Peering Editor: Charles Petrie. petrie @stanford. edu Embracing"web3.0” Ora Lassila. Nokia Research Center James Hendler. Rensselaer Polytechnic Institute n an article published in The New York Times representation(KR), which is a subfield of artifi- this past November, reporter John Markoff stat- cial intelligence(Al)concerned with constructing ed that "commercial interest in Web 3.0-or and maintaining (potentially complex) models of the 'Semantic Web, for the idea of adding mean- the world that enable reasoning about themselves ing- is only now emerging. This characteriza- and their associated information. As such, we can tion caused great confusion with respect to the understand the Semantic Web through the lessons relationships between the Semantic Web and the learned from the Web's development and adoption, Web itself, as well as between the Semantic Web as well as (perhaps somewhat painfully) from the and some aspects of the so-called Web 2.0. Some deployment of Al technologies. wanted to reject the term" Web 3.0"as too On the Web, we've seen the emergence of some business-oriented; others felt that the vision in the completely new business models that do indeed article was only part of the larger Semantic Web work, despite initially seeming infeasible. These vision, and still others felt that, whatever it was include the models introduced or perfected by called, the Semantic Web's arrival in the Business Netscape (creating a community by giving stuff section of The New york Times reflected an impor- away), Amazon and eBay (marketplaces), and Yahoo! and Google(advertising-supported sites With the Resource Description Framework Sharing data (or content, as it's often called when (RDF)and Web Ontology Language(OWL)-the discussing the Web) has unexpected and serendip- languages that power the Semantic Web- becom- itous outcomes-once you make something avail ing standards and new technologies reaching able, you have no idea how some people will us maturity for embedding semantics in existing Web it. The long-tail phenomenon for example, pages and querying RDF knowledge stores, some- aggregate sales of low-selling items, such as spe- thing exciting is clearly happening in this area. cialized books, surpassing the total number of best- sellers sold -defies traditional thinking about Semantic Web Background business models, but it's important to the new Web- With more than 10 years work on the Semantic based economy. Web sites don't really exist in iso Web's foundations and more than five years since lation -linking is what makes search engines work the phrase became popular, it's an opportune and gives the"blogosphere"its power. moment to look at the field's current state and From the euphoria surrounding AI in the 1980s ture opportunities. From a humble beginning as through the hangover of the"AI winter"in the methodology for machine-interpretable meta- 1990s, we've learned what doesn't work: you cant data and through a "world-embracing"vision of a sell a stand-alone"Al application. These tech- new era of software (often -erroneously, in our nologies make sense only when embedded within opinion attributed as science fiction), the other systems Tools are hard to sell and often fail Semantic Web has matured into a set of standards to make good business sense (they certainly dont that support"open"data and a view of informa- make sense according to venture capitalists). Final- tion processing that emphasizes information rather ly, thinking of Al itself, we observe that reasoning than processing. engines are a means to an end, rather than the end From one viewpoint, the Semantic Web is the itself; how you use them is more important tha ymbiosis of Web technologies and knowledge the mere fact that you use them Published by the IEEE Computer Society 1089-7801/07/52500●2007EEE IEEEINTERNET COMPUTINGPeering 90 Published by the IEEE Computer Society 1089-7801/07/$25.00 © 2007 IEEE IEEE INTERNET COMPUTING Embracing “Web 3.0” I n an article published in The New York Times this past November, reporter John Markoff stat￾ed that “commercial interest in Web 3.0 — or the ‘Semantic Web,’ for the idea of adding mean￾ing — is only now emerging.”1 This characteriza￾tion caused great confusion with respect to the relationships between the Semantic Web and the Web itself, as well as between the Semantic Web and some aspects of the so-called Web 2.0. Some wanted to reject the term “Web 3.0” as too business-oriented; others felt that the vision in the article was only part of the larger Semantic Web vision, and still others felt that, whatever it was called, the Semantic Web’s arrival in the Business section of The New York Times reflected an impor￾tant coming of age. With the Resource Description Framework (RDF) and Web Ontology Language (OWL) — the languages that power the Semantic Web — becom￾ing standards and new technologies reaching maturity for embedding semantics in existing Web pages and querying RDF knowledge stores, some￾thing exciting is clearly happening in this area. Semantic Web Background With more than 10 years’ work on the Semantic Web’s foundations and more than five years since the phrase became popular, it’s an opportune moment to look at the field’s current state and future opportunities. From a humble beginning as a methodology for machine-interpretable meta￾data and through a “world-embracing” vision of a new era of software (often — erroneously, in our opinion — attributed as science fiction), the Semantic Web has matured into a set of standards that support “open” data and a view of informa￾tion processing that emphasizes information rather than processing. From one viewpoint, the Semantic Web is the symbiosis of Web technologies and knowledge representation (KR), which is a subfield of artifi￾cial intelligence (AI) concerned with constructing and maintaining (potentially complex) models of the world that enable reasoning about themselves and their associated information. As such, we can understand the Semantic Web through the lessons learned from the Web’s development and adoption, as well as (perhaps somewhat painfully) from the deployment of AI technologies. On the Web, we’ve seen the emergence of some completely new business models that do indeed work, despite initially seeming infeasible. These include the models introduced or perfected by Netscape (creating a community by giving stuff away), Amazon and eBay (marketplaces), and Yahoo! and Google (advertising-supported sites). Sharing data (or content, as it’s often called when discussing the Web) has unexpected and serendip￾itous outcomes — once you make something avail￾able, you have no idea how some people will use it. The long-tail phenomenon — for example, aggregate sales of low-selling items, such as spe￾cialized books, surpassing the total number of best￾sellers sold — defies traditional thinking about business models, but it’s important to the new Web￾based economy. Web sites don’t really exist in iso￾lation — linking is what makes search engines work and gives the “blogosphere” its power. From the euphoria surrounding AI in the 1980s through the hangover of the “AI winter” in the 1990s, we’ve learned what doesn’t work: you can’t sell a stand-alone “AI application.” These tech￾nologies make sense only when embedded within other systems. Tools are hard to sell and often fail to make good business sense (they certainly don’t make sense according to venture capitalists). Final￾ly, thinking of AI itself, we observe that reasoning engines are a means to an end, rather than the end itself; how you use them is more important than the mere fact that you use them. Ora Lassila • Nokia Research Center James Hendler • Rensselaer Polytechnic Institute Editor: Charles Petrie • petrie@stanford.edu