Interactive Hierarchical Visualization for Exploring the Neotoma Paleoecological Taxonomy
Authors
Yanbing Chen (University of Wisconsin-Madison), Jonathan Nelson (University of Wisconsin-Madison), Simon Goring (University of Wisconsin-Madison), Qianheng Zhang (University of Wisconsin-Madison), Jessica Blois (University of California, Merced), John Williams (University of Wisconsin-Madison)
Presentation
- Session
- Connecting the Dots
- Time
- Wednesday, Nov 11, 13:18 – 13:27 (US/Eastern) · session 13:00 – 14:30
- Location
- Hall Essex north
Keywords
Hierarchy Visualization, Paleoecology Taxonomy, Circular Dendrogram, Collapsible Tree
Abstract
Paleoecological researchers rely on large community-curated databases such as Neotoma to locate, interpret, and compare taxa across geologic timescales. Existing query interfaces assume users already know what they are looking for and offer little support for exploring the hierarchical taxonomic structure itself. Neotoma's taxonomy compounds this problem: its 67,885 taxa span 52 taxagroups that vary from a handful of nodes to nearly twenty thousand, follow a non-Linnaean parent-child structure without fixed rank assignments, and carry historical naming ambiguities accumulated over a century of curation. We present a two-part formative design study focused on detailing our process of, and key takeaways from, developing the Hierarchical Taxonomy Visualizer to address these challenges.
For Practitioners
This paper would be of interest to visualization designers, database curators, biodiversity informatics practitioners, paleoecologists, taxonomists, and data scientists working with complex hierarchical data. Practitioners can apply the paper’s lessons when designing tools for messy, legacy, or community-curated databases where the underlying hierarchy is incomplete, uneven, or inconsistent. In particular, they can use adaptive layouts to match different group sizes and structures, make structural anomalies visible, and provide provenance-aware naming support when records contain competing classifications. These strategies can help practitioners build interfaces that support both exploratory use by domain researchers and diagnostic review by data stewards.