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						Checking InterpretabilityThe data are interpretable 
						if they are sufficiently documented to be not only 
						understood, but either further reduced or used to derive 
						some scientific result. Consequently, attempting to 
						derive some scientific result is probably the best way 
						to test this. For example, you might try something like 
						one of these: 
									Generate a plot or graph of the primary 
									datum. Are the magnitudes, features and axis 
									values reasonable? Attempt to calibrate a primitive image. 
									Were the necessary flat fields, etc., 
									available? Display an image. Does the appearance 
									reflect the documented pointing and state of 
									reduction? Attempt photometry or astrometry. Was it 
									possible to derive meaningful results? Were 
									they consistent internally? With external 
									references? Compare the data in this data set with a 
									similar published data set. Do they agree? 
									If not, is there an explanation included in 
									the documentation?
                                 	 Problems that arise during this process should be 
						directed to the discipline node so that they may be 
						addressed at the review.  Back to What We Need 
						from Reviewers Back to Help for Data 
						Reviewers   |