{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T18:38:33Z","timestamp":1772044713190,"version":"3.50.1"},"reference-count":4,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2018,1,9]],"date-time":"2018-01-09T00:00:00Z","timestamp":1515456000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["SIGSPATIAL Special"],"published-print":{"date-parts":[[2018,1,9]]},"abstract":"<jats:p>\n            GeoVisual analytics,\n            <jats:italic>abbr. GeoViz<\/jats:italic>\n            , is the science of analytical reasoning assisted by GeoVisual map interfaces. For example, a GeoViz heat map of the New York City taxi trips tells the taxi company where the hot pick-up and drop-off locations are. GeoViz involves the following two memory and compute intensive phases:\n            <jats:bold>Phase I: Spatial Data Preparation:<\/jats:bold>\n            In this phase, the system first loads the designated spatial data from the database (e.g., Shape files, PostGIS, HDFS). Based on the application, the system may then need to perform data processing operations (e.g., spatial range query, spatial join query) on the loaded spatial data to return the set of spatial objects to be visualized.\n            <jats:italic>Phase II: Map Visualization:<\/jats:italic>\n            In this phase, the system applies the map visualization effect, e.g., Heatmap, on the spatial objects produced in the Phase I. The system first pixelizes the spatial objects, then aggregates overlapped pixels, and finally renders an image for each geospatial map tile.\n          <\/jats:p>","DOI":"10.1145\/3178392.3178394","type":"journal-article","created":{"date-parts":[[2018,1,10]],"date-time":"2018-01-10T16:51:38Z","timestamp":1515603098000},"page":"2-3","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["SRC: geospatial visual analytics belongs to database systems"],"prefix":"10.1145","volume":"9","author":[{"given":"Jia","family":"Yu","sequence":"first","affiliation":[{"name":"Arizona State University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2018,1,9]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"crossref","unstructured":"Ahmed Eldawy Mohamed F. Mokbel and Christopher Jonathan. 2016. HadoopViz: A MapReduce framework for extensible visualization of big spatial data. In ICDE. 601--612.  Ahmed Eldawy Mohamed F. Mokbel and Christopher Jonathan. 2016. HadoopViz: A MapReduce framework for extensible visualization of big spatial data. In ICDE. 601--612.","DOI":"10.1109\/ICDE.2016.7498274"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/2996913.2996923"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/2882903.2915237"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2820783.2820860"}],"container-title":["SIGSPATIAL Special"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3178392.3178394","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3178392.3178394","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T02:26:23Z","timestamp":1750213583000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3178392.3178394"}},"subtitle":["the BABYLON approach"],"short-title":[],"issued":{"date-parts":[[2018,1,9]]},"references-count":4,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2018,1,9]]}},"alternative-id":["10.1145\/3178392.3178394"],"URL":"https:\/\/doi.org\/10.1145\/3178392.3178394","relation":{},"ISSN":["1946-7729"],"issn-type":[{"value":"1946-7729","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,1,9]]},"assertion":[{"value":"2018-01-09","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}