Simplified Approach for Representing Part-Whole Relations in OWL-DL Ontologies

Simplified Approach for Representing Part-Whole Relations in OWL-DL Ontologies Pace University IEEE BigDataSecurity, 2015 Aug. 24, 2015

Outline Ontology and Knowledge Representation 1 Ontology and Knowledge Representation Ontology for representing knowledge Ontology Relations OWL: Representing and Reasoning 2 Scenario Current Approach (W3.org Best Practice) 3 Proposed Approach Comparison and Demo 4 Limitations and Future Work

Ontology for representing knowledge Ontology Relations OWL: Representing and Reasoning Ontology and Knowledge Representation Why we need to represent knowledge? Definition: an ontology formally represents knowledge as a set of concepts within a domain, using a shared vocabulary to denote the types, properties and interrelationships of those concepts. (Wikipedia) Goals for having ontology (AI systems): What is this? (Representation). How this relates to that? (Inference).

Ontology for representing knowledge Ontology Relations OWL: Representing and Reasoning Ontology and Knowledge Representation Example of an ontology model Sample ontology for a human body anatomy

IS-A and Part-Whole Relations Class hierarchy Ontology for representing knowledge Ontology Relations OWL: Representing and Reasoning We are focusing on two types of ontology taxonomy: Generalization-based (e.g. Heart is an Organ) Partonomic-based (e.g. Retina is part of the Eye)

TBox vs. ABox Statements Definitions Ontology for representing knowledge Ontology Relations OWL: Representing and Reasoning Terminological Box and Assertional Box Statements TBox: Relations Between Concepts, e.g. Every Car is a Vehicle. Car Vehicle An Engine is part of a Vehicle. Engine CarPart OR Engine partof Vehicle ABox: Assertion Sentences (between an instance and concept), e.g. BMW is a Car. Car(BMW) TBox + ABox = Knowledge Base

OWL Building ontology Ontology and Knowledge Representation Ontology for representing knowledge Ontology Relations OWL: Representing and Reasoning Web Ontology Language: OWL is a family of knowledge representation languages for authoring ontologies (Semantic Web). Description Logics: DL (variant of FOL) used in OWL to specify the semantics of a relation. Reasoning in ontologies and knowledge bases is one of the reasons why a specification needs to be formal one.

What is the Problem? Scenario Current Approach (W3.org Best Practice) Let s introduce the problem through a simple Use Case.

Scenario Current Approach (W3.org Best Practice) Scenario For representing a simple IS-A and Part-Of relations in OWL Example: How to assert the following model? In words, Car class as a generalization of (is a) Vehicle class, and Engine class as a component of (part of) Vehicle class.

Scenario Current Approach (W3.org Best Practice) Scenario For representing a simple IS-A and Part-Of relations in OWL... IS-A relation (very simple way) : Example < owl : Class rdf : about ="ns#car "> < rdfs : subclassof rdf : resource ="ns# Vehicle "/> </owl : Class > Part-Whole relation:... OWL does not provide simple (and straightforward) primitives for part-whole relations.

Why is that? Difficulty in representing part-whole relations Scenario Current Approach (W3.org Best Practice) Because, Part-Whole relations are variants (many different forms). Thus Some constraints (e.g. transitivity, cardinality) need to be imposed to specify the semantic of the relation. C. M. Keet and A. Artale, Representing and reasoning over a taxonomy of part-whole relations, Applied Ontology, vol. 3, Jan. 2008

Current Approach For representing Part-Whole in OWL Scenario Current Approach (W3.org Best Practice) The Current Approach provides a manual implementation of the underlying steps (thus a long and error-prone process) for achieving a single task.

Current Approach Three steps implemented separately and manually Scenario Current Approach (W3.org Best Practice) 1 Create an objectproperty (i.e. partof) with specifying the characteristics it holds. 2 Create a new part-aggregating class (i.e. VehiclePart) to represent the parts type. And (using OWL-DL) make it: equivalentclass to the restriction partof some Vehicle. e.g. carpart partof Vehicle 3 Extend the part Class Engine to cope with the constraints. By using OWL-DL to: make it a subclassof of the restriction partof some Vehicle. e.g. Engine partof Vehicle

