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Know Thy Sensor: Trust, Data Quality, and Data Integrity in Scientific Digital Libraries

Abstract

For users to trust and interpret the data in scientific digital libraries, they must be able to assess the integrity of those data. Criteria for data integrity vary by context, by scientific problem, by individual, and a variety of other factors. This paper compares technical approaches to data integrity with scientific practices, as a case study in the Center for Embedded Networked Sensing (CENS) in the use of wireless, in-situ sensing for the collection of large scientific data sets. The goal of this research is to identify functional requirements for digital libraries of scientific data that will serve to bridge the gap between current technical approaches to data integrity and existing scientific practices.

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