Presentation by Gerrit Hendriksen (Deltares) at Earth Observation and Data Science Symposium, during Delft Software Days 2016. Monday 24 October 2016, Delft.

1. OpenEarth
components in Data Science
some examples
Gerrit Hendriksen
Willem Stolte, Frank Keppel, Maarten Pronk, Dave de Koning,
Matthijs Schaap, Joan Sala, Anna van Gils, Kees den Heijer, Fedor
Baart, Johan Beekhuizen, Giorgio Santinelli, Almar Joling, Rens van
de Bergh, Amrit Cado van der Lelij, André Speelmans, Arthur van
Rooij, ….

2. A small survey to start with
Go to Kahoot.it with your smartphone!

3. What is OpenEarth?
OpenEarth consists of Open Source tools to transform and
store your data in a standardized format. This enables you to
easily:
• Show the data in online viewers
• Help others find your data in online catalogues
• Share the data through an online download
• Store the changes in the data (version control)

4. Benefits of OpenEarth Data management tools

5. Data Stages
tailored
data
> WCS
> WFS
> SOS
> SOAP
> netCDF-CF-
OPeNDAP
> ISO SQL–
PostGIS> SVN
> GIT
> http
> ftp
> KML
> WMS
> WFS
> CSWgraphics
of data
standard
data
raw
data
catalogue
of data
work done
on server
work done
on client
what
where
when
who
why
how
…
data URLs
smart phone & tablet usersscientists professionals

6. Techniques - Basics

7. Techniques - Basics
• OpenEarth:
• Open standards (OGC WxS)
• Open data
• Open source
• Web technology:
• Dissemination
• Interface between users and data
• Geoserver (OGC WxS)
• WPS
• Geonetwork (data discovery)
storage
(geo)database
OGC WxS services
dissemination
THREDDS
netCDF

8. Some examples
Where:
- Data management is unified
- Reuse of information
- Reuse of tools
Side information:
- Target audience
- Which data is used
- Which protocols

9. FAST

10. FAST
Description:
- Assessment tool
Stakeholders:
- Decision makers
- Education
Techniques:
- WMS
- WCS
- WPS
- XBeach modelling
Data: Global, Regional

11. Expert version with regional data

12. OET-WIS
Description:
Data management system for data intensive projects with:
- Time series (models, loggers, …)
- Geo data in various kinds
Stakeholders:
- Researchers, Clients
Data:
- Global, regional, local
Techniques:
- OGC services, FEWS, statistics, Mobile Apps

13. OET-WIS
storage
(geo)database
OGC WxS services
dissemination
THREDDS
netCDF
FEW
S
functions
Models

14. (Inter)national (I)WRM projects

15. WIS animated results

16. Waterviewer + NO3-app

17. Hydrological Statistical Functions
Description:
- Hydrological statistical functions enabled by WPS builder
Stakeholders:
- Researchers, end users
Data
- Timeseries, geospatial
Techniques:
- WPS, OGC-WxS, Statistics

18. Hydrological Statistical Functions

19. Hydrological Statistical Functions

20. Subsurface data handling
storage
(geo)database
OGC WxS services
THREDDS
netCDF
dissemination
OGC WxS services
OGC WxS services (WPS)

21. Subsurface Data Handling
Description:
- Central place for national (ground) water modelling data
Stakeholders:
- Researchers, Modellers, Waterboards, National government
Data
- National data for groundwater modelling and model results
Techniques:
- WPS, OGC-WxS

22. Subsurface data handling

23. Subsurface Examples - Infoline

24. Subsurface Examples - Infoline

25. Subsurface Examples - Infoline
dissemination
TNO - REGIS
THREDDS
netCDF
OGC WxS services
OGC WxS services (WPS)
LHM/NHI
(GMDB)
THREDDS
netCDF
OGC WxS services

26. Subsurface Examples - Watersoils
Description:
- Risk assessment tool for water infrastructure
- Quick access to sub surface data
Stakeholders:
- Governmental researchers/engineers
Techniques:
- OPeNDAP
- WPS
Data:
- national, regional data

27. Subsurface Examples - Watersoils

28. Subsurface Examples - Watersoils

29. Dynamic Reporting
Description:
- Quick access to high level information on trends in …
Stakeholders:
- End users at governmental level
Techniques:
- (spatial)database
- R-shiny
Data:
- National, regional data

30. Reporting made dynamic

31. Reporting made dynamic

32. Future work
Extensions:
- Reporting functions
- Statistical functions
- Running models
- Data entry modules
Attention to:
- User management
- security

33. Message
Data acquisition
• Standardisation of data and metadata
• Standardised Processes to ‘create’/reuse data
• 3 clicks …
• Easy information dissemination
Main components of OpenEarth data systems:
• Central storage
• Knowledge exchange (i.e. statistical tools, Infoline)
• Highly standardised data formats
• Meta data
• Information and viewing services