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Auflistung nach Schlagwort "data exchange"

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  • Textdokument
    Computation Offloading in JVM-based Dataflow Engines
    (BTW 2019 – Workshopband, 2019) Gavriilidis, Haralampos
    State-of-the-art dataflow engines, such as Apache Spark and Apache Flink scale out on large clusters for a variety of data-processing tasks, including machine learning and data mining algorithms. However, being based on the JVM, they are unable to apply optimizations supported by modern CPUs. On the contrary, specialized data processing frameworks scale up by exploiting modern CPU characteristics. The goal of this thesis is to find the sweet spot between scale-out and scale-up systems by offloading computation from dataflow engines to specialized systems. We propose two computation offloading methods, reason about their applicability, and implement a prototype based on Apache Spark. Our evaluation shows that for compute-intensive tasks, computation offloading leads to performance improvements of up to a factor of 2.5x. For certain UDF scenarios, computation offloading performs worse by up to a factor of 3x: our microbenchmarks show that 80% of the time is spent on serialization operations. By employing data exchange without serialization, computation offloading achieves performance improvements by up to 10x.
  • Zeitschriftenartikel
    eXtensible Business Reporting Language (XBRL)
    (Wirtschaftsinformatik: Vol. 44, No. 5, 2002) Nutz, Andreas; Strauß, Markus
    The eXtensible Business Reporting Language, or XBRL, is a royalty-free language based on XML that provides for a standardization of method and content in the exchange of business information. XBRL aims to reduce inefficiencies in data exchange and analysis, coupled with an improved comparability of information.The first taxonomies based on XBRL have: •identified opportunities for significant improvement in the efficiency of data exchange and automated analysis.•shown that comparisons between and the compatibility of information within business reports have not improved due to XBRL.
  • Konferenzbeitrag
    Towards Robust Trust Frameworks for Data Exchange: A Multidisciplinary Inquiry
    (Open Identity Summit 2024, 2024) Badirova, Aytaj; Alangot, Bithin; Dimitrakos, Theo; Yahyapour, Ramin
    Data exchange is essential in the fast-changing field of data-driven innovations. In exploring the importance of data and data exchange, this paper highlights the necessity of building trust. For data sharing to be successful, trust is essential for assuring reliability, security, and ethical behaviour. We review the current state of the art where research and real-world applications converge in both academia and industry. Notably, trust framework-based projects are starting to take shape, promoting safe and open data markets that are included in this work. Nonetheless, challenges still exist, such as complex legal, technological, and business issues. Some of the main challenges that are faced while establishing a trust framework have also been briefly mentioned in this paper.