| Discovery Science |
Article Index for Discovery |
Website Links For Discovery |
Information AboutDiscovery Science |
|
Discovery-based methodologies are often viewed in contrast to traditional scientific practice, where hypotheses are formed before close examination of experimental data. However, from a philosophical perspective where all or most of the observable "low hanging fruit" has already been plucked, examining the Phenomenological world more closely than the senses alone (even augmented senses, e.g. via microscopes, telescopes, etc.) allows represents a new source of knowledge for hypothesis formation. Data Mining is the most common tool used in Discovery Science, and is applied to data from diverse fields of study such as DNA Analysis , Climate Modeling , Nuclear Reaction Modeling , and others. The use of data mining in Discovery Science follows a general trend of increasing use of computers and Computational Theory in all fields of science. Further following this trend, the cutting edge of data mining employs specialized Machine Learning algorithms for automated hypothesis forming and Automated Theorem Proving . REFERENCES [http://biology.plosjournals.org/perlserv/?request=get-document&doi=10.1371/journal.pbio.0030059 Discovery-Based Science Education: Functional Genomic Dissection in Drosophila by Undergraduate Researchers], PLoS Biology, Volume 3, Issue 2, February 2005 |
|
|