Open (Geo) Data and IoT: A Revolution in Earth Sciences

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Presentation transcript:

Open (Geo) Data and IoT: A Revolution in Earth Sciences Alexander Kotsev

About JRC In-house science service of the European Commission Independent, evidence-based scientific and technical support for EU policies Established 1957 7 institutes in 6 locations Around 3000 staff, including PhDs and visiting scientists 1 370 publications in 2014

Open (Geo) Data

9900 + http://drdsi.jrc.ec.europa.eu/ Data source Number of datasets Relative share (%) National INSPIRE Geoportals 3912 51.9 Danube_Net data inventory 3536 Open Data Portals 2502 Projects 1565 Pan-European institutions 144 http://drdsi.jrc.ec.europa.eu/

Example datasets JRC Research databases Unlocking content Flood Hazard Map (JRC) Unlocking content ICPDR datasets European data services e.g. Copernicus Land Services Data from INSPIRE Geoportals Project repositories/Sustainability FP7 EnviroGrids results

Platform Based on investment in INSPIRE/Open Data Distributed (SOA) architecture Open source architecture Powered by CKAN GeoNetwork Collaborative components Yammer LinkedIn Strong emphasis on geospatial data

Community Data

Community Data

Community Data IAS in Europe MyNatura2000

Data From Sensors

AirSensEUR Open by design (EUPL) Hardware Software

Architecture

Results 24 million + observations Reports 3-D printable boxing

An error???

Not really …. 

SenseEurAir app (MyGEOSS) Develop GEOSS-based apps Inform European citizens on the changes affecting their local environment Data from 52N REST API. Subscription to networks is possible

IoT Open hardware/software High quality observation data Reusable architecture Interoperable data management Community of Practice (DiY) Aligned with two EU Directives INSPIRE Air Quality Directive Precision farming already includes the ‘smart’ application of fertilizers due to tractor localization, soil data, bio-chemical knowledge, etc. Data is owned by the farmer Data is not used for EU-wide monitoring However, monitoring of 9 tractors and 23 application machines for one farm of a size around 1'300 hectares generates 10 MB of data a day. Monitoring of any medium sized agricultural company would scale up to several 3 GB of monitoring data each day. What are appropriate methods and tools to use such data? Tracking in near-realtime Reusable data Easy data integration/mashup Cross-border Cross-domain Based on standards Apps for farmers (smartphone & web)

Population from Cell Phone data Mobile devices at 08:01 h.