Data Rich - Information Poor : Conclusion

Data Rich - Information Poor : Conclusion
© Mahes Visvalingam, 2000

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Advances in technology have been harnessed for data gathering and processing. We have large storehouses of very detailed data. We are now data rich.

However, there is wide agreement that the state of the art of data mining and information abstraction is poor.

This is partly because the data, themselves, are rich! They encode multiple context-dependent meanings. Often, it is difficult to decipher the pertinent information from the given data alone.

Conjoint use of maps, diagrams, tables and images are helpful. They fire neural nets in our own collective brains! They not only help us retrieve pertinent facts and knowledge from our vast personal stores of ill-structured knowledge, but they also help to pull in other knowledge in the published domain from academic colleagues and local perspectives from those well-versed in street knowledge.

It is such extraneous knowledge which helps us detect errors; spot conceptual weaknesses in methodology; question underpinning assumptions; distinguish between quantitative data and their qualitative shades of meaning; and, distill place from person related problems.

Talking about street knowledge, the Internet offers increasing opportunities for public participation in social research. The British Cartographic Society and some other societies have already set up Research Funds to promote such independent research. The Institute of Analysts and Programmers already has tutorial pages on the web.

The 21^st Century has started with some very high profile, potentially anarchic, vigilante movements. Can we steer some of this desire to influence public policy into co-ordinated vigilante research?

The creation of systems for creative information visualisation will stretch the discipline of Human Computer Interaction to its limit. I believe that this is a worthy challenge for 21^st Century Informatics.

THANK YOU