe points","availability":{"historical":"5 years of historical data"},"geo_coverage":["Andorra","Argentina","Australia","Austria","Belgium","Brazil","Bulgaria","Canada","Croatia","Czech Republic","Denmark","Finland","France","Germany","Greece","Hungary","India","Indonesia","Ireland","Italy","Luxembourg","Malaysia","Mexico","Monaco","Netherlands","New Zealand","Norway","Poland","Portugal","Qatar","Romania","Russia","San Marino","Saudi Arabia","Singapore","Slovakia","Slovenia","South Africa","Spain","Sweden","Switzerland","Turkey","Ukraine","United Arab Emirates","United Kingdom","USA","Vatican City"]},"project_data_category.name":"Road Conditions","category_name":"Road Conditions"},{"category_id":"d13fbdee-8f71-4e16-ab8c-24a5bb884304","description":"","image_url":"37f39aa1-2380-465b-9a8c-beafe91de756.png","id":"80d16157-9261-4cfc-98a9-261860716fa4","name":"HERE Real Time Traffic Flow & Incidents","type_id":"8e8f5094-8df7-4479-b9d5-de236bb3d5fd","url_id":"here-real-time-traffic-flow-&-incidents","published_step":2,"data_specs":{"params":[{"name":"TMC (Traffic Message Channel) Location Code info","frequency":"Per minute"},{"name":"Timestamp","frequency":"Per minute"},{"name":"Speed (uncapped, average capped by speed limit)","frequency":"Per minute"},{"name":"Free flow speed","frequency":"Per minute"},{"name":"Jam factor (0->10)","frequency":"Per minute"},{"name":"Jam tendency","frequency":"Per minute"},{"name":"Lane info","frequency":"Per minute"},{"name":"Incident type & description","frequency":"Per 2 minutes"},{"name":"Incident start & end time","frequency":"Per 2 minutes"},{"name":"Incident criticality & road closed info","frequency":"Per 2 minutes"},{"name":"Vehicle restrictions","frequency":"Per minute"},{"name":"Map version","frequency":""},{"name":"Map_DVN","frequency":""},{"name":"TMC table version","frequency":""},{"name":"Units","frequency":""},{"name":"Roadway sections (RWS)","frequency":""},{"name":"Roadway (RW)","frequency":""},{"name":"RW info (name, country code, table, units etc.) ","frequency":""},{"name":"Flow Items (FI) per RW","frequency":""},{"name":"FI info (TMC, DLR, SHP, Speed, Traversability etc.)","frequency":"Per minute"}],"sources":["Probe data","Vehicle sensor data","Fixed sensors","Government sources","Trillions of historical traffic records"],"language":["English"],"data_volume":"Trillions of historical traffic records","availability":{"real_time":"Traffic flow updated every minute and incident data is updated every 2 minutes"},"geo_coverage":["Andorra","Argentina","Australia","Austria","Belgium","Bosnia and Herzegovina","Brazil","Bulgaria","Canada","Chile","Colombia","Croatia","Czech Republic","Denmark","Estonia","Finland","France","Germany","Greece","China","Hungary","India","Indonesia","Ireland","Italy","Latvia","Lithuania","Luxembourg","Malaysia","Mexico","Monaco","Montenegro","Netherlands","New Zealand","Norway","Philippines","Peru","Poland","Portugal","Qatar","Romania","Russia","San Marino","Saudi Arabia","Serbia","Singapore","Slovenia","South Africa","Spain","Sweden","Switzerland","Turkey","Ukraine","United Arab Emirates","United Kingdom","USA","Vatican City","Vietnam","Cyprus"]},"project_data_category.name":"Road Conditions","category_name":"Road Conditions"},{"category_id":"3bad6aa3-dabc-46c4-bce8-e3191d6b3b5b","description":"","image_url":null,"id":"844bdf93-5440-4070-b34a-bbf6cf36c477","name":"Hotel & Flight Demand Forecast ","type_id":"8e8f5094-8df7-4479-b9d5-de236bb3d5fd","url_id":"hotel-&-flight-demand-forecast---market-insight-(ota-insight)","published_step":2,"data_specs":{"params":[],"sources":["Search data","hotel","flight"],"language":["English"],"data_volume":"300+ markets (cities)","availability":{"forecast":"Next 365 days"},"geo_coverage":["ASIA","AFRICA","EUROPE","NORTH_AMERICA","SOUTH_AMERICA","OCEANIA"]},"project_data_category.name":"Other","category_name":"Other"},{"category_id":"3bad6aa3-dabc-46c4-bce8-e3191d6b3b5b","description":"","image_url":null,"id":"fd972cce-035c-4f01-96b5-2f09ba452eed","name":"Hotel Rate Data ","type_id":"8e8f5094-8df7-4479-b9d5-de236bb3d5fd","url_id":"ota-insight---rate-insight-(hotel-rate-data)","published_step":2,"data_specs":{"params":[],"sources":["Search Data","Online Hotel Rates"],"language":["English","French","Japanese"],"data_volume":"55,000+ hotels","availability":{"forecast":"Next 365 Days","real_time":""},"geo_coverage":["ASIA","AFRICA","EUROPE","NORTH_AMERICA","SOUTH_AMERICA","OCEANIA"]},"project_data_category.name":"Other","category_name":"Other"},{"category_id":"ad03fae1-a5ad-427a-a9b8-743fee39d1ed","description":"","image_url":"988a972a-3ba4-4ca0-9006-f59b0b3b2a31.png","id":"4caef44c-eaea-47f8-94b6-233d65353e3c","name":"Points of Interest - Greece","type_id":"13bbf0af-8c8f-4554-8247-8de6643fa25c","url_id":"points-of-interest---greece","published_step":3,"data_specs":{"params":[],"sources":["On-site manual count","Vehicle telematics devices"],"language":["Greek","English"],"data_volume":"over 116,000 points ","availability":{"real_time":""},"geo_coverage":["Greece"]},"project_data_category.name":"POI","category_name":"POI"},{"category_id":"50c30d34-9dab-4447-af72-96c10eb44789","description":"","image_url":"c93b4e6c-9de6-4678-ad09-ee95a9ce1e31.png","id":"6da49ead-bfcd-4059-8077-6a7d25c563a0","name":"Street network","type_id":"13bbf0af-8c8f-4554-8247-8de6643fa25c","url_id":"street-network","published_step":3,"data_specs":{"params":[{"name":"Direction","frequency":"2-3 times per year"},{"name":"parity","frequency":"2-3 times per year"},{"name":"hierachy","frequency":"2-3 times per year"},{"name":"oneway","frequency":"2-3 times per year"},{"name":"navigation","frequency":"2-3 times per year"}],"sources":["Vehicle telematics devices"],"language":["English","Greek"],"data_volume":"412,000 navigable kilometers of road network","availability":{"real_time":"updated 2-3 times a year"},"geo_coverage":["Greece"]},"project_data_category.name":"Map Data","category_name":"Map Data"},{"category_id":"50c30d34-9dab-4447-af72-96c10eb44789","description":"","image_url":"2e28f4b9-61a0-4bf0-81dc-e3d6ac6d98a6.png","id":"7eca8745-4e43-4c47-a202-450e9c1e1efb","name":"Greek Post Codes Polygons","type_id":"13bbf0af-8c8f-4554-8247-8de6643fa25c","url_id":"greek-post-codes-polygons","published_step":3,"data_specs":{"params":[{"name":"Area","frequency":"2-3 times yearly"},{"name":"Postal code","frequency":"2-3 times yearly"},{"name":"Prefecture","frequency":"2-3 times yearly"},{"name":"Municipality name","frequency":"2-3 times yearly"},{"name":"Area multipolygon coordinates","frequency":"2-3 times yearly"}],"sources":["Hellenic Postal service"],"language":["English","Greek"],"data_volume":"1453 Post Code polygons","availability":{"real_time":null,"historical":null},"geo_coverage":["Greece"]},"project_data_category.name":"Map Data","category_name":"Map Data"},{"category_id":"ad03fae1-a5ad-427a-a9b8-743fee39d1ed","description":"Company sector \n<hr />\nRetail information data Category of data \n<hr />\nFootfall data Data sources \n<hr />\nLocatus Fieldworkers Temporal availability \n<hr />\nHistorical data dating back to over 10 years for most areas Geographical coverage \n<hr />\nBenelux (Belgium, Netherlands, Luxembourg) Key data attributes \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Footfall per street segment</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Footfall pattern over the day</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Footfall for every day of the week</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Footfall Mapped</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Number of visitors per week and per 1.000 m2 RFS</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Number of outlets within shopping area</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Penetration rate in a shopping area</li>\n</ul>\nSee attached sample file for more details on the available data attributes Data frequency \n<hr />\nData is updated every year or every two years Delivery method \n<hr />\nPDF files available in Mobito’s Amazon S3 Bucket Language \n<hr />\nDutch and English in one report Pricing model \n<hr />\n<ul>\n<li> One-off delivery:  € 295* per report</li>\n</ul>\nVolume discount:\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">1 or 2 reports: € 295* per report</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">3 up to 8 reports: € 275* per report</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">9 up to 25 reports: € 255* per report </li>\n</ul>\n*VAT excluded \nData Product Description \n<hr />\nLocatus is a market leader in the field of independently sourced retail information in Europe. Locatus gathers its own data on all shops and consumer-oriented service companies and makes this information accessible for its clients through an online database. For over 20 years we count Footfall in a very structured manner, so different retail areas can be compared also in time. \nThis footfall report gives you an insight into the footfall flow within a shopping area. How many visitors does an area have, where do they walk and when are they visiting? Because Locatus has a uniform approach to counting footfall for years, we are also able to identify changes over the years. This report provides you with reliable data regarding shopping area’s popularity, information indispensable for location decisions, market analyses, valuations and monitoring of shopping areas.","image_url":"af42d60e-d062-4f25-a837-b67e11a1d563.png","id":"32c6011c-dcab-48e8-b442-e1a5bc4c0e1d","name":"Footfall Data Reports within Shopping Areas","type_id":"13bbf0af-8c8f-4554-8247-8de6643fa25c","url_id":"footfall-data-reports-within-shopping-areas","published_step":3,"data_specs":{"params":[{"name":"Footfall per street segment","frequency":"Data is updated every one or two years"},{"name":"Footfall pattern over the day","frequency":""},{"name":"Footfall for every day of the week","frequency":""},{"name":"Footfall Mapped","frequency":""},{"name":"Number of visitors per week and per 1.000 m2 RFS","frequency":""},{"name":"Number of outlets within shopping area","frequency":""},{"name":"Penetration rate in a shopping area","frequency":""}],"sources":["On-site manual count"],"language":["English","Dutch"],"data_volume":"N/A","availability":{"historical":"Dating back to over 10 years for most areas"},"geo_coverage":["Belgium","Netherlands","Luxembourg"]},"project_data_category.name":"POI","category_name":"POI"},{"category_id":"5de1963c-4f7f-4fae-8021-86797a72beba","description":"Company sector\n<hr />\nGlobal weather data provider Category of data \n<hr />\nWeather & climate data Data sources \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Modis satellite-based near real-time flood occurrence and storm surge data.</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">All storm surge and flooding occurrence data is at the meter level.</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Incorporates NWS Hurricane Center flooding models & other global models.</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Includes NWS and Canadian flood warnings (polygons).</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Climate influenced long-term and seasonal forecast data available.