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Drowning in Data: Digital Library Architecture to Support Scientific Use of Embedded Sensor Networks by Christine L. Borgman; Jillian C. Wallis; Matthew S. Mayernik; Alberto Pepe is a scholarly article available to read on EtoBox.

What is Drowning in Data: Digital Library Architecture to Support Scientific Use of Embedded Sensor Networks about?

New technologies for scientific research are producing a deluge of data that is overwhelming traditional tools for data capture, analysis, storage, and access. We report on a study of scientific practices associated with dynamic deployments of embedded sensor networks to identify requirements for data digital libraries. As part of continuing research on scientific data management, we interviewed 22 participants in 5 environmental science projects to identify data types and uses, stages in their data life cycle, and requirements for digital library architecture. We found that scientists need continuous access to their data from the time that field experiments are designed through final analysis and publication, thus reflecting a broader notion of "digital library." Six categories of requirements are discussed: the ability to obtain and maintain data in the field, verify data in the field, document data context for subsequent interpretation, integrate data from multiple sources, analyze data, and preserve data. Three digital library efforts currently underway within the Center for Embedded Networked Sensing are addressing these requirements, with the goal of a tightly coupled interop

Author

Christine L. Borgman; Jillian C. Wallis; Matthew S. Mayernik; Alberto Pepe

Publisher

ACM

Published

2007

Language

EN