Current Approach The three steps serialized in RDF/XML syntax Scenario Current Approach (W3.org Best Practice) Example <!-- Step 1 --> < owl : ObjectProperty rdf : about ="&part ; partof "> < rdf :type rdf : resource ="&owl ; TransitiveProperty "/> </owl : ObjectProperty > <!-- Step 2 --> < owl : Class rdf : about ="ns# VehiclePart "> < owl : equivalentclass > < owl : Restriction > < owl : onproperty rdf : resource ="ns# partof "/> < owl : somevaluesfrom rdf : resource ="ns# Vehicle "/> </owl : Restriction > </owl : equivalentclass > </owl : Class > <!-- Step 3 --> < owl : Class rdf : about ="ns# Engine "> < rdfs : subclassof > < owl : Restriction > < owl : onproperty rdf : resource ="ns# partof "/> < owl : somevaluesfrom rdf : resource ="ns# Vehicle "/> </owl : Restriction > </rdfs : subclassof > </owl : Class >

Proposed Approach Simplifying Part-Whole Relations in OWL Proposed Approach Comparison and Demo Integrate the three steps into a single line Example i.e. part-whole relations in a similar manner to subclassof, as follows: < owl : Class rdf : about ="ns# Engine "> < relation : partof transitive ="yes " rdf : resource ="ns# Vehicle "/> </owl : Class > Then, automatically 1 extract and build the relation s constraints. 1 Using pyowl module.

Proposed Approach Work flow of our method Proposed Approach Comparison and Demo Simplified Relations Extraction and Transformation Generate Final layout Using OWL s Annotations Relation Elements Mapping Standardized RDF/XML

Proposed Approach Simple Conceptual Model Proposed Approach Comparison and Demo

Transformation Method Mapping stage 1 Proposed Approach Comparison and Demo Extend current class to be a subclassof its declared parent Example < owl : Class rdf : about =" onto # Engine "> <!-- Auto generated mapping --> < rdfs : subclassof > < owl : Restriction > < owl : onproperty rdf : resource =" onto # partof "/> < owl : somevaluesfrom rdf : resource =" onto # Vehicle "/> </ owl : Restriction > </ rdfs : subclassof > <!-- End mapping --> </ owl : Class >

Transformation Method Mapping stage 2 Proposed Approach Comparison and Demo Generate an objectproperty for the relation Example <!-- Property --> <!-- Auto generated mapping --> < owl : ObjectProperty rdf : about =" onto # partof "> < rdf : type rdf : resource ="& owl ; TransitiveProperty "/> </ owl : ObjectProperty > <!-- End mapping -->

Transformation Method Mapping stage 3 Proposed Approach Comparison and Demo Generate the parts-aggregating Class as an equivalentclass of parent Example <!-- Auxiliary Class --> <!-- Auto generated mapping --> < owl : Class rdf : about =" onto # partof_vehicle "> < owl : equivalentclass > < owl : Restriction > < owl : onproperty rdf : resource =" onto # partof "/> < owl : somevaluesfrom rdf : resource =" onto # Vehicle "/> </ owl : Restriction > </ owl : equivalentclass > </ owl : Class > <!-- End mapping -->

Comparison Ontology Metrics of Both Approaches Proposed Approach Comparison and Demo Sample Ontology Metrics The proposed method reduces the axiom count by 40% to 50% simplify the expressivity level (of DL) from ALE+ to AL

Proposed Approach Comparison and Demo Comparison Evaluation: classification results are the same (safe representation) Inferred model 2 from each approach 3 : (a) Our Transformed Approach (b) Current Approach 2 OWL-Viz and HermiT 1.3.8 reasoner plugins (built-in in Protege) 3 Ontology example3.owl from Rector, Alan, et al.

Demo of the approach Proposed Approach Comparison and Demo A complete working example: see

Limitations Of the proposed approach Limitations and Future Work Currently, this approach supports ALE+ expressivity level three constraints Transitivity, Cardinality, and Inverse. applies to relations of TBox statements only.

Future Work and Contributions Limitations and Future Work Future Work Support different DL levels (ALEHI+ e.g. subproperties). Applicability to other OWL syntaxes (e.g. Manchester and functional). Interfacing the module with Protege. Contribution The proposed approach contributes to: simplify the complexity involved in representing part-whole relations. reduce work overhead and amount of work needed, thus minimizing the possibility of error making. provide support to Semi-Auto Ontology Building. proved the feasiability of the approach.

Ontology and Knowledge Representation Limitations and Future Work In summary, Representing the semantics of part-whole relations is a fairly complex process. Why? Because each relation may hold different (inference) characteristics depending on the context. Description Logics introduced in OWL to capture such varieties. So what s wrong? OWL-DL is applied through a manual (and separately implemented steps of the same) process. Therefore, we introduced Simplified approach for applying OWL-DL for representing part-whole relations.

Questions? Thank You For Your Attention