The semantic web vision persists, but the tools and processes don't stand up to today's data chaos.
I've been a semantic web skeptic for years. SemWeb is a narrowly purposed replica of a subset of the World Wide Web. It's useful for information enrichment in certain domains, via a circumscribed set of tools. However, the SemWeb offers a vanishingly small benefit to the vast majority of businesses. The vision persists but is unachievable; the business reality of SemWeb is going pretty much nowhere.
The SemWeb dream centers on sharing linked data via the W3C's Resource Description Framework protocol. There is no question that SemWeb aspires to a worthy goal, but its tools and processes are no match for the reality of never-diminishing online, social, and enterprise data chaos. SemWeb can't keep up with the flow, even on the limited portion of the data universe that is published on the World Wide Web. We will never achieve its ideal universe of neatly marked up data, published by content producers in accordance with the prescriptive W3C standards.
More achievable is an ad-hoc, semanticized web of after-the-fact, situational markup (annotation) by content consumers and data intermediaries, including the leading Internet search engines and data brokers. The reality isn't a linked data web of interconnected resources. More real is a set of linkable data -- marked up or stored in some queryable format, selectively findable and accessible via tools -- and methods that may or may not be standardized. This has been achieved, and it is rapidly advancing, in the hands of companies that range from AlchemyAPI to ClearStory to IBM and hundreds (or perhaps thousands) of other analytics and big data startups and established firms.
As I told Jenny Zaino for her SemanticWeb.com post Good-Bye 2013:
Adoption of Linked Data and expansion of the Semantic Web [has been] far outpaced by the development of private knowledge graphs and focused search and query systems (often affording external access) from the likes of Facebook, Google, Wolfram Research, and Apple (Siri). A set of solution providers, as varied as NetBase, Digital Reasoning, and DataSift, are bringing similar capabilities, based on data mined from online, social, and enterprise sources, to government and corporate users.
The heart of an IBM Watson instance, whether applied to play Jeopardy or for medical diagnosis or customer intelligence, is a big, fat knowledge base. (Disclosure: IBM's jStart innovation program is a sponsor of the 2014 Sentiment Analysis Symposium, and Digital Reasoning is sponsoring my 2014 Text Analytics Market Study.)
A semantics-infused example of social graph connectivity on Facebook. (Source: Wikipedia).
This article was prompted by a note from the consultant David Siegel, who not only shares but also has lived my view regarding the lack of semantic web business interest. He wrote to me that his four years in "Semantic Web stuff" didn't pay off. He has now switched to management consulting. With David's permission, I'll relay his explanation.
"My goal was to be the bridge between business decision-makers and SemTech. There's still a huge gap there," he wrote. "Management seems to be lurching toward [semantic technology in] ways like via social and mobile and Google integration," but not via the semantic web. "I really thought I'd get a ton of consulting out of it, but instead I worked for four years and got two keynote speeches, nothing else. I got a TON of interest, but no paying clients, so I'm moving on."
David has shifted his focus to business agility consulting. "Agile" describes what the semantic web is not. It can't keep up with the fast rate of data production (per big data's velocity characteristic), or with the variety (another big data "V") of types, linkages, and usages (many unforeseen and unaccommodated by the data provider's chosen markup approach) of modern-world data.
The semantic web is more than 12 years old and still puttering along. From a business perspective, it is going nowhere slowly.
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