How often have you heard the excuse of blaming blown project budgets on unanticipated systems integration costs? For good reason, nobody wants to do customized point-to-point integrations if they can help it -– it’s difficult if not impossible to leverage the work.
But in one respect, such integrations contained one potentially messy issue. When working with designated source and target, you became all too intimately familiar with the data that you were trying to integrate and therefore didn’t have to worry about the context or meaning of the data that you were trying to exchange.
Nonetheless, when you think about reusing software assets, context stares you in the face. For instance, what if you want to reuse a process for tracking customer preferences in another entity, only to learn that privacy laws prevent the use of some portions of that data? And if another part of your business has a different definition of what constitutes a customer, the divergent meanings become show stoppers.
Admittedly, given the difficulty of attaining software reuse, concerns about context or the meaning of data remained academic. eBizQ’s Beth-Gold Bernstein recalled being at the event where IBM announced SNA and told everybody to start building their enterprise data dictionaries. “I worked with organizations that did that. They had the books on their shelves, but it didn’t do anything. They were just books on the shelves.”
And in fact, thinking about systems that can automatically decide meaning or context from data kind of conjures up some of the original goals of Artificial Intelligence, which was supposed to produce software that could think. Japan mounted a fifth generation computing project back in the 1980s that was supposed to leapfrog the west with AI software, replicating their successes with lean manufacturing. We’re not terribly sure if the Japanese effort actually got as far as generating shelfware.
About a decade ago, web pioneer and W3C director Tim Berners-Less began pushing the idea of a Semantic Web that would provide a web that was searchable, not only by keywords, but real meaning. Along the way, the W3C developed several standards including Resource Description Framework (RDF) and Web Ontology Language (OWL) that specify how to represent entity relationships or meanings using XML. But today, we’re still on Web 2.0, which is a more dynamic, interactive, but hardly a semantic place.
The emergence of SOA has made the possibility of software reuse less academic. According to IT architectural consultant Todd Biske, a consistent semantic model is critical to SOA if your services are going to be adequately consumed. Without such a model, suggests Biske, it’ll be harder for users to figure out if the service is what they’re looking for.
While short of the true meaning of semantics, the use of metadata has exploded through integration middleware and SOA registries/repositories that provide descriptors to help you, or some automated process, find the right data or service. There are also tools from providers like Software AG that are starting to infer relationships between different web services. This is all tactical semantics with a lower case “s” –- it provides some descriptors that present at best a card catalog “what” information is out there, and from a technical standpoint, “how” to access it.
It may be lower case “semantic web,” but it’s a useful one. And that’s similar to the lower case “ai” that spawned modest pieces of functionality that didn’t make machines smarter per se, but made them more convenient (e.g.,context-based menus).
Our sense is also that we’re ages away from Semantic Web, or Semantic Services with a capital “S.” Current Analysis principal analyst and longtime Network World contributor Jim Kobielus equated the challenge as a “boil the ocean” initiative during a recent Dana Gardner podcast. Few have covered the topic as extensively. In a recent Network World column, Kobielus summarized the prospects: Most vendors are taking a wait and see attitude. For instance, Microsoft, which is sponsoring a project code-named Astoria to extend ADO.NET with a new entity data model that would implement some of the W3C semantic web standards, has yet to promise whether to implement any of the technology in SQL Server.
Kobielus believes that it will take at least another decade before any of this is commercialized. While our gut believes he’s optimistic, we find it hard to argue with his facts. Besides, he adds, it took a full half-century for hypertext to advance from “Utopian Vision” to something taken for granted today on the web.