Suggestions for Checking Intelligibility

ASCII Data

Most often this is in the form of a table. Reviewers have repeatedly demonstrated a preference for ASCII format for tabular data, even when the data were delivered in a binary format, because it is so easy to visually inspect the data and determine that it is intact. Thus, human-readability is usually a large factor in determining the intelligibility of ASCII data sets. The best test of intelligibility is to print out a section of the file and examine it.

• If the data are intended to be used primarily via visual inspection (a cross-identification list or small catalog, for example), is the record size small enough that the file may be easily printed or viewed with an editor?
• Was the file printable? Displayable on a computer screen?
• Are data values appropriately aligned (i.e., decimal points aligned, character values left-justified, etc.)?
• Is there a blank column or other delimiter separating fields?
• Are the data values appropriately formatted, especially fields with exponent values?

Binary Data

There are essentially two types of binary data: image and tabular. Image data is 2-dimensional and should be displayable with suitable software; tabular data is either a simple vector or an inhomogeneous array, yielding either a plot or an equivalent ASCII table of values, respectively. Given that ASCII is so often preferred for tables, some nodes routinely convert this last form into an ASCII table prior to ingest. However, some data sets are so large or so clearly intended to be used as input to a display or reduction routine that they are left as binary tables in order to conserve disk space.

Either way, checking the intelligibility of binary data will almost always involve some programming.

• For binary tables: is it possible to generate an ASCII equivalent?
• For linear data: is it possible to produce a graph or plot of the primary datum?
• For image data: is it possible to display the image?
• In all cases, do the data values look real, or do they look like noise?

Problems?

Problems encountered reading the data should be relayed to the discipline node as soon as possible so that they can be resolved immediately. (Clearly, an inability to read the data precludes the possibility of determining its fitness for archiving.)

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