Applicability of Existing Attribution Systems to Visualization and HCI

Determine to what degree existing systems of attribution, including the Contributor Role Taxonomy (CRediT), apply to research practices in visualization and human-computer interaction, with the aim of identifying and addressing mismatches between those systems and the contribution types common in these fields.

Background

The paper observes that contribution statements and formal contributorship systems remain uncommon in visualization and HCI. It identifies a potential barrier to their adoption: existing attribution systems may have been developed around disciplinary assumptions that do not align with visualization and HCI research practices.

CRediT is presented as a particularly salient example because its “Visualization” role is intended for the preparation of visualizations as manuscript figures, making the role confusing when applied to research in the field of visualization itself. The unresolved issue is therefore whether, and to what extent, current attribution frameworks can represent the range of conceptual, design, participatory, qualitative, and technical contributions found in visualization and HCI.

References

Potentially limiting or impeding the use of contribution statements is that it is unclear to what degree current systems of attribution apply to research practices in visualization and HCI.

— Considering Contribution Statements in Visualization and HCI Research  (2608.12792 - Solen et al., 13 Aug 2026) in Section 1, Introduction

Our measure of collaboration is also coarse. It quantifies the breadth of a researcher's coauthorship network but not the substance of the relationships that compose it, and it cannot distinguish a coauthor who shaped a study from one who contributed a specific technical service. The propensity to list contributors also varies across fields, institutions, and individual practices. Our area-resolved analyses partially address the disciplinary component of this heterogeneity, and a role-resolved treatment is a natural direction for future work.

— Causal asymmetry suggests productivity underlies scientific collaboration  (2610.08477 - Frota et al., 6 Oct 2026) in Discussion and conclusions, paragraph beginning “A further set of considerations concerns how the two quantities are measured.”