2011 | OriginalPaper | Chapter
A Panel Discussion on Data Intensive Science: Moving towards Solutions
Author : Terence Critchlow
Published in: Scientific and Statistical Database Management
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Over the past several years, a number of groups, including the National Academy of Engineering, have identified grand challenge problems facing scientists from around the world [1]. While addressing these problems will have global impact, solutions are years away at best – and the next set of challenges are likely to be even harder to solve. Because of the complexity of questions being asked, meeting these challenges requires large, multi-disciplinary teams working closely together for extended periods of time. Enabling this new type of science, involving distributed teams that need to collaborate despite vastly different backgrounds and interests, is the cornerstone of Data Intensive Science.