Knols, Wikipedia and truth in Openwater Service Networks

Last month, Google unveiled knols. In Udi Manber's words,

The key idea behind the Knol project is to highlight authors.

Unlike Wikipedia, which contains a single definition for each topic, authors write competing knols about the same topic.

Udi argues that competition is a good thing. Google will not edit the knols, but use its considerable Search Quality expertise to let the best version float to the top.

Considering Wikipedia and Knol raises interesting philosophical questions about truth. Take Hugo Chávez . Many view him as a socialist liberator, many others view him as an authoritarian demagogue.

Wikipedia editors deal with these versions of the truth in a variety of ways, labeling actions or statements as "controversial", requiring references to facts from reputable sources, flagging text as "opinion" and even introducing a separate topic Criticism of Hugo Chávez . However admirable these efforts, some bias undoubtedly remains. For example, these graphs make him look like a hero to a visual person like me. The text next to it has enough nuance that I couldn't tell. And that's where Wikipedia (or any encyclopedia, for that matter) usually leaves me -- my head full of facts from more or less reputable sources, various conflicting interpretations of these facts but no point of view.

Enter Knol. Knol isn't live yet, but I imagine we'd get at least two knols: Hugo the Good and Hugo the Bad. It will be interesting to see which Hugo will float to the top -- it will be a reflection of the community that views and rates knols.

The word "community" provides a good segueway into what we do at Openwater. Rather than demanding one version of the truth, or letting several truths compete, we build service networks for communities (specifically the installed base of a high-tech product), each of which creates its own Community Encyclopedia.

As in Wikipedia, anyone in the service network can edit a topic and each topic has experts assigned who monitor the quality. But like Knol, the editors don't have to balance every sentence that appears to carry an opinion or bias. And perhaps the biggest difference with both Knol and Wikipedia: there is no need to consider all possible meanings of each word -- just the current meaning within the installed base community is fine.

As a result, topics can be more specific and concise than those in either Knol or Wikipedia, and at the same time they can index more specific (proprietary) information and people in the installed base community.

There is one other major difference I'd like to mention in this blog -- this is what makes us an "implicit web" company. Unlike Wikipedia and Knol, topic pages don't start as an empty page and a blinking cursor.

In an Openwater Service Network, we start by indexing all the structured and unstructured information that's already available to the installed base, such as technical documentation, forums, bug tracking systems, LDAP directories, mailing lists, project plans, etc.

From the index, we then extract candidate topics by applying Natural Language Processing techniques to the unstructured text and by applying queries to the structured information. These candidate topics come with links to relevant documents, people, terms and other information. Users select suitable topics and refine them into the Community Encyclopedia.

The resulting pages look a lot like those in Wikipedia and Knol, but they're a lot more relevant to the community and a lot less effort to produce.

Because of the way it's built, we can also use the encyclopedia to program the network, but that's another story.