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Auflistung nach Autor:in "Tristram, Frank"

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  • Konferenzbeitrag
    On Advancement of Information Spaces to Improve Prediction-Based Compression
    (INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft, 2019) Cayoglu, Ugur; Tristram, Frank; Meyer, Jörg; Kerzenmacher, Tobias; Braesicke, Peter; Streit, Achim
    One of the scientific communities that generate the largest amounts of data today are the climate sciences. New climate models enable model integrations at unprecedented resolution, simulating timescales from decades to centuries of climate change. Nowadays, limited storage space and ever increasing model output is a big challenge. For this reason, we look at lossless compression using prediction-based data compression. We show that there is a significant dependence of the compression rate on the chosen traversal method and the underlying data model. We examine the influence of this structural dependency on prediction-based compression algorithms and explore possibilities to improve compression rates. We introduce the concept of Information Spaces (IS), which help to improve the accuracy of predictions by nearly 10% and decrease the standard deviation of the compression results by 20% on average.
  • Konferenzbeitrag
    Status report of bwfdm-communities - A state wide research data management initiative
    (Informatik 2014, 2014) Tristram, Frank; Wehrle, Dennis; Çayoğlu, Uğur; Rex, Jessica; Suchodoletz, Dirk Von
    Research data are valuable goods that are often only reproducible with significant effort or, in the case of unique observations, not at all. Scientists focus on data analysis and its results. By now, data exploration is accepted as a fourth scientific pillar (next to experiments, theory, and simulation). A main prerequisite for easy data exploration is successful data management. A holistic approach includes all phases of a data lifecycle: data generation, data analysis, data ingest, data preservation, data access, reusage and long term preservation. Tackling the challenge of increasing complexity in managing research data, the objective of bwFDM-Communities is to expose problems of research communities.1 To achieve this goal, the project's key account managers enter into a dialogue with all relevant research groups at each university in Baden- Württemberg. Next to the identification of best practices, possible developments will be determined together with the scientists.