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II Jornadas sobre Ontologías y Web Semántica. WebSemántica'2007
Method for ontology generation from concept maps in shallow domains
Alfredo Simón1
Luigi Ceccaroni2 Alejandro Rosete1
1 Technical Institute “José Antonio Echeverría” (Cuba)2 Technical University of Catalonia, Software department (Spain)
Introduction
The development and use of ontologies is increasing today
The design and creation of ontologies, the tools available and the specification languages are still complex (*environment of human collaboration)
These suggests the use of a form of representation that can be used naturally by humans and integrated with ontologies
Integration between an informal, flexible and graphic model of knowledge (*Concept Map) and OWL ontologies
It based on a concept sense-disambiguation procedure and WordNet
It applied to concept maps of shallow domain with labels in the Spanish language
Oriented to obtain OWL-Lite and OWL-DL
Method proposed
Defined by Novak (70’s) within the pedagogical sciences as graphical tools for organize and represent descriptive knowledge
Kind of semantic network but not formal and more flexible
Include concepts and relationship between concepts
Propositions (concept, link-word, concept) are the smallest semantic structure with proper sense
Oriented to be used and interpreted by humans Knowledge is expressed in natural language
Concept Map
Examples (spanish concept maps)
Medical Domain Ontology from the @LIS TechNET Project
It is an ontological and conceptual knowledge representation
It is a sort of semantic network. Therefore similar to Frame Systems
propositions and triples (subject, predicate, object) of RDF have similar structures
structural correspondence:concept with class/subclasslinks and link-word with propertypropositions with restriction and other OWL specifications
Concept maps & OWL ontologies
but it isn’t enough
To increase the formalization levels of the link-words in the concept map
To analyze the concept map as a structured text:Identify the correct sense of the concepts (synset in WordNet)Identify the semantic of the relation between concepts using WordNet (hypernym-hyponym,meronym-holonym)
Five Phases
Formal Transformation
Identification of the Concept Map Domain
Concept Sense Disambiguation for Domain
Concept Sense Disambiguation for Context
Using Spanish WordNet Lexical Database
1st Phase. Concept sense disambiguation
Concept Map Domain
Senses of Arteria concept
1st Phase. Concept sense disambiguation
2nd Phase. Initial coding of OWL classes
3rd Phase. Identification of subclass relations
hypernym relations inhypernym relations in WordNetWordNet
3rd Phase. Identification of subclass relations
4th Phase. Identification of instance relations
5th Phase. Identification of property relations
5th Phase. Identification of property relations
5th Phase. Identification of property relations
5th Phase. Identification of property relations
5th Phase. Identification of property relations
Java application
Input: XML (generated for Macosoft -Concept Maps Editor)
Output: OWL
Validated with Protégé and WonderWeb OWL Ontology Validator
Implementation and Validation
Conclusions
It has been shown that a tight relationship exists between conceptual maps and ontologies
The interpretation of conceptual maps as structured text allows the semantic inference needed for their coding in OWL, without losing flexibility
The defined procedures generate OWL ontologies from conceptual maps
The proposed integration creates the bases for generalization to other domains and for the collaborative development of ontologies
identifications of more OWL specifications inside the concept maps as: TransitiveProperty and SymmetricProperty, property value (hasValue), intersection of class (intersectionOf) and equivalent class
reuse of public ontologies and concept maps repositories
Future Work
