Wide, long, or nested data? Reconciling the machine and human viewpoints

Hall, Alan Geoffrey; Wermelinger, Michel; Hirst, Tony and Phithakkitnukoon, Santi (2018). Wide, long, or nested data? Reconciling the machine and human viewpoints. In: Proceedings of the 2018 Conference of the Psychology of Programming Interest Group (PPIG), 5-7 Sep 2018, London.

URL: http://www.ppig.org/node/1088

Abstract

Data expressed in tables may be re-arranged in various forms, while conveying the same information. This can create a tension when one form is easier to comprehend by a human reader, but another form is more convenient for processing by machine. This problem has received considerable attention for data scientists writing code, but rather less for end user analysts using spreadsheets. We propose a new data model, the “lish”, which supports a spreadsheet-like flexibility of layout, while capturing sufficient structure to facilitate processing. Using a typical example in a prototype editor, we demonstrate how it might help users resolve the tension between the two forms. A user study is in preparation.

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