The paper discusses a method to triangulate process and product data. We
suggest converting Translog data into a relational format which contains
both process and product data. We outline how this representation allows
us to retrieve and correlate the various dimensions of the data more easily.
The concept of Alignment Unit (AU) is introduced and contrasted with that
of Translation Unit (TU). While AUs refer to translation equivalences in the
source and target texts of the product data, TUs refer to cognitive entities that
can be observed in the process data. With an (almost) exhaustive fragmentation
of the source and target texts into AUs, we are able to distribute and
allocate the entire set of keystroke data to appropriate AUs. Using the properties
of the keystroke data, AUs are quantified in a novel way which enables
us to visualise and investigate the structure of translation production on a
fine-grained scale.
