Semantic Web Business: Going Nowhere Slowly

I’ve been a Semantic Web skeptic for years. SemWeb is a narrowly purposed replica of a subset of the World Wide Web, useful for information enrichment in certain domains, via a circumscribed set of tools, however offering vanishingly small benefit to the vast majority of businesses. The vision persists but is unachievable; the business reality of the Semantic Web is going pretty-much nowhere.

The SemWeb dream centers on a data sharing (Linked Data) via the W3C’s Resource Description Framework (RDF) 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. The Semantic Web can’t keep up the flow, even on the limited portion of the data universe that is published on the World Wide Web. We will never achieve SemWeb’s ideal universe of neatly marked up data, published by content producers in accordance with W3C’s prescriptive standards.

More achievable is an ad-hoc semanticized Web of after-the-fact, situational markup (annotation) by content consumers and by data intermediaries including the 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 is a reality that has been achieved, and that 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 start-ups and established firms.

(I’ve been promoting this alternative vision for years. See, for instance, my 2011 white paper written for OpenText, 12 Things the Semantic Web Should Know about Content Analytics, and check out my Sentiment Analysis Symposium conference, which includes extensive coverage of Natural Language Processing (NLP) and information-extraction and analytical technologies.)

http://en.wikipedia.org/wiki/File:Social_graph.gif#filelinks
Social Graph connectivity, semantics-infused: A Facebook example

Per a response I provided to SemanticWeb.com for Jenny Zaino’s Good-Bye 2013, “adoption of LinkedData 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).”

I observed that “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.

I’ve buried the motivation for this article, seven paragraphs in. This article was prompted by a note I got last week from consultant David Siegel, who not only shares my view regarding the lack of Semantic Web business interest, but has lived it. David wrote me that his 4 years in “Semantic Web stuff” didn’t pay off, that 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. Management seems to be lurching toward [semantic technology in] ways like via social and mobile and Google integration,” but not via the capital-S capital-W Semantic Web. David wrote me, “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, fast rate of data production (per Big Data’s Velocity characteristic), or with the variety (another Big Data “V”) of the types, linkages, and usages (many unforeseen and unaccommodated) of modern-world data.

The Semantic Web is over twelve years old, still puttering along. From a business perspective, it is going nowhere slowly.

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