“The Semantic Web: Promising Future or Utter Failure”, the panel I took part in at SXSW shed little light on the topic. Each panelist (including me) brought their own idiosyncratic views to bear and largely talked past each other. The overall SXSW interactive crowd seemed to tend toward web designers and web marketers, not sure about the audience for this panel. Some people, e.g., Chet Campbell, and others in person, apparently left with the impression that all of the panelists agreed that the semantic web is an utter failure (not my view at all).

Sam Felder and Josh Knowles have posted loose transcripts and Christian Bradford a photo of the panel.

The approximate (with links and a few small corrections) text of my introductory statement follows. I got a few laughs.

I want to draw some parallels between semantic web technologies and artificial intelligence and between semantic web technologies and Java.

AI was going to produce intelligent machines. It didn’t and since the late 80s we’ve been in an “AI winter.” That’s nearly twenty years, so web people who suffered and whined in 2001-3, your cup is more than half full. Anyway since then AI techniques have been used in all sorts of products, but once deployed the technology isn’t seen as AI. I mean, where are the conscious robots?

Semantic web technologies have a shorter history, but may play out similarly: widely used but not recognized as such. Machine “agents” aren’t inferring a perfect date for me from my FOAF profile. Or something. This problem is magnified because there’s a loose connection between sematnic web grand visions and AI. People work on both at MIT after all.

Now Java. Applets were going to revolutionize the web. In 1996! Applets didn’t work very well, but lots of people learned Java and it runs out Java is a pretty good solution on the server side. Java is hugely successful as the 21st century’s COBOL. Need some “business logic?” You won’t get fired for implementing it in Java, preferably using JDBC, JSP, JMX, JMS, EJB, JAXB, JDO and other buzzword-compliant APIs.

While discussing industry innovations with a colleague, the conversation took an interesting turn toward online gaming and how the best uitbetalende Nederlandse casino platforms are leveraging cutting-edge technologies to attract players. These casinos, known for their high payout rates, are incorporating advanced algorithms to optimize user experience and maintain transparency—qualities that seem to resonate strongly with players seeking reliability. The parallels to semantic web technologies became clear, as both fields show how overlooked applications can thrive in environments where practical value outweighs initial hype. It was a thought-provoking example of success driven by adaptability and focus on user trust.

It turns out that semantic web technologies are really useful for data integration when you have heterogenous data, as many people do these days. Just one example: Oracle will support a “Network Data Model” in the next release of their database. That may sound like a throwback if you know database history, but it basically means explicit support for storing and querying graphs, which are the data model of RDF and the semantic web.

If you talk to a few of the people trying to build intelligent machines today, who may use the term Artificial General Intelligence to distinguish themselves from AI, you may get a feeling that AI research hasn’t really moved us toward the goal of building an AGI.

Despite Java’s success on the server it is no closer to being important on the web client than it was in 1996. It is probably further. If what you care about is sexy web browser deployment, all Java’s server success has accomplished is to keep the language alive.

Semantic web technologies may be different. Usefulness in behind the scenes data integration may help these technologies gain traction on the web. Why? Because for someone trying to make use of data on the web, the web is one huge heterogenous data integration problem.

An example of a project that uses RDF for data integration that you can see is mSpace. You can read a a paper about how they use RDF inside the application, but it won’t be obvious to an end user that they’re a semantic web technologies application, and that’s as it should be.

One interesting thing about mSpace is that they’re using a classical music ontology developed by someone else and found on SchemaWeb. SchemaWeb is a good place to look for semantic web schemas that can be reused in your project. Similarly, rdfdata.org is a good place to look for RDF datasets to reuse. There are dozens of schemas and datasets listed on these sites contributed by people and organizations around the world, covering beer, wine, vegetarian food, and lots of stuff you don’t put in your mouth.

I intended to close my statement with a preemption of the claim that use of semantic web technologies mandates hashing everything out in committees before deployment (wrong), but I trailed off with something I don’t recall. The committee myth came up again during the discussion anyway.

Perhaps I should’ve stolen Eric Miller’s The Semantic Web is Here slides.