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.

Metadata

publication

2017 IEEE 13th International Conference on e-Science (e-Science), 79-88, 2017

year

2017

publication date

2017/10/24

authors

Alejandro Bugacov, Karl Czajkowski, Carl Kesselman, Anoop Kumar, Robert E Schuler, Hongsuda Tangmunarunkit

link

https://ieeexplore.ieee.org/abstract/document/8109125/

resource_link

https://pmc.ncbi.nlm.nih.gov/articles/PMC5939963/pdf/www.facebase.org

conference

2017 IEEE 13th International Conference on e-Science (e-Science)

pages

79-88

publisher

IEEE