</li>\n</ul>\nData volume size \n<hr />\n20mb\nTemporal availability \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Historical data back to 2012 in hourly and daily format</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Near real-time</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Forecast</li>\n</ul>\nGeographical coverage \n<hr />\nGlobal\nKey data attributes \n<hr />\nPlease see the attached sample files for a better overview of supported variables.\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Precipitation</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">River flooding</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Drought conditions</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Storm surge</li>\n</ul>\nData frequency \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Inundation data: This consists of the past 14 days of flood detection on historically dry land and it shows the percentage of time over the past 14 days that flooding was detected (e.g., if flooding was detected over a certain area over the past 7 days, then the 14 day product would show 50%. </li>\n<li>Flood data: This consists of 2 day flood detection. The product represents areas where at least two flooding detentions happened over a two day time period.</li>\n</ul>\n Delivery method \n<hr />\nDelivery via Mobito’s Amazon S3 Buckets Language \n<hr />\nEN Pricing model\n<hr />\nPricing dependent on product and geographic scope. Data Product Description\n<hr />\nOur storm surge and flooding geospatial products incorporate metadata and deep, historical context down to the meter-scale to provide powerful insights that integrate seamlessly into any GIS application or other visualization tool.","image_url":"0acae688-a6d4-4f57-85e7-f0950947a7c7.png","id":"b0864807-215a-4682-be0a-448e8afdd60f","name":"Weather Source Flood Data","type_id":"13bbf0af-8c8f-4554-8247-8de6643fa25c","url_id":"weather-source-flood-data","published_step":3,"data_specs":{"params":[{"name":"Precipitation","frequency":""},{"name":"River flooding","frequency":""},{"name":"Drought conditions","frequency":""},{"name":"Storm surge","frequency":""}],"sources":["Satelites","Weather stations","Radars"],"language":["English"],"data_volume":"20mb (general size for the 14 day flooding data globally)","availability":{"forecast":"","real_time":"","historical":"Dating back to 2012 in hourly and daily format."},"geo_coverage":["ASIA","AFRICA","EUROPE","NORTH_AMERICA","SOUTH_AMERICA","OCEANIA"]},"project_data_category.name":"Weather & Air quality","category_name":"Weather & Air quality"},{"category_id":"ad03fae1-a5ad-427a-a9b8-743fee39d1ed","description":"Company sector \n<hr />\nRetail information data Category of data \n<hr />\nPoint of Interest (POI) Data sources \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">On-site retail visits</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Data exchange with retailers</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Desk research & scrapping</li>\n</ul>\nData volume size \n<hr />\n450k retail records across 200 sectors (food & beverage, transport & fuel, supermarkets, banks etc.) See attached 'Retail Sectors\" document for a full list of supported sectors Temporal availability \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Current</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Historical data dating back to 2008</li>\n</ul>\nGeographical coverage \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Benelux (Belgium, Netherlands, Luxembourg)</li>\n</ul>\nKey data attributes \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Location (x, y coordinates)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Name</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Address</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Retail sector, category & activity</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Floor space</li>\n</ul>\nSee attached sample file for more details on the available data attributes Data frequency \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Data is updated on a weekly basis based on desk research and scrapping. </li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Constant updates based on on-site retail visits</li>\n</ul>\nDelivery method \n<hr />\nCSV files available in Mobito’s Amazon S3 Buckets Language \n<hr />\nEN Pricing model \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">One-off delivery: 2.40€* per outlet</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Yearly subscription: 1.20€* per outlet (minimum 3 year subscription) </li>\n</ul>\n*VAT excluded Data Product Description \n<hr />\nLocatus is a market leader in the field of independently sourced retail information in Europe. Locatus gathers its own data on all shops and consumer-oriented service companies and makes this information accessible for its clients through an online database. \nThe Locatus database provides property-level information, such as the name of each outlet, its retail floor area and the retail sector in which it operates. Furthermore we record information about shopping and catchment areas and footfall, provided <a href=\"../../module/32c6011c-dcab-48e8-b442-e1a5bc4c0e1d\">here</a>.","image_url":"ceb7353d-2ae1-443f-9feb-d61b0400bb83.png","id":"23a807bf-29bc-492a-8cad-d96c7a7240ce","name":"Retail Store Data","type_id":"13bbf0af-8c8f-4554-8247-8de6643fa25c","url_id":"retail-store-data","published_step":3,"data_specs":{"params":[{"name":"Location (x, y coordinates)","frequency":"Data is updated on a weekly basis based on desk research and scrapping. Constant updates based on on-site retail visits"},{"name":"Name","frequency":""},{"name":"Address","frequency":""},{"name":"Retail sector, category & activity","frequency":""},{"name":"Floor space","frequency":""}],"sources":["On-site manual count","Data exchange with retailers","Desk research & scrapping"],"language":["English"],"data_volume":"450k retail records across 200 sectors (food & beverage, transport & fuel, supermarkets, banks etc.)","availability":{"real_time":"Current retailers status","historical":"Dating back to 2008"},"geo_coverage":["Belgium","Netherlands","Luxembourg"]},"project_data_category.name":"POI","category_name":"POI"},{"category_id":"1be67912-4f98-4a65-84ff-84cc120a048b","description":"Company sector \n<hr />\nMobility B2C application Category of data \n<hr />\nTransport Data Data sources \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Ualabee Mobile app SDK</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Manual real-time reports by Ualabee app users</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Local authorities & government</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Mobility operators</li>\n</ul>\nData features \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Origin-destination trip searches in the app</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Completed trips</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Security reports</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Trip quality reports</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Trips with vehicle occupancy data</li>\n</ul>\n* Please contact us to know the data volume size of every feature.\nTemporal availability \n<hr />\nHistorical data until the day before the query is run for the following datasets:\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Origin-destination trip searches dating back to  2018</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Completed trips dating back to 2019</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Trip quality reports dating back to 2019</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Security reports dating back to 2019</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Trips with vehicle occupancy dating back to 2019</li>\n</ul>\nGeographical coverage \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Argentina (Alta Gracia, Bahía Blanca, Buenos Aires, Córdoba Capital, Junín, La Plata, Mendoza, Río Cuarto, Río Tercero, Rosario, Salta, San Francisco, Santa Fe, Villa Carlos Paz, Villa María)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Chile (Concepción, Santiago de Chile, Valparaíso)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Colombia (Bogotá, Cali and Medellín)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">México (Ciudad de México)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Uruguay (Montevideo)</li>\n</ul>\nKey data attributes \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Origin_location (longitude / latitude)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Destination_location (longitude / latitude)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Timestamp (microseconds)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Advertising_id</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Search_radius</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Search_session_uuid</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">User_location (longitude / latitude)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Transport_types</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Taxi_remis_results_found</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Results_found</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Security issue</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Vehicle occupancy level</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">User satisfaction rating (and reason)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">User basic demographics (age, gender)</li>\n</ul>\nData frequency \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Event triggered for reports coming from app users (security, quality)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Origin-destination trip searches dataset is updated upon each user search</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Completed trips and vehicle occupancy is updated after trip is completed</li>\n</ul>\nDelivery method \n<hr />\nCSV files available in Mobito’s Amazon S3 Buckets Language \n<hr />\nEnglish (Spanish for manual user report fields) Pricing model \n<hr />\n1500$ / Month for 1 city coverage Data Product Description \n<hr />\nUalabee is a crowdsourced mobility solution that gives passengers the fastest and safest way to move from Point A to Point B, combining schedules and routes of urban transportation, micro-mobility, and ride-hailing services. showing the best choice for their commutes.\nIt also offers the unique opportunity to app users to create real time reports about security issues (e.g. low lightning in a bus stop, robbery, dangerous driving etc) as well as user rating on the quality of trips.\nBy looking at the daily mobility traffic, Ualabee can create datasets about different vehicle occupancy levels.\nThe data is mostly used by Public and Private Transport Agencies, Mobility Analysts and Geo survey companies.\nUse cases: \nUrban planning systems can add geolocated information layers in their maps.\nIt can also be helpful for smart home applications to get contextual information about the real-time status of urban mobility in Latam cities.