TableToLongForm automatically converts hierarchical Tables
intended for a human reader into a simple LongForm Dataframe that is
machine readable, hence enabling much greater utilisation of the data.
It does this by recognising positional cues present in the hierarchical
Table (which would normally be interpreted visually by the human brain)
to decompose, then reconstruct the data into a LongForm Dataframe. The
article motivates the benefit of such a conversion with an example
Table, followed by a short user manual, which includes a comparison
between the simple one argument call to TableToLongForm, with code for
an equivalent manual conversion. The article then explores the types of
Tables the package can convert by providing a gallery of all recognised
patterns. It finishes with a discussion of available diagnostic methods
and future work.