MC2 — Spatio-Temporal Provenance Data Aggregation for Visual Analysis

Abstract

We describe our approach to the analysis of 2017 VAST Challenge Mini-Challenge 2 data. The challenge deals with readings from air sampler stations. To answer the main question, the provenance of the chemicals measured at the sampler stations, we extend the provided data set by aggregated spatio-temporal provenance data. This data is generated from the provided meteorological data and locations map by using it as input for a particle tracer which calculates the provenance of the particles arriving from the emitters (factories) at the collectors (the locations of sampler stations). We use ComVis [3], a coordinated multiple views (CMV) system, to analyze the whole data set (the provided and generated data) by applying a sensor centric data model.