{'fraction_non_alphanumeric': 0.01529051987767584, 'fraction_numerical': 0.00764525993883792, 'mean_word_length': 5.179245283018868, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Visual Integration of Meteorological and Sensor Data for Identifying Suspicious Company Behavior

We present an approach developed in course of the VAST 2017 Mini-Challenge 2. To help the ornithologist Mitch to investigate the noxious gases emitted by the four companies south of the nature preserve, we employ a combination of interactive visualizations that allow for an exploration of the data. In this paper, we present our visual-interactive approach for analyzing suspicious patterns in the data. By taking the wind data into consideration, as well, our approach allows the retrieval of patterns in the chemical releases and identify key polluters.