Semantic Grid Tools for Rural

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21 Οκτ 2013 (πριν από 3 χρόνια και 11 μήνες)

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Semantic Grid Tools for Rural

Policy 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

Courtesy

Carole 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
-
G

pilot demonstrator project.


PolicyGrid


What are the methodological drivers behind

our 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 simulation

framework to the wider community


To support collaboration among social

scientists by providing a shared

co
-
laboratory environment for

experimentation.


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

@begin

environmentType


Toroidal
-
Moore

neighbourhoodRadius 1

climateBSSize 0

economyBSSize 16

landParcelBSSize 0

nLandUse 8

pLandUseDontCare 0.0

clumping



None

envXSize 15

envYSize 15

nSubPops 2

strategyChangeUnit 0.0

neighbourNoiseMax 0.0

neighbourNoiseMin 0.0

breakEvenThreshold 8

landParcelPrice 16

subPopFile subPopDesc.sd

suddenchange150clim

0000000000

0001000000

0000000001

0000010000

0000000000

1111110111

1111111111

1111111101

1110111111

1111101111

1111011111

@begin

NumberOfStrategyClasses: 3

Class

AboveThresholdProbability

BelowThresholdNonImitativeProbability

BelowThresholdImitativeProbability

InitialProbability

HabitStrategy

1.0

0.0

0.0

0.0

RandomStrategy

0.0

1.0

0.0

1.0

NoStrategy


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 using

terms (metadata in RDF).


Represent terms and their

relationships (ontology in OWL).


Annotations help to connect

Web resources.

Annotations
-

Qualitative Social Science View


Qualitative data analysis tools such as NVivo.

Can we combine the Semantic Web view with

the 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