Telco 14. Fourth of the second phase of the IE

When: WED 29 Apr 2020 - 3:00 PM-4:30 PM

Attendants

• Joan Masó, Clay Herbaugh, James Sprinks (Earthwatch), Jan-Erik Vinje, Lucy Bastin, Lukas Mocek, Metis Meloche, Simon Jirka, Valantis Tsiakos, Andy Cobley, Steffen Fritz, Anne Bowser, Maya Charnell, Ester Prat

Meeting recording

Agenda and minutes

• SensorThings API clients and services. What can we implement with the resources we have.
  • 52N Helgoland Server - version 5.1 tested and works nice. Can support 3 different services: SOS, STA and REST API
    • Valantis asks Simon to share URI of the server so that they can try to visualize directly the resources exposed to their clients
    • JM suggests to use phenology observations as a dataset to test --> AP2
  • JM has made some progress with his browser reading SensorThings API data and will use this approach suggested by Thunyathep Santhanavanich in the April 15th email to create a map and to query for observations (in datastreams):
    • Get locations:
      • COVID19: http://193.196.138.56:8080/STACOVID/v1.0/Things?$expand=Locations
        • there are 264 locations. I only get the first 100 by default.
      • SCENT: https://mariaisawsome.iccs.gr:8443/SensorThing/v1.0/Things?$expand=Locations
        • there are 167 locations. I only get the first 100 by default.
      • There is a paging mechanim that can be controled by the parameters $top= and $skip= only in the "first level" (not in the expanded levels)
        • The presence of the element @iot.nextLink is an indication that you have not recovered all the information available.
    • COVID19: Observations in a place: http://193.196.138.56:8080/STACOVID/v1.0/Things?$filter=name%20eq%20%27Germany%27&$expand=Datastreams/Observations
      • 3 datastreams for deads, recovered and confirmed cases
      • Each datastream returns a time series. You can get them all datastreams and the "internal" observations in a single request because none of the elements involved has more than 100 hits.
    • SCENT: Observations in a place for Scent is more complicated. Due to paging limitations you need to discover them in several steps:
      • https://mariaisawsome.iccs.gr:8443/SensorThing/v1.0/Things(14)?$expand=Datastreams
        • returns 4 datastreams: Soil Moisture, Air Temperature, Water Level and LC/LU.
          • Each datastream has a @iot.selfLink that we can use to ask for observations
        • Soil Moisture (11 observations, range: 0-11%): https://mariaisawsome.iccs.gr:8443/SensorThing/v1.0/Datastreams(20)/Observations?$top=10000
        • Temperature (7 observations, range: 17.4-18.1 C): https://mariaisawsome.iccs.gr:8443/SensorThing/v1.0/Datastreams(24)/Observations?$top=10000
        • Water Level observations (only one 40cm): https://mariaisawsome.iccs.gr:8443/SensorThing/v1.0/Datastreams(251)?$expand=Observations&$top=1000
        • LC/LU observations (seem empty): https://mariaisawsome.iccs.gr:8443/SensorThing/v1.0/Datastreams(252)/Observations?$top=10000
    • Once 52N Helgoland Server is ready, we can try with it
  • Steffen Fritz wants some advice to adopt the SensorThings API approach with his land cover street level photographs --> AP3
    • Maybe StoryMaps can be helpful on this. EarthChallenge Storymaps link: https://earthchallenge2020.earthday.org/
• INSPIRE Hackathon coordination
  • https://www.plan4all.eu/updates/dubrovnik-inspire-hackathon-2020-challenges/
  • ICCS: Identified 3 use cases in the Challange #8
    • Data transformation to the STA data model
    • Visualization resources from STA
    • Integration of data sources in a single STA using the LandSense federation
  • Lukas wants to have a separate call with Joan about the CitSci Enginnering Report to better understand how they can participate --> AP4
• COVID-19 + AirQuality correlation
  • Lukas was in a webinar where this EEA platform was presented linking air quality data monitoring and COVId-19: https://op.europa.eu/en/web/eudatathon
  • Resources and discussions on gitter
    • https://github.com/codersagainstcovidorg/covid19testing-map/blob/master/src/data/schema.json
    • https://gispub.epa.gov/airnow/
    • From Copernicus we can get NO2 distribution https://atmosphere.copernicus.eu/charts/cams/particulate-matter-forecast
    • https://earthchallenge2020.earthday.org/app/529a00a3c5244df5b6f12bf92d6c1d06
    • CAMS paper on impact of COVID-19 using NO2: https://atmosphere.copernicus.eu/air-quality-information-confirms-reduced-activity-levels-due-lockdown-italy
  • Citizen Science and COVID curiosity:
    • https://www.catalannews.com/tech-science/item/algorithm-aims-to-detect-covid-19-cases-with-app-that-records-coughing
      • opensigma.mit.edu
  • Lucy will provide data on air quality in WCS format
• Earth Challenge 2020
  • Results from Earth Challenge 2020 on STA to CitSci
    • Presentation: https://docs.google.com/presentation/d/1dMdZfY07IyygQPyoKiiF_zkdFVvkn18MqpoqrpIwdhg/edit?usp=sharin
    • Trying https://api.citizenscience.host/
    • 
    • POST a json text {"table_name": "OGC_Data", "offset":0, "limit":9999, "encoding": "json", "options": {}} to https://api.citizenscience.host/get/records
    • The results are a complete mistery to me:

