Frag men tation

This is my last piece directly about the 8th International Semantic Web Conference, though I’ll continue to be inspired by the things I picked up there. My other two pieces were about ontologies and data visualization.

I was sorry to leave ISWC today – and not just because of my fondness of suburban Virginia. For a humanities-oriented undergrad in a crowd of expert scientists and researchers, I learned an astonishing amount in the past few days – certainly enough to spark my interest in continuing to learn and discuss more, if only I could find a corollary to the community I just  met somewhere online.

The problem is that the great discussions I witnessed or joined at ISWC are – online – fragmented into such specialized subgroups that they have no place for a beginner like me. What’s more, the subjects that are addressed are so narrow that they turn into conversations restricted to a few participants and many uninvolved witnesses (when they take place on listservs, many unread emails). Experts talking to experts – great for solving specific technical problems, horrible for sharing the general knowledge and thoughts that spark real insight.

What I thought was greatest about ISWC was that nearly everyone was an expert at something different – which meant that any discussion with a largish audience or any happenstance encounter between two specialists (say, a natural language researcher and an RDF programmer) had to avoid the technical jargon of either specialty and instead frame everything with the best precision afforded by regular English (believe me, this is much more difficult than dipping into a pre-made vocabulary). Not only is that a good exercise for anyone who wants understand her own subject area more clearly, it’s also the best way to discover parallels between disparate fields. Whereas a psychologist might have nothing to say about “distributed computing,” when talking about “parallel processing,” he may actually turn out to be quite the expert. It’s almost a test of ontology-matching – suddenly finding out that the concept I represent as X in my specialty’s categorization structure is practically the same as what you happened to call Y in yours. What’s the significance of that? As David Karger and Jim Hendler stressed at Wednesday’s mentoring lunch, that discovery is usually one of the best conditions for creative insight. Science is well accustomed to seeing a person with a problem figure out how to solve it by happening upon a person with the solution in another field. All they needed was to run into each other.

But where is that uncontrolled, randomly-matching social space online? Online, communications function more as structured discussions than freewheeling conversations. In shedding their haphazardness, they lose a lot of creativity.

I should probably point out that this isn’t particularly a problem of the Semantic Web; fragmentation and increasingly self-selected groups are a byproduct of the web in general. It may become intensified by the Semantic Web – which decreases the randomness and facilitates intentional self-selection on the web – but it’s a problem for everyone. Only maybe a little more so for scientists, who have always tended to break into autonomous, self-referential subgroups of experts rather easily.

Specialized, self-selected communities reinforce their own ideas and biases and make insightful leaps more difficult, to the detriment of all fields. The web facilitates self-selection and thus fragmentation. What is to be done?

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One thought on “Frag men tation

  1. I read a few of your recent posts about the event in Washington D.C. last week. Your insights are quite good and I applaud your efforts to take on such an esoteric subject.

    I really agree with your point about visualizing the semantic web. I think most people are either primarily “text” oriented or “visual” oriented, yet neither side realizes how different they are from the other in terms of their cognitive processes. Some would say it is a matter of left and right brain, but this is an over simplification. We all have some capabilities in both areas, but we tend to be “dominant” in one or the other. Tying together the meaning of words with images is a high art, which happens a lot in Mapping, Architecture, Flow Charts, Data Base Schema Diagrams, and other areas. These challenges require people to use “both sides of the brain”, or to be more “middle brained”.

    The fact that a panel/workshop focusing on data visualization was turned down by the ISWC is not at all a surprise to me. I have been dealing with a lot of Ontologists over the last year, and I have yet to see a compelling visualization.

    If you want a challenging read in this area, you might consider
    The Alphabet Versus The Goddess: The Conflict Between Word and Image
    by Leonard Schlain (who just recently passed away)

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