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

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

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

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

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

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

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

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

Objective

Objective

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

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

Towards the Model Web paradigm

Towards the Model Web paradigm Technology platform: Cloud computing

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

Towards the Model Web paradigm Proof of Concept: Barcelona Aquifer

Towards the Model Web paradigm

Towards the Model Web paradigm http://h2-lod.cloudapp.net/ Technology platform: Strabon

Impact

Beyond the Model Web paradigm from Smart Cities to Smart Regions

Crowd Sensing from Smart Cities to Smart Regions

Crowd Sensing from Smart Cities to Smart Regions Technology platform

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

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.

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.

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.

Thank you. http://melodiesproject. eu info@melodiesproject Thank you! http://melodiesproject.eu info@melodiesproject.eu @MelodiesProject francisco.batlle@hydromodelhost.com