Category: Ontologies

Excerpts from Ontology Building: A Survey of Editing Tools:

With databases virtually all of the semantic content has to be captured in the application logic. Ontologies, however, are often able to provide an objective specification of domain information by representing a consensual agreement on the concepts and relations characterizing the way knowledge in that domain is expressed.

All ontologies have a part that historically has been called the terminological component. This is roughly analogous to what we know as the schema for a relational database or XML document. It defines the terms and structure of the ontology’s area of interest. The second part, the assertional component, populates the ontology further with instances or individuals that manifest that terminological definition. This extension can be separated in implementation from the ontology and maintained as a knowledge base.

CL – Common Logic is the emerging successor to the KIF ontology construction language.

The wide array of information residing on the Web has given ontology use an impetus, and ontology languages increasingly rely on W3C technologies like RDF Schema as a language layer, XML Schema for data typing, and RDF to assert data.

…tools, like Microsoft’s Visio for Enterprise Architects, use an object-oriented specification language to model an information domain (in this case, the Object Role Modeling language). These tools presently lack useful export capabilities, although independent tools to convert between UML and ontology languages like DAML+OIL are under development.

Methodology…in today’s tools…explicit support for a particular knowledge engineering methodology (like KADS) is not common.

Interoperability…Ontologies are for sharing…One consideration in the enterprise realm, for example, is the ability of a domain ontology to accommodate specialized XML languages and controlled vocabularies being adopted as standards in various industries. None of the current ontology editors address this capability. Interoperability, instead, is being addressed simply through an editor’s ability to import and export ontologies in different language serializations.

Usability…The standard approach is the use of multiple tree views with expanding and contracting levels. A graph presentation is less common, although it can be quite useful for actual ontology editing functions that change concepts and relations. The more effective graph views provide local magnification to facilitate browsing ontologies of any appreciable size. The hyperbolic viewer included with the Applied Semantics product, for example, magnifies the center of focus on the graph of concepts (without labeled relations). Other approaches like the Jambalaya plug-in for Protégé-2000 achieve a kind of graphical zooming that nests child concepts inside their parents and allow the user to follow relations by jumping to related concepts. Some practitioners however, such as GALEN users, indicate a preference for non-graphic views for complex ontologies.

Get a pot of coffee or two in me and out pops another article, this time in Digital Web under the unwieldy title of Smarter Content Publishing, Building a semantic website to increase the efficiency and usability of publishing systems. Don’t bother reading it, I’ll sum it up for you:

1. Manually marking up HTML is lame, computers should automatically do that for us
2. The content management system trend is making publishing easier and less expensive (see Movable Type)
3. CMS still has a lot of inefficiencies, requiring business users to think about web design instead of business
4. Metadata to the rescue! Just keep layering the stuff until you’re talking business terms instead of design terms
5. It’s hard, but that never kept us from using technology before
6. It’s actually an application of the Semantic Web, but aren’t you glad I didn’t tell you that at the beginning?

If you do bother to read it, hopefully you won’t agree with this guy from the Web Ontology Working Group who wrote in to tell me it was great. ‘Cause that doesn’t help me improve. I need some constructive feedback. Did you like the topic but thought the level was too hard or too easy? Do you want more examples? More theory? Too long, too short? Tell me.

Deborah L. McGuinness, ontology goddess, released Ontologies Come of Age, a chapter to an upcoming book. A relatively gentle introduction, along the way she illustrates the difference between controlled vocabularies and ontologies: the former have implicit is-a relationships and the latter have explicit is-a relationships (e.g. in a taxonomy a Merlot is a narrower term of Red Wine, whereas in an ontology a Merlot is-a Red Wine). Expressing those relationships explicitly helps computers understand what we understand. So it’s more like knowledge representation, though it relies on the classification techniques of controlled vocabularies.

She’s done hardcore research at Rutgers, AT&T, Lucent, & Stanford and seems to be looking for wider applications of this work via Sandpiper Software.

Steve Pepper, author of The Tao of Topic Maps (and whose title, incidentally is Information Architect) – makes a concise, interesting comparison of Topic Maps and RDF, arguing for the former. Here’s a few points that struck me:

One key difference – I don’t know if it is the key difference – is that topic maps take a topic-centric view whereas RDF takes a resource-centric view. That, to me, speaks of the LIS point of view vs. the W3C point of view on these matters, focusing on something that can be indexed vs. something that can have a URI.

Because RDF is fundamentally a “framework for metadata”, i.e. for attaching property-value pairs to information resources, it can do the same job as facets. RDF could be used instead of facets, and would arguably provide more power (because of the recursive model and the fact that more metadata semantics, such as datatypes, are pre-defined). But to use RDF instead of facets would mean to lose the connection between the semantic network layer and the metadata, which today is provided for by the fact that facet types and facet value types are topics.

chema, RDF has something topic maps don’t (yet), that is, a standardized way of expressing an ontology and the constraints upon it…Holger will be going one step further (I believe) with a concrete proposal for a topic map schema language….

Ontopia, of which Pepper is the CEO, has published the The Ontopia Schema Language.