\nAnalysts can use our data to build their custom models based on our historical data, to predict the behavior of mobility flow in Latam cities, predict road accidents, detours and transit anomalies in time, allowing them to notify and react in advance.\nIt is helpful to better plan and build the next transport network architecture, understanding where to set the stops/stations and routes, knowing from where to where people are moving everyday in their daily commutes to optimize energy and money and making passengers happy.\nGovernment and public agencies can use the security data to fix bad lightning and better distribute the security personnel around the city, locating the hot spots regarding crime and other insecurity reasons.","image_url":"f984cbfd-bbbd-4921-a146-3983c7fcfc79.png","id":"2aaf28a0-efbb-4b0c-9586-78fa05948fd1","name":"Origin-Destination Mobility Data","type_id":"13bbf0af-8c8f-4554-8247-8de6643fa25c","url_id":"origin-destination-mobility-data","published_step":3,"data_specs":{"params":[{"name":"Origin (long/ lat)","frequency":"- Event triggered for reports coming from app users (security, quality)"},{"name":"Destination (long/ lat)","frequency":"- Origin-destination trip searches dataset is updated upon each user search"},{"name":"Timestamp","frequency":"- Completed trips and vehicle occupancy is updated after trip is completed"},{"name":"Advertising ID","frequency":""},{"name":"Search radius","frequency":""},{"name":"Search session uuid","frequency":""},{"name":"User location (long/ lat)","frequency":""},{"name":"Transport types","frequency":""},{"name":"Taxi remis results found","frequency":""},{"name":"Results found","frequency":""},{"name":"Security issue","frequency":""},{"name":"Vehicle occupancy level","frequency":""},{"name":"User satisfaction rating (and reason)","frequency":""},{"name":"User basic demographics (age, gender)","frequency":""}],"sources":["Mobile apps","Public sector municipalities","Manual real-time reports by Ualabee app users","Mobility operators"],"language":["English","Spanish"],"data_volume":"Data volume size of every dataset can be shared upon request","availability":{"historical":"Until the day before the query is run"},"geo_coverage":["Argentina","Chile","Colombia","Mexico","Uruguay"]},"project_data_category.name":"Mobile Phone","category_name":"Mobile Phone"},{"category_id":"61b7129a-ac95-49ac-a917-b1a1e7576aea","description":"Company sector \n<hr />\nRide hailing aggregator solution Category of data\n<hr />\nMobility operators Data sources\n<hr />\nData captured by the Good Seat API which is integrated in numerous 3rd party platforms offering data and booking services for available ride hailing and taxi operators Data volume size \n<hr />\nNumber of trips: 15k completed trips Temporal availability \n<hr />\nHistorical data dating back to November 2019 Geographical coverage\n<hr />\nFrance Key data attributes \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Origin location (longitude, latitude, street, postal code, city, country)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Destination location (longitude, latitude, street, postal code, city, country)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Trip status (planned, booked, accepted, completed, cancelled)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Trip start timestamp</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Trip end timestamp</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Provider name (e.g. Uber, Free Now, Bolt, Heetch) </li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Timeframe</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Trip price</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Event creation timestamp</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Event last modified timestamp</li>\n</ul>\nDelivery method \n<hr />\nCSV files available in Mobito’s Amazon S3 Buckets Language \n<hr />\nEN Pricing model \n<hr />\n5€/trip requested with a minimum of 1000 requested trips. Data product description \n<hr />\nAt The Good Seat, we believe that to create the world of tomorrow, more inclusive and sustainable, we have to change the way people move first.\nOur data comes from our white-label solution that makes it easy for experience platforms to add ride-hailing & taxi offers to their product. We provide these platforms - in several industries (mobility, travel, hospitality, corporates and other) - with a comparator supporting booking and payment, and favoring better offers for everyone (electric vehicles, accessibility preference and other)\nOur data is exhaustive and will inform you both on ride-hailing providers data and ride-hailing users' habits. ","image_url":"c47d3eb4-ea12-4044-96da-01d60168c298.png","id":"053bae1f-9fbd-46bf-90e9-edddb53709d4","name":"Maas/SMART CITY : Ride-hailing & Taxi Trips (Uber, Bolt, Freenow, taxis...)","type_id":"13bbf0af-8c8f-4554-8247-8de6643fa25c","url_id":"ride-hailing-&-taxi-trips","published_step":3,"data_specs":{"params":[{"name":"- Origin (long/ lat, street, postal code, city, country)"},{"name":"- Destination location (longitude, latitude, street, postal code, city, country)"},{"name":"- Trip status (planned, booked, accepted, completed, cancelled)"},{"name":"- Timestamp (trip start, trip end)"},{"name":"- Provider name (e.g. Uber, Free Now, Bolt, Heetch)"},{"name":"- Timeframe"},{"name":"- Trip price"},{"name":"- Timestamp (event creation, last modified)"}],"sources":["Mobile apps","Data captured by the Good Seat API which is integrated in numerous 3rd party platforms offering data and booking services for available ride hailing and taxi operators","On-demand data creation available","Fleet operations"],"language":["English","French"],"data_volume":"Number of trips: 10K-100k completed trips","availability":{"forecast":"1 month","real_time":"24 hours","historical":"Dating back to November 2019"},"geo_coverage":["France","EUROPE","Mexico"]},"project_data_category.name":"Mobility Services","category_name":"Mobility Services"},{"category_id":"1be67912-4f98-4a65-84ff-84cc120a048b","description":"Company sector \n<hr />\nIoT B2B solutions Category of data\n<hr />\nFootfall data and pedestrian behavioral data Data sources\n<hr />\nNodes devices* detecting radio frequency signals generated by mobile devices in proximity and optical sensors at mall & store entrances\n*Our Nodes devices  are intelligent routers that collect radio frequency signals of Smartphones at 2.4GHz and 5GHz . The raw data is transmitted via internet connectivity to our cloud platform and in turn a unique distinct user id ( anonymous ) is assigned to each smartphone. The presence of the smartphone is subsequently detected in each zone anonymously  and mobility behavior and patterns are derived . Data volume size \n<hr />\nTotal 1,000 Nodes in EU Temporal availability \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Real time (10’ frequency time)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">1-day replication time (daily updates)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Historical data (3 years)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Competitive comparison data by year & by month</li>\n</ul>\nGeographical coverage \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Spain</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">France</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">UK</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Greece</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Portugal</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Germany</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Saudi Arabia</li>\n</ul>\nKey data attributes \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Number of unique visitors within a Node proximity area</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Footfall data at optical sensors location (e.g. mall & store entrance)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Paths that users follow</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Visit times, dwell time,  average presence time in a zone</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Areas of interest</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Heatmaps</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Loyalty info (frequency of visits, first time / recurrent time visitors ratio)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Behavioural profiling</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Mobile device info (device model, operating system)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Opportunities - frequency of visits of unique visitors (by day & by zone distributions, by time frame)</li>\n</ul>\nSee attached sample files for detailed information Data frequency \n<hr />\nData granularity options:\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Near real time (every 10 minutes) </li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Per hour</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Per day</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Per month</li>\n</ul>\nDelivery method \n<hr />\nAPI Language \n<hr />\nEN Pricing model  \n<hr />\n5.75 euros / 1000 users/ month \nFor example: Accessing 1 year of data including 1,000,000 unique users would cost 5.75*1,000 *12 = 69,000 euros\nMinimum transaction: 23,000 euros Company and Data Product Description \n<hr />\nSCCA Advisory Ltd in cooperation with its vendors and partners as well as its customers develops intelligent solutions for businesses in the retail, Malls, Hospitality, Tourism, entertainment, health, insurance and public sectors. \nWithin this framework our company has established exclusive partnerships  with the leading industry technology companies ( Seeketing SA, Neoma Ltd)  certified in the areas of Proximity Marketing and Analytics.\nOur Nodes or Beacons track the physical locations of mobile devices of end users and communicate targeted messages and marketing content videos, photos, loyalty coupons or offerings that have been provided by our customers.\nAt SCCA Advisory Ltd we connect the physical and digital worlds for our customers and contribute to their efforts to create better brand experiences on the go. Our solutions comply 100% with EU GDPR regulations and laws for private data protection.\nOur differential advantage is that we identify uniquely and reliably and track over 80% of SP’s based on 2.4GHz, 2.5GHz or 5GHz  radio-frequency band transmissions solving the randomization problem, while at the same time our Nodes based  solution does not require any  application. In parallel we connect the digital behavior of the customer ( App ,Web)  with its physical presence in the zones in a unique way that leverages  omnichannel philosophy . Our technology provides data reliability, something that has been proven in several use cases over a large number of installations.