Towards Semantic KPI Measurement

Linked Data (LD) represent a great mechanism towards integrating information across disparate sources. The
respective technology can also be exploited to perform inferencing for deriving added-value knowledge. As
such, LD technology can really assist in performing various analysis tasks over information related to business
process execution. In the context of Business Process as a Service (BPaaS), the first real challenge is to
collect and link information originating from different systems by following a certain structure. As such, this
paper proposes two main ontologies that serve this purpose: a KPI and a Dependency one. Based on these
well-connected ontologies, an innovative Key Performance Indicator (KPI) analysis system is then built which
exhibits two main analysis capabilities: KPI assessment and drill-down, where the second can be exploited to
find root causes of KPI violations. Compared to other KPI analysis systems, LD usage enables the flexible
construction and assessment of any KPI kind allowing experts to better explore the possible KPI space.