A Multi-sensor Visualization Tool for Harvested Web Information: Insights on Data Quality

摘要

In order to inform about sensors veracity and handle the data imprecision, an interactive visualization tool for industrial needs has been developed and presented in this paper. The tool allows user to get deep understandings in a multi-sensor context, especially when considering harvested web data. In order to deal with data imperfection, our methodology is based on quantiles and on the specific modeling for missing values. We present diverse dashboards and visual indicators serve to validate common flow data and help to discover hidden knowledge. According to a use case, we show how our visualization approaches can assist to review data quality about possible critical situations.