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What We Need From
Reviewers The 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
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