Ontology-based data integration

About: Ontology-based data integration is a research topic. Over the lifetime, 11065 publications have been published within this topic receiving 216888 citations.

Measuring semantic similarity between Gene Ontology terms

Abstract: Many bioinformatics applications would benefit from comparing proteins based on their biological role rather than their sequence. This paper adds two new contributions. First, a study of the correlation between Gene Ontology (GO) terms and family similarity demonstrates that protein families constitute an appropriate baseline for validating GO similarity. Secondly, we introduce GraSM, a novel method that uses all the information in the graph structure of the Gene Ontology, instead of considering it as a hierarchical tree. GraSM gives a consistently higher family similarity correlation on all aspects of GO than the original semantic similarity measures.

Method and system for collaborative ontology modeling

Abstract: A distributed ontology system including a central computer comprising a global ontology directory, a plurality of ontology server computers, each including a repository of class and relation definitions, and a server for responding to queries relating to class and relation definitions in the repository, and a computer network connecting the central computer with the plurality of ontology server computers. A method is also described and claimed.

A methodology for ontology integration

Abstract: Although ontology reuse is an important research issue only one of its subprocesses (merge) is fairly well understood. The time has come to change the current state of affairs with the other reuse subprocess: integration. In this paper we describe the activities that compose this process and describe a methodology to perform the ontology integration process..

The ontology of the gene ontology.

Abstract: The rapidly increasing wealth of genomic data has driven the development of tools to assist in the task of representing and processing information about genes, their products and their functions. One of the most important of these tools is the Gene Ontology (GO), which is being developed in tandem with work on a variety of bioinformatics databases. An examination of the structure of GO, however, reveals a number of problems, which we believe can be resolved by taking account of certain organizing principles drawn from philosophical ontology. We shall explore the results of applying such principles to GO with a view to improving GO's consistency and coherence and thus its future applicability in the automated processing of biological data.

An ontology of scientific experiments

Abstract: The formal description of experiments for efficient analysis, annotation and sharing of results is a fundamental part of the practice of science. Ontologies are required to achieve this objective. A few subject-specific ontologies of experiments currently exist. However, despite the unity of scientific experimentation, no general ontology of experiments exists. We propose the ontology EXPO to meet this need. EXPO links the SUMO (the Suggested Upper Merged Ontology) with subject-specific ontologies of experiments by formalizing the generic concepts of experimental design, methodology and results representation. EXPO is expressed in the W3C standard ontology language OWL-DL. We demonstrate the utility of EXPO and its ability to describe different experimental domains, by applying it to two experiments: one in high-energy physics and the other in phylogenetics. The use of EXPO made the goals and structure of these experiments more explicit, revealed ambiguities, and highlighted an unexpected similarity. We conclude that, EXPO is of general value in describing experiments and a step towards the formalization of science.