Reasoning for Ontology Engineering and Usage 1. Introduction, - - PowerPoint PPT Presentation

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Reasoning for Ontology Engineering and Usage 1. Introduction, - - PowerPoint PPT Presentation

Aug 19, 2022 404 likes •780 views

Reasoning for Ontology Engineering and Usage 1. Introduction, standard reasoning (Ralf Mller) 2. Bottom-up approach for ontology design (Anni-Yasmin Turhan) 3. Understanding and repairing inferences (Matthew Horridge) 4. Data integration through

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The TONES Consortium:

  • Free University of Bozen-Bolzano
  • Università di Roma “La Sapienza”
  • The University of Manchester
  • Technische Universität Dresden
  • Technische Universität Hamburg-Harburg

http://www.tonesproject.org/

Reasoning for Ontology Engineering and Usage

  • 1. Introduction, standard reasoning (Ralf Möller)
  • 2. Bottom-up approach for ontology design (Anni-Yasmin Turhan)
  • 3. Understanding and repairing inferences (Matthew Horridge)
  • 4. Data integration through ontologies

(Diego Calvanese, Giuseppe de Giacomo, Mariano Rodriguez)

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The TONES Consortium:

  • Free University of Bozen-Bolzano
  • Università di Roma “La Sapienza”
  • The University of Manchester
  • Technische Universität Dresden
  • Technische Universität Hamburg-Harburg

http://www.tonesproject.org/

Reasoning for Ontology Engineering and Usage Part 1: Introduction

Ralf Möller Hamburg University of Technology

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Ralf Möller 3 Reasoning for Ontology Engineering and Usage

Terminological knowledge

  • Represent an application domain in terms of
  • Classes (concept descriptions),
  • Properties (relations, role descriptions), and
  • Objects (instances, individuals)
  • First step: select names (define signature)
  • Atomic concept descriptions:

Student, Professor, Chair, Department, …

  • Atomic role descriptions: headOf, takesCourse, memberOf
  • Individuals: FullProfessor01, Department09, …
  • Use axioms to impose “constraints” (restrictions)
  • n the interpretation of these names
  • A chair must be a person,
  • Persons are no departments
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Ontologies

  • Standardization of ontology languages
  • DL (abstract syntax), OWL 2 (and various sublanguages)
  • Standardization of query and manipulation languages
  • DIG 1.2, OWL API, OWLlink
  • Decision problems
  • Does the ontology make sense (satisfiability)
  • Find implicit terminology (e.g. subsumption)
  • Find implicit facts
  • Need reasoning for solving problems
  • Need optimized techniques to achieve scalability

TBox - Class-level Ontology ABox - Instance-level Reasoner

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Editing Ontologies

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Various approaches for design

  • Top-down, bottom-up, reuse, …

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TBox - Class-level Ontology ABox - Instance-level Top-down

  • ntology design

Reasoner

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Ralf Möller 7 Reasoning for Ontology Engineering and Usage

Software infrastructure for ontology engineering

  • Standard Reasoning:
  • CEL, Fact++, Pellet, RacerPro
  • Non-Standard Reasoning:
  • Commonalities, Approximation, Matching, Modularization, Explanation
  • SONIC as a Racer plugin, Pellet Extensions
  • Ontology-based data access
  • RacerPro, QuOnto
  • User Interfaces:
  • RacerPorter (Tutorial Part 1) + SONIC plugin
  • Protégé + Plugins:
  • Racer plugin (Tutorial Part 1)
  • SONIC plugin (Tutorial Part 2)
  • Modularization plugin (Tutorial Part 3)
  • Explanation plugin (Tutorial Part 3)
  • OBDA plugin (Tutorial Part 4)
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Ralf Möller 8 Reasoning for Ontology Engineering and Usage

OWL, a textual ontology language

  • Various syntaxes
  • OWL/XML syntax
  • RDF/XML syntax
  • Functional syntax(es)
  • Need to understand the semantics
  • Semantics based on description logics
  • Abstract syntax
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Ralf Möller 9 Reasoning for Ontology Engineering and Usage

Representative DL:

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Ralf Möller 10 Reasoning for Ontology Engineering and Usage

Example concept descriptions

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Ralf Möller 13 Reasoning for Ontology Engineering and Usage

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Ralf Möller 14 Reasoning for Ontology Engineering and Usage

Functional style: Manchester Syntax Class: Person and (worksFor some Organization) OWL/XML Syntax <ox:Intersection> <ox:OWLClass ox:URI=“Person”> <ox:ObjectSomeValuesFrom> <ox:ObjectProperty ox:URI=“worksFor”/> <ox:OWLClass ox:URI=“Organization”/> <ox:ObjectSomeValuesFrom/> <ox:Intersection/>

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Ralf Möller 15 Reasoning for Ontology Engineering and Usage

ALCQ Semantics

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Interpretation of concept descrs

P1 P2 P3 P4 DL DB Sem Web Person Person Person Person Course Course Course

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Satisfiability of concept descriptions

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Tbox

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19

Model of Tbox, Subsumption

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Tbox inference problems

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Ralf Möller 21 Reasoning for Ontology Engineering and Usage

ALC as a fragment of FOL

  • Concepts = unary predicates
  • Roles = binary predicates
  • Concept descriptions = FOL-formulae with one free

variable

  • GCIs = FOL-formulae without free variables

(sentences)

  • KB = set of sentences
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Ralf Möller 22 Reasoning for Ontology Engineering and Usage

Classification

Person Organization Course Professor FullProfessor Student Chair UndergraduateStudent Department

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Ralf Möller 23 Reasoning for Ontology Engineering and Usage

Classification

Person Organization Course Professor FullProfessor Student Chair UndergraduateStudent Department

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Demo

  • RacerPro and RacerPorter

Ralf Möller 24 Reasoning for Ontology Engineering and Usage

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What about individuals?

Ralf Möller 25 Reasoning for Ontology Engineering and Usage

TBox - Class-level Ontology ABox - Instance-level Querying Ontologies Reasoner

Chair(x) Ralf, Ian,...

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Abox

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Example

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Abox consistency

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Abox inference problems

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Ontology usage

  • Example: curriculum design

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Unique name assumption

  • Different individuals are mapped to different

domain objects

  • Example:

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Example

  • Find eager students

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Open world assumption

  • If something cannot be proven, it is not

concluded that the negation holds

  • Example: find lazy professors
  • Epistemic aspects in query languages

required (e.g., nRQL)

Ralf Möller 33 Reasoning for Ontology Engineering and Usage

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Query Answering

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Ralf Möller 35 Reasoning for Ontology Engineering and Usage

Query answering w.r.t. ontologies

  • Incomplete information, but need the certain answers
  • Expressivity of different query languages
  • Grounded conjunctive queries plus additions
  • In principle:

reduction to instance tests (standard service)‏

  • But: non-trivial optimization techniques

required (e.g., query execution plans)

  • Efficient QA in practical applications for expr. DLs
  • Aggregation operators and
  • Server-side processing of query results

with optimization

  • Practical implementation as part of RacerPro
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State of the Art

Expressive DLs, answering GCQs

  • 5 years ago: 100 Individuals
  • 3 years ago: 1000 Individuals
  • Now: 10000 individuals, interactive queries,

up to 100000 depending on the expressivity used in the Tbox

  • Note that we talk about sound and complete

reasoning

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