OntoLoki: an automatic, instance-based method for the evaluation of biological ontologies on the Semantic Web
The delineation of logical definitions for each class in an ontology and the consistent application of these definitions to the assignment of instances to classes are important criteria for ontology evaluation. If ontologies are specified with property-based restrictions on class membership, then such consistency can be checked automatically. If no such logical restrictions are applied, as is the case with many biological ontologies, there are currently no automated methods for measuring the semantic consistency of instance assignment on an ontology-wide scale, nor for inferring the patterns of properties that might define a particular class. We constructed a program that takes as its input an OWL/RDF knowledge base containing an ontology, instances associated with each of the classes in the ontology, and properties of those instances. For each class, it outputs: 1) a rule for determining class membership based on the properties of the instances and 2) a quantitative score for the class that reflects the ability of the identified rule to correctly predict class membership for the instances in the knowledge base. We evaluated this program using both artificial knowledge bases of known quality and real, widely used ontologies. The results indicate that the suggested method can be used to conduct objective, automatic, data-driven evaluations of biological ontologies without formal class definitions in regards to the property-based consistency of instance-assignment. This inductive method complements existing, purely deductive approaches to automatic consistency checking, offering not just the potential to help in the ontology engineering process but also in the knowledge discovery process.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Large language models as oracles for instantiating ontologies with domain-specific knowledge
Background. Endowing intelligent systems with semantic data commonly requires designing and instantiating ontologies with domain-specific knowledge. Especially in the early phases, those activities are typically performe…
Converting Instance Checking to Subsumption: A Rethink for Object Queries over Practical Ontologies
Efficiently querying Description Logic (DL) ontologies is becoming a vital task in various data-intensive DL applications. Considered as a basic service for answering object queries over DL ontologies, instance checking …
CQE in Description Logics Through Instance Indistinguishability (extended version)
We study privacy-preserving query answering in Description Logics (DLs). Specifically, we consider the approach of controlled query evaluation (CQE) based on the notion of instance indistinguishability. We derive data co…
Privacy PreservingPN-OWL: A Two Stage Algorithm to Learn Fuzzy Concept Inclusions from OWL Ontologies
OWL ontologies are a quite popular way to describe structured knowledge in terms of classes, relations among classes and class instances. In this paper, given a target class T of an OWL ontology, with a focus on ontologi…
Improving the Competency of First-Order Ontologies
We introduce a new framework to evaluate and improve first-order (FO) ontologies using automated theorem provers (ATPs) on the basis of competency questions (CQs). Our framework includes both the adaptation of a methodol…