{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T10:11:23Z","timestamp":1775815883717,"version":"3.50.1"},"reference-count":34,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2019,3,31]],"date-time":"2019-03-31T00:00:00Z","timestamp":1553990400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"European Research Council","award":["339539 (AOC)"],"award-info":[{"award-number":["339539 (AOC)"]}]},{"name":"EU FP7 programme","award":["617508 (ViDa)"],"award-info":[{"award-number":["617508 (ViDa)"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Spatial Algorithms Syst."],"published-print":{"date-parts":[[2019,3,31]]},"abstract":"<jats:p>Nowadays, massive amounts of point cloud data can be collected thanks to advances in data acquisition and processing technologies such as dense image matching and airborne LiDAR scanning. With the increase in volume and precision, point cloud data offers a useful source of information for natural-resource management, urban planning, self-driving cars, and more. At the same time, on the scale that point cloud data is produced, management challenges are introduced: it is important to achieve efficiency both in terms of querying performance and space requirements. Traditional file-based solutions to point cloud management offer space efficiency, however, they cannot scale to such massive data and provide the declarative power of a DBMS.<\/jats:p>\n          <jats:p>In this article, we propose a time- and space-efficient solution to storing and managing point cloud data in main memory column-store DBMS. Our solution, Space-Filling Curve Dictionary-Based Compression (SFC-DBC), employs dictionary-based compression in the spatial data management domain and enhances it with indexing capabilities by using space-filling curves. SFC-DBC does so by constructing the space-filling curve over a compressed, artificially introduced dictionary space. Consequently, SFC-DBC significantly optimizes query execution and yet does not require additional storage resources, compared to traditional dictionary-based compression. With respect to space-filling-curve-based approaches, it minimizes storage footprint and increases resilience to skew. As a proof of concept, we develop and evaluate our approach as a research prototype in the context of SAP HANA. SFC-DBC outperforms other dictionary-based compression schemes by up to 61% in terms of space and up to 9.4\u00d7 in terms of query performance.<\/jats:p>","DOI":"10.1145\/3299770","type":"journal-article","created":{"date-parts":[[2019,6,6]],"date-time":"2019-06-06T12:28:42Z","timestamp":1559824122000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Dictionary Compression in Point Cloud Data Management"],"prefix":"10.1145","volume":"5","author":[{"given":"Mirjana","family":"Pavlovic","sequence":"first","affiliation":[{"name":"\u00c9cole Polytechnique F\u00e9d\u00e9ale de Lausanne, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kai-Niklas","family":"Bastian","sequence":"additional","affiliation":[{"name":"SAP SE, Walldorf, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hinnerk","family":"Gildhoff","sequence":"additional","affiliation":[{"name":"SAP SE, Walldorf, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anastasia","family":"Ailamaki","sequence":"additional","affiliation":[{"name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne 8 RAW Labs SA, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2019,6,6]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.14778\/2824032.2824110"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.5555\/645965.674403"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/2517349.2522714"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/32.6184"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/73721.73746"},{"key":"e_1_2_1_6_1","first-page":"28","article-title":"The SAP HANA database\u2014An architecture overview","volume":"35","author":"F\u00e4rber Franz","year":"2012","journal-title":"IEEE Data Eng. Bull."},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2996913.2997005"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/602259.602266"},{"key":"e_1_2_1_9_1","volume-title":"Photogrammetric Week","volume":"11","author":"Haala Norbert","year":"2011"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/0146-664X(80)90055-6"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/93597.98742"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.5555\/1316689.1316756"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/2933349.2933356"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/1989323.1989448"},{"key":"e_1_2_1_15_1","volume-title":"EUROGRAPHICS","volume":"85","author":"Laurini Robert","year":"1985"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/2744700.2744702"},{"key":"e_1_2_1_17_1","doi-asserted-by":"crossref","unstructured":"Mohamed F. Mokbel and Walid G. Aref. 2009. Space-filling curves for query processing. In Encycl. Datab. Syst. 2675--2680.  Mohamed F. Mokbel and Walid G. Aref. 2009. Space-filling curves for query processing. In Encycl. Datab. Syst. 2675--2680.","DOI":"10.1007\/978-0-387-39940-9_350"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/69.908985"},{"key":"e_1_2_1_19_1","unstructured":"Actueel Hoogte Bestand Nederland. 2017. AHN Datasets. Retrieved from http:\/\/www.ahn.nl.  Actueel Hoogte Bestand Nederland. 2017. AHN Datasets. Retrieved from http:\/\/www.ahn.nl."},{"key":"e_1_2_1_20_1","unstructured":"Oracle. 2017. Spatial and Graph Developer\u2019s Guide. Retrieved from https:\/\/docs.oracle.com\/database\/121\/SPATL\/.  Oracle. 2017. Spatial and Graph Developer\u2019s Guide. Retrieved from https:\/\/docs.oracle.com\/database\/121\/SPATL\/."},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/588011.588037"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3139958.3139969"},{"key":"e_1_2_1_23_1","volume-title":"Mathematische Annalen","author":"Peano Giuseppe"},{"key":"e_1_2_1_24_1","unstructured":"PostgreSQL. 2017. A PostgreSQL Extension for Storing Point Cloud (LiDAR) Data. Retrieved from https:\/\/github.com\/pgpointcloud\/pointcloud.  PostgreSQL. 2017. A PostgreSQL Extension for Storing Point Cloud (LiDAR) Data. Retrieved from https:\/\/github.com\/pgpointcloud\/pointcloud."},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.14778\/2824032.2824043"},{"key":"e_1_2_1_26_1","unstructured":"Rapidlasso GmbH. 2017. LAStools. Retrieved from https:\/\/rapidlasso.com\/lastools\/.  Rapidlasso GmbH. 2017. LAStools. Retrieved from https:\/\/rapidlasso.com\/lastools\/."},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/1811158.1811178"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/356924.356930"},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/2213836.2213946"},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.is.2004.12.001"},{"key":"e_1_2_1_31_1","first-page":"71","article-title":"Multidimensional range search in dynamically balanced trees","volume":"2","author":"Tropf Hermann","year":"1981","journal-title":"ANGEWANDTE INFO."},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cag.2015.01.007"},{"key":"e_1_2_1_33_1","first-page":"68","article-title":"Airborne laser scanning\u2014An introduction and overview","volume":"54","author":"Wehr Aloysius","year":"1999","journal-title":"P&RS"},{"key":"e_1_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.14778\/1687627.1687671"}],"container-title":["ACM Transactions on Spatial Algorithms and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3299770","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3299770","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T00:26:12Z","timestamp":1750206372000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3299770"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,3,31]]},"references-count":34,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2019,3,31]]}},"alternative-id":["10.1145\/3299770"],"URL":"https:\/\/doi.org\/10.1145\/3299770","relation":{},"ISSN":["2374-0353","2374-0361"],"issn-type":[{"value":"2374-0353","type":"print"},{"value":"2374-0361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,3,31]]},"assertion":[{"value":"2018-04-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2018-12-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2019-06-06","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}