\nBased on existing installations and legal rights we can provide available anonymous data for customers in the fields of behavioral and footfall data , telematics in vehicle and location services data  and finally the new field of Telematics in Health data.","image_url":"1d3c7308-d6ae-41a1-9eeb-d1e4918f9b80.PNG","id":"7e8c972e-69b4-46bf-8570-96b0a82152d5","name":"Pedestrian Behavioral Data","type_id":"8e8f5094-8df7-4479-b9d5-de236bb3d5fd","url_id":"pedestrian-behavioral-data","published_step":2,"data_specs":{"params":[{"name":"- Number of unique visitors within a Node proximity area","frequency":"Near real time (every 10 minutes), Per hour, Per day, Per month"},{"name":"- Footfall data at optical sensors location (e.g. mall & store entrance)","frequency":""},{"name":"- Paths that users follow","frequency":""},{"name":"- Visit times, dwell time, average presence time in a zone","frequency":""},{"name":"- Areas of interest","frequency":""},{"name":"- Heatmaps","frequency":""},{"name":"- Loyalty info (frequency of visits, first time / recurrent time visitors ratio)","frequency":""},{"name":"- Behavioural profiling","frequency":""},{"name":"- Mobile device info (device model, operating system)","frequency":""},{"name":"- Opportunities - frequency of visits of unique visitors (by day & by zone distributions, by time frame)","frequency":""}],"sources":["Nodes devices detecting radio frequency signals generated by mobile devices in proximity and optical sensors at mall & store entrances"],"language":["English"],"data_volume":"Total 1,000 Nodes in EU","availability":{"real_time":"10' frequency time","historical":"1-day replication time for daily updates. Up to 3 years of historical data"},"geo_coverage":["Spain","United Kingdom","France","Portugal","Germany","Saudi Arabia"]},"project_data_category.name":"Mobile Phone","category_name":"Mobile Phone"},{"category_id":"5de1963c-4f7f-4fae-8021-86797a72beba","description":"Forecast data provides a forward forecast view of up to 240 hours or 15 full days.\nCompany sector \n<hr />\nGlobal weather data provider Category of data \n<hr />\nWeather & climate data Data sources \n<hr />\n<ul>\n<li>Airport observation stations</li>\n<li>NOAA & NWS data</li>\n<li>Satellites</li>\n<li>Radar</li>\n<li>Weather analyses and model outputs</li>\n<li>IoT devices and sensors</li>\n<li>Telematics</li>\n</ul>\nTemporal availability \n<hr />\n<ul>\n<li>240 hours or 15 full days of Forecast data in hourly and daily format </li>\n</ul>\nGeographical coverage \n<hr />\nGlobal Key data attributes \n<hr />\nPlease see the API documentation for a full list of supported variables.\n<ul>\n<li>Cloud cover</li>\n<li>Humidity</li>\n<li>Precipitation</li>\n<li>Solar radiation</li>\n<li>Surface pressure</li>\n<li>Temperature</li>\n<li>Wet & dry bulb</li>\n<li>Wind speed & direction (10m, 80m and 100m)</li>\n<li>Snowfall</li>\n<li>Pressure</li>\n<li>Hail</li>\n<li>Hurricane</li>\n<li>Lightning strike</li>\n<li>River flooding</li>\n<li>Solar Radiation</li>\n<li>Astronomy data</li>\n<li>Heat Index</li>\n</ul>\nDelivery method \n<hr />\nAPI Language \n<hr />\nEN, FR Pricing model \n<hr />\nSee the Pricing section in the top right-hand side of the page for the tiered API pricing details Company Description\n<hr />\nOnPoint Weather is described exactly as it sounds, weather data for any location at any point in time. Unlike other providers who rely on singular inputs that in many instances may be many miles away from your location of interest to be meaningful or actionable, Weather Source ingests all of the best weather sensing inputs available including:\n<ul>\n<li>Airport observation stations</li>\n<li>NOAA & NWS data</li>\n<li>Satellites</li>\n<li>Radar</li>\n<li>IoT Devices and other sensor information</li>\n<li>Telematics</li>\n<li>Weather analyses and model outputs</li>\n</ul>\nWeather Source unifies and homogenizes the inputs on our high resolution global grid. The globally consistent, 5-kilometer OnPoint Grid covers every land mass in the world and up to 200 miles offshore. Each grid point - nearly 2 million in total - represents a “virtual” weather station with a unique OnPoint ID from which weather data can be mapped to any lat/lon coordinates or specified geographically bounded areas such as:\n<ul>\n<li>Census tract/block</li>\n<li>County/parish or state</li>\n<li>Designated Market Area (DMA)</li>\n<li>ZIP/Postal Code</li>\n</ul>\nAll Weather Source data is available in hourly or daily format. Daily format includes minimum and maximum values as well as daily averages for each supported weather parameter.","image_url":"cb091ad3-06a6-423a-87f9-afdd12aa1416.png","id":"adcb8037-af33-49b7-a86f-6230b1a4d7fc","name":"Weather Source GFS Forecast Weather Data","type_id":"8e8f5094-8df7-4479-b9d5-de236bb3d5fd","url_id":"weather-source-gfs-forecast-weather-data","published_step":3,"data_specs":{"params":[{"name":"Clouds","frequency":""},{"name":"Humidity","frequency":""},{"name":"Precipitation","frequency":""},{"name":"Solar radiation","frequency":""},{"name":"Surface pressure","frequency":""},{"name":"Temperature","frequency":""},{"name":"Wet & dry bulb","frequency":""},{"name":"Wind speed","frequency":""},{"name":"Wind direction","frequency":""},{"name":"Snowfall","frequency":""},{"name":"Air pressure","frequency":""},{"name":"Hail","frequency":""},{"name":"Hurricane","frequency":""},{"name":"Lightning","frequency":""},{"name":"River flooding","frequency":""},{"name":"Solar radiation","frequency":""},{"name":"Astronomy data","frequency":""},{"name":"Heat index","frequency":""}],"sources":["Weather stations","Satelites","Radars","IoT hardware","NOAA & NWS data","Weather analyses and model outputs","Telematics"],"language":["English","French"],"data_volume":"N/A","availability":{"forecast":"240 hours or 15 full days of Forecast data in hourly and daily format."},"geo_coverage":["ASIA","AFRICA","EUROPE","NORTH_AMERICA","SOUTH_AMERICA","OCEANIA"]},"project_data_category.name":"Weather & Air quality","category_name":"Weather & Air quality"},{"category_id":"5de1963c-4f7f-4fae-8021-86797a72beba","description":"The Historical dataset is a curated continuum of historical data from the year 2000 to present in both hourly and daily format.\nCompany sector \n<hr />\nGlobal weather data provider Category of data \n<hr />\nWeather & climate data Data sources \n<hr />\n<ul>\n<li>Airport observation stations</li>\n<li>NOAA & NWS data</li>\n<li>Satellites</li>\n<li>Radar</li>\n<li>Weather analyses and model outputs</li>\n<li>IoT devices and sensors</li>\n<li>Telematics</li>\n</ul>\nTemporal availability\n<hr />\n<ul>\n<li>Historical data back to 2000 in both hourly and daily format</li>\n<li>Present conditions in hourly and daily format</li>\n</ul>\nGeographical coverage \n<hr />\nGlobal Key data attributes \n<hr />\nPlease see the API documentation for a full list of supported variables.\n<ul>\n<li>Cloud cover</li>\n<li>Humidity</li>\n<li>Precipitation</li>\n<li>Solar radiation</li>\n<li>Surface pressure</li>\n<li>Temperature</li>\n<li>Wet & dry bulb</li>\n<li>Wind speed & direction (10m, 80m and 100m)</li>\n<li>Snowfall</li>\n<li>Pressure</li>\n<li>Hail</li>\n<li>Hurricane</li>\n<li>Lightning strike</li>\n<li>River flooding</li>\n<li>Solar Radiation</li>\n<li>Astronomy data</li>\n<li>Heat Index</li>\n</ul>\nDelivery method \n<hr />\nAPI Language \n<hr />\nEN, FR Pricing model\n<hr />\nSee the Pricing section in the top right-hand side of the page for the tiered API pricing details Company Description\n<hr />\nOnPoint Weather is described exactly as it sounds, weather data for any location at any point in time. Unlike other providers who rely on singular inputs that in many instances may be many miles away from your location of interest to be meaningful or actionable, Weather Source ingests all of the best weather sensing inputs available including:\n<ul>\n<li>Airport observation stations</li>\n<li>NOAA & NWS data</li>\n<li>Satellites</li>\n<li>Radar</li>\n<li>IoT Devices and other sensor information</li>\n<li>Telematics</li>\n<li>Weather analyses and model outputs</li>\n</ul>\nWeather Source unifies and homogenizes the inputs on our high resolution global grid. The globally consistent, 5-kilometer OnPoint Grid covers every land mass in the world and up to 200 miles offshore. Each grid point - nearly 2 million in total - represents a “virtual” weather station with a unique OnPoint ID from which weather data can be mapped to any lat/lon coordinates or specified geographically bounded areas such as:\n<ul>\n<li>Census tract/block</li>\n<li>County/parish or state</li>\n<li>Designated Market Area (DMA)</li>\n<li>ZIP/Postal Code</li>\n</ul>\nAll Weather Source data is available in hourly or daily format. Daily format includes minimum and maximum values as well as daily averages for each supported weather parameter.","image_url":"80d39fd3-d171-4c2f-82cf-f90081da1ddd.png","id":"78547ea6-e38f-44f4-97db-398a4ed98623","name":"Weather Source Historical Weather Data","type_id":"8e8f5094-8df7-4479-b9d5-de236bb3d5fd","url_id":"weather-source-historical-weather-data","published_step":3,"data_specs":{"params":[{"name":"Clouds","frequency":""},{"name":"Humidity","frequency":""},{"name":"Precipitation","frequency":""},{"name":"Solar radiation","frequency":""},{"name":"Surface pressure","frequency":""},{"name":"Temperature","frequency":""},{"name":"Wet & dry bulb","frequency":""},{"name":"Wind speed","frequency":""},{"name":"Wind direction","frequency":""},{"name":"Snow","frequency":""},{"name":"Air pressure","frequency":""},{"name":"Hail","frequency":""},{"name":"Hurricane","frequency":""},{"name":"Lightning","frequency":""},{"name":"River flooding","frequency":""},{"name":"Solar radiation","frequency":""},{"name":"Astronomy data","frequency":""},{"name":"Heat index","frequency":""}],"sources":["Weather stations","Satelites","Radars","IoT hardware","Weather analyses and model outputs","Telematics"],"language":["English","French"],"data_volume":"N/A","availability":{"real_time":"Present conditions in hourly and daily format","historical":"Back to 2000 in both hourly and daily format"},"geo_coverage":["ASIA","AFRICA","EUROPE","NORTH_AMERICA","SOUTH_AMERICA","OCEANIA"]},"project_data_category.name":"Weather & Air quality","category_name":"Weather & Air quality"},{"category_id":"5de1963c-4f7f-4fae-8021-86797a72beba","description":"Company sector \n<hr />\nGlobal weather data provider Category of data \n<hr />\nWeather data Data sources \n<hr />\nWeather station observations, radar & satellite information, global & regional models, and other proprietary sources.\nGerman Icon and GFS models are used for Forecast data in the EU. Temporal availability \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Real time</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Forecast (15 days for daily, hourly and other intervals)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Historical data (since 2011)</li>\n</ul>\nGeographical coverage \n<hr />\nGlobal Key data attributes \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Temperature</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Precipitation</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Wind speed & direction</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Air pressure</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Visibility</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Humidity</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Dew point</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Sun + Moon</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Alerts</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Lightning</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Air Quality</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Tropical Cyclones</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Daily Records</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Earthquakes</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Indices (Health & Outdoors)</li>\n</ul>\nDelivery method \n<hr />\nAPI Language \n<hr />\nEN Pricing model \n<hr />\nPricing packages with different access limits (see pricing section for details) Product Description \n<hr />\nThe AerisWeather API provides a broad range of hyper-local environmental data for global businesses, with access to historical datasets, granular forecasts, and unique data endpoints.