A time series data transformation engine for non-programmer end users

With high networking connectivity and low-cost, high-grade sensors, production environments continue to collect abundant amounts of process data. While data acquisition and archiving systems are exceptional at collecting and storing time series data from disparate sources, the raw data from these systems are rarely presented in a format that is directly meaningful for end users. Decision makers often require to combine, interpolate, and transform the otherwise uninformative raw data in order to bring context and meaning to them. To this end, this paper presents the design and integration of an automated data calculation engine with an existing web-based data acquisition and visualization system called CLICS. At the core of the engine is an expression language for the specification of transformation/calculation formulae over time series data. With the calculation engine, a user can interactively specify a formula to transform multiple existing time series to create a new one that is significantly easier to understand and manipulate, or calculate a single value using a formula. To illustrate the communicative power of the engine, specific case examples are presented relating to three interconnected facilities (a greenhouse, a food waste digester, and an energy cabin) that are designed for conducting research and educational activities in energy efficiency and environmental sustainability on a university campus.