Science, Semantics, and Big Data

The scientific method is classically hypothesis-first, refutation-second. The experiment and its data support or refute our suppositions of the world. As applied in a decentralized manner by millions of scientists over half a millennia, we attempt an imperfect, yet ever-broadening, self-consistent cognitive model of Nature and the universe. While the scientific method writ large is alive and well, the way we as scientists exercise the discipline is undergoing substantial change. The advent of Big Data in the early decades of this century may have as large an effect on the century's science as the advent of grand theories did at the beginning of the previous century. As the saying goes: Quantity has a Quality all its own. This change in how we do science affects not just discovery, but education, policy, and society So what's a scientist to do? This talk will focus on how science, in both discovery and collaboration, is changing under the pressure of data; how in addressing this, semantics and ontologies both deliver, and leave us short, and how we can think about leveraging and deploying infrastructual resources to advance discovery and better our world.

 Damian Gessler is the Lead Applications and Systems Developer at the Common Logic expert-firm Highfleet, and Founder of Semantic Options, LLC. Damian served as the Semantic Web Architect for the iPlant project at the University of  Arizona and prior to that as a Program Lead at the National Center for Genome Resources. Damian’s computational focus is in semantics, data integration, and scientific computation, with a scientific expertise in computational Evolution and  Population Genetics.

David R. Maidment is the Hussein M. Alharthy Centennial Chair in Civil Engineering at the University of Texas at Austin where he has been on the faculty since 1981. Dr Maidment is a specialist in surface water hydrology, and in particular in the application of geographic information systems to hydrology.