1. Groundwater model service driven by Open Data and crowd sensing
Francisco Batlle & Xavier Almolda

2. It’s a source of conflicts.
Motivation
Water is a vital natural resource with growing demand and constrained supply.
It’s a source of conflicts.
The Water Framework Directive demands:
Public participation
Intense monitoring
Active management

3. It’s a source of conflicts.
Motivation
Water is a vital natural resource with growing demand and constrained supply.
It’s a source of conflicts.
The Water Framework Directive demands:
Public participation
Intense monitoring
Active management

4. It’s a source of conflicts.
Motivation
Water is a vital natural resource with growing demand and constrained supply.
It’s a source of conflicts.
The Water Framework Directive demands:
Public participation
Intense monitoring
Active management

5. It’s a source of conflicts.
Motivation
Water is a vital natural resource with growing demand and constrained supply.
It’s a source of conflicts.
The Water Framework Directive demands:
Public participation
Intense monitoring
Active management

6. It’s a source of conflicts.
Problem
Water is a vital natural resource with growing demand and constrained supply.
It’s a source of conflicts.
The Water Framework Directive demands:
Public participation
Intense monitoring
Active management

7. It’s a source of conflicts.
Problem
Water is a vital natural resource with growing demand and constrained supply.
It’s a source of conflicts.
The Water Framework Directive demands:
Public participation
Intense monitoring
Active management

8. It’s a source of conflicts.
Motivation
Water is a vital natural resource with growing demand and constrained supply.
It’s a source of conflicts.
The Water Framework Directive demands:
Public participation
Intense monitoring
Active management
Numerical models are the natural tool to integrate diverse data, to assess the natural evolution of water bodies and their sensitivity to human actions, and to communicate the actual status of water bodies

9. Objective

10. Objective

11. Linked Open Data - Ontology
Time series of:
Mesh values
Point values
nodes
elements

12. LOD – Web Services Time series of: Mesh values Point values nodes
elements

13. Towards the Model Web paradigm

14. Towards the Model Web paradigm
Technology platform: Cloud computing

15. Towards the Model Web paradigm
Cloud Computing
Numerical Models
8th Phase of the GEOSS Architecture Implementation Pilot (jan-2015) …
4. Build toward the vision of the Model Web:
Models are the codification of the best understanding we have about physical phenomena and processes and should be further applied
The vision of the Model Web is to serve as the basis for development of a dynamic web of models, integrated with databases and websites, to form a consultative infrastructure where researchers, managers, policy makers, and the general public can gain insight into “what if” questions

16. Towards the Model Web paradigm
Proof of Concept:
Barcelona Aquifer

17. Towards the Model Web paradigm

18. Towards the Model Web paradigm
Technology platform: Strabon

19. Impact

20. Beyond the Model Web paradigm
from Smart Cities to Smart Regions

21. Crowd Sensing
from Smart Cities to Smart Regions

22. Crowd Sensing
from Smart Cities to Smart Regions
Technology platform

23. Crowd Sensing Models driven by citizen data: Numerical Models 2.0
Cloud Computing

24. Crowd Sensing Models driven by citizen data: Numerical Models 2.0
How to incorporate crowd sensing data to the model:
Citizen supplied absolute head levels aren’t useful (no unique way to measure it).
Citizen supplied changes in time are meaningful.
Observed measures in a controlled network are more valid, both in absolute or relative terms.
Computed (absolute) values must be corrected for each user according to the first supplied absolute value.

25. To Conclude INNOVATIONS / IMPACT 1
Treat numerical models results as satellite data
Basis to integrate numerical model results with other remote sensing processes.
“Activate” numerical models with field data.
Groundwater model results as Linked Open Data (LOD)
Link geospatial data with groundwater data.
Basis to expand LOD to model results of different areas.
Model Web as consultative infrastructure
Best understanding of physical phenomena.
General public can gain insight into “what if” questions.

26. To Conclude INNOVATIONS / IMPACT 2 Smart Regions
Leverage smart city tools to smart regions.
Public information extended to territories.
Numerical models 2.0: Models driven by citizen data
Model’s quality increased with new observations.
Public participation in both directions.
Sense of shared ownership.
Build trust between water stakeholders.

27. Thank you. http://melodiesproject. eu info@melodiesproject
Thank you!