\n It offers the ability to query by location name, coordinates, postal codes or for some endpoints within a circular or polygonal search area.","image_url":"833b8766-9451-4e00-a27d-0c3837de1350.jpg","id":"40386356-3ea5-47bf-bf13-154f325c7976","name":"Vaisala Xweather-Flex with Lightning and Air Quality Data","type_id":"8e8f5094-8df7-4479-b9d5-de236bb3d5fd","url_id":"aerisweather-api","published_step":3,"data_specs":{"params":[{"name":"Temperature"},{"name":"Precipitation"},{"name":"Wind speed"},{"name":"Wind direction"},{"name":"Air pressure"},{"name":"Visibility"},{"name":"Humidity"},{"name":"Dew point"},{"name":"Sun + Moon"},{"name":"Alerts"},{"name":"Lightning"},{"name":"Air quality"},{"name":"Tropical cyclones"},{"name":"Daily records"},{"name":"Earthquakes"},{"name":"Indices (Health & Outdoors)"}],"sources":["Weather stations","Satelites","Radars","Sensors","Regional and Global Models","Other Proprietary Models and Sources"],"language":["English"],"data_volume":"N/A","availability":{"forecast":"15 days for daily, hourly and other intervals","real_time":"","historical":"Dating back to 2011"},"geo_coverage":["Europe","Africa","Australia","Asia","Russia","North America","South America"]},"project_data_category.name":"Weather & Air quality","category_name":"Weather & Air quality"},{"category_id":"5de1963c-4f7f-4fae-8021-86797a72beba","description":"Nowcast is a representation of present conditions for any location at any point in time.\n \nCompany sector \n<hr />\nGlobal weather data provider Category of data \n<hr />\nWeather & climate data Data sources \n<hr />\n<ul>\n<li>Airport observation stations</li>\n<li>NOAA & NWS data</li>\n<li>Satellites</li>\n<li>Radar</li>\n<li>Weather analyses and model outputs</li>\n<li>IoT devices and sensors</li>\n<li>Telematics</li>\n</ul>\nTemporal availability \n<hr />\n<ul>\n<li>Current conditions in hourly and daily format</li>\n</ul>\nGeographical coverage \n<hr />\nGlobal Key data attributes \n<hr />\nPlease see the API documentation for a full list of supported variables.\n<ul>\n<li>Cloud cover</li>\n<li>Humidity</li>\n<li>Precipitation</li>\n<li>Solar radiation</li>\n<li>Surface pressure</li>\n<li>Temperature</li>\n<li>Wet & dry bulb</li>\n<li>Wind speed & direction (10m, 80m and 100m)</li>\n<li>Snowfall</li>\n<li>Pressure</li>\n<li>Hail</li>\n<li>Hurricane</li>\n<li>Lightning strike</li>\n<li>River flooding</li>\n<li>Solar Radiation</li>\n<li>Astronomy data</li>\n<li>Heat Index</li>\n</ul>\nDelivery method \n<hr />\nAPI Language \n<hr />\nEN, FR Pricing model\n<hr />\nSee the Pricing section in the top right-hand side of the page for the tiered API pricing details Company Description \n<hr />\nOnPoint Weather is described exactly as it sounds, weather data for any location at any point in time. Unlike other providers who rely on singular inputs that in many instances may be many miles away from your location of interest to be meaningful or actionable, Weather Source ingests all of the best weather sensing inputs available including:\n<ul>\n<li>Airport observation stations</li>\n<li>NOAA & NWS data</li>\n<li>Satellites</li>\n<li>Radar</li>\n<li>IoT Devices and other sensor information</li>\n<li>Telematics</li>\n<li>Weather analyses and model outputs</li>\n</ul>\nWeather Source unifies and homogenizes the inputs on our high resolution global grid. The globally consistent, 5-kilometer OnPoint Grid covers every land mass in the world and up to 200 miles offshore. Each grid point - nearly 2 million in total - represents a “virtual” weather station with a unique OnPoint ID from which weather data can be mapped to any lat/lon coordinates or specified geographically bounded areas such as:\n<ul>\n<li>Census tract/block</li>\n<li>County/parish or state</li>\n<li>Designated Market Area (DMA)</li>\n<li>ZIP/Postal Code</li>\n</ul>\nAll Weather Source data is available in hourly or daily format. Daily format includes minimum and maximum values as well as daily averages for each supported weather parameter.","image_url":"d9ba31fd-3967-4998-a9f4-240aa940f81a.png","id":"99785ab1-0206-41e4-bb3d-5907eceb9219","name":"Weather Source Nowcast (Present Conditions) Weather Data","type_id":"8e8f5094-8df7-4479-b9d5-de236bb3d5fd","url_id":"weather-source-nowcast-(present-conditions)-weather-data","published_step":3,"data_specs":{"params":[{"name":"Clouds","frequency":""},{"name":"Humidity","frequency":""},{"name":"Precipitation","frequency":""},{"name":"Solar radiation","frequency":""},{"name":"Surface pressure","frequency":""},{"name":"Temperature","frequency":""},{"name":"Wet & dry bulb","frequency":""},{"name":"Wind speed","frequency":""},{"name":"Wind direction","frequency":""},{"name":"Snow","frequency":""},{"name":"Air pressure","frequency":""},{"name":"Hail","frequency":""},{"name":"Hurricane","frequency":""},{"name":"Lightning","frequency":""},{"name":"River flooding","frequency":""},{"name":"Solar radiation","frequency":""},{"name":"Astronomy data","frequency":""},{"name":"Heat Index","frequency":""}],"sources":["Weather stations","Satelites","Radars","IoT hardware","NOAA & NWS data","Weather analyses and model outputs","Telematics"],"language":["English","French"],"data_volume":"N/A","availability":{"real_time":"Current conditions in hourly and daily format"},"geo_coverage":["ASIA","AFRICA","EUROPE","NORTH_AMERICA","SOUTH_AMERICA","OCEANIA"]},"project_data_category.name":"Weather & Air quality","category_name":"Weather & Air quality"},{"category_id":"5de1963c-4f7f-4fae-8021-86797a72beba","description":"Climatology is the statistics of weather over time and provides valuable informations such as the mean, standard deviation and frequency of occurrence information.\nCompany sector \n<hr />\nGlobal weather data provider Category of data \n<hr />\nWeather & climate data Data sources \n<hr />\n<ul>\n<li>Airport observation stations</li>\n<li>NOAA & NWS data</li>\n<li>Satellites</li>\n<li>Radar</li>\n<li>Weather analyses and model outputs</li>\n<li>IoT devices and sensors</li>\n<li>Telematics</li>\n</ul>\nTemporal availability \n<hr />\n<ul>\n<li>Hourly and daily format.</li>\n</ul>\nGeographical coverage \n<hr />\nGlobal Key data attributes \n<hr />\nPlease see the API documentation for a full list of supported variables.\n<ul>\n<li>Cloud cover</li>\n<li>Humidity</li>\n<li>Precipitation</li>\n<li>Solar radiation</li>\n<li>Surface pressure</li>\n<li>Temperature</li>\n<li>Wet & dry bulb</li>\n<li>Wind speed & direction (10m, 80m and 100m)</li>\n<li>Snowfall</li>\n<li>Pressure</li>\n<li>Hail</li>\n<li>Hurricane</li>\n<li>Lightning strike</li>\n<li>River flooding</li>\n<li>Solar Radiation</li>\n<li>Astronomy data</li>\n<li>Heat Index</li>\n</ul>\nDelivery method \n<hr />\nAPI Language \n<hr />\nEN, FR Pricing model\n<hr />\nSee the Pricing section in the top right-hand side of the page for the tiered API pricing details Company Description \n<hr />\nClimatology is the statistics of weather over time and provides valuable information such as the mean, std. dev. and frequency of occurrence information.\n OnPoint Weather is described exactly as it sounds, weather data for any location at any point in time. Unlike other providers who rely on singular inputs that in many instances may be many miles away from your location of interest to be meaningful or actionable, Weather Source ingests all of the best weather sensing inputs available including:\n<ul>\n<li>Airport observation stations</li>\n<li>NOAA & NWS data</li>\n<li>Satellites</li>\n<li>Radar</li>\n<li>IoT Devices and other sensor information</li>\n<li>Telematics</li>\n<li>Weather analyses and model outputs</li>\n</ul>\nWeather Source unifies and homogenizes the inputs on our high resolution global grid. The globally consistent, 5-kilometer OnPoint Grid covers every land mass in the world and up to 200 miles offshore. Each grid point - nearly 2 million in total - represents a “virtual” weather station with a unique OnPoint ID from which weather data can be mapped to any lat/lon coordinates or specified geographically bounded areas such as:\n<ul>\n<li>Census tract/block</li>\n<li>County/parish or state</li>\n<li>Designated Market Area (DMA)</li>\n<li>ZIP/Postal Code</li>\n</ul>\nAll Weather Source data is available in hourly or daily format. Daily format includes minimum and maximum values as well as daily averages for each supported weather parameter.","image_url":"e813009e-0ef7-4823-aa98-b644c7d0b5ba.png","id":"5e092b88-d692-435c-8957-9f16913b77f3","name":"Weather Source Climatology Weather Data","type_id":"8e8f5094-8df7-4479-b9d5-de236bb3d5fd","url_id":"weather-source-climatology-weather-data","published_step":3,"data_specs":{"params":[{"name":"Clouds","frequency":""},{"name":"Humidity","frequency":""},{"name":"Precipitation","frequency":""},{"name":"Solar radiation","frequency":""},{"name":"Surface pressure","frequency":""},{"name":"Temperature","frequency":""},{"name":"Wet & dry bulb","frequency":""},{"name":"Wind speed","frequency":""},{"name":"Wind direction","frequency":""},{"name":"Snow","frequency":""},{"name":"Air pressure","frequency":""},{"name":"Hail","frequency":""},{"name":"Hurricane","frequency":""},{"name":"Lightning","frequency":""},{"name":"River flooding","frequency":""},{"name":"Solar radiation","frequency":""},{"name":"Astronomy data","frequency":""},{"name":"Heat index","frequency":""}],"sources":["Weather stations","Satelites","Radars","IoT hardware","NOAA & NWS data","Weather analyses and model outputs","Telematics"],"language":["English","French"],"data_volume":"N/A","availability":{"historical":"Statistics of weather over time in hourly and daily format."