Interactive client side data visualization with d3.js

Geoscience data associated with near surface research and operational sites is increasingly voluminous and heterogeneous (both in terms of providers and data types - e.g. geochemical, hydrological, geophysical, modeling data, of varying spatiotemporal characteristics). Such data allows scientists to investigate fundamental hydrological and geochemical processes relevant to agriculture, water resources and climate change. For scientists to easily share, model and interpret such data requires novel tools with capabilities for interactive data visualization. Under sponsorship of the US Department of Energy, Subsurface Insights is developing the Predictive Assimilative Framework (PAF): a cloud based subsurface monitoring platform which can manage, process and visualize large heterogeneous datasets. Over the last year we transitioned our visualization method from a server side approach (in which images and animations were generated using Jfreechart and Visit) to a client side one that utilizes the D3 Javascript library. Datasets are retrieved using web service calls to the server, returned as JSON objects and visualized within the browser. Users can interactively explore primary and secondary datasets from various field locations. Our current capabilities include interactive data contouring and heterogeneous time series data visualization. While this approach is very powerful and not necessarily unique, special attention needs to be paid to latency and responsiveness issues as well as to issues as cross browser code compatibility so that users have an identical, fluid and frustration-free experience across different computational platforms. We gratefully acknowledge support from the US Department of Energy under SBIR Award DOE DE-SC0009732, the use of data from the Lawrence Berkeley National Laboratory (LBNL) Sustainable Systems SFA Rifle field site and collaboration with LBNL SFA scientists.