Integrating Scientific Data through External, Concept-Based Annotations
Proceedings of the VLDB 2002 Workshop EEXTT and CAiSE 2002 Workshop DTWeb on Efficiency and Effectiveness of XML Tools and Techniques and Data Integration over the Web-Revised Papers
Bioinformatics integration and agent technology
Journal of Biomedical Informatics
Life science research and data management—what can they give each other?
ACM SIGMOD Record
A knowledge-based approach to merging information
Knowledge-Based Systems
Optimizing Terminological Reasoning for Expressive Description Logics
Journal of Automated Reasoning
An ontology-based multi-agent system conceptual model
International Journal of Computer Applications in Technology
In situ migration of handcrafted ontologies to reason-able forms
Data & Knowledge Engineering
Building a Fuzzy Ontology of Edutainment Using OWL
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007
Psychiatric document retrieval using a discourse-aware model
Artificial Intelligence
The Knowledge Engineering Review
Description logics in ontology applications
TABLEAUX'05 Proceedings of the 14th international conference on Automated Reasoning with Analytic Tableaux and Related Methods
Faster pattern matching algorithm for arc-annotated sequences
Proceedings of the 2005 international conference on Federation over the Web
Applications of description logics: state of the art and research challenges
ICCS'05 Proceedings of the 13th international conference on Conceptual Structures: common Semantics for Sharing Knowledge
Reasoning support for expressive ontology languages using a theorem prover
FoIKS'06 Proceedings of the 4th international conference on Foundations of Information and Knowledge Systems
Reasoning in description logics: basics, extensions, and relatives
RW'07 Proceedings of the Third international summer school conference on Reasoning Web
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This paper describes the initial stages of building an ontology of bioinformatics and molecular biology. The conceptualization is encoded using the ontology inference layer (OIL), a knowledge representation language that combines the modeling style of frame-based systems with the expressiveness and reasoning power of description logics (DLs). This paper is the second of a pair in this special issue. The first described the core of the OIL language and the need to use ontologies to deliver semantic bioinformatics resources. In this paper, the early stages of building an ontology component of a bioinformatics resource querying application are described. This ontology (TaO) holds the information about molecular biology represented in bioinformatics resources and the bioinformatics tasks performed over these resources. It, therefore, represents the metadata of the resources the application can query. It also manages the terminologies used in constructing the query plans used to retrieve instances from those external resources. The methodology used in this task capitalizes upon features of OIL-The conceptualization afforded by the frame-based view of OIL's syntax; the expressive power and reasoning of the logical formalism; and the ability to encode both handcrafted, hierarchies of concepts, as well as defining concepts in terms of their properties, which can then be used to establish a classification and infer relationships not encoded by the ontologist. This ability forms the basis of the methodology described here: For each portion of the TaO, a basic framework of concepts is asserted by the ontologist. Then, the properties of these concepts are defined by the ontologist and the logic's reasoning power used to reclassify and infer further relationships. This cycle of elaboration and refinement is iterated on each portion of the ontology until a satisfactory ontology has been created.