{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T12:00:31Z","timestamp":1771329631535,"version":"3.50.1"},"reference-count":64,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2024,4,16]],"date-time":"2024-04-16T00:00:00Z","timestamp":1713225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,4,16]],"date-time":"2024-04-16T00:00:00Z","timestamp":1713225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"NSFC","doi-asserted-by":"crossref","award":["61802128"],"award-info":[{"award-number":["61802128"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Yangtze River Delta Science and Technology Innovation Community Project","award":["23002400400"],"award-info":[{"award-number":["23002400400"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Vis"],"published-print":{"date-parts":[[2024,8]]},"DOI":"10.1007\/s12650-024-00986-y","type":"journal-article","created":{"date-parts":[[2024,4,16]],"date-time":"2024-04-16T18:02:53Z","timestamp":1713290573000},"page":"603-622","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["GeoVis: a data-driven geographic visualization recommendation system via latent space encoding"],"prefix":"10.1007","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-0393-9244","authenticated-orcid":false,"given":"Hanfeng","family":"Chen","sequence":"first","affiliation":[]},{"given":"Shiqi","family":"Jiang","sequence":"additional","affiliation":[]},{"given":"Xuan","family":"Yu","sequence":"additional","affiliation":[]},{"given":"Hong","family":"Yin","sequence":"additional","affiliation":[]},{"given":"Xiping","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Yanpeng","family":"Hu","sequence":"additional","affiliation":[]},{"given":"Changbo","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Chenhui","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,4,16]]},"reference":[{"issue":"9","key":"986_CR1","doi-asserted-by":"publisher","first-page":"346","DOI":"10.3390\/ijgi7090346","volume":"7","author":"A Acedo","year":"2018","unstructured":"Acedo A, Painho M, Casteleyn S, Roche S (2018) Place and city: toward urban intelligence. ISPRS Int J Geo Inf 7(9):346","journal-title":"ISPRS Int J Geo Inf"},{"issue":"10","key":"986_CR2","doi-asserted-by":"publisher","first-page":"1647","DOI":"10.1109\/TIP.2005.851684","volume":"14","author":"HA Aly","year":"2005","unstructured":"Aly HA, Dubois E (2005) Image up-sampling using total-variation regularization with a new observation model. IEEE Trans Image Process 14(10):1647\u20131659","journal-title":"IEEE Trans Image Process"},{"key":"986_CR3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-56146-8","volume-title":"Visual analytics for data scientists","author":"N Andrienko","year":"2020","unstructured":"Andrienko N, Andrienko G, Fuchs G, Slingsby A, Turkay C, Wrobel S (2020) Visual analytics for data scientists. Springer, Berlin"},{"key":"986_CR4","doi-asserted-by":"crossref","unstructured":"Andrienko G, Andrienko N, Boldrini C, Caldarelli G, Cintia P, Cresci S, Facchini A, Giannotti F, Gionis A, Guidotti R et al (2020) (So) Big data and the transformation of the city. Int J Data Sci Anal 1\u201330","DOI":"10.1007\/s41060-020-00207-3"},{"key":"986_CR5","unstructured":"Andrienko G, Andrienko N, Drucker S, Fekete J-D, Fisher D, Idreos S, Kraska T, Li G, Ma K-L, Mackinlay J et al (2020) Big data visualization and analytics: future research challenges and emerging applications. In: BigVis 2020: big data visual exploration and analytics"},{"key":"986_CR6","doi-asserted-by":"crossref","unstructured":"Bertini E, Santucci G (2004) By chance is not enough: preserving relative density through nonuniform sampling. In: Proceedings of eighth international conference on information visualisation, 2004. IV 2004. IEEE, pp 622\u2013629","DOI":"10.1109\/IV.2004.1320207"},{"key":"986_CR7","unstructured":"Birren F (1969) A grammar of color, a basic treatise on the color system of Albert H. Munsell"},{"issue":"12","key":"986_CR8","doi-asserted-by":"publisher","first-page":"2306","DOI":"10.1109\/TVCG.2013.234","volume":"19","author":"MA Borkin","year":"2013","unstructured":"Borkin MA, Vo AA, Bylinskii Z, Isola P, Sunkavalli S, Oliva A, Pfister H (2013) What makes a visualization memorable? IEEE Trans Visual Comput Graph 19(12):2306\u20132315","journal-title":"IEEE Trans Visual Comput Graph"},{"issue":"2","key":"986_CR9","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1080\/00401706.1977.10489521","volume":"19","author":"L Breiman","year":"1977","unstructured":"Breiman L, Meisel W, Purcell E (1977) Variable kernel estimates of multivariate densities. Technometrics 19(2):135\u2013144","journal-title":"Technometrics"},{"issue":"4","key":"986_CR10","doi-asserted-by":"publisher","first-page":"662","DOI":"10.1111\/1467-8306.00310","volume":"92","author":"CA Brewer","year":"2002","unstructured":"Brewer CA, Pickle L (2002) Evaluation of methods for classifying epidemiological data on choropleth maps in series. Ann Assoc Am Geogr 92(4):662\u2013681","journal-title":"Ann Assoc Am Geogr"},{"issue":"1","key":"986_CR11","doi-asserted-by":"publisher","first-page":"729","DOI":"10.1109\/TVCG.2019.2934541","volume":"26","author":"X Chen","year":"2019","unstructured":"Chen X, Ge T, Zhang J, Chen B, Fu C-W, Deussen O, Wang Y (2019) A recursive subdivision technique for sampling multi-class scatterplots. IEEE Trans Vis Comput Graph 26(1):729\u2013738","journal-title":"IEEE Trans Vis Comput Graph"},{"key":"986_CR12","doi-asserted-by":"crossref","unstructured":"Chen J, Huang Q, Wang C, Li C (2023) Sensemap: urban performance visualization and analytics via semantic textual similarity. IEEE Trans Vis Comput Graph","DOI":"10.1109\/TVCG.2023.3333356"},{"key":"986_CR13","doi-asserted-by":"crossref","unstructured":"Chen J, Huang H, Ye H, Zhong P, Li C, Wang C (2024) Salientime: user-driven selection of salient time steps for large-scale geospatial data visualization. In: Proceedings of the 2024 CHI conference on human factors in computing systems","DOI":"10.1145\/3613904.3642944"},{"key":"986_CR14","doi-asserted-by":"publisher","first-page":"39","DOI":"10.14714\/CP80.1314","volume":"80","author":"M DeBoer","year":"2015","unstructured":"DeBoer M (2015) Understanding the heat map. Cartograph Perspect 80:39\u201343","journal-title":"Cartograph Perspect"},{"issue":"5","key":"986_CR15","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1109\/MCG.2019.2924636","volume":"39","author":"V Dibia","year":"2019","unstructured":"Dibia V, Demiralp \u00c7 (2019) Data2vis: automatic generation of data visualizations using sequence-to-sequence recurrent neural networks. IEEE Comput Graphics Appl 39(5):33\u201346","journal-title":"IEEE Comput Graphics Appl"},{"key":"986_CR16","doi-asserted-by":"crossref","unstructured":"Dix A, Ellis G (2002) By chance enhancing interaction with large data sets through statistical sampling. In: Proceedings of the working conference on advanced visual interfaces, pp 167\u2013176","DOI":"10.1145\/1556262.1556289"},{"key":"986_CR18","doi-asserted-by":"crossref","unstructured":"Ellis G, Dix A (2002) Density control through random sampling: