Visualising category recoding and numeric redistributions

Cynthia A Huang

Room: 110

2023-10-22T22:00:00ZGMT-0600Change your timezone on the schedule page
Exemplar figure, described by caption below
A crossmap for converting values observed using Australian occupation categories (ANZSCO22) into observations under the International Standard Classification of Occupations (ISCO8). Crossmaps are directed multipartite graph structures for capturing details of cross-taxonomy transformation. This crossmap is visualised using a two-layer bigraph layout, with ANZSCO22 codes forming the first source layer, and ISCO8 codes the second target layer. The weights on the links indicate what share of ANZSCO22 observed values are redistributed to corresponding ISCO8 codes.

This paper proposes graphical representations of data and rationale provenance in workflows that convert both category labels and associated numeric data between distinct but semantically related taxonomies. We motivate the graphical representations with a new task abstraction, the cross-taxonomy transformation, and associated graph-based information structure, the crossmap. The task abstraction supports the separation of category recoding and numeric redistribution decisions from the specifics of data manipulation in ex-post data harmonisation. The crossmap structure is illustrated using an example conversion of numeric statistics from a country-specific taxonomy to an international classification standard. We discuss the opportunities and challenges of using visualisation to audit and communicate cross-taxonomy transformations and present candidate graphical representations.