Graphical Modelling of Workflows: Foundation for Handling Uncertainty in the Model Web 76th OGC...

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Graphical Modelling of Workflows: Foundation for Handling Uncertainty in the Model Web 76th OGC Technical Committee Bonn, Germany Benjamin Proß, IfGI/52°North March 01, 2011

Transcript of Graphical Modelling of Workflows: Foundation for Handling Uncertainty in the Model Web 76th OGC...

Graphical Modelling of Workflows: Foundation for Handling Uncertainty in

the Model Web

76th OGC Technical CommitteeBonn, Germany

Benjamin Proß, IfGI/52°NorthMarch 01, 2011

Overview

• UncertWeb Project• 52°North Web Based Workflow Modeller

UncertWeb Facts

• Uncertainty-enabled Model Web, FP7 Project (http://www.uncertweb.org/)

• Feb 2010 – Jan 2013• 8 Partners

• Aston University• Italian National Research Council • Food and Environment Research Agency • Joint Research Centre• Norwegian Institute for Air Research• Eindhoven University of Technology• University of Muenster• Wageningen University

Definitions

• Uncertainty– Model inputs

• E.g. through measurement errors of sensors • Taking outputs of other models as inputs

– Models itself• By aproximating reality, models introduce errors, and

should inform the user about (annotate its output with) the degree this happens

Definitions

• Model Web“The goal of the Model Web is to enable the development of a modelling infrastructure. To achieve this, the Model Web focuses on enhancing interoperability of existing models and making their outputs more accessible” (GEOSS AIP-2 Summary Engineering Report GEOSS Architecture Implementation Pilot).

• Vision, NOT implementation• Infrastructure is not yet existing

The UncertWeb concept

When chaining services of limited or unknown quality, uncertainty must be accounted for if rational decisions are to be made.

ECMWFensembles

GEMSensembles

Emissions data

Air quality forecastmodel

Modelparameters

Uncertaintyenabled air quality

forecast

Air qualitysensor network

Short range airquality forecasts

Meteorologicalsensor network

ECMWF model

GEMS models

Near real-time airquality nowcasts

Land use data

Albatross individualactivity simulator

Historical activitydata

Traffic model

Individualexposure

assessment

Emissions model

GISinfrastructure

data

Demographicdata

“UncertWeb develops mechanisms, standards, tools and test-beds for accountable uncertainty propagation in web service chains.”

Uncertainty quantification

• Even more important when considering service chains.

• Quantification achieved by:– Standards for representing and communicating

uncertainty.– Adding uncertainty-enabled inputs and outputs to

existing services.– Developing tools to assist users with uncertainty

management.• Computational issues will be non-trivial too!

UncertWeb and UncertML

• Standards for coupling models under uncertainty.– Develop UncertML to provide a complete

probabilistic model for uncertainty, and consider other (e.g. Fuzzy, Bayes Linear) representations.

– Provide an API for using UncertML.– Take UncertML through the standardisation

process (where? OGC?, W3C?, IETF?).

Chaining UncertWeb services

• Chaining and discovery of services under uncertainty.– Extend existing interoperable services to permit

their use in the uncertainty-enabled model web.– Implement a framework for uncertainty-enabled

model web services.– Develop uncertainty-enabled OGC Web Services.– Also support standard W3C WS.

• Uncertainty enabled WPS (UWPS)– Encapsulates models– Understands UncertML– Executes Monte Carlo simulations

• Uncertainty Transformation Service (UTS)– Transforms Uncertainties– E.g. distributions to realisations

• Spatio Temporal Aggregation Service (STAS)

Use of WPS

WP2: Chaining and discovery services under

uncertainty• Develop the methods and the Web-based

technology framework needed to discover and chain uncertainty-enabled or deterministic models in the presence of uncertainty– Composition as a Service (CaaS) approach– SOAP/WSDL + WPS service profiles– Metadata extensions

The CaaS

• Definition of a Composition-as-a-Service– From the literature

• A service “…for avoiding the need to install a client-side composition infrastructure”

– From a Cloud Computing point-of-view• Something between the customized Software-as-a-

Service (SaaS) and the flexible but complex Platform-as-a-Service (PaaS)

The UncertWeb CaaS

• Features– The CaaS supports business process modelling

through composition ( = re-use of existing) of (software) services

– BPMN -> BPEL– Preprocessing– The composition result is still exposed as a

service through a Workflow Engine

The UncertWeb CaaS

• Three functional Layers:– User Interface (editor, library, pre-processor for

domain-specific notations,…)– Mediation (orchestration logic, abstract

processes selector,…)– Adaption (adapters for external processes)

52°North Web Based Workflow Modeller

• http://52north.org/maven/project-sites/wps/52n-wps-orchestration-site/index.html

• Developed during a research project with the Sejong University, Seoul through the funding from the Seoul R&BD program(10540)

• Further use and development in the context of UncertWeb

52°North Web Based Workflow Modeller

• Lightweight browser application, that allows the:– Graphical composition and execution of

workflows consisting of different OGC services like WPS, WFS and WMS

– Execution of single WPS-processes– Visualisation of results– Creation of a new BPEL-process out of a workflow

and uploading it to a WPS-T

52°North Web Based Workflow Modeller

OpenLayers-map.

Easy adding and connecting of WPS-processes and data.

Graphical workflow-modelling.

Drag & Drop of Workflow-elements, like e.g. WFS-Layer.

52°North Web Based Workflow Modeller

• Features– GWT web application– OpenLayers map– Orchestration of workflows either through

• 52°North WPS Orchestration API• Workflow Engine (e.g. Apache ODE)

52°North Web Based Workflow Modeller

• Demo/Video

52°North Web Based Workflow Modeller

• A more complex scenario

Estimation of air pollution

from local emissions at point locations

• Special thanks to:• Lydia Gerharz• Christoph Stasch• Richard Jones• Dan Cornford• Lucy Bastin• Matthew Williams• Stefano Nativi• Paolo Mazzetti

The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n° [248488].

Thank you for your attention!