Abstract | ||
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Linked Data (LD) technology enables integrating information across disparate sources and can be exploited to perform inferencing for deriving added-value knowledge. As such, it can really support performing different kinds of analysis tasks over business process (BP) execution related information. When moving BPs in the cloud, giving rise to Business Process as a Service (BPaaS) concept, the first main challenge is to collect and link, based on a certain structure, information originating from different systems. To this end, two main ontologies are proposed in this paper to enable this structuring: a KPI and a Dependency one. Then, via exploiting these well-connected ontologies, an innovative Key Performance Indicator (KPI) analysis system is built that offers two main analysis capabilities: KPI assessment and drill-down, where the second can enable finding root causes of KPI violations. This system advances the state-of-the-art by exhibiting the capability, through the LD usage, of the flexible construction and assessment of any KPI kind, allowing experts to better explore the possible KPI space. |
Year | Venue | Field |
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2017 | CLOSER (Selected Papers) | Ontology (information science),Performance indicator,System of measurement,Business process,Software engineering,Computer science,Linked data,Structuring,Database,Cloud computing |
DocType | Citations | PageRank |
Conference | 1 | 0.35 |
References | Authors | |
19 | 3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Kyriakos Kritikos | 1 | 595 | 42.10 |
Dimitris Plexousakis | 2 | 2586 | 326.38 |
Robert Woitsch | 3 | 1 | 0.35 |