Developing ontologies for representing data about key performance indicators

Poveda Villalón, María ORCID: https://orcid.org/0000-0003-3587-0367, Radulovic, Filip and García Castro, Raúl ORCID: https://orcid.org/0000-0002-0421-452X (2014). Developing ontologies for representing data about key performance indicators. In: "2nd eeBuilding Key Performance Indicators Workshop (KPIs)", 01-03 Oct 2014, Niza, Francia. pp. 1-16.

Description

Title: Developing ontologies for representing data about key performance indicators
Author/s:
Item Type: Presentation at Congress or Conference (Article)
Event Title: 2nd eeBuilding Key Performance Indicators Workshop (KPIs)
Event Dates: 01-03 Oct 2014
Event Location: Niza, Francia
Date: 2014
Subjects:
Freetext Keywords: Ontology development; Ontology development methodologies; Key performance indicator
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Multiple indicators are of interest in smart cities at different scales and for different stakeholders. In open environments, such as The Web, or when indicator information has to be interchanged across systems, contextual information (e.g., unit of measurement, measurement method) should be transmitted together with the data and the lack of such information might cause undesirable effects. Describing the data by means of ontologies increases interoperability among datasets and applications. However, methodological guidance is crucial during ontology development in order to transform the art of modeling in an engineering activity. In the current paper, we present a methodological approach for modelling data about Key Performance Indicators and their context with an application example of such guidelines.

Funding Projects

Type
Code
Acronym
Leader
Title
FP7
FP7-608711
Unspecified
Unspecified
Ready4SmartCities - ICT Roadmap and Data Interoperability for Energy Systems in Smart Cities
Unspecified
FPU2012/04084
Unspecified
Unspecified
Unspecified

More information

Item ID: 36714
DC Identifier: https://oa.upm.es/36714/
OAI Identifier: oai:oa.upm.es:36714
Deposited by: Memoria Investigacion
Deposited on: 12 Feb 2016 12:06
Last Modified: 12 May 2020 09:07
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