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| This site may be down on Thursdays 
between 7:00 and 9:30 pm Central Time for maintenance. |  | What We Need From 
						ReviewersThe purpose of the review process is to 
						ensure that the data are complete, intelligible, 
						interpretable, and of archival quality. All these 
						attributes are subjective to some extent. Here are some 
						guidelines for evaluation. Completeness  Completeness means that the data set contains all the 
						documentation, calibration information, and other 
						ancillary information needed to interpret the data.  Intelligibility  Intelligibility is concerned with the physical and 
						logical formatting of the data files. Electronic data 
						are considered intelligible if they are readable by any 
						reasonable computer system operated by a knowledgeable 
						user who has access to the data set documentation. We 
						assume that such a user and system can display any ASCII 
						files included in the data set without difficulty, and 
						thus has access to the documentation included with the 
						data set. The documentation should provide sufficient 
						details about the physical and logical format for the 
						user to either read the data directly into an 
						application, or reformat the data as necessary to use 
						it.  Interpretability  Whether the data are interpretable or not depends 
						largely on the documentation. At the record level, the 
						documentation should define the meaning, units of 
						measure and significance of each field. At higher levels 
						the documentation should describe how the data were 
						collected and reduced to their current state. 
						Calibration files and other ancillary data should be 
						available and themselves documented.  Interpretability should be measured with respect to a 
						knowledgeable professional. That is, interpretability 
						does not mean that the documentation must explain the 
						data and their significance at the level of the general 
						lay public.  Archive Quality  The opinions of the outside reviewers are weighed 
						very heavily in determining whether a data set is of 
						archive quality; that is, will it still be useable many 
						years after the mission is over, when the data providers 
						are no longer available to answer questions.  Back to Help for Data 
						Reviewers   |