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On Advancement of Information Spaces to Improve Prediction-Based Compression

dc.contributor.authorCayoglu, Ugur
dc.contributor.authorTristram, Frank
dc.contributor.authorMeyer, Jörg
dc.contributor.authorKerzenmacher, Tobias
dc.contributor.authorBraesicke, Peter
dc.contributor.authorStreit, Achim
dc.contributor.editorDavid, Klaus
dc.contributor.editorGeihs, Kurt
dc.contributor.editorLange, Martin
dc.contributor.editorStumme, Gerd
dc.date.accessioned2019-08-27T12:55:24Z
dc.date.available2019-08-27T12:55:24Z
dc.date.issued2019
dc.description.abstractOne 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.en
dc.identifier.doi10.18420/inf2019_39
dc.identifier.isbn978-3-88579-688-6
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/24987
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofINFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-294
dc.subjectcompression algorithms
dc.subjectencoding
dc.subjectmeteorology
dc.subjectprediction-based compression
dc.subjectinformation spaces
dc.titleOn Advancement of Information Spaces to Improve Prediction-Based Compressionen
dc.typeText/Conference Paper
gi.citation.endPage272
gi.citation.publisherPlaceBonn
gi.citation.startPage271
gi.conference.date23.-26. September 2019
gi.conference.locationKassel
gi.conference.sessiontitleData Science

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