Abstract.To facilitate the adoption of open-source software (OSS) in industry, it is important to provide potential users (i.e., those who could decide to adopt OSS) with the means for evaluating the trustworthiness of OS products. This paper presents part of the work done in the QualiPSo project for this purpose. A set of factors that are believed to affect the perception of trustworthiness are introduced. In order to test the feasibility of deriving a correct, complete and reliable evaluation of trustworthiness on the basis of these factors, a set of well-known OSS projects have been chosen. Then, the possibility to assess the proposed factors on each project was verified: not all the factors appear to be observable or measurable. The paper reports what information is available to support the evaluation and what is not. This knowledge is considered to be useful to users, who are warned that there are still dark areas in the characterization of OSS products, and to developers, who should provide more data and characteristics on their products in order to support their adoption.
To support the adoption of big data value, it is essential to foster, strengthen, and support the development of big data value technologies, successful use cases and data-driven business models. At the same time, it is necessary to deal with many different aspects of an increasingly complex data ecosystem. Creating a productive ecosystem for big data and driving accelerated adoption requires an interdisciplinary approach addressing a wide range of challenges from access to data and infrastructure, to technical barriers, skills, and policy and regulation. In order to overcome the adoption challenges, collective action from all stakeholders in an effective, holistic and coherent manner is required. To this end, the Big Data Value Public-Private Partnership (BDV PPP) was established to develop the European data ecosystem and enable data-driven digital transformation, delivering maximum economic and societal benefit, and achieving and sustaining Europe’s leadership in the fields of big data value creation and Artificial Intelligence. This chapter describes the different steps that have been taken to address the big data value adoption challenges: first, the establishment of the BDV PPP to mobilise and create coherence with all stakeholders in the European data ecosystem; second, the introduction of five strategic mechanisms to encourage cooperation and coordination in the data ecosystem; third, a three-phase roadmap to guide the development of a healthy European data ecosystem; and fourth, a systematic and strategic approach towards actively engaging the key communities in the European Data Value Ecosystem.
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