A Specification Language for Organisational Performance Indicators

Popova, Viara; Treur, Jan

doi:10.1007/11504894_92

Cited by 3 publications

(1 citation statement)

References 2 publications

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“…From a bottom-up perspective, early formal specification languages (Popova & Treur, 2005) and ontologies (del Río-Ortega, Resinas, & Ruiz-Cortés, 2010) are also used for the annotation of structural definition of indicators to enhance business goals representation (del Mar Roldán García, García-Nieto, & Aldana-Montes, 2016). An example of this can be found in Kehlenbeck and Breitner (2009), where based on MathML markup language, an ontology is defined to explicitly define formula of indicators, hence allowing the automatic linking to specific data warehouse elements.…”

Section: Related Workmentioning

confidence: 99%

Ontology-driven approach for KPI meta-modelling, selection and reasoning

Roldán‐García

García-Nieto

Maté

et al. 2021

International Journal of Information Management

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A key challenge in current Business Analytics (BA) is the selection of suitable indicators for business objectives. This requires the exploration of business data through data-driven approaches, while modelling business strategies together with domain experts in order to represent domain knowledge. In particular, Key Performance Indicators (KPIs) allow human experts to properly model ambiguous enterprise goals by means of quantitative variables with numeric ranges and clear thresholds. Besides business-related domains, the usefulness of KPIs has been shown in multiple domains, such as: Education, Healthcare and Agriculture. However, finding accurate KPIs for a given strategic goal still remains a complex task, specially due to the discrepancy between domain as-sumptions and data facts. In this regard, the semantic web emerges as a powerful technology for knowledge representation and data modeling through explicit representation formats and standards such as RDF(S) and OWL. By using this technology, the semantic annotation of indicators of business objectives would enrich the strategic model obtained. With this motivation, an ontology-driven approach is proposed to formally concep-tualize essential elements of indicators, covering: performance, results, measures, goals and relationships of a given business strategy. In this way, all the data involved in the selection and analysis of KPIs are then integrated and stored in common repositories, hence enabling sophisticated querying and reasoning for semantic validation. The proposed semantic model is evaluated on a real-world case study on water management. A series of data analysis and reasoning tasks are conducted to show how the ontological model is able to detect semantic conflicts in actual correlations of selected indicators.

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Section: Related Workmentioning

confidence: 99%

Ontology-driven approach for KPI meta-modelling, selection and reasoning

Roldán‐García

García-Nieto

Maté

et al. 2021

International Journal of Information Management

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Challenges in Performance Analysis in Enterprise Architectures

Cardoso

2013

2013 17th IEEE International Enterprise Distributed Object Computing Conference Workshops

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Agent-Based Modeling of Third-Party Logistics Performance Indicators

Krauth

Moonen

Popova

et al.

IEEE/WIC/ACM International Conference on Intelligent Agent Technology

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Monitoring of relevant performance indicators can greatly contribute to the success of a logistics service provider. In practice, however, this is often done in an adhoc manner, leaving huge potential for improvement through adequate IT support. This paper proposes an approach to build an agent-based information system with emphasis on the interaction between the operational and strategic goals of the company. We present an example of the applied approach for the context of schedule generation and selection.

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A Specification Language for Organisational Performance Indicators

Cited by 3 publications

References 2 publications

Ontology-driven approach for KPI meta-modelling, selection and reasoning

Ontology-driven approach for KPI meta-modelling, selection and reasoning

Challenges in Performance Analysis in Enterprise Architectures

Agent-Based Modeling of Third-Party Logistics Performance Indicators

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