Large research projects are more likely to involve working with the results of data from multiple studies at multiple sites across multiple time periods than working with single studies alone. High-performance computing has made it possible to analyze much larger aggregates of data, expanding vision across space and time in ways previously not possible. Researchers working with such datasets need...institutional arrangements that ensure access to that data irrespective of where it resides or in what form....
The desire to maximize knowledge reuse has become a much more important factor in the design of libraries, databases, storage collections, and archives. Knowledge reuse occurs in several different ways: conducting a secondary analysis of a researcher’s raw data, analyzed either by another in the same field or by people in other fields; revisiting data through new analytical lenses; analyzing data of multiple types through a single analytical lens; synthesizing the results of many different types of studies for simultaneous analysis of multiple types of data about the same problem; adapting analyses of data for application in new contexts; and visualizing results of data analyses....
There is...a tension between the need to centralize data that is being used by multiple parties for multiple purposes and the interest in dispersing data in order to respond to vulnerabilities and to maximize access...
Posted by
Peter Suber at 8/29/2006 08:42:00 AM.
The open access movement:
Putting peer-reviewed scientific and scholarly literature
on the internet. Making it available free of charge and
free of most copyright and licensing restrictions.
Removing the barriers to serious research.
I recommend the OA tracking project (OATP) as the best way to stay on top of new OA developments. You can read the OATP feed on a blog-like web page or subscribe to it by RSS, email, or Twitter. You can also help build the feed by tagging new developments you encounter.
