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

2. 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

3. Open (Geo) Data

4. 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

5. 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

6. 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

7. Community Data

8. Community Data

9. Community Data
IAS in Europe
MyNatura2000

10. Data From Sensors

11. AirSensEUR
Open by design (EUPL)
Hardware
Software

12. Architecture

13. Results
24 million + observations
Reports
3-D printable boxing

14. An error???

15. Not really …. 

16. 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

17. 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)

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