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Industry-wide collaborative ontology development efforts can distribute development costs over organizations, address a wider range of use cases, and have the potential to be of higher quality than many project or application-specific ontologies. Based on our experience with several industry ontologies, we will present several of the most important lessons learned in developing ontologies for industry applications, ranging from establishing critical policies from the outset, to reusing standards-based patterns, to leveraging collaborative tools for integration and test. Participants will select example use cases as the basis for an in-class ontology, reuse example patterns, and test their work using open-source tools for serializing ontologies as well as that tools that check for syntactic and semantic issues that well-known tools such as Protégé miss, providing direct experience with capabilities that are found essential for industry standard ontology development.

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Detailed Description

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Tutorial Overview

Standards that bridge the labeled property graph to knowledge graph divide will make it easier to use ontologies as the basis for machine learning, natural language processing (NLP) and other graph-based analyses to address real world business challenges. Several well-known graph database vendors have implemented (or are implementing) the emerging RDF (Resource Description Framework) 1.2 [1] and SPARQL (SPARQL Protocol and RDF Query Language) 1.2 W3C [2] specifications to that end. Using richer vocabularies improves the results obtained from querying diverse data sources, particularly from structured data, using large language models (LLMs) in ways that property graphs alone cannot [3].

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In this tutorial we will present several of the most important lessons learned in developing ontologies for industry applications, ranging from establishing critical policies from the outset, to reusing standards-based patterns, to leveraging collaborative tools for integration and test. Participants will select from several example use cases as the basis for an in-class ontology, and reuse at least three of the example patterns in order to complete their projects. They will also test their work using open-source tools for serializing ontologies consistently to enable line-by-line comparison of changes in environments such as GitHub. Projects will also be evaluated for quality using open source tools that check for syntactic and semantic issues that well-known tools such as Protégé miss, providing participants with direct experience with the capabilities we have found essential for industry standard ontology development.

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Learning Outcomes

Participants can expect to learn

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·       How to use and customize the EDM Council’s open-source platform tests and tools for collaboration to improve quality and increase the likelihood of reusability and success 

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Presentation / Interaction Style

This tutorial will involve a combination of lecture plus exercises using open-source standards and technology, all freely available, for use in collaborative ontology development projects.

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Motivation

Advances over the last several years in large language models, natural language processing, and in the use of machine learning for automating knowledge acquisition, have highlighted the need for consistency and higher quality in model development. Accelerated artificial intelligence technology development has raised serious questions and requirements for improving quality, limiting hallucinations, limiting error more generally, and gaining trust among users. Recent research has highlighted the need for ontologies including metadata, provenance, and formal semantics to address some of these gaps, especially with respect to interoperability across and integration of structured data. Development methods that incorporate consistent, recognizable patterns for certain concepts, that systematically test for minimal metadata, that support regression testing with examples, such as those established for projects supported by the EDM Council, are essential to ensuring a high level of quality, and to reassuring users that their projects will continue to work in light of changes made to the ontologies over time. Because these tools are freely available and open source, we believe that sharing them with the broader semantic web community is timely.

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Communities such as the OBO Foundry provide some tools for ontology checking and comparison but do not support regression testing, testing with key examples, or CI/CD (continuous integration / continuous deployment) capabilities. These kinds of capabilities have proven essential for industry ontology development and collaboration with commercial partners, however.

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Format

Half-day tutorial, including lecture and hands-on experimentation.

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Tutorial type and audience

Type: introductory tutorial

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Target Audience: practitioners interested in enterprise and cross-organizational ontology efforts and/or promoting ontologies for broader use, particularly for standardization; ideally 20-40 people, small enough that individual challenges during hands-on sessions can be addressed 

Prerequisites: familiarity with the Web Ontology Language (OWL), ontology development using tools such as Protégé or similar editors, and tools such as GitHub is preferred

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Presenters

Elisa F. Kendall – Partner, Thematix Partners LLC and Lead Ontologist, EDM Council

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Bio: Pawel Garbacz has 20 years of professional experience in ontology development and more recently in project management as a technical lead. In his IT career, Dr Garbacz has worked for small and medium-sized IT companies, where he promoted and applied the Semantic Web technologies in the enterprise-level computer systems. Pawel’s mission for the EDM Council is to oversee the development of its flagship infrastructure for collaborative ontology development. Dr Garbacz has earned a PhD in philosophy from the John Paul II Catholic University of Lublin, where he is currently a full professor and the chair of the Department of Foundations of Computer Science. 

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References

[1] RDF 1.2 Concepts and Abstract Syntax, Olaf Hartig; Champin, Pierre-Antoine; Kellogg, Gregg; Seaborne, Andy, eds. W3C Working Draft, 02 May 2024. Available at https://www.w3.org/TR/rdf12-concepts/ .

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[6] Industrial Ontologies Foundry (IOF) – available at https://oagi.org/pages/industrial-ontologies , and https://github.com/iofoundry/ontology .

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