Collaborative Building of an Ontology of Key Performance Indicators

Diamantini, Claudia; Genga, Laura; Potena, Domenico; Storti, Emanuele

doi:10.1007/978-3-662-45563-0_9

Cited by 16 publications

(11 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Rijgersberg et al [115] have presented an ontology for the measurement units focusing on Web Ontology Language (OWL) [93] axioms that facilitate their five pre-defined use cases: 1) the representation of obser-vations, 2) the representation of formulas, 3) manual annotation, 4) automatic annotation, and 5) unit conversions. To mention more targeted measurementcentric ontologies, some authors have designed semantic models of business performance indicators and properties of them, such as causality, aggregation, and correlation [42,41,107]. All these works have defined inference rules for the metrics, either presented in Prolog [31] or SWRL.…”

Section: Semantic Modelling and Reasoning In Network-and Measurement mentioning

confidence: 99%

“…Some works infer knowledge from measurement data [132,136,47], but no inference rules or descriptions of reasoning about metric dependencies are mentioned. Generally, there have been efforts to define metric ontologies including correlations, aggregations, and hierarchies among metrics [115,42,41,107]. Similar ideas are applied to the semantic modelling and inference in this work by especially targeted to SON functions and context-specific network measurements related to those.…”

Section: Semantic Modelling and Reasoning In Network-and Measurement mentioning

confidence: 99%

See 1 more Smart Citation

Correlation-Based Feature Mapping of Crowdsourced LTE Data

Apajalahti

Walelgne

Manner

et al. 2018

2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

View full text Add to dashboard Cite

Section: Semantic Modelling and Reasoning In Network-and Measurement mentioning

confidence: 99%

Section: Semantic Modelling and Reasoning In Network-and Measurement mentioning

confidence: 99%

Correlation-Based Feature Mapping of Crowdsourced LTE Data

Apajalahti

Walelgne

Manner

et al. 2018

2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

View full text Add to dashboard Cite

“…They highlight the importance of managing and maintaining up-to-date knowledge about enterprise KPIs. In [7,9] the authors propose a collaborative framework based on KPIOnto for sharing PIs and KPIs to track the performance of collaborations at the strategic level. The information is stored in the form of an online dictionary that can be continuously updated, much similar to our proposal, which highlights the importance of always maintaining up-to-date KPI information.…”

Section: Related Workmentioning

confidence: 99%

Specification and derivation of key performance indicators for business analytics: A semantic approach

Mat

Trujillo

Mylopoulos

2017

Data & Knowledge Engineering

View full text Add to dashboard Cite

Key Performance Indicators (KPI) measure the performance of an enterprise relative to its objectives thereby enabling corrective action where there are deviations. In current practice, KPIs are manually integrated within dashboards and scorecards used by decision makers. This practice entails various shortcomings. First, KPIs are not related to their business objectives and strategy. Consequently, decision makers often obtain a scattered view of the business status and business concerns. Second, while KPIs are defined by decision makers, their implementation is performed by IT specialists. This often results in discrepancies that are difficult to identify. In this paper, we propose an approach that provides decision makers with an integrated view of strategic business objectives and conceptual data warehouse KPIs. The main benefit of our proposal is that it links strategic business models to the data for monitoring and assessing them. In our proposal, KPIs are defined using a modeling language where decision makers specify KPIs using business terminology, but can also perform quick modifications and even navigate data while maintaining a strategic view. This enables monitoring and what-if analysis, thereby helping analysts to compare expectations with reported results.

show abstract

“…It is an extended version of [6], and major improvements include a detailed formalisation of the methodology, a thorough experimental study and evaluation of results and a deeper analysis of related work.…”

Section: Introductionmentioning

confidence: 99%