Loyola Marymount University
Data is inherently dynamic. If the failures of the
past few decades (or human history) prove nothing
else, they underscore the foolishness of only tracking
and making decisions based on only one aspect of
data. Today’s databases still suffer from a rigidity that
handicaps their ability to perform as “expert” systems.
Early prototype databases modeled terrorist social networks
and made inferences about their associations using
relatively straightforward rules and representations.
Inheritance relations of object-oriented programming
have found their way into relational databases, yet our
representation mechanisms and query languages have
note changed substantially in twenty years. While
search and retrieval mechanisms have become more sophisticated,
software programs still do not reflect understanding
of the documents they process. And adapting
them to changing values and attitudes is problematic.
The future promises the opportunity to express preferences
over hard and fast rules and the ability to reprogram
aspects of our code without recoding and recompiling
an entire software system. Until then, our ability
to reason about our data, while more extensive, won’t
be much different in terms of depth and nuance than it
was in the 1980s and will still be bound by the static
nature of the knowledge we store in our programs. Decisions
made on the advice of these expert systems (from
military to medical realms) will most certainly suffer.
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June 20, 2009 - June 25, 2009
176 works by 303 authors indexed
Conference website: http://web.archive.org/web/20130307234434/http://mith.umd.edu/dh09/
Series: ADHO (4)