Towards Semantic KPI Measurement

Kyriakos Kritikos, Dimitris Plexousakis, Robert Woitsch

2017

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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Paper Citation


in Harvard Style

Kritikos K., Plexousakis D. and Woitsch R. (2017). Towards Semantic KPI Measurement . In Proceedings of the 7th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-758-243-1, pages 91-102. DOI: 10.5220/0006238000910102


in Bibtex Style

@conference{closer17,
author={Kyriakos Kritikos and Dimitris Plexousakis and Robert Woitsch},
title={Towards Semantic KPI Measurement},
booktitle={Proceedings of the 7th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2017},
pages={91-102},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006238000910102},
isbn={978-989-758-243-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - Towards Semantic KPI Measurement
SN - 978-989-758-243-1
AU - Kritikos K.
AU - Plexousakis D.
AU - Woitsch R.
PY - 2017
SP - 91
EP - 102
DO - 10.5220/0006238000910102