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Semantics Simplified
The Semantic Web is a collection of tools, techniques and standards with the goal of transforming the Web into a useful repository of information with a rich layer of description (semantics) that software applications can understand and even draw conclusions from. Some feel that in the foreseeable future, all of human knowledge will reside on the Web and will be accessible without additional effort. While this is subject to debate, more immediately interesting is how semantic technology will affect the way we work in the near term. Anyone using a wiki, (like Wikipedia), RSS feeds or social networking tools such as LinkedIn or MySpace is already using semantic technology. The most immediate and obvious application of semantic technology is to make sense of exploding data volumes and to understand or integrate overlapping data from multiple sources. Existing metadata, taxonomy and integration tools have not been able to keep up with this problem. But first, some background.
The World Wide Web began as a collection of documents developed in a simple markup language (HTML) that could be viewed on many different devices through a browser. But in just a few years, the Web was about much more than posting static content for review. With new interactivity that allowed search and two-way communication, e-commerce was born. Within five years, widespread use of XML, .NET and J2EE transformed the Web into an interactive, transactional platform. The next wave of the Web, the Semantic Web, is all about advisors, cognitive engines and personal agents; its most remarkable characteristic is that it is largely built by and used by other applications, as well as people.
In 1994, there were 38 million (estimated) users of the Web and about 3,000 Web sites. Today, there are over one billion users and Google indexes more than five billion Web pages. The magnitude of the Web in terms of size and functional breadth overwhelms the original design concept. The man credited with inventing the Web, Tim Berners-Lee, quickly realized that the Web needed to be more than just a collection of pages. It had to be a utility for mining knowledge. But first there needed to be a way to describe the content of the Web in a way that computers could make sense of, a sort of catalogue of the meaning and relationships of the material. This required more than a description or a definition, it needed a representational framework that could actually capture the semantics of the content and even allow computers to draw their own conclusions.
Search engines were useful for finding lists of things based on keywords, but for the Web to be useful as a data source, things need to be found conceptually, not just structurally. Some straightforward ideas were developed, such as "tagging" web pages with descriptive material, but it became apparent that this was insufficient. Who was going to tag the entire Web? But the thought spawned a remarkable community effort to apply techniques of linguistic programming, artificial intelligence and branches of mathematics like graph theory to develop semantic technologies to attack the problem. Unfortunately, the terminology can be offsetting. Ontology is not the sort of word that people warm up to, but it has a fairly simple application in semantics. It captures the meaning of things by defining them and showing their relationships to other things, allowing devices to perform a sort of reasoning and draw conclusions based on the content of things, not the structure.
Some visionaries like Nora Spivak freely predict that, "Within a year or two you will see mass-consumer Semantic Web products and services hit the market, and within five years there will be at least a few 'killer apps' of the Semantic Web. Ten years from now the Semantic Web will have spread into many of the most popular sites and applications on the Web. Within 20 years all content and applications on the Internet will be integrated with the Semantic Web," (Nora Spivak, "Minding The Planet - The Meaning and Future of the Semantic Web," November, 2006 at http://www.mindingtheplanet.net/.)
Many critics disagree with Spivak, but the principles of the Semantic Web and the developments it is enabling, are relevant to businesses. For example, exchanging information between computer systems is a recurring obstacle to the efficient operation of business processes. Because of the way computer systems have evolved, managing "interfaces" between applications consumes a great deal of the IT budget. Mapping fields is relatively easy and moving data physically is not much of a challenge - but that is only half the job. Making data usable for the destination system is much more complicated.
The discordance and semantic mismatch in data between even closely-related systems is an endemic problem. These issues are serious enough in intra-organizational processes, but the rapid externalization of business as a result of the Internet and what it spawned are forcing the "interface" issue to a potential breaking point. Existing data cleansing and integration tools cannot scale to the volumes and service levels needed because their algorithms are based on data structure, not semantics (meaning). Most tools operate on a pattern-based or syntactic level - so whatever meaning is needed to perform the transformation has to be supplied by the developer. Neither are they competent enough to perform the needed translations without a great deal of handwork and maintenance, consuming the two scarcest resources of all - time and competent people.
Some other concepts of the Semantic Web that are already seeping into the corporate consciousness are:
- Collective intelligence: How to harness and leverage what people know, not in the rigid, programmatic manner of early Knowledge Management, but to passively capture the output, catalogue it and provide tools to understand it, reuse it, and apply it in novel ways.
- Large volumes of data: Data can come from anywhere today and there is too much of it, with too much disparity for rules-based processing. Understanding the semantics, drawing conclusions about meaning and priority - these are all applications of semantic technology
- Efficient marketplaces: Current approaches to optimizing supply chains, pricing products and generally finding things are based on pre-built and rigid models. The application of graph theory, how things are connected, and deductive logic, combined with linguistic algorithms to untangle the variation in naming and description, can simplify the supply/fulfillment chain, (and cause heartburn for those who profit from market inefficiencies).
Ultimately, the Semantic Web is not about replacing humans in the workforce or creating a sentient class of robot overlords, nor is it about doing what humans do, but rather facilitating what humans do. This transcends the Web and applies to any application of computer technology. What does the Semantic Web mean to businesspeople? Everything.
Neil Raden is the founder of Hired Brains, Inc., http://www.hiredbrains.com. Hired Brains provides consulting, systems integration and implementation services in business intelligence, decision automation and business process integration for clients worldwide. Hired Brains Research provides consulting, market research, product marketing and advisory services to the software ndustry. Based in Santa Barbara, CA, Raden is an active consultant and widely published author and speaker. He welcomes your comments at nraden@hiredbrains.com.
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