| Literature DB >> 29756001 |
Alejandro Bugacov1, Karl Czajkowski1, Carl Kesselman1, Anoop Kumar1, Robert E Schuler1, Hongsuda Tangmunarunkit1.
Abstract
The pace of discovery in eScience is increasingly dependent on a scientist's ability to acquire, curate, integrate, analyze, and share large and diverse collections of data. It is all too common for investigators to spend inordinate amounts of time developing ad hoc procedures to manage their data. In previous work, we presented Deriva, a Scientific Asset Management System, designed to accelerate data driven discovery. In this paper, we report on the use of Deriva in a number of substantial and diverse eScience applications. We describe the lessons we have learned, both from the perspective of the Deriva technology, as well as the ability and willingness of scientists to incorporate Scientific Asset Management into their daily workflows.Entities:
Year: 2017 PMID: 29756001 PMCID: PMC5939963 DOI: 10.1109/eScience.2017.20
Source DB: PubMed Journal: Proc IEEE Int Conf Escience ISSN: 2325-372X