Towards certified open data in digital service ecosystems

    Research output: Contribution to journalArticleScientificpeer-review

    19 Citations (Scopus)

    Abstract

    The opportunities of open data have been recently recognized among companies in different domains. Digital service providers have increasingly been interested in the possibilities of innovating new ideas and services around open data. Digital service ecosystems provide several advantages for service developers, enabling the service co-innovation and co-creation among ecosystem members utilizing and sharing common assets and knowledge. The utilization of open data in digital services requires new innovation practices, service development models, and a collaboration environment. These can be provided by the ecosystem. However, since open data can be almost anything and originate from different kinds of data sources, the quality of data becomes the key issue. The new challenge for service providers is how to guarantee the quality of open data. In the ecosystems, uncertain data quality poses major challenges. The main contribution of this paper is the concept of the Evolvable Open Data based digital service Ecosystem (EODE), which defines the kinds of knowledge and services that are required for validating open data in digital service ecosystems. Thus, the EODE provides business potential for open data and digital service providers, as well as other actors around open data. The ecosystem capability model, knowledge management models, and the taxonomy of services to support the open data quality certification are described. Data quality certification confirms that the open data is trustworthy and its quality is good enough to be accepted for the usage of the ecosystem's services. The five-phase open data quality certification process, according to which open data is brought to the ecosystem and certified for the usage of the digital service ecosystem members using the knowledge models and support services of the ecosystem, is also described. The initial experiences of the still ongoing validation steps are summarized, and the concept limitations and future development targets are identified.
    Original languageEnglish
    Pages (from-to)1257-1297
    Number of pages41
    JournalSoftware Quality Journal
    Volume26
    Issue number4
    Early online date2017
    DOIs
    Publication statusPublished - 2018
    MoE publication typeNot Eligible

    Keywords

    • digital service ecosystem
    • interoperability
    • knowledge sharing
    • quality of data
    • quality policy
    • semantics

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