  We propose a Web-Mashup Application Service Framework for Multivariate Time
Series Analytics (MTSA) that supports the services of model definitions,
querying, parameter learning, model evaluations, data monitoring, decision
recommendations, and web portals. This framework maintains the advantage of
combining the strengths of both the domain-knowledge-based and the
formal-learning-based approaches and is designed for a more general class of
problems over multivariate time series. More specifically, we identify a
general-hybrid-based model, MTSA-Parameter Estimation, to solve this class of
problems in which the objective function is maximized or minimized from the
optimal decision parameters regardless of particular time points. This model
also allows domain experts to include multiple types of constraints, e.g.,
global constraints and monitoring constraints. We further extend the MTSA data
model and query language to support this class of problems for the services of
learning, monitoring, and recommendation. At the end, we conduct an
experimental case study for a university campus microgrid as a practical
example to demonstrate our proposed framework, models, and language.
