Authors:
Kyriakos Kritikos
1
;
Dimitris Plexousakis
1
and
Robert Woitsch
2
Affiliations:
1
FORTH, Greece
;
2
BOC, Austria
Keyword(s):
KPI, Semantics, Ontologies, Quality, QoS, Linked Data, Analysis, SPARQL.
Abstract:
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.
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