an architectural perspective. In: Proceedings sixth international conference on information visualisation. IEEE, pp 82\u201390","DOI":"10.1109\/IV.2002.1028760"},{"issue":"6","key":"986_CR17","doi-asserted-by":"publisher","first-page":"1216","DOI":"10.1109\/TVCG.2007.70535","volume":"13","author":"G Ellis","year":"2007","unstructured":"Ellis G, Dix A (2007) A taxonomy of clutter reduction for information visualisation. IEEE Trans Vis Comput Graph 13(6):1216\u20131223","journal-title":"IEEE Trans Vis Comput Graph"},{"key":"986_CR19","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1016\/j.proeng.2017.02.357","volume":"181","author":"M Eremia","year":"2017","unstructured":"Eremia M, Toma L, Sanduleac M (2017) The smart city concept in the 21st century. Procedia Eng 181:12\u201319","journal-title":"Procedia Eng"},{"key":"986_CR20","unstructured":"Goodfellow I, Pouget-Abadie J, Mirza M, Xu B, Warde-Farley D, Ozair S, Courville A, Bengio Y (2014) Generative adversarial nets. Adv Neural Inf Process Syst 27"},{"key":"986_CR21","unstructured":"Heimerl F, Chang C-C, Sarikaya A, Gleicher M (2018) Visual designs for binned aggregation of multi-class scatterplots. Preprint arXiv:1810.02445"},{"key":"986_CR24","doi-asserted-by":"crossref","unstructured":"Hu K, Orghian D, Hidalgo C (2018) Dive: a mixed-initiative system supporting integrated data exploration workflows. In: Proceedings of the workshop on human-in-the-loop data analytics, pp 1\u20137","DOI":"10.1145\/3209900.3209910"},{"issue":"2","key":"986_CR22","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1145\/3377000.3377002","volume":"11","author":"Y Hu","year":"2019","unstructured":"Hu Y, Gao S, Lunga D, Li W, Newsam S, Bhaduri B (2019) GeoAI at ACM SIGSPATIAL: progress, challenges, and future directions. Sigspatial Spec 11(2):5\u201315","journal-title":"Sigspatial Spec"},{"key":"986_CR23","doi-asserted-by":"crossref","unstructured":"Hu K, Bakker MA, Li S, Kraska T, Hidalgo C (2019) Vizml: A machine learning approach to visualization recommendation. In: Proceedings of the 2019 CHI conference on human factors in computing systems, pp 1\u201312","DOI":"10.1145\/3290605.3300358"},{"key":"986_CR25","volume-title":"Data-driven security: analysis, visualization and dashboards","author":"J Jacobs","year":"2014","unstructured":"Jacobs J, Rudis B (2014) Data-driven security: analysis, visualization and dashboards. Wiley, New York"},{"issue":"3","key":"986_CR26","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1109\/MCG.2005.64","volume":"25","author":"DA Keim","year":"2005","unstructured":"Keim DA, Panse C, North SC (2005) Medial-axis-based cartograms. IEEE Comput Graph Appl 25(3):60\u201368","journal-title":"IEEE Comput Graph Appl"},{"issue":"3","key":"986_CR27","doi-asserted-by":"publisher","first-page":"1381","DOI":"10.1109\/TVCG.2017.2668409","volume":"24","author":"C Li","year":"2017","unstructured":"Li C, Baciu G, Han Y (2017) Streammap: smooth dynamic visualization of high-density streaming points. IEEE Trans Vis Comput Graph 24(3):1381\u20131393","journal-title":"IEEE Trans Vis Comput Graph"},{"key":"986_CR29","doi-asserted-by":"crossref","unstructured":"Li M, Choudhury F, Bao Z, Samet H, Sellis T (2018) Concavecubes: Supporting cluster-based geographical visualization in large data scale. In: Computer graphics forum, Wiley, vol 37, pp 217\u2013228","DOI":"10.1111\/cgf.13414"},{"issue":"1","key":"986_CR28","doi-asserted-by":"publisher","first-page":"1062","DOI":"10.1109\/TVCG.2021.3114762","volume":"28","author":"C Li","year":"2021","unstructured":"Li