SLAS

Category:Data collection and processing

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By definition, the primary product of any laboratory is data. Automating the activities of a laboratory only serves to increase the volume of data that can be generated. It follows that the key set of skills required by a laboratory that utilizes automation includes the ability to detect, collect, store, transmit, track, manage and analyze experimental data. Planning for the proper handling of experimental data generated by an automated laboratory is a task that is best performed simultaneously with planning for the automated instrumentation itself. The topics in this category address these essential requirements which must be in place in order to fulfill a laboratory's core mission of generating data that illuminate the underlying essence of the phenomena under investigation.

Subcategories

This category has the following 4 subcategories, out of 4 total.

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Pages in category "Data collection and processing"

The following 3 pages are in this category, out of 3 total.