I enjoyed Jason Pontin’s most recent editor’s letter (“On Beautiful Machines,” May/June 2007). He is right: machines should be simple. A decade ago I bought a 1996 Buick Century, and in 2001 I bought a new one. When I put the shifting lever into drive in the 1996 car, I could clearly see the pointer in sunlight striking it from any angle. But my luxurious 2001 Buick doesn’t have a pointer; it has a small lit-up orange square that moves across a screen of letters when you move the shift lever. I found this change impressive until I put my car into drive one late afternoon when the sun hung low in the sky. I couldn’t see the orange square. I had to block the sunlight with my left hand to find drive. Some improvement.
The Semantic Web
We read with interest John Borland’s piece on the Semantic Web (“A Smarter Web,” March/April 2007). We agree that this is an exciting time in the Semantic Web’s development, yet we want to point out that its great degree of structure has drawbacks. As the article noted, Semantic Web users must learn complex ontology languages and structure their information and data using them. This difficulty inhibits the growth of the Semantic Web. It is thus arguable whether the Semantic Web can approach the scale of the standard Web, where anyone can easily create and publish content.
Ideally, we should combine the strengths of the Semantic Web and the normal Web. Search would be a good place to start. Today, global free-text search is the primary means of querying the whole Web, but it provides only coarse-grained access to documents. In contrast, the Semantic Web allows much more precise queries across multiple information sources (say, querying for a particular attribute, such as “street address”). However, it is on a much smaller scale, involving far fewer documents. We could imagine combining normal and Semantic Web queries–for instance, to search the free text of all real-estate Web pages written by women in Boston during the last week for the word “Jacuzzi.” Taking this further, the few structured relationships currently in the Semantic Web could be used to refine the results of mainstream search engines.
Finally, as so much activity in the life sciences is focused on large-scale interoperation on the Web (as found in drug discovery), we feel that biological research could serve as a useful guide and driving force for the development of Web 3.0.
Mark Gerstein and Andrew Smith
Computational Biology and Bioinformatics Program
New Haven, CT