DeepSee: Multidimensional Visualizations of Seabed Ecosystems

TL;DR

DeepSee addresses the challenge of maximizing scientific return from sparse deep-sea sediment samples by providing multidimensional visualizations that integrate 2D environmental context with 3D subseafloor interpolations and sediment core histories. Developed through a user-centered design study, it comprises three coordinated views (Map, Core, Interpolation) and supports real-time exploration, annotation, and data-driven sampling decisions, even offline. The work contributes a characterization of domain-driven visualization needs, a working open-source workspace, and qualitative evidence of enhanced planning, collaboration, and cost-efficiency in fieldwork. Practically, DeepSee offers a template for fieldwork-driven geovisualization that can guide sampling strategies in extreme environments and inform future visualization design in related domains.

Abstract

Scientists studying deep ocean microbial ecosystems use limited numbers of sediment samples collected from the seafloor to characterize important life-sustaining biogeochemical cycles in the environment. Yet conducting fieldwork to sample these extreme remote environments is both expensive and time consuming, requiring tools that enable scientists to explore the sampling history of field sites and predict where taking new samples is likely to maximize scientific return. We conducted a collaborative, user-centered design study with a team of scientific researchers to develop DeepSee, an interactive data workspace that visualizes 2D and 3D interpolations of biogeochemical and microbial processes in context together with sediment sampling history overlaid on 2D seafloor maps. Based on a field deployment and qualitative interviews, we found that DeepSee increased the scientific return from limited sample sizes, catalyzed new research workflows, reduced long-term costs of sharing data, and supported teamwork and communication between team members with diverse research goals.

Figures (7)

• Figure 1: DeepSee presents side-by-side views of 2D geological and biological landscape maps (A) as well as 2D visualizations and 3D interpolations of physical, geochemical, and biological parameter gradients in deep sea sediment cores (B).
• Figure 2: Region-level data represented as maps, provided by Paduan:2022:VentMaps. Maps reveal two important features: (A) geological landscapes, such as locations of hydrothermal vent mounds and chimneys, visualized by topography from AUV and low-altitude survey system (LASS) multibeam surveys; and (B) surface biological and ephemeral “soft” features, such as white patches of microbial mats growing in hydrothermal fluids, visualized by photomosaics, acoustic backscatter and LIDAR bathymetry. DeepSee solves a critical challenge of combining region-, core-, and sample-level data in a single interface using expressive and interactive visualizations (Sect. \ref{['sec:system']}).
• Figure 3: The Map View plots cores by latitude/longitude on a map layer to show the spatial and geographic history of sampling. Users can drill down to cores of interest (A), explore the map (B), see details on demand (C), switch maps on the fly (D), draw annotations (E), and select cores (F) to view in the Core View and Interpolation View.
• Figure 4: The Core View arranges sets of horizontal bar charts to compare parameter values between cores across horizons.
• Figure 5: The Interpolation View visualizes parameter values interpolated in three dimensions (latitude/longitude/depth) between cores. We provide several reconfiguration interactions (A) to help users make sense of an unfamiliar data representation. Users can update the view on the fly in several ways: swapping between standard and Value-Suppressing Color Palettes (VSUPs) Correll:2018:VSUP(B); changing the interpolation method and/or grid size (C); and clipping through the interpolation (D). Finally, users can select an interpolated core to export as JSON (E).