},"geo_coverage":["ASIA","AFRICA","EUROPE","NORTH_AMERICA","SOUTH_AMERICA","OCEANIA"]},"project_data_category.name":"Weather & Air quality","category_name":"Weather & Air quality"},{"category_id":"5de1963c-4f7f-4fae-8021-86797a72beba","description":"Company sector \n<hr />\nAir quality global data provider Category of data \n<hr />\nAir quality Data sources \n<hr />\nPatented eLichens algorithms using weather data, real-time traffic data, and local air quality agencies data including the eLichens hardware air quality sensors Temporal availability \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Real time</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Forecast data: up to 4-days</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Historical data: Starting from October 2020</li>\n</ul>\nGeographical coverage \n<hr />\nGlobal Key data attributes \n<hr />\nA. Pollutants: NO2, O3, PM10, PM2.5\nPollutants concentration:\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"2\">In terms of the proportion of the total volume that it accounts for</li>\n<li style=\"font-weight: 400;\" aria-level=\"2\">In terms of weight of pollutant within a standard volume of air</li>\n</ul>\nB. Air Quality Indices (AQI):\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"2\">the U.S. Environmental Protection Agency (EPA) index, which is mainly taken into account in the United States</li>\n<li style=\"font-weight: 400;\" aria-level=\"2\">the Citeair index, developed during the Citeair European project, and used to compare air quality situation in European cities</li>\n<li style=\"font-weight: 400;\" aria-level=\"2\">eLichens Air Quality Index (eAQI)</li>\n</ul>\nC. Pollen: Birch, Grass, Olive, Ragweed Data frequency \n<hr />\nHourly updates Delivery method \n<hr />\nAPI Language \n<hr />\nEN Pricing model \n<hr />\nPricing package with access limits (see Pricing section) Company Description \n<hr />\nThe AQ eLichens API can be divided into three main products:\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Geolocated API: choose a specific latitude and longitude anywhere in the world, and obtain historic, current and future air quality description in terms of main pollutants concentration, pollen concentration and air quality indexes</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Street-level locations API: through this API, you can obtain summary measurements (minimum, maximum and average) coming from a hyper-local Air Quality model powered by eLichens for + 300 locations around the world where this model is deployed.</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Local Agency Stations API: through this API, you can obtain measurements and forecasts of + 8000 local agency stations around the world.</li>\n</ol>\nAll the API data can be queried in the endpoints listed below.\n NOTE!: This is a free trial expiring after 15 days","image_url":"10174de6-26af-4215-9450-1096a38fa338.png","id":"77783e57-af4e-40ee-a95d-5e31b091a41f","name":"Air Quality API - Free Trial","type_id":"8e8f5094-8df7-4479-b9d5-de236bb3d5fd","url_id":"air-quality-api---free-trial","published_step":3,"data_specs":{"params":[{"name":"NO2 pollutant","frequency":"Hourly updates for all parameters"},{"name":"O3 pollutant","frequency":""},{"name":"PM10 pollutant","frequency":""},{"name":"PM2.5 pollutant","frequency":""},{"name":"Pollutants concentration","frequency":""},{"name":"EPA AQI","frequency":""},{"name":"Citeair AQI","frequency":""},{"name":"eAQI (eLichens AQI)","frequency":""},{"name":"Birch pollen","frequency":""},{"name":"Grass pollen","frequency":""},{"name":"Olive pollen","frequency":""},{"name":"Ragweed pollen","frequency":""}],"sources":["Local air quality agencies","Weather data sources","eLichens hardware air quality sensors","Real-time traffic data sources"],"language":["English"],"data_volume":"N/A","availability":{"forecast":"Up to 4 days","real_time":"","historical":"Starting from October 2020"},"geo_coverage":["ASIA","AFRICA","EUROPE","NORTH_AMERICA","SOUTH_AMERICA","OCEANIA"]},"project_data_category.name":"Weather & Air quality","category_name":"Weather & Air quality"},{"category_id":"5de1963c-4f7f-4fae-8021-86797a72beba","description":"Company sector \n<hr />\nAir quality global data provider Category of data \n<hr />\nAir quality Data sources \n<hr />\nPatented eLichens algorithms using weather data, real-time traffic data, and local air quality agencies data including the eLichens hardware air quality sensors Temporal availability \n<hr />\n<ul>\n<li aria-level=\"1\">Real time</li>\n<li aria-level=\"1\">Forecast data: up to 4-days</li>\n<li aria-level=\"1\">Historical data: Starting from October 2020</li>\n</ul>\nGeographical coverage \n<hr />\nGlobal Key data attributes \n<hr />\nA. Pollutants: NO2, O3, PM10, PM2.5\nPollutants concentration:\n<ul>\n<li aria-level=\"2\">In terms of the proportion of the total volume that it accounts for</li>\n<li aria-level=\"2\">In terms of weight of pollutant within a standard volume of air</li>\n</ul>\nB. Air Quality Indices (AQI):\n<ul>\n<li aria-level=\"2\">the U.S. Environmental Protection Agency (EPA) index, which is mainly taken into account in the United States</li>\n<li aria-level=\"2\">the Citeair index, developed during the Citeair European project, and used to compare air quality situation in European cities</li>\n<li aria-level=\"2\">eLichens Air Quality Index (eAQI)</li>\n</ul>\nC. Pollen: Birch, Grass, Olive, Ragweed Data frequency \n<hr />\nHourly updates Delivery method \n<hr />\nAPI Language \n<hr />\nEN Pricing model \n<hr />\nPricing package with access limits (see Pricing section) Company Description \n<hr />\nThe AQ eLichens API can be divided into three main products:\n<ol>\n<li aria-level=\"1\">Geolocated API: choose a specific latitude and longitude anywhere in the world, and obtain historic, current and future air quality description in terms of main pollutants concentration, pollen concentration and air quality indexes</li>\n<li aria-level=\"1\">Street-level locations API: through this API, you can obtain summary measurements (minimum, maximum and average) coming from a hyper-local Air Quality model powered by eLichens for + 300 locations around the world where this model is deployed.</li>\n<li aria-level=\"1\">Local Agency Stations API: through this API, you can obtain measurements and forecasts of + 8000 local agency stations around the world.</li>\n</ol>\nAll the API data can be queried in the endpoints listed below.","image_url":"b1538c11-7a30-472b-b49a-bbd0db7fd20c.png","id":"3b9df53e-948f-4c21-8c7a-04f33cd52196","name":"Air Quality API","type_id":"8e8f5094-8df7-4479-b9d5-de236bb3d5fd","url_id":"air-quality-api","published_step":3,"data_specs":{"params":[{"name":"NO2 pollutant","frequency":"Hourly updates for all parameters"},{"name":"O3 pollutant","frequency":""},{"name":"PM10 pollutant","frequency":""},{"name":"PM2.5 pollutant","frequency":""},{"name":"Pollutants concentration","frequency":""},{"name":"EPA AQI","frequency":""},{"name":"Citeair AQI","frequency":""},{"name":"eAQI (eLichens AQI)","frequency":""},{"name":"Birch pollen","frequency":""},{"name":"Grass pollen","frequency":""},{"name":"Olive pollen","frequency":""},{"name":"Ragweed pollen","frequency":""}],"sources":["Local air quality agencies","Weather data sources","eLichens hardware air quality sensors","Real-time traffic data sources"],"language":["English"],"data_volume":"N/A","availability":{"forecast":"Up to 4 days","real_time":"","historical":"Starting from October 2020"},"geo_coverage":["ASIA","AFRICA","EUROPE","NORTH_AMERICA","SOUTH_AMERICA","OCEANIA"]},"project_data_category.name":"Weather & Air quality","category_name":"Weather & Air quality"},{"category_id":"d4fe4922-0f95-4119-93a9-d99a3c4c10ba","description":"Company sector \n<hr />\nParking Management Category of data \n<hr />\nKerbside parking data Data sources \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Local Councils using our software to digitally manage their kerbside.</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">HD Surveys (high resolution 360˚ panoramic street-level imagery of streets)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Data Heroes (team of GIS experts analysing data & manually mapping streets)</li>\n</ul>\nTemporal availability \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Static data representing present conditions</li>\n</ul>\nGeographical coverage\n<hr />\nUK \nThe largest 30 locations covered:\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Greater London (33 authorities)</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Birmingham, Glasgow City, Liverpool, City of Bristol, Sheffield, Manchester, Leeds, City of Edinburgh,</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">City of Leicester, Bradford, Caerdydd - Cardiff, Coventry, City of Nottingham, City of Kingston upon Hull,</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">City of Stoke-on-Trent, Newcastle, City of Wolverhampton, City of Derby, City of Portsmouth, Reading,</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Northampton, Luton, Aberdeen City, Bolton, Bournemouth, Swindon, Abertawe - Swansea, Sunderland, Milton Keynes</li>\n</ul>\nKey data attributes \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Parking Bays:</li>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"2\">Free</li>\n<li style=\"font-weight: 400;\" aria-level=\"2\">Paid</li>\n<li style=\"font-weight: 400;\" aria-level=\"2\">Residents</li>\n<li style=\"font-weight: 400;\" aria-level=\"2\">Motorcycle</li>\n</ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Charges & Tariffs</li>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"2\">Parking Price</li>\n<li style=\"font-weight: 400;\" aria-level=\"2\">Max Stay</li>\n<li style=\"font-weight: 400;\" aria-level=\"2\">Operating Hours</li>\n<li style=\"font-weight: 400;\" aria-level=\"2\">Payment Providers</li>\n</ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Specialised Bays</li>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"2\">Electric Vehicle</li>\n<li style=\"font-weight: 400;\" aria-level=\"2\">Loading</li>\n<li style=\"font-weight: 400;\" aria-level=\"2\">Car Club</li>\n<li style=\"font-weight: 400;\" aria-level=\"2\">Disabled</li>\n</ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Additional Information</li>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"2\">Yellow Line Rules</li>\n<li style=\"font-weight: 400;\" aria-level=\"2\">Bay and Line Sizes & Capacity</li>\n<li style=\"font-weight: 400;\" aria-level=\"2\">Event Day Rules</li>\n<li style=\"font-weight: 400;\" aria-level=\"2\">EV Charge Point Information</li>\n<li style=\"font-weight: 400;\" aria-level=\"2\">Parking payment provider</li>\n<li style=\"font-weight: 400;\" aria-level=\"2\">Parking payment location code</li>\n</ul>\n</ul>\nSee API documentation for more details Data frequency \n<hr />\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Local council data updates in our software are updated real time</li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Continuous updating cycle from other data sources</li>\n</ul>\nDelivery method \n<hr />\nAPI Language \n<hr />\nEN Pricing model \n<hr />\nSee Pricing section (top right hand-side of the page) Data Product Description \n<hr />\nThe last meter to any destination is parking. With the average driver wasting 150 hours every year searching for parking in London, the cost of traffic congestion to the UK economy is a staggering £7 billion. The AppyWay Parking API increases the probability for drivers of finding parking on-street with insights on where to park at any given time and location.\nThe data returned by the AppyWay Parking API can be rendered on a map as it contains the geospatial information of parking restrictions, it can also support any other product experience around parking.\nThe data covers Traffic Regulation Order (TRO) data for Controlled Parking Zones (CPZs) in 476 UK towns and cities and enables searching for parking rules and prices, and fetching geospatial data for map-based applications.