00000000000000 {"status":"OK","message":"","data_type":"get_records_response",
00000000000063 "data":"","data_str":"{\"table_name\":\"OGC_Data\",\"type_name\
00000000000126 ":\"58308572548224431\",\"type_schema\":\"{\\\"type\\\":\\\"rec
00000000000189 ord\\\",\\\"name\\\":\\\"type_name\\\",\\\"fields\\\":[{\\\"nam
00000000000252 e\\\":\\\"datastreamName\\\",\\\"type\\\":[\\\"string\\\",\\\"n
00000000000315 ull\\\"]},{\\\"name\\\":\\\"datastreamDescription\\\",\\\"type\
00000000000378 \\":[\\\"string\\\",\\\"null\\\"]},{\\\"name\\\":\\\"observatio
00000000000441 nType\\\",\\\"type\\\":[\\\"string\\\",\\\"null\\\"]},{\\\"name
00000000000504 \\\":\\\"unitOfMeasurement\\\",\\\"type\\\":[\\\"string\\\",\\\
00000000000567 "null\\\"]},{\\\"name\\\":\\\"unitOfMeasurementName\\\",\\\"typ
00000000000630 e\\\":[\\\"string\\\",\\\"null\\\"]},{\\\"name\\\":\\\"unitOfMe
00000000000693 asurementSymbol\\\",\\\"type\\\":[\\\"string\\\",\\\"null\\\"]}
00000000000756 ,{\\\"name\\\":\\\"unitOfMeasurementDescription\\\",\\\"type\\\
00000000000819 ":[\\\"string\\\",\\\"null\\\"]},{\\\"name\\\":\\\"unitOfCount\
00000000000882 \\",\\\"type\\\":[\\\"string\\\",\\\"null\\\"]},{\\\"name\\\":\
00000000000945 \\"unitOfCountName\\\",\\\"type\\\":[\\\"string\\\",\\\"null\\\
00000000001008 "]},{\\\"name\\\":\\\"unitOfTruth\\\",\\\"type\\\":[\\\"string\
00000000001071 \\",\\\"null\\\"]},{\\\"name\\\":\\\"unitOfTruthName\\\",\\\"ty
00000000001134 pe\\\":[\\\"string\\\",\\\"null\\\"]},{\\\"name\\\":\\\"unitOfT
00000000001197 ruthDescription\\\",\\\"type\\\":[\\\"string\\\",\\\"null\\\"]}
00000000001260 ,{\\\"name\\\":\\\"unitOfCategory\\\",\\\"type\\\":[\\\"string\

• • • I can clean it with "search and replace" ((gc response.json) -replace '\\"', '"' | Out-File -encoding UTF8 response2.json) several times etc...

            "phenomenonTime": 1587225291609,
            "resultTime": 1587225291609,
            "submitTime": 1587225291609,
            "projectObservationUID": "11ca4f9ab12f4832bca7039513f27de4_1587225321657",
            "license": " ",
            "licenseName": "CC0",
            "resultQuality":
            {
               "IsImageAdultClassified": "true",
               "IsImageRacyClassified": "true"
            },
            "validationStatus": "some",
            "validationMethod": "Photos flagged for adult or racy content",
            "validationResult": "TRUE",
            "qualityGrade": "Consumer",
            "observedPropertyName": "Particulate matter (PM)",
            "sensorName": "11ca4f9ab12f4832bca7039513f27de4",
            "sensorDescription": "Anonymous user cell phone",
            "sensorEncodingType": "JSON object",
            "featureOfInterestFeature":
            {
               "verify_location_long": "11.754730549739106",
               "verify_location_lat": "48.38568609534866",
               "user_location_lat": "0",
               "user_location_long": "0"
            },

Connections

• New channel on Gitter:
• Usual channel in GoToMeeting number:
• Or use our email interop-cop3@listsNOspamPlease.weobserve.eu

Next Action points

• AP1: Andy Cobley to provide samples of air temperature & soil moisture data to Simon
  • Completed: Email was sent on May 5th at 14:42pm CEST
• AP2: Joan to provide phenology dataset to Simon
• AP3: Steffen will check availability for an ad-hoc meeting with Joan, Clay, Andy and Valantis
• AP4: Set up a separate call with Lukas and Joan about the CitSci Engineering Report
• AP5: Set up a meeting with Joan and Clay to talk about how to clean the JSON file

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