domain ontology usage analysis framework (ousaf)
DESCRIPTION
OUSAF implements set of metrics to measure the domain ontology usage in RDF dataset.TRANSCRIPT
Domain Ontology Usage Analysis Framework Analyzing the Usage of Domain Ontologies on the (Semantic) Web
Jamshaid Ashraf, Maja Hadzicaja Hadzic
Domain Ontology Usage Analysis Framework Analyzing the Usage of Domain Ontologies on the (Semantic) Web
Jamshaid Ashraf, Maja Hadzicaja Hadzic
Presenter : Presenter : Dr Omar Khadeer HussainDr Omar Khadeer Hussain
>> SKG2011 , Beijing, China Oct. 24-26, 2011
Measuring the Semantic Web on the WebWebWeb
Semantic Web data (Linked data cloud)
Structured
Semantic Web data (Linked data cloud)
Structured
attribute: http://richard.cyganiak.de/2007/10/lod
Q) What and how ontologies are being used on the web?
This research attempts to answers
What What
Significant growth in semantic web dataRDF enabling machines to read
Imperial analysis by using ontologies
Growth of Ontologies• Tremendous growth in the use of ontologies
• Swoogle has an index of 10,000 ontologies
• PingTheSemanticWeb has listed 1442 known namespaces used in the documents
• Ontologies are developed based on Ontology development process based on certain methodology
What is needed?• Evaluate and analyse the usage of an ontology
• Its adoption and uptake by different users on the semantic web.
• Provide an insight into the structure, understand the pattern available, actual use and the intended use
• Understand Ontology Usage in Billions of triples in Linked Open Data (LOD) cloud.
Contributions of this paper
• Ontology Usage Analysis Framework
• Proposes a set of metrics to measure the ontology usage
• Understand the depth of ontology adoptions and the structured data patterns available in the web of data
Difference of Ontology Usage with Ontology Evaluation and Evolution
• Ontology Usage analyses the use of ontology on the web by measuring its usage, usefulness and commercial advantages
• Ontology Evaluation is the analysis of guaranteeing what is built meets the requirements and is error free
• Ontology Evolution is the timely adoption of ontology to the arisen changes and consistent management of these changes
• Overlap between ontology usage, evaluation and evolution
Why Ontology Usage Analysis (OUA)
• Think• Design• Develop & evaluate
(ontology only)• Deploy• Evangelize• Adoption!
• Measure and analyze• Learn from it to influence
future thinking and design
Typical ontology LifecycleTypical ontology Lifecycle
Ontology
OUA contribution (in red)OUA contribution (in red)
Why Why
Domain Domain OOntology ntology USUSage age AAnalysis nalysis FFramework ramework (OUSAF) (OUSAF)
Metrics Metrics
ConceptConcept related metrics
RelationshipRelationship related metrics
AttributeAttribute (data properties) related metrics
Metrics Metrics
ConceptConcept related metrics
>>Concept Richness Richness (CR): Describes the relationship with other concepts and the number of attributes to describe the instances
CR (C) = |PC| + |AC|
>>Concept Usage Usage (CU): Measures the instantiation of the concept in the knowledge base
CU(C) = | {t = (s,p,o) | p= rdf:type, o = C }|
>>Concept Population Population (CP): Calculates all the triplets in the KB where concept’s instances is used to either create relationships or provide data descriptions
CP(C) = | {t = (s,p,o) | s = C(I) , o= C(I) or L }|
Metrics Metrics
RelationshipRelationship related metrics
>>Relationship Value Value (RV): Reflects the possible role of an object property in creating typed relationship between different concepts
RV (P) = | dom(P)| + |range(P) |
>>Relationship Usage Usage (RU): Calculates the number of triplets in a dataset in which object property is used to create relationships between different concept’s instances
RU(P) = | { t:=(s,p,o) | p= P} |
Metrics Metrics
Attribute (data properties)Attribute (data properties) related metrics
>>Attribute Value Value (RV): Reflects the number of concepts that have data properties used to provide values to instances
AV (A) = | dom(A) |
>>Attribute Usage Usage (RU): Measures how much data description is available in the knowledge base for a concept instance
AU(A) = | { t:=(s,p,o) | p A, o L) |
Metrics Metrics
Domain Ontology Population (DOP)Domain Ontology Population (DOP)
Measures the amount of structured data available in the Knowledge base that is annotated using ontology RDF terms
Domain Ontology Usage (DOU)Domain Ontology Usage (DOU)
Measures the use of ontology vocabulary in the dataset
DOU= KBS
DOP
DOP =
Implementation Implementation
Domain Ontology = Domain Ontology =
Why?
GoogleYahooBestBuyVolkswagenOverstockO’ReillySears
Dataset Dataset
• Collected via Sindice, Watson, Google, Linked Open
Commerce, GR wiki
• 105 web sources (web sites)
• Published Company and/or product/service Offering
GoodRelations Dataset (GRDS)(GRDS)
AnalysisAnalysis
Concept Richness (CR) in dataset
Several object and data properties available in the conceptual model providing rich set for semantic annotation
AnalysisAnalysis Concept Richness with Concept Usage
A small part of the ontology is widely used.Concepts with higher richness value also have large instantiationsGeneralized concepts have fewer instantiations compared with specialized concept
AnalysisAnalysis
Ontology Usage Analysis
Provides an overview of ontology usage, trend and patterns available in the KB
Conclusion Conclusion
Ontology Usage Analysis
• helps is finding the data patterns available in the web of data
• helps ontology engineers/developer to understand the usage patterns and evolve the ontology accordingly
• helps is mapping different vocabularies based on their usages
• helps developers in anticipating the available knowledge (T-Box) in knowledgebase
• Expand the dataset and include other ontologies • Automate the analysis process • Instance data quality, consistency• Recommendations to publishers and vocabulary designers
Future workFuture work
Thanks! Thanks!
Questions……… Please email: [email protected] Questions……… Please email: [email protected]