Friday, September 26, 2008

Inside Web 3.0

Web 3.0 is on its way: Why should you care?

It’s been said that content is king. But with the unstoppable proliferation of corporate, editorial, academic, government and user-generated content, it’s more like a mad monarch running amok in the asylum. How do we make sense of it all and bring some sanity back to our digital lives?  Some say that the integration of Web 3.0 will begin to save us from this constant barrage of information, and that web searching will soon have an entirely new meaning.

With the current state of the web, it is often difficult to find relevant content in the mess. Then, when you do find it, you know it could be doing so much more for you — if it were speaking to related content and services. Better search is not the answer. Systems need to start understanding what content means so that they can accurately gauge what users want, and curtail hunting and gathering by intermingling disparate sources of information.

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The underlying strategy of the Semantic Web, or Web 3.0, is to create data and websites that are “machine-readable.” Why do we care if machines can read data? If machines could comprehend the meaning of the content on a website, they could manipulate data in more meaningful ways, identifying more precisely the information that the user wants, and eliminating much of the annoying noise in our everyday lives.

For example, you can use Google Maps to find the nearest Starbucks. But what if you’re looking for something even more ambiguous? Say you’re at work and you suddenly remember that you need to buy a present for your nephew whose birthday is tomorrow. Web 3.0 promises the capability to search for nearby stores that are open late and sell gifts suitable for a tech-minded teenage boy.
Or maybe you need to search for something along a number of very specific criteria. Busy at work, but need a haircut?  The Semantic Web and coordinating computers can help search for neighborhood salons and narrow the choices based on available appointments that fit in your full calendar — and provide these suggestions without the time-wasting phone calls to get an appointment. 

So, how do machines know what data means?

The Building Blocks of Web 3.0

Here are the elements that have to come together to enable the Semantic Web.

• IDs. Machines need a unique, consistent way to identify a thing or concept. For example, if I mention “Bill Clinton,” how does a machine know that this is the same person as President William Jefferson Clinton? People can usually tell by context, but a machine needs that unique identifier.

• New web standards. Web 1.0 and 2.0 were built on standards like HTML, XML, and CSS. Some new standards have been developed specifically for expressing metadata and metadata relationships. Standards such as RDF, OWL, SKOS and Dublin Core are used to define metadata in a machine-readable way.

• Ontology. These shared classifications, relationships and logic will allow machines to integrate distinct data sets and extrapolate new, unexpected information from stated information. Think of it as a hyper-glossary.

The three things listed here make the Semantic Web hypothetically possible, but to make it a reality we need commercially available software and systems that will allow people and companies to easily create, manipulate, interpret and use semantic data. Without these tools, the obstacles to adoption would be prohibitive for most organizations.

Is the Semantic Web right for you?

If you want to leverage the vast stores of excellent content and data that your company has to offer or provide rich, relevant search results, then yes.

These are the kinds of features that savvy web users are already starting to expect. Soon they’ll be demanding them. A few years ago, the common view was that you wouldn’t be able to benefit from the Semantic Web without investing huge amounts of time and money. Now the prevailing attitude has shifted toward “a little semantics goes a long way.” Semantic solutions can be adopted incrementally, with the ability to grow as needed.

As with any emerging technology, there are costs and risks associated. This technology, however, will change the way we research, search and find the things we need — cutting down on the clutter and enhancing our everyday lives.

 

Rachel Lovinger is a senior content strategist with the Boston office of interactive marketing services firm Avenue A | Razorfish. She may be reached at Rachel.lovinger@avenuea-razorfish.com.