Skip to main content Accessibility help
×
Hostname: page-component-76fb5796d-wq484 Total loading time: 0 Render date: 2024-04-26T12:47:16.880Z Has data issue: false hasContentIssue false

10 - Conceptual Modeling with Description Logics

Published online by Cambridge University Press:  06 July 2010

Franz Baader
Affiliation:
Technische Universität, Dresden
Diego Calvanese
Affiliation:
Freie Universität Bozen, Bolzano
Deborah L. McGuinness
Affiliation:
Rensselaer Polytechnic Institute, New York
Daniele Nardi
Affiliation:
Università degli Studi di Roma 'La Sapienza', Italy
Peter F. Patel-Schneider
Affiliation:
AT&T Bell Laboratories, New Jersey
Get access

Summary

Abstract

The purpose of the chapter is to help someone familiar with DLs to understand the issues involved in developing an ontology for some universe of discourse, which is to become a conceptual model or knowledge base represented and reasoned about using Description Logics.

We briefly review the purposes and history of conceptual modeling, and then use the domain of a university library to illustrate an approach to conceptual modeling that combines general ideas of object-centered modeling with a look at special modeling/ontological problems, and DL-specific solutions to them.

Among the ontological issues considered are the nature of individuals, concept specialization, non-binary relationships, materialization, aspects of part–whole relationships, and epistemic aspects of individual knowledge.

Background

Information modeling is concerned with the construction of computer-based symbol structures that model some part of the real world. We refer to such symbol structures as information bases, generalizing the term from related terms in Computer Science, such as databases and knowledge bases. Moreover, we shall refer to the part of a real world being modeled by an information base as its universe of discourse (UofD). The information base is checked for consistency, and sometimes queried and updated through special-purpose languages. As with all models, the advantage of information models is that they abstract away irrelevant details, and allow more efficient examination of both the current, as well as past and projected future states of the UofD.

Type
Chapter
Information
The Description Logic Handbook
Theory, Implementation and Applications
, pp. 377 - 401
Publisher: Cambridge University Press
Print publication year: 2007

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×