{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T10:11:15Z","timestamp":1781086275614,"version":"3.54.1"},"reference-count":29,"publisher":"Association for Computing Machinery (ACM)","issue":"10","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2014,6]]},"abstract":"<jats:p>Visual analysis of high-volume time series data is ubiquitous in many industries, including finance, banking, and discrete manufacturing. Contemporary, RDBMS-based systems for visualization of high-volume time series data have difficulty to cope with the hard latency requirements and high ingestion rates of interactive visualizations. Existing solutions for lowering the volume of time series data disregard the semantics of visualizations and result in visualization errors.<\/jats:p>\n          <jats:p>In this work, we introduce M4, an aggregation-based time series dimensionality reduction technique that provides error-free visualizations at high data reduction rates. Focusing on line charts, as the predominant form of time series visualization, we explain in detail the drawbacks of existing data reduction techniques and how our approach outperforms state of the art, by respecting the process of line rasterization.<\/jats:p>\n          <jats:p>We describe how to incorporate aggregation-based dimensionality reduction at the query level in a visualization-driven query rewriting system. Our approach is generic and applicable to any visualization system that uses an RDBMS as data source. Using real world data sets from high tech manufacturing, stock markets, and sports analytics domains we demonstrate that our visualization-oriented data aggregation can reduce data volumes by up to two orders of magnitude, while preserving perfect visualizations.<\/jats:p>","DOI":"10.14778\/2732951.2732953","type":"journal-article","created":{"date-parts":[[2015,5,12]],"date-time":"2015-05-12T15:37:52Z","timestamp":1431445072000},"page":"797-808","source":"Crossref","is-referenced-by-count":74,"title":["M4"],"prefix":"10.14778","volume":"7","author":[{"given":"Uwe","family":"Jugel","sequence":"first","affiliation":[{"name":"SAP AG, Dresden, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zbigniew","family":"Jerzak","sequence":"additional","affiliation":[{"name":"SAP AG, Dresden, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gregor","family":"Hackenbroich","sequence":"additional","affiliation":[{"name":"SAP AG, Dresden, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Volker","family":"Markl","sequence":"additional","affiliation":[{"name":"Technische Universit\u00e4t Berlin, Berlin, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2014,6]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.14778\/2367502.2367533"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1147\/sj.41.0025"},{"key":"e_1_2_1_3_1","doi-asserted-by":"crossref","unstructured":"G.\n      Burtini S.\n      Fazackerley and \n      R.\n      Lawrence\n  . \n  Time series compression for adaptive chart generation\n  . In CCECE pages \n  1\n  --\n  6\n  . \n  IEEE 2013\n  .  G. Burtini S. Fazackerley and R. Lawrence. Time series compression for adaptive chart generation. In CCECE pages 1--6. IEEE 2013.","DOI":"10.1109\/CCECE.2013.6567840"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1111\/1467-8659.00303"},{"key":"e_1_2_1_5_1","volume-title":"Data Compression","author":"Salomon David","year":"2007","unstructured":"David Salomon . Data Compression . Springer , 2007 . David Salomon. Data Compression. Springer, 2007."},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.3138\/FM57-6770-U75U-7727"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.5555\/2033546.2033561"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1198\/106186002317375604"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/2379776.2379788"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2094114.2094126"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2010.09.007"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2007.04.009"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2010.5447930"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.5555\/902273"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/2335484.2335536"},{"key":"e_1_2_1_16_1","volume-title":"VLDB PhD Workshop. VLDB Endowment","author":"Jugel U.","year":"2012","unstructured":"U. Jugel and V. Markl . Interactive visualization of high-velocity event streams . In VLDB PhD Workshop. VLDB Endowment , 2012 . U. Jugel and V. Markl. Interactive visualization of high-velocity event streams. In VLDB PhD Workshop. VLDB Endowment, 2012."},{"key":"e_1_2_1_17_1","volume-title":"Pushing the limit in visual data exploration: Techniques and applications. Lecture notes in artificial intelligence, (2821):37--51","author":"Keim D. A.","year":"2003","unstructured":"D. A. Keim , C. Panse , J. Schneidewind , M. Sips , M. C. Hao , and U. Dayal . Pushing the limit in visual data exploration: Techniques and applications. Lecture notes in artificial intelligence, (2821):37--51 , 2003 . D. A. Keim, C. Panse, J. Schneidewind, M. Sips, M. C. Hao, and U. Dayal. Pushing the limit in visual data exploration: Techniques and applications. Lecture notes in artificial intelligence, (2821):37--51, 2003."},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.5555\/646418.693335"},{"key":"e_1_2_1_19_1","volume-title":"Efficient algorithms for vectorization and polygonal approximation","author":"Kolesnikov A.","year":"2003","unstructured":"A. Kolesnikov . Efficient algorithms for vectorization and polygonal approximation . University of Joensuu , 2003 . A. Kolesnikov. Efficient algorithms for vectorization and polygonal approximation. University of Joensuu, 2003."},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2006.143"},{"key":"e_1_2_1_21_1","first-page":"86","volume-title":"Proc. SPIE, Multimedia Computing and Networking","volume":"3969","author":"Ma W.-Y.","year":"2000","unstructured":"W.-Y. Ma , I. Bedner , G. Chang , A. Kuchinsky , and H. Zhang . A framework for adaptive content delivery in heterogeneous network environments . In Proc. SPIE, Multimedia Computing and Networking , volume 3969 , pages 86 -- 100 . SPIE, 2000 . W.-Y. Ma, I. Bedner, G. Chang, A. Kuchinsky, and H. Zhang. A framework for adaptive content delivery in heterogeneous network environments. In Proc. SPIE, Multimedia Computing and Networking, volume 3969, pages 86--100. SPIE, 2000."},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/2488222.2488283"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-17622-7_10"},{"key":"e_1_2_1_24_1","first-page":"467","volume-title":"Proceedings of the International Computing Symposium","author":"Reumann K.","year":"1974","unstructured":"K. Reumann and A. P. M. Witkam . Optimizing curve segmentation in computer graphics . In Proceedings of the International Computing Symposium , pages 467 -- 472 . North-Holland Publishing Company , 1974 . K. Reumann and A. P. M. Witkam. Optimizing curve segmentation in computer graphics. In Proceedings of the International Computing Symposium, pages 467--472. North-Holland Publishing Company, 1974."},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1179\/000870406X93490"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1179\/caj.1993.30.1.46"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2003.819861"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/1989323.1989449"},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/354756.354857"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/2732951.2732953","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T10:57:30Z","timestamp":1672225050000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/2732951.2732953"}},"subtitle":["a visualization-oriented time series data aggregation"],"short-title":[],"issued":{"date-parts":[[2014,6]]},"references-count":29,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2014,6]]}},"alternative-id":["10.14778\/2732951.2732953"],"URL":"https:\/\/doi.org\/10.14778\/2732951.2732953","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2014,6]]}}}