\nThe rules and regulations governing parking, loading, and everything in between can be very complicated. The AppyWay API seeks to abstract away this complexity and provide answers to key questions, such as:\n<ul>\n<li>Where is it authorised to park at a specific time for a specific duration?</li>\n<li> How long can I park for?</li>\n<li> How much will it cost?</li>\n<li> How much will I have to walk from each suitable parking option to my destination?</li>\n</ul>\nYou can search for answers to these questions within areas of interest and periods of time. These answers can vary depending on a number of factors, including:\n<ul>\n<li>Whether looking to park (leave the vehicle unattended) or load (stay with the vehicle)</li>\n<li> The desired parking or loading duration</li>\n<li> The vehicle driven</li>\n<li> Any permits held</li>\n</ul>","image_url":"58926a04-7a28-4806-bb8f-af29d0f4fd66.jpg","id":"fcecb343-4b55-44a9-98ff-838d17747431","name":"Kerbside data to find parking faster","type_id":"8e8f5094-8df7-4479-b9d5-de236bb3d5fd","url_id":"kerbside-data-to-find-parking-faster","published_step":3,"data_specs":{"params":[{"name":"- Parking bays (free, paid, residents, motorcycle)","frequency":"Local council data updates in our software are updated real time"},{"name":"- Charges & tarrifs (parking price, max stay, operating hours, payment providers)","frequency":"Continuous updating cycle from other data sources"},{"name":"- Specialised bays (EV, loading, car club, disabled)","frequency":""},{"name":"- Yellow line rules","frequency":""},{"name":"- Bay and Line sizes & capacity","frequency":""}],"sources":["Public sector municipalities","HD Surveys (high resolution 360˚ panoramic street-level imagery of streets)","Data Heroes (team of GIS experts analysing data & manually mapping streets)"],"language":["English"],"data_volume":"N/A","availability":{"real_time":"Static data representing present conditions"},"geo_coverage":["United Kingdom"]},"project_data_category.name":"Parking","category_name":"Parking"},{"category_id":"5de1963c-4f7f-4fae-8021-86797a72beba","description":"This Listing provides information about weather and air pollution levels in different regions around the world.\nThe data are provided by the Sensor.Community. Sensor.Community is a contributors driven global sensor network that creates Open Environmental Data.\nThe Listing provides data approximately from 12k sensors located in 60+ countries around the world.\nKey data attributes:\n<ul>\n<li>Temperature</li>\n<li>Air pressure</li>\n<li>Humidity</li>\n<li>PM2.5</li>\n<li>PM10</li>\n</ul>\nMeasurements can be either actual or average numbers based on the query.\nPossible query parameters:\n<ul>\n<li>Sensor type</li>\n<li>Area (lat, lon, distance)</li>\n<li>Bounding box (lat1, lon1, lat2, lon2)</li>\n<li>Country</li>\n<li>Sensor ID</li>\n</ul>\nTemporal availability: Last 1h or last 24h\nData Frequency: An endpoint covering data in the last minute is updated every minute. While an endpoint covering data for the last 24 hours is updated every 5 minutes.\nGeographical coverage: Global (60+ countries)","image_url":"https://svgshare.com/i/R_W.svg","id":"b8bbafac-e017-4e36-a238-0404cb86588f","name":"Weather and Air Pollution Data","type_id":"8e8f5094-8df7-4479-b9d5-de236bb3d5fd","url_id":"weather-and-air-pollution-data","published_step":3,"data_specs":{"params":[],"sources":["IoT hardware"],"language":["English"],"data_volume":"Data approximately from 12k sensors located in 60+ countries around the world","availability":{"real_time":"","historical":"last 24h"},"geo_coverage":["ASIA","EUROPE","AFRICA","NORTH_AMERICA","SOUTH_AMERICA","OCEANIA"]},"project_data_category.name":"Weather & Air quality","category_name":"Weather & Air quality"},{"category_id":"c006c57e-16c0-468a-ba61-047b5509924d","description":"This Listing provides data related to the bicycle usage in the region of Brussels, Belgium.\nThe number of bikers is retrieved by camera sensors installed in several locations within the city of Brussels.\nReal time and historical data are available.\nPossible output formats: json, csv\nQuery arguments examples:\n<ul>\n<li>Real time data for all the sensors: ?request=live</li>\n<li>Historical data for a specific sensor ID with 15 minute-granularity for the specified time range: ?request=history&featureID=CB2105&startDate=20181206&endDate=20181210&outputFormat=json</li>\n</ul>\nGeographical coverage: Brussels","image_url":"https://i.imgur.com/zvGZF0b.jpg","id":"a3da5475-93a0-4c88-a147-dc05485fc0d9","name":"Bicycle Counts in Key Urban Areas","type_id":"8e8f5094-8df7-4479-b9d5-de236bb3d5fd","url_id":"bicycle-counts-in-key-urban-areas","published_step":3,"data_specs":{"params":[{"name":"Bike count (hourly, daily, yearly) per sensor","frequency":"The counts are only updated when a bike passes the sensor"},{"name":"Timestamp","frequency":""},{"name":"Camera sensor ID","frequency":""}],"sources":["Camera sensors"],"language":["English"],"data_volume":"N/A","availability":{"real_time":"The livestream count with the number of bikers passed last hour, day and year","historical":"with 15 minute-granularity for the specified time range"},"geo_coverage":["Belgium"]},"project_data_category.name":"Bicycle","category_name":"Bicycle"},{"category_id":"e77d9098-5fa0-4953-9681-6652a229f600","description":"This Listing provides detailed information about electric charging stations around the world provided by Open Charge Map.\nInformation can include: location, operating status, provider, connection type, kW etc.\nGeographical coverage: Global\n ","image_url":"https://imagizer.imageshack.com/img923/3313/IAthI1.png","id":"d8403d51-2db7-4eae-8288-ce62455865bd","name":"Electric Charging Stations","type_id":"8e8f5094-8df7-4479-b9d5-de236bb3d5fd","url_id":"electric-charging-stations","published_step":3,"data_specs":{"params":[{"name":"Location","frequency":""},{"name":"Operating status","frequency":""},{"name":"Provider","frequency":""},{"name":"Connection type","frequency":""},{"name":"Usage type","frequency":""},{"name":"Submission status","frequency":""},{"name":"Date created","frequency":""},{"name":"Data License","frequency":""}],"sources":["Electric Charging Stations"],"language":["English"],"data_volume":"global","availability":{"real_time":""},"geo_coverage":["ASIA","AFRICA","EUROPE","NORTH_AMERICA","SOUTH_AMERICA","OCEANIA"]},"project_data_category.name":"EV Charging","category_name":"EV Charging"},{"category_id":"d4fe4922-0f95-4119-93a9-d99a3c4c10ba","description":"This dataset presents real time availability of parking spaces in the car parks operated by Saemes in Paris and Ile-de-France.\nThe data is refreshed every 1 to 2 minutes.\nCounter type description:\n<ul>\n<li>STANDARD = spaces for cars (light vehicles)</li>\n<li>MOTOR_BIKE = places for motorcycles and scooters</li>\n<li>ELECTRIC_CAR = places equipped with recharges for electric vehicles Language: French</li>\n</ul>\nGeographical coverage: Paris and Ile-de-France","image_url":"https://svgshare.com/i/R0u.svg","id":"0d287b22-9736-4ba5-b681-1d3db0a94fb1","name":"Off-street parking - Paris","type_id":"8e8f5094-8df7-4479-b9d5-de236bb3d5fd","url_id":"off-street-parking","published_step":3,"data_specs":{"params":[],"sources":["IoT hardware"],"language":["English"],"data_volume":"All car parks operated by Saemes in Paris and Ile-de-France","availability":{"real_time":"every 1-2 minutes"},"geo_coverage":["France"]},"project_data_category.name":"Parking","category_name":"Parking"},{"category_id":"d13fbdee-8f71-4e16-ab8c-24a5bb884304","description":"On the Paris network, the majority of traffic is measured by electromagnetic loops located in the roadway.\nThe data are raw without any interpretation or analysis. They give an overview of the occupancy rate and the flow rate on more than 3000 track sections.\nTwo types of data are thus produced:\n<ul>\n<li>The Occupancy Rate which corresponds to the time of presence of vehicles on the loop as a percentage of a fixed time interval (one hour for the data provided). Thus, 25% occupancy rate over one hour means that vehicles were present on the loop for 15 minutes. The rate provides information on traffic congestion. The layout of the loops is designed so as to be able to deduce, from a punctual measurement, the state of the traffic on an arc.</li>\n<li>The Throughput which is the number of vehicles having passed the metering point during a fixed time interval (one hour for the data provided).</li>\n</ul>\nThe coupled observation at a point of the occupancy rate and the throughput makes it possible to characterize the traffic.\nThe equipment of the Parisian network: The main axes of the City of Paris are equipped with counting stations for vehicles and measuring the occupancy rate, for the purposes of both traffic regulation and public transport, information to users (broadcast on the Sytadin site), and study.\nThere are two types of stations on the network: stations for measuring the occupancy rate alone, and stations for both measuring the rate and counting vehicles.\nThe rate measurement stations are set up very regularly: they provide detailed knowledge of traffic conditions.\nThe debit stations are less numerous, and generally located between the main intersections. In fact, the flow is generally maintained over a section between two large intersections.\nGeographical coverage: Paris","image_url":"https://svgshare.com/i/R0u.svg","id":"db198dee-ca74-44bd-bfda-445230849142","name":"Road Traffic - Paris","type_id":"8e8f5094-8df7-4479-b9d5-de236bb3d5fd","url_id":"road-traffic","published_step":3,"data_specs":{"params":[],"sources":["IoT hardware"],"language":["English","French"],"data_volume":"more than 3,000 track sections","availability":{"real_time":""},"geo_coverage":["France"]},"project_data_category.name":"Road Conditions","category_name":"Road Conditions"},{"category_id":"c006c57e-16c0-468a-ba61-047b5509924d","description":"This Dataset provides information about the availability of terminals for mechanical and electric bikes at Vélib 'Métropole stations in Paris.\nVélib 'Métropole has nearly 1,400 stations spread over 55 municipalities in the Métropole that serve 400 km², making it the largest shared bicycle service in the world including rechargeable electric bikes in stations.\nThis data will allow you to know in real time the number of mechanical / electric bikes at each station as well as the number of free terminals.\nLanguage: French\nThese datasets are updated every minute according to the GBFS 1.0 standard, a standard for providing information flows for shared mobility services.\nGeographical coverage: Paris","image_url":"https://svgshare.com/i/R0u.svg","id":"dc8f387c-48a3-4867-9c01-95ef56882145","name":"Bicycle Stations","type_id":"8e8f5094-8df7-4479-b9d5-de236bb3d5fd","url_id":"bicycle-stations","published_step":3,"data_specs":{"params":[],"sources":["IoT hardware"],"language":["French"],"data_volume":"Nearly 1,400 stations spread over 55 municipalities in the Metropolitan France","availability":{"real_time":""},"geo_coverage":["France"]},"project_data_category.name":"Bicycle","category_name":"Bicycle"},{"category_id":"e77d9098-5fa0-4953-9681-6652a229f600","description":"Real time availability of the sockets equipping the Belib 'terminals - Charging network for electric vehicles of the City of Paris.