Quality in open data based digital service ecosystem: Dissertation

    Research output: ThesisDissertationCollection of Articles

    Abstract

    To a growing extent, the software systems of today are provided as digital services distributed across networks, dynamically fulfilling the complex demands of consumers. As people have access to the Internet almost everywhere with the help of the mobile devices, such digital services are expected to be available when requested, and to provide services reliably and without any interruptions. Recently, the use of freely available data on the Internet has increased continuously in the context of digital services. This kind of open data has been identified as providing several benefits to service providers, such as new ideas, services, data-based contents, and confirmation in business decision making. Digital service engineering itself is evolving, and is shifting from isolated development environments towards open innovation and co-development environments, called ecosystems. Digital service ecosystems enable service providers to strengthen their position by cooperating, while still being able to act independently. The ecosystem supports the business models of its actors, also enabling the utilisation of existing ecosystem assets, such as knowledge and services. This dissertation concentrates on the quality of digital service, with an emphasis on open data in ecosystem-based service engineering. The contribution of this research is a concept of an open data based digital service ecosystem, which provides the assets for service providers to design the quality of services and to ensure the quality of open data. These assets include the service engineering model that enables quality-driven service co-innovation and co-development among ecosystem members, the knowledge that can be utilised in digital service engineering, and the enabling environment with knowledge management models and support services for acting in the ecosystem. Additionally, the ecosystem provides support for defining an open business model, for evaluating the quality of open data, and for communication between digital service providers and open data providers. The ecosystem concept is generic, and can be adapted to different application domains; the domain model used together with generic knowledge management models adapts the service engineering and digital services, for example, to the healthcare, energy or traffic domains. The developed concept has been validated incrementally in several application domains.
    Original languageEnglish
    QualificationDoctor Degree
    Awarding Institution
    • University of Oulu
    Supervisors/Advisors
    • Ovaska, Eila, Supervisor, External person
    • Seppänen, Veikko, Supervisor, External person
    Award date29 Sep 2017
    Place of PublicationEspoo
    Publisher
    Print ISBNs978-951-38-8557-1
    Electronic ISBNs978-951-38-8556-4
    Publication statusPublished - 2017
    MoE publication typeG5 Doctoral dissertation (article)

    Fingerprint

    Ecosystems
    Knowledge management
    Innovation
    Internet
    Industry
    Mobile devices
    Quality of service
    Decision making
    Communication

    Keywords

    • open data
    • quality
    • digital service
    • service ecosystem

    Cite this

    Immonen, A. (2017). Quality in open data based digital service ecosystem: Dissertation. Espoo: VTT Technical Research Centre of Finland.
    Immonen, Anne. / Quality in open data based digital service ecosystem : Dissertation. Espoo : VTT Technical Research Centre of Finland, 2017. 220 p.
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    publisher = "VTT Technical Research Centre of Finland",
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    Immonen, A 2017, 'Quality in open data based digital service ecosystem: Dissertation', Doctor Degree, University of Oulu, Espoo.

    Quality in open data based digital service ecosystem : Dissertation. / Immonen, Anne.

    Espoo : VTT Technical Research Centre of Finland, 2017. 220 p.

    Research output: ThesisDissertationCollection of Articles

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    Immonen A. Quality in open data based digital service ecosystem: Dissertation. Espoo: VTT Technical Research Centre of Finland, 2017. 220 p.