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dc.contributor.authorKenett, Ron
dc.contributor.authorFranch Gutiérrez, Javier
dc.contributor.authorSusi, Angelo
dc.contributor.authorGalanis, Nikolaos
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació
dc.identifier.citationKenett, R. [et al.]. Adoption of Free Libre Open Source Software (FLOSS): A risk management perspective. A: Annual IEEE International Computer Software and Applications Conference. "IEEE 38th Annual International Computers, Software and Applications Conference: 27–29 July 2014, Västerås, Sweden: proceedings". Vasteras: Institute of Electrical and Electronics Engineers (IEEE), 2014, p. 171-180.
dc.description.abstractFree Libre Open Source Software (FLOSS) has become a strategic asset in software development, and open source communities behind FLOSS are a key player in the field. The analysis of open source community dynamics is a key capability in risk management practices focused on the integration of FLOSS in all types of organizations. We are conducting research in developing methodologies for managing risks of FLOSS adoption and deployment in various application domains. This paper is about the ability to systematically capture, filter, analyze, reason about, and build theories upon, the behavior of an open source community in combination with the structured elicitation of expert opinions on potential organizational business risk. The novel methodology presented here blends together qualitative and quantitative information as part of a wider analytics platform. The approach combines big data analytics with automatic scripting of scenarios that permits experts to assess risk indicators and business risks in focused tactical and strategic workshops. These workshops generate data that is used to construct Bayesian networks that map data from community risk drivers into statistical distributions that are feeding the platform risk management dashboard. A special feature of this model is that the dynamics of an open source community are tracked using social network metrics that capture the structure of unstructured chat data. The method is illustrated with a running example based on experience gained in implementing our approach in an academic smart environment setting including Moodbile, a Mobile Learning for Moodle ( This example is the first in a series of planned experiences in the domain of smart environments with the ultimate goal of deriving a complete risk model in that field.
dc.format.extent10 p.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Informàtica::Enginyeria del software
dc.subject.lcshOpen source software
dc.subject.otherFree Libre Open Source Software
dc.subject.otherRisk management
dc.subject.otherBayesian networks
dc.subject.otherSocial network analysis
dc.subject.otherSmart environment
dc.subject.otherSmart device
dc.subject.otherMobile technologies
dc.titleAdoption of Free Libre Open Source Software (FLOSS): A risk management perspective
dc.typeConference report
dc.subject.lemacProgramari lliure
dc.contributor.groupUniversitat Politècnica de Catalunya. inSSIDE - integrated Software, Service, Information and Data Engineering
dc.contributor.groupUniversitat Politècnica de Catalunya. SUSHITOS - Grup de recerca en serveis per a tecnologies d'informació socials, ubiqües i humanístiques, i per a software lliure
dc.description.peerreviewedPeer Reviewed
dc.rights.accessRestricted access - publisher's policy
dc.description.versionPostprint (published version)
upcommons.citation.authorKenett, R.; Franch, X.; Susi, A.; Galanis, N.
upcommons.citation.contributorAnnual IEEE International Computer Software and Applications Conference
upcommons.citation.publicationNameIEEE 38th Annual International Computers, Software and Applications Conference: 27–29 July 2014, Västerås, Sweden: proceedings

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