C, Baciu G, Wang Y, Chen J, Wang C (2021) Ddlvis: real-time visual query of spatiotemporal data distribution via density dictionary learning. IEEE Trans Vis Comput Graph 28(1):1062\u20131072","journal-title":"IEEE Trans Vis Comput Graph"},{"key":"986_CR30","doi-asserted-by":"crossref","unstructured":"Li H, Wang Y, Zhang S, Song Y, Qu H (2021) Kg4vis: a knowledge graph-based approach for visualization recommendation. IEEE Trans Vis Comput Graph","DOI":"10.1109\/TVCG.2021.3114863"},{"key":"986_CR31","doi-asserted-by":"crossref","unstructured":"Luo Y, Qin X, Tang N, Li G (2018) Deepeye: towards automatic data visualization. In: 2018 IEEE 34th international conference on data engineering (ICDE). IEEE, pp 101\u2013112","DOI":"10.1109\/ICDE.2018.00019"},{"issue":"9","key":"986_CR32","doi-asserted-by":"publisher","first-page":"3717","DOI":"10.1109\/TVCG.2020.2980227","volume":"27","author":"R Ma","year":"2020","unstructured":"Ma R, Mei H, Guan H, Huang W, Zhang F, Xin C, Dai W, Wen X, Chen W (2020) LADV: Deep learning assisted authoring of dashboard visualizations from images and sketches. IEEE Trans Vis Comput Graph 27(9):3717\u20133732","journal-title":"IEEE Trans Vis Comput Graph"},{"issue":"6","key":"986_CR33","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TVCG.2007.70594","volume":"13","author":"J Mackinlay","year":"2007","unstructured":"Mackinlay J, Hanrahan P, Stolte C (2007) Show me: automatic presentation for visual analysis. IEEE Trans Vis Comput Graph 13(6):1137\u20131144","journal-title":"IEEE Trans Vis Comput Graph"},{"issue":"9","key":"986_CR34","doi-asserted-by":"publisher","first-page":"1526","DOI":"10.1109\/TVCG.2013.65","volume":"19","author":"A Mayorga","year":"2013","unstructured":"Mayorga A, Gleicher M (2013) Splatterplots: overcoming overdraw in scatter plots. IEEE Trans Vis Comput Graph 19(9):1526\u20131538","journal-title":"IEEE Trans Vis Comput Graph"},{"issue":"4","key":"986_CR35","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1364\/JOSA.34.000234","volume":"34","author":"P Moon","year":"1944","unstructured":"Moon P, Spencer DE (1944) Aesthetic measure applied to color harmony. JOSA 34(4):234\u2013242","journal-title":"JOSA"},{"key":"986_CR36","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1016\/S0020-0255(02)00404-8","volume":"152","author":"DCL Ngo","year":"2003","unstructured":"Ngo DCL, Teo LS, Byrne JG (2003) Modelling interface aesthetics. Inf Sci 152:25\u201346","journal-title":"Inf Sci"},{"key":"986_CR37","doi-asserted-by":"crossref","unstructured":"N\u00f6llenburg M (2007) Geographic visualization. In: Human-centered visualization environments. Springer, Berlin, pp 257\u2013294","DOI":"10.1007\/978-3-540-71949-6_6"},{"key":"986_CR38","unstructured":"Owonibi PKM (2017) A review on visualization recommendation strategies. In: Proceedings of the 12th international joint conference on computer vision, imaging and computer graphics theory and applications (VISIGRAPP 2017)"},{"issue":"3","key":"986_CR39","doi-asserted-by":"publisher","first-page":"1065","DOI":"10.1214\/aoms\/1177704472","volume":"33","author":"E Parzen","year":"1962","unstructured":"Parzen E (1962) On estimation of a probability density function and mode. Ann Math Stat 33(3):1065\u20131076","journal-title":"Ann Math Stat"},{"issue":"1","key":"986_CR40","doi-asserted-by":"publisher","first-page":"171701","DOI":"10.1007\/s11704-021-0609-0","volume":"17","author":"Y Peng","year":"2023","unstructured":"Peng Y, Fan X, Chen R, Yu Z, Liu S, Chen Y, Zhao Y, Zhou F (2023) Visual abstraction