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Modular Ontology Engineering with CoModIDE

CoModIDE is a plugin for Protégé that enables graphical drag-and-drop editing of ontologies, with built in support for Ontology Design Patterns (ODPs). CoModIDE allows for simple construction and maintenance of modular ontologies; moreover, by taking an opinionated position on how to render OWL axioms on a graphical canvas, and which axioms to generate from constructs on said canvas, CoModIDE represents an attempt to develop the fine-grained method guidance we believe is missing from ODP usage methodologies.

This tutorial aims to illustrate to participants how to use CoModIDE for both applied ontology engineering, and research on ontology engineering methodology. Specifically, our objectives are:

  1. To teach the participants how to use the CoModIDE tool for the construction and maintenance of small- to medium-sized modular ontologies based on design patterns.
  2. To illustrate the utility of modular ontology engineering to researchers, such that they can use and spread these methods and tools in projects with industry.

Learning Objectives

After taking this tutorial, participants should:

  1. Be able to select, instantiate, align, and remove ontology design pattern-based modular into/from a modular ontology using CoModIDE.
  2. Be able to create and import new ontology design patterns, adding them to the CoModIDE pattern library.
  3. Be able to apply the XD methodology and CoModIDE to create and evolve medium-sized ontologies.
  4. Understand the design choices that have gone into the CoModIDE tooling, including the tradeoffs between usability and logic expressivity that need to be considered when rendering ontologies graphically; and how the use of OPLa allows us to emulate concepts not native to the OWL language, such as interfaces and modules.

Tutorial Schedule

Exercise 1 – Introduction to CoModIDE modelling – Instructions/Workflows domain – 90 minutes

Break

Exercise 2 – Advanced modelling topics – Smart Buildings domain – 90 minutes

Presenters

Karl Hammar
Jönköping AI Lab, Jönköping University, Sweden
Email: karl.hammar@jonkoping.ai
Web: https://karlhammar.com

Karl holds a PhD from Linköping University, Sweden, and is employed within the Jönköping Artificial Intelligence Lab (JAIL) at Jönköping University, Sweden. Karl’s PhD dissertation focused specifically on ontology engineering methods and tools supporting the use of Ontology Design Patterns. His research since has continued in this direction, focusing on applied ontology engineering in real-world scenarios, ranging from building automation and analytics, to veterinary syndromic surveillance.

Cogan Shimizu
Data Semantics Lab, Kansas State University, USA

Cogan is a PhD candidate at Kansas State University (KSU), USA and is a member of the Data Semantics Laboratory, also at KSU. Cogan’s dissertation work focuses on ontology engineering methodologies, specifically those that involve ontology design patterns, with an intended result of making ontology engineering more accessible to non-ontologists. Currently, his work involves the development, use, and evaluation of intuitive tooling infrastructure to support such methodologies.