1. Interoperability as a cornerstone for EIONET
Jan Bliki
27 November 2008

2. The strategic perspective for SEIS towards 2020
The current data flows
Live Information Systems
Member states
Organisations
Member states
Organisations
One-way flow of information
Humans to system
Different formats (colors)
Package data deliveries
Omnipresent flow of information
System to system
One standard
Live data deliveries
OGC ?

3. INSPIRE in GI standards

4. European Environment Agency as Technical Committee Member For OGC
Since July 2007

5. Web-service Providers
Application Providers
Data Providers
WMS/WFS
SWE/WFS-T/WCS
Application Demandeur
Data Demandeur
End User
End User

6. National Datasets to one unified European Dataset+ + +
National level + + +
European level

7. National Datasets to one unified European Dataset+ + +
National level + + +
European level
Hourly data
Daily data
Monthly data

8. Improvement of EEA’s data/information flows (500 dataflows in ReportNet)
60%
Questionairs
30%
Standalone systems
10%
Online systems

9. Data flow structure National system Object Based EU system
Table 2
Table 1
Table 5
Table 4
Table 3
Object Based
EU system
Dataset Based

10. Type A Type B Type C Type D Data flow frequency High frequency
Object Based
Dataset Based
ReportNet (500 Dataflows)

11. Data flow structure National system Object Based EU system
Field 1
Field 2
Field 3
Field 4
Field 1
Field 2
Field 3
Field 4
Field 1
Field 2
Field 3
Field 4
EU system
Dataset Based

12. Type A Type B Type C Type D Data flow frequency High frequency
OzoneWeb (2 Dataflows)
Type A
Type B
Type C
Type D
Object Based
High Frequency = Once a week, day, hour
Low Frequency = Once a Month, Year, 2 Years
Datasets we talk about in Type A is probably not more then 10% today.
Type D = Questionair, small, one report per country, … , Slow changing databases such as Natura 2000?!?
Slow changes makes this flow very costly. (Monitoring/infrastructure != possible)
Spatial reference data not changing offten. (Lakes, Rivers, Land change) most probably is cheaper in a Type D rather then Type A
Type A would be perfect for Monitoring stations, National system filled all year arround, Flood monitoring, Air stations, etc..., Interpolation results from other services feeding other services.
Dataset Based
ReportNet (500 Dataflows)

13. Similarities in data flows
Fully automated flow !!
Change
Send
Receive
Aggregate
INTEROPERABILITY = Using standards
Measurement Values
Co2
NoX
Count
Spatial Component
Parameters
Time of change
Nuts code
Grouping
Country
Rules
Filtering
Validation
Aggregation
Merge
Goal should be that ”the less we need to think about the technical implementations, the easier agreements and re-use of data will be possible”

14. ”the less we need to re-invent how data flows; the easier data flows”