UNCERTML%20-%20DESCRIBING%20AND%20COMMUNICATING%20UNCERTAINTY - PowerPoint PPT Presentation

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UNCERTML%20-%20DESCRIBING%20AND%20COMMUNICATING%20UNCERTAINTY

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Title: UNCERTML%20-%20DESCRIBING%20AND%20COMMUNICATING%20UNCERTAINTY


1
UNCERTML - DESCRIBING AND COMMUNICATING
UNCERTAINTY
  • Matthew Williams
  • williamw_at_aston.ac.uk

2
OVERVIEW
  • Introduction.
  • Motivation the Semantic and Sensor Webs.
  • UncertML overview.
  • Use case The INTAMAP project.
  • Conclusions.

3
MOTIVATION
  • The semantic and sensor webs

4
THE SENSOR WEB
5
SENSOR WEB ENABLEMENT (SWE)
  • Open Geospatial Consortium (OGC) initiative
  • Interoperability interfaces and metadata
    encodings.
  • Real time integration of heterogeneous sensor
    webs into the information infrastructure.
  • Current SWE standards
  • Observations Measurements
  • SensorML
  • SWE Common
  • No formal standard for quantifying uncertainty

6
HOW UNCERTAINTY IS USED WITHIN THE SEMANTIC WEB
  • PR-OWL a Bayesian Ontology Language for the
    Semantic Web
  • Extends OWL to allow probabilistic knowledge to
    be represented in an ontology.
  • Used for reasoning with Bayesian inference.
  • Random variables are described by either a PR-OWL
    table (discrete probability) or using a
    proprietary format.
  • Other standards looking at similar concepts
  • BayesOWL.
  • FuzzyOWL.

7
What next?
  • A formal open standard for quantifying complex
    uncertainties
  • Extend to allow continuous distributions
  • More powerful reasoning, richer representations

8
UNCERTML
9
OVERVIEW
  • Split into three distinct packages
    (distributions, statistics realisations).

10
DISTRIBUTIONS
11
UNCERTML
  • An overview

12
WEAK VS. STRONG
  • Weak-typed
  • Strong-typed
  • Benefits
  • Generic features have generic properties
    extensible
  • Drawbacks
  • Validation becomes less meaningful
  • Benefits
  • Produces relatively simple XML features
  • Drawbacks
  • Not easily extended all domain features must be
    known a priori

13
THE UNCERTML DICTIONARY
  • Weak-typed designs rely on dictionaries.
  • Includes definitions of key distributions
    statistics.
  • URIs link to dictionary entry and provide
    semantics.
  • Could be written in Semantic Web standards (OWL,
    RDF etc).

14
UNCERTML DICTIONARY EXAMPLE
15
SEPARATION OF CONCERNS
  • Several competing standards already exist
    addressing the issue of units and location.
  • Geospatial information not always relevant
    Systems biology.
  • Do what we know do it well!

16
UNCERTML
  • An applied case study

17
THE INTAMAP PROJECT
  • An automatic, interoperable service providing
    real time interpolation between observations.
  • EURDEP providing radiological data as a case
    study.
  • Provide real time predictions to aid risk
    management through a Web Processing Service
    interface.

18
UNCERTML IN INTAMAP
19
COMPARING PREDICTIONS WITH AND WITHOUT UNCERTML
  • Without UncertML
  • With UncertML

20
CONCLUSIONS
  • Currently no interoperable standard which fully
    describes random variables.
  • UncertML provides an extensible, weak-typed,
    design that can quantify uncertainty using
  • Distributions.
  • Statistics.
  • Realisations.
  • Provide richer information for use in decision
    support systems.

21
UNCERTML IN INTAMAP
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