\nA station is equipped with several terminals (charging point, post) itself equipped with different types of sockets.\nAvailability status description:\n<ul>\n<li>Available : the charging point is free</li>\n<li>Excluding communication : The charging point is no longer communicating, the charging station can however be used under certain conditions.</li>\n<li>Busy : the charging point is occupied by a charging vehicle</li>\n<li>Neutralized : The charging point is occupied by a plugged-in vehicle whose charging is complete</li>\n<li>Reserve : the charging point has been reserved by a user</li>\n<li>In diagnosis : The charging point is not available</li>\n<li>Under maintenance : The charging point is not available</li>\n<li>In programming : The charging point is neutralized for work to come or in progress</li>\n</ul>\nLanguage: French\nGeographical coverage: Paris","image_url":"https://svgshare.com/i/R0u.svg","id":"e6b0e501-637a-4ab1-bec5-4cdb7e6aafaa","name":"EV Charging Stations","type_id":"8e8f5094-8df7-4479-b9d5-de236bb3d5fd","url_id":"ev-charging-stations","published_step":3,"data_specs":{"params":[],"sources":["IoT hardware"],"language":["French"],"data_volume":"All EV charging stations operated by Belib in Paris","availability":{"real_time":""},"geo_coverage":["France"]},"project_data_category.name":"EV Charging","category_name":"EV Charging"}],"data_requests":[{"category_id":"6b9154e1-a7c2-48bc-b94a-d6cbe47f522b","id":"22b8f26e-85e4-408b-bf8c-88a91ce81ade","title":"Telematics Data","url_id":"telematics-data","data_specs":{"params":[],"sources":["Vehicle telematics devices","Connected cars","Satelites"],"language":["English"],"data_volume":"The most ","availability":{"real_time":"Maximum 1 week delay"},"geo_coverage":["ASIA","AFRICA","SOUTH_AMERICA","EUROPE","OCEANIA"]},"listing_specs":{"is_public":true},"project_data_category.name":"Telematics Vehicle","category_name":"Telematics Vehicle"},{"category_id":"d4ede441-9021-4f05-93cf-9f9902113d3c","id":"a5f61236-65b9-4ebb-bfaf-23a06a1fe181","title":"Macro traffic figures per country","url_id":"macro-traffic-figures-per-country","data_specs":{"params":[{"name":"total number of trips per vehicle type per country per day/week","frequency":"daily / weekly"},{"name":"average travel time per vehicle type per country per day/week","frequency":"daily / weekly"}],"sources":["Connected cars","Fleet operations","Vehicle telematics devices","Camera sensors"],"language":["English"],"data_volume":"total trips per country per day or week","availability":{"real_time":"daily or weekly updates","historical":"7 years"},"geo_coverage":["Argentina","Australia","Brazil","Canada","China","France","Germany","India","Indonesia","Italy","Japan","Mexico","Russia","Saudi Arabia","South Africa","Turkey","United Kingdom","United States","EUROPE"]},"listing_specs":{"is_public":true},"project_data_category.name":"Connected Vehicle","category_name":"Connected Vehicle"},{"category_id":"1be67912-4f98-4a65-84ff-84cc120a048b","id":"c2ffa6fe-18da-4883-9e39-405e59fd6fd6","title":"Mobility Data for London (within M25)","url_id":"mobility-data-for-london-(within-m25)","data_specs":{"params":[{"name":"Longitude","frequency":""},{"name":"Latitude","frequency":""},{"name":"user id","frequency":""},{"name":"","frequency":""}],"sources":["Mobile apps"],"language":["English"],"data_volume":"1 000 000 users for the last 12months","availability":{"historical":"12 months"},"geo_coverage":["EUROPE","United Kingdom"]},"listing_specs":{"is_public":true},"project_data_category.name":"Mobile Phone","category_name":"Mobile Phone"},{"category_id":"d4ede441-9021-4f05-93cf-9f9902113d3c","id":"84f47c30-2f9d-44f9-86ad-d48fb3b3eef4","title":"Traffic Count EV Vehicles","url_id":"traffic-count-ev-vehicles","data_specs":{"params":[],"sources":["Connected cars","Fleet operations","Vehicle telematics devices","Weather stations"],"language":["English"],"data_volume":"Need to understand seasonality, 6 months to 1 year historical data","availability":{"historical":"6 months to a year"},"geo_coverage":["France","Italy","Portugal"]},"listing_specs":{"is_public":true},"project_data_category.name":"Connected Vehicle","category_name":"Connected Vehicle"},{"category_id":"d4ede441-9021-4f05-93cf-9f9902113d3c","id":"493066ac-836d-460d-af51-e85813349172","title":"Vehicle data with DTC Codes","url_id":"vehicle-data-with-dtc-codes","data_specs":{"params":[{"name":"Unique vehicle ID","frequency":"highest possible (time series data is important)"},{"name":"Car Brand","frequency":""},{"name":"Car Model","frequency":""},{"name":"Model year","frequency":""},{"name":"Fuel type","frequency":""},{"name":"Displacement","frequency":""},{"name":"Engine power (kW)","frequency":""},{"name":"Timestamp","frequency":""},{"name":"Engine Speed","frequency":""},{"name":"Engine torque or load","frequency":""},{"name":"Vehicle speed","frequency":""},{"name":"Engine coolant temperature","frequency":""},{"name":"Engine oil temperature","frequency":""},{"name":"Longitude","frequency":""},{"name":"Latitude","frequency":""},{"name":"Current gear","frequency":""},{"name":"Throttle position","frequency":""},{"name":"Accelerator pedal position","frequency":""},{"name":"Brake pedal position","frequency":""},{"name":"Battery SOC (state of health and charge)","frequency":""},{"name":"Battery temperature","frequency":""},{"name":"Battery voltage","frequency":""},{"name":"Battery current","frequency":""},{"name":"Battery capacity","frequency":""},{"name":"Ambient temperature","frequency":""},{"name":"Humidity","frequency":""},{"name":"All P-codes (DTCs) or SPN/FMI","frequency":""}],"sources":["Connected cars","Vehicle telematics devices"],"language":["English"],"data_volume":"Hundreds of vehicles","availability":{"historical":"1-2 years"},"geo_coverage":["EUROPE","United States"]},"listing_specs":{"is_public":true},"project_data_category.name":"Connected Vehicle","category_name":"Connected Vehicle"},{"category_id":"e77d9098-5fa0-4953-9681-6652a229f600","id":"623de8bd-a5bc-4b5f-ba43-2b138ce6ac4c","title":"Dynamic Charging Utilization Data of EV Stations","url_id":"dynamic-charging-utilization-data-of-ev-stations","data_specs":{"params":[{"name":"Charging Status (on/off)","frequency":""},{"name":"Charging station information","frequency":""},{"name":"Charging pricing","frequency":""}],"sources":["EV infrastructure","Public sector","Any source available"],"language":["English"],"data_volume":"High coverage of total stations (public and private) in each city that is available","availability":{"historical":"1 year"},"geo_coverage":["United Kingdom","Belgium","France","Netherlands","Germany"]},"listing_specs":{"is_public":true},"project_data_category.name":"EV Charging","category_name":"EV Charging"},{"category_id":"61b7129a-ac95-49ac-a917-b1a1e7576aea","id":"145dc214-a781-408f-bbbd-0820c71579a7","title":"Last Mile Delivery Data","url_id":"last-mile-delivery-data","data_specs":{"params":[{"name":"Trip Origin","frequency":""},{"name":"Trip Destination","frequency":""},{"name":"Delivery type (e.g. parcel, food)","frequency":""},{"name":"Vehicle type (e.g. van, bike, scooter etc.)","frequency":""},{"name":"Date/time","frequency":""}],"sources":["Mobile apps","Vehicle telematics devices","Connected cars","IoT hardware","Any type of source"],"language":["English"],"data_volume":"anything available","availability":{"historical":""},"geo_coverage":["United States","EUROPE"]},"listing_specs":{"is_public":true},"project_data_category.name":"Mobility Services","category_name":"Mobility Services"},{"category_id":"d4ede441-9021-4f05-93cf-9f9902113d3c","id":"56b11e3f-0dc9-403d-80ea-d16f5f4d8523","title":"Vehicle Trucks Driving Behaviour Data","url_id":"vehicle-driving-behaviour-data","data_specs":{"params":[{"name":"Longitude","frequency":"minimum 1 HZ"},{"name":"Latitude","frequency":"minimum 1 HZ"},{"name":"Timestamp","frequency":"minimum 1 HZ"},{"name":"Vehicle Speed (ideally wheel speed from tachometer but GPS-computed could also be ok)","frequency":"minimum 1 HZ"},{"name":"Weight (optional)","frequency":"minimum 1 HZ"},{"name":"Brake pedal position (optional)","frequency":"minimum 1 HZ"},{"name":"Accelerator pedal position (otpional)","frequency":"minimum 1 HZ"}],"sources":["Connected cars","Vehicle telematics devices"],"language":["English"],"data_volume":"Looking for driving data of N2-N3 truck categories from hundreds of vehicles\n","availability":{"historical":""},"geo_coverage":["EUROPE","ASIA","AFRICA","NORTH_AMERICA","SOUTH_AMERICA","OCEANIA"]},"listing_specs":{"is_public":true},"project_data_category.name":"Connected Vehicle","category_name":"Connected Vehicle"},{"category_id":"d4ede441-9021-4f05-93cf-9f9902113d3c","id":"a76e7de5-7456-4007-919e-73426cdeb2f2","title":"Vehicle Video Footage Data","url_id":"vehicle-video-footage-data","data_specs":{"params":[],"sources":["Vehicle telematics devices","Connected cars"],"language":["English"],"data_volume":"1,000 vehicles","availability":{"historical":"3 months"},"geo_coverage":["Japan","United States"]},"listing_specs":{"is_public":true},"project_data_category.name":"Connected Vehicle","category_name":"Connected Vehicle"},{"category_id":"d4ede441-9021-4f05-93cf-9f9902113d3c","id":"d316aec2-e81b-4c8e-a061-8719934c62a7","title":"Vehicle Probe & Driving Behaviour Data","url_id":"vehicle-probe-&-driving-behaviour-data","data_specs":{"params":[{"name":"Longitude","frequency":"any"},{"name":"Latitude","frequency":"any"},{"name":"Acc X","frequency":"any"},{"name":"Acc Y","frequency":"any"},{"name":"Acc Z","frequency":"any"},{"name":"Steering right/ left (optional)","frequency":"any"},{"name":"Brake pedal (optional)","frequency":"any"}],"sources":["Connected cars","Vehicle telematics devices"],"language":["English"],"data_volume":"1,000 vehicles","availability":{"historical":"3 months"},"geo_coverage":["Japan","United States"]},"listing_specs":{"is_public":true},"project_data_category.name":"Connected Vehicle","category_name":"Connected Vehicle"},{"category_id":"d4ede441-9021-4f05-93cf-9f9902113d3c","id":"a63653d3-d621-45a9-829a-667174953ee6","title":"Origin/Destination pairs for metropolitan centers over time","url_id":"origin-destination-pairs-for-metropolitan-centers-over-time","data_specs":{"params":[],"sources":["Fleet operations","Mobile apps","Connected cars","Public sector municipalities"],"language":["English"],"data_volume":"Ideally as close to the movements of a full metro population over 48 hours. ","availability":{"real_time":"24 -48 hours"},"geo_coverage":["United States"]},"listing_specs":{"is_public":true},"project_data_category.name":"Connected Vehicle","category_name":"Connected Vehicle"},{"category_id":"d4ede441-9021-4f05-93cf-9f9902113d3c","id":"1fca99c2-9dd1-46cc-acb8-d05b08e401d5","title":"GPS probe data","url_id":"gps-probe-data","data_specs":{"params":[{"name":"","frequency":""}],"sources":["Node sensors","Fleet operations","Mobile apps","Radars","On-site manual count","Vehicle telematics devices","Connected cars","IoT hardware","Public sector municipalities","Camera sensors","Satelites"],"language":["English","Japanese"],"data_volume":"one or two years. one or two city. 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