Semantic Grid Tools for RuralPolicy Development & Appraisal

Department of Computing Science, University of Aberdeen

Department of Geography & Environment, University of Aberdeen

Macaulay Institute, Aberdeen

Outline

eSocial Science & The Grid The Semantic Grid PolicyGrid – Aims & Activities Supporting Social Simulation Metadata Challenges for eSocial Science Supporting Argumentation Summary

eSocial Science & The Grid

eScience UK DTI characterises as distributed global

collaborations enabled by the Internet. The concept of the Grid promises to provide access

to large data collections, near unlimited processing resources for running experiments and studies, and advanced visualisation facilities.

Grid Components Computational grid (Scavenging grid) Data grid

The Semantic Grid

Semantic Grid A vision of eScience infrastructure in which there is

much richer support for researchers to publish, share and re-use resources, integrate heterogeneous information, collaborate, access decision support tools, etc.

Central to this view is the integration of Grid technologies with Semantic Web technologies.

RDF Resource Description Framework OWL Web Ontology Language

The Semantic Grid

Data mining

Knowledge Discovery

Smart search

Social networking

Smart portals

Agents

Information Integration and aggregation

CourtesyCarole Goble,

University of Manchester

Ontologies

PolicyGrid

Aims To facilitate evidence-based rural, social, and land-use

policy-making through integrated analysis of mixed data types;

To demonstrate that Semantic Web/Grid solutions can be deployed to support various facets of evidence-based policy-making through the development of appropriate tools;

To focus on the authoring of relevant ontologies to support rural, social and land-use policy domains;

To investigate issues surrounding communication of semantic metadata to social scientists and policy practitioners;

To promote awareness of the Semantic Grid vision and supporting technologies amongst social scientists.

Builds upon work of the earlier Fearlus-Gpilot demonstrator project.

PolicyGrid

What are the methodological drivers behindour activities? A myriad of policy evaluation challenges facing

contemporary social scientists; Increased focus on methods and tools for integrated policy

evaluation; Increased emphasis on multi-method or mixed-methods

approaches to evaluation, where emphasis is placed on plural types and sources of data;

Diverse epistemological approaches and analytical techniques.

A key driver - evidence-based policy making – a mantra often summarised as meaning ‘what matters is what works’ (Cabinet Office, 1999).

Supporting Social Simulation

Fearlus Land-Use Model Case Study Aims

To serve a well-established simulationframework to the wider community

To support collaboration among socialscientists by providing a sharedco-laboratory environment forexperimentation.

Achievements Distributed simulation experiments run across Grid nodes. Simulation results annotated with metadata (RDF). Users can publish and share simulation model

parameters and re-run experiments. Support for creation of hypotheses, arguments. Ontology to support annotation of simulation resources.

Simulation Parameters

@beginenvironmentType Toroidal-MooreneighbourhoodRadius 1climateBSSize 0economyBSSize 16landParcelBSSize 0nLandUse 8pLandUseDontCare 0.0clumping NoneenvXSize 15envYSize 15nSubPops 2strategyChangeUnit 0.0neighbourNoiseMax 0.0neighbourNoiseMin 0.0breakEvenThreshold 8landParcelPrice 16subPopFile subPopDesc.sd

suddenchange150clim00000000000001000000000000000100000100000000000000111111011111111111111111111101111011111111111011111111011111

@beginNumberOfStrategyClasses: 3Class AboveThresholdProbabilityBelowThresholdNonImitativeProbabilityBelowThresholdImitativeProbability InitialProbabilityHabitStrategy 1.0 0.0 0.0 0.0RandomStrategy 0.0 1.0 0.0 1.0NoStrategy 0.0 0.0 1.0

Architecture

Desktop Application FEARLUS

Experiment Service

Upload Service

Repository Service

ELDAS Data Access Service

MODEL 0-6-5<CLASS>

FEARLUS Model<INTERFACE>

Model Factory<INTERFACE>

FEARLUS

META-DATA

My Workspace

Web Interface

Public Repository (Longwell)

Web Interface

My SQL

OGSA 3.2.1

WEB/GRID SERVICES FEARLUS MODEL INTERFACE

JDBC4ELDAS

My Workspace

Simulation Workflow Support

Taverna workflow tool

Allows scientists to describe and enact their experimental processes in a structured, repeatable and verifiable way.

MetaData Challenges for eSocial Science

Ontological Approach:– Universally shared conceptualisation of a domain of

discourse.– Provides a controlled vocabulary.

How to capture fuzzy/vague concepts?– sustainability, accessibility, poverty …

How to make different conceptualisations of a domain of discourse co-exist?– Differences in granularity.– Inconsistent points of view.– Meaning is often fluid, contextual.

There will never be just one ontology![In social science or any other activity]

Annotations - Semantic Web View

NVivo

Country Country

Political Office

City

Place

Annotation - assert facts usingterms (metadata in RDF).

Represent terms and theirrelationships (ontology in OWL).

Annotations help to connectWeb resources.

Annotations - Qualitative Social Science View

Qualitative data analysis tools such as NVivo.

Can we combine the Semantic Web view withthe qualitative analysis approach?

Folksonomies - A Solution for eSocial Science?

Ontologies are often seen as a “top-down” solution.– Will the social science community accept this?

Folksonomy– Derivation: “folk” + “taxonomy”– Collaboratively generated, open labelling system.– Social networks and collective intelligence.– Power derived from community “buy-in”.– Problem of meta-noise…

Folksonomies - A Solution for eSocial Science?

Folksonomies - A Solution for eSocial Science?

Supporting Argumentation

Arguments & Evidence

PolicyGrid Team

Project Investigators– John Farrington (Geography & Environment)– Gary Polhill, Nick Gotts (Macaulay Institute)– Pete Edwards, Alun Preece, Chris Mellish

(Computing Science)

Project Staff– Abdelkader Gouaich, Feikje Hielkema,

Edoardo Pignotti, ChuiChing Tan

www.policygrid.org