Industry Commentary

RDFS (RDF Schema) allows developers to create vocabularies that describe groups of related RDF resources and the relationships between those resources. An RDFS vocabulary defines the allowable properties that can be assigned to RDF resources within a given domain, and it allows creation of classes of resources that share common properties.

In an RDFS vocabulary, resources are defined as instances of classes. A class is a resource too, and any class can be a subclass of another. This hierarchical semantic information is what allows machines to determine the meanings of resources based on their properties and classes.

Building upon RDFS is OWL, which is a much richer, more expressive standard for defining Semantic Web ontologies that formally define the hierarchies and relationships between different resources. Semantic Web ontologies consist of a taxonomy (system of classification) and a set of inference rules from which machines can make logical conclusions. OWL is used to assign properties to classes of resources, and their subclasses inherit the same properties. OWL also utilizes the XML Schema datatypes and supports class axioms such as subClassOf, disjointWith, etc., and class descriptions such as unionOf, intersectionOf, etc. Many other advanced concepts are included in OWL, making it the richest standard ontology description language available today. There are three flavors of OWL, each with increasing flexibility: OWL Lite, OWL DL, and OWL Full. Developers choose the OWL dialect to work with based on the level of expressive restriction they need in their ontology.

Because RDF, RDFS, and OWL documents express hierarchies and relationships between resources, they are often created and conceptualized in a graphical manner to make the underlying relationships immediately obvious. Figure 2 shows an example of a simple RDF graph.

Even in this simple example, it's easy to see how a Semantic Web agent could make logical connections based on the defined relationships. For example, since the secret agent is Niki Devgood, and the secret agent drives a red convertible, it follows that Niki Devgood drives a red convertible.

Complex ontologies are represented with multiple, interdependent graphs that visually reveal the relationships between resources. Once Semantic Web documents are defined and mapped out graphically, they must be coded in RDF/XML or N-Triples format to be accessed programmatically. Unfortunately, the manual coding process can be extremely tedious and error-prone, considering that even simple ontologies can represent hundreds of lines of code and given that neither RDF/XML nor N-Triples provide visual cues as to the hierarchy of the information contained therein. Developers need a way to translate their graphical ontology representations into RDF/XML or N-Triples easily, thus removing a significant barrier to Semantic Web adoption.

Semantic Web Evolution
Even when developers are armed with tools that make Semantic Web development practical, it's important to note that implementation of RDF, OWL, and the Semantic Web as a whole will be a gradual process. Questions about what the Semantic Web is and how it can benefit businesses and individuals echo the initial confusion about why we needed HTTP, HTML, and the basic Web infrastructure before "WWW" was a staple of our daily vocabulary. However, considering how those technologies have proliferated, it's likely that the Semantic Web vision is one that will be realized, even if it's on a small scale initially.

Though there are certainly far-fetched visions of Semantic Web technologies allowing your PC to talk to your refrigerator to auto-generate recipes and shopping lists, the number of scenarios that could potentially benefit from Semantic Web technologies as they continue to evolve is truly impressive. Think of the possibilities opened to everything from crime investigation, scientific research, and literary analysis, to shopping, finding long-lost friends, and vacation planning when computers can find, present, and act on data in meaningful, productive ways. Despite the theoretical possibilities, only time will tell if these advanced Semantic Web visions will come to fruition.

In the meantime, the W3C has put forth a list of practical use cases for Semantic Web technologies (www.w3.org/TR/webont-req/#section-use-cases), several of which are already in place today. For instance, semantic information can be added to resources on Web portals to improve information syndication and increase the productivity of searches within the portal. Because a Web portal generally includes information related to a narrow community of interest, it's well suited to ontological definition. The Semantic Web can also be used to describe non-textual resources, such as multimedia collections that contain audio, video, and other file types, making locating, combining, and utilizing these resources infinitely easier.

Another example is the Dublin Core Metadata Initiative, which applies Semantic Web technologies to create vocabularies that define the properties of informational resources, such as creator, format, creation date, description, and so on. The Dublin Core vocabulary is in use today in a wide variety of projects (a full list is available on dublincore.org).

These few examples make it clear that industry adoption is increasing, and that trend will only continue with the availability of productive RDF and OWL editors.

Visual Semantic Web Tools
Recognizing this need for practical Semantic Web development tools, Altova recently released SemanticWorks 2006. SemanticWorks is a visual RDF/OWL editor that allows developers to define RDF, RDFS, and OWL documents graphically. Its functionality comprises:

• Support for visual creation and editing of RDF, RDFS, OWL Lite, OWL DL, and OWL Full documents
• Intelligent entry helpers that offer context-sensitive editing choices
• Syntax checking for RDF, RDFS, and OWL documents
• Semantics checking for OWL Lite and OWL DL ontologies
• Autogeneration and editing of RDF/XML or N-Triples formats based on visual RDF/OWL design

SemanticWorks supports RDF, RDFS, OWL Lite, OWL DL, and OWL Full with full syntax checking. Context-sensitive entry-helpers present the available options based on the type of document being created (RDF, OWL Lite, etc.), so it's easy to experiment and work with the technologies to create valid documents quickly. Support for OWL semantics checking also helps ensure consistency throughout an ontology. An example of the visual ontology design view is shown in Figure 3.

The graphical display includes informative icons that indicate item types, containers and collections (bag, sequence, etc.), class descriptions (unionOf, intersectionOf, etc.), class axioms (subClassOf, disjointWith, etc.), property descriptions (subPropertyOf, inverseOf, etc.), and more. These connectors can be inserted using a context-sensitive right-click menu or by selecting them from the toolbar. Yellow boxes encapsulate resources that are defined elsewhere in the ontology, and mouse-over hints display a connector's meaning or a resource's URI.

Based on the visual design, SemanticWorks generates the corresponding code in RDF/XML or N-Triples, depending on the user's preference. This allows developers to focus on the relationships they're defining while leaving the low-level code writing to the application, which reduces the semantic technology learning curve significantly. This is also helpful for viewing the impact of changes during editing, whether you change the visual design and view the corresponding code, or vice versa.

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