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dc.creatorPérez Álvarez, José Migueles
dc.creatorGómez López, María Teresaes
dc.creatorParody Núñez, María Luisaes
dc.creatorMartínez Gasca, Rafaeles
dc.date.accessioned2020-06-12T08:53:26Z
dc.date.available2020-06-12T08:53:26Z
dc.date.issued2016
dc.identifier.citationPérez Álvarez, J.M., Gómez López, M.T., Parody Núñez, M.L. y Martínez Gasca, R. (2016). Process Instance Query Language to Include Process Performance Indicators in DMN. En EDOCW 2016: IEEE 20th International Enterprise Distributed Object Computing Workshop Vienna, Austria: IEEE Computer Society.
dc.identifier.isbn978-1-4673-9933-3es
dc.identifier.issn2325-6605es
dc.identifier.urihttps://hdl.handle.net/11441/97726
dc.description.abstractCompanies are increasingly incorporating commercial Business Process Management Systems (BPMSs) as mechanisms to automate their daily procedures. These BPMSs manage the information related to the instances that flow through the model (business data), and recover the information concerning the process performance (Process Performance Indicators). Process Performance Indicators (PPIs) tend to be used for the detection of possible deviations of expected behaviour, and help in the post-mortem analysis and redesign by improving the goals of the processes. However, not only are PPIs important in terms of their ability to measure and detect a derivation, but they should also be included at decision points to make the business processes more adaptable to the process reality at runtime. In this paper, we propose a complete solution that allows the incorporation of the PPIs into decision tasks, following the Decision Model and Notation (DMN) standard, with the aim of enriching the decisions that can be taken during the process execution. Our proposal firstly includes an extension of the decision rule grammar of the DMN standard, by incorporating the definition and the use of a Process Instance Query Language (PIQL) that offers information about the instances related to the PPIs involved. In order to achieve this objective, a framework has also been developed to support the enrichment of process instance query expressions (PIQEs). This framework combines a set of mature technologies to evaluate the decisions about PPIs at runtime. As an illustration a real sample has been used whose decisions are improved thanks to the incorporation of the PPIs at runtime.es
dc.description.sponsorshipMinisterio de Ciencia y Tecnología TIN2015-63502-C3-2-Res
dc.formatapplication/pdfes
dc.format.extent8es
dc.language.isoenges
dc.publisherIEEE Computer Societyes
dc.relation.ispartofEDOCW 2016: IEEE 20th International Enterprise Distributed Object Computing Workshop (2016),
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectBusiness processeses
dc.subjectPerformance Indicatorses
dc.subjectDecision Model and Notationes
dc.subjectProcess Instance Queryes
dc.titleProcess Instance Query Language to Include Process Performance Indicators in DMNes
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/submittedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticoses
dc.relation.projectIDTIN2015-63502-C3-2-Res
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/7584381es
dc.identifier.doi10.1109/EDOCW.2016.7584381es
dc.eventtitleEDOCW 2016: IEEE 20th International Enterprise Distributed Object Computing Workshopes
dc.eventinstitutionVienna, Austriaes
dc.relation.publicationplaceNew York, USAes
dc.contributor.funderMinisterio de Ciencia Y Tecnología (MCYT). Españaes

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