Abstract
AbstractThe emergence of “big data” offers unprecedented opportunities for not only accelerating scientific advances, but also enabling new modes of discovery. While we understand how to automate routine aspects of data management and analytics, most elements of the scientific process currently require considerable human expertise and effort. We argue that realizing the full potential of data to accelerate discovery calls for a concerted effort in advancing Discovery Informatics: (i) understanding, formalization, and information processing descriptions of the entire scientific process; (ii) design, development, and evaluation of the computational artifacts (representations and processes) that embody such understanding; and (iii) application of the resulting artifacts and systems to advance science (by augmenting individual or collective human efforts, or by fully automating science).
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