Last year, Gartner predicted that semantic technology would emerge as one of the top 10 disruptive technologies within the next four years.

That's right: I'm keeping tabs on that prediction.

I've written on several occasions about how semantic technology can be used in integration, a field known as semantic integration. It's a fascinating emerging technology to follow, but so far, it's still outside the mainstream, used primarily by large tech companies, pharmaceutical companies and other large, cutting-edge organizations, including NASA.

Still. We can dream, can't we?

Recently, Dr. Dobb's Journal interviewed Richard Keller, senior research computer scientist and group lead for the information sharing and integration group at NASA, about semantic integration. It's a fascinating discussion, and I particularly liked that Keller addressed one critical questions I've long wondered about: What's it going to take to make semantic integration possible for more companies?

Granted, that isn't the question he was asked, so don't try skimming the interview to find it. The question he was asked was, “What's the next big hurdle to achieving semantic integration?” He gave a two-part answer, responding that ontology mapping is the first big hurdle, and it's long been an issue for the semantic Web community.

It's the second part of his answer that speaks to my long-standing question:

More broadly, I think the challenge for making semantic integration work in the marketplace is to make it quicker and easier to specify data semantics. Currently, specifying semantics using ontologies is a somewhat arcane and tedious process. ...Although we are starting to see some good tools on the market to make this process easier, the cost/benefit calculations are not yet sufficiently favorable to support widespread adoption of this approach.

Keller explains the challenges and opportunities with semantic integration in a concise, accessible manner. He explains why standards aren't the answer to ongoing data-integration problems – they're onerous and expensive – and how the W3C's SPARQL will help but not solve the difficulty of semantic integration. The W3C's SPARQL applies to querying, but as Keller explains, that's not the underlying difficulty. Construction of the ontologies is tricky with semantic integration. That's why the maps are so critical, and so difficult.

Definitely check out this short interview if you're interested in semantic integration. You might also find the following IT Business Edge posts helpful in understanding semantic technology and its impact on integration:
Semantic Integration Is Emerging Field - Should You Care?
Myths About Semantic Technology Part I and Part II
Can Semantics Tech Eliminate the Need for Data Integration?