We often walk away from pivotal business meetings and conferences excited about what we have learned, the people we have met, and
the refreshing destruction of barriers to understanding.
That is, until we try to put that new information and insight to work. In the face of an overabundance of information, we stumble over limitations of time and memory. We can't integrate our new knowledge effectively with what we already know. And we can't convey that knowledge effectively to others in our organization who need it most. (See Overabundance of information.)
That's because a simple reality is ignored: You can't act effectively until you convert information into meaning. That process often begins by identifying a simple set of choices among options, examining the consequences of each choice, and agreeing on the best option. That meaning may be refined through several steps and become a detailed specification or a CAD illustration ... and ultimately tools, software, machines, services (precise instructions for activities), or any number of other more complex objects that have value to a target market.
That's always been true. It's still true. To be productive and competitive, you have to do those things well and do them efficiently. But the superabundance of information in the form of documents and other unstructured communications — resources that once seemed our allies — has become a serious stumbling block to productivity and competitiveness.
Overcoming those stumbling blocks is
the fundamental motivation of "semantic technologies" — an emerging set of practices and tools, some with deep roots in the much-maligned
field of artificial intelligence, that help us get beyond reliance on words.
Semantic technologies help us by:
Semantic technologies are often associated with terms like the Semantic Web, ontologies, taxonomies, and "reasoners" ... acronyms like RDF, OWL, and NEPOMUK ... and such arcane-sounding practices as "mind mapping."
Mills Davis of Project10x has identified more than 250 vendors in the "semantic technologies" space in his publicly-available introduction to The Semantic Wave 2008. However, just as marketing hoopla and rebranding of old technologies led to a sudden (and highly questionable) profusion of "knowledge management technologies" in the 1990s, it's best to ask what functions the tools and practices address. Skip the labels. (At the CSE, we're working on ways to help you do that, too.)
It's not as if "semantic technologies" haven't been with us for quite a while. The most common example is the relational database, which is all about precise definition of aspects of reality. The semantic precision and appropriateness of an RDMS model for representing realities makes processing of large amounts of information about those realities possible.
"Semantics"
are pervasive in technologies, applications, standards, and modeling tools. Even project management. But we don't think of them that
way. We don't think of them in terms of making meaning explicit and more processable. But that's precisely what they do.
The Center for Semantic Excellence is working with vendors, experts in both academia and technology, and the business community at large to make work more effective through a grounded semantic approach — to represent the collective, evolving expertise and opinion of the community in explicit, persistent, and actionable forms using semantic technologies, enabling the community to continuously refresh and adapt its information supply chain.