of dynamic network via improved multi-class blue noise sampling. Front Comp Sci 17(1):171701","journal-title":"Front Comp Sci"},{"key":"986_CR41","doi-asserted-by":"crossref","unstructured":"Polisciuc E, Ma\u00e7\u00e3s C, Assun\u00e7\u00e3o F, Machado P (2016) Hexagonal gridded maps and information layers: a novel approach for the exploration and analysis of retail data. In: SIGGRAPH ASIA 2016 symposium on visualization, pp 1\u20138","DOI":"10.1145\/3002151.3002160"},{"key":"986_CR42","doi-asserted-by":"crossref","unstructured":"Qian X, Rossi RA, Du F, Kim S, Koh E, Malik S, Lee TY, Chan J (2020) Ml-based visualization recommendation: Learning to recommend visualizations from data. Preprint arXiv:2009.12316","DOI":"10.1145\/3447548.3467224"},{"issue":"1","key":"986_CR43","doi-asserted-by":"publisher","first-page":"75","DOI":"10.26599\/BDMA.2018.9020007","volume":"1","author":"X Qin","year":"2018","unstructured":"Qin X, Luo Y, Tang N, Li G (2018) Deepeye: an automatic big data visualization framework. Big Data Min Anal 1(1):75\u201382","journal-title":"Big Data Min Anal"},{"issue":"1","key":"986_CR44","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1007\/s00778-019-00588-3","volume":"29","author":"X Qin","year":"2020","unstructured":"Qin X, Luo Y, Tang N, Li G (2020) Making data visualization more efficient and effective: a survey. VLDB J 29(1):93\u2013117","journal-title":"VLDB J"},{"key":"986_CR45","first-page":"42","volume":"42","author":"B Rankin","year":"2010","unstructured":"Rankin B (2010) Cartography and the reality of boundaries. Perspecta 42:42\u201345","journal-title":"Perspecta"},{"key":"986_CR46","doi-asserted-by":"crossref","unstructured":"Santala S (2020) Fast interactive design of scatterplots for large data set visualisation. In: Extended abstracts of the 2020 CHI conference on human factors in computing systems, pp 1\u20136","DOI":"10.1145\/3334480.3381443"},{"key":"986_CR47","doi-asserted-by":"publisher","DOI":"10.1002\/9781118575574","volume-title":"Multivariate density estimation: theory, practice, and visualization","author":"DW Scott","year":"2015","unstructured":"Scott DW (2015) Multivariate density estimation: theory, practice, and visualization. Wiley, New York"},{"key":"986_CR48","doi-asserted-by":"crossref","unstructured":"Setlur V, Battersby S, Wong T (2021) Geosneakpique: visual autocompletion for geospatial queries. In: 2021 IEEE visualization conference (VIS). IEEE, pp 166\u2013170","DOI":"10.1109\/VIS49827.2021.9623324"},{"key":"986_CR50","unstructured":"Shen L, Shen E, Tai Z, Song Y, Wang J (2021) Taskvis: task-oriented visualization recommendation. In: Proc. EuroVis, vol 21"},{"issue":"4","key":"986_CR49","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1007\/s41019-022-00195-3","volume":"7","author":"L Shen","year":"2022","unstructured":"Shen L, Shen E, Tai Z, Xu Y, Dong J, Wang J (2022) Visual data analysis with task-based recommendations. Data Sci Eng 7(4):354\u2013369","journal-title":"Data Sci Eng"},{"key":"986_CR51","doi-asserted-by":"publisher","DOI":"10.1201\/9781315140919","volume-title":"Density estimation for statistics and data analysis","author":"BW Silverman","year":"2018","unstructured":"Silverman BW (2018) Density estimation for statistics and data analysis. Routledge, New York"},{"issue":"5","key":"986_CR52","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1109\/38.788803","volume":"19","author":"LA Treinish","year":"1999","unstructured":"Treinish LA (1999) Task-specific visualization design. IEEE Comput Graphics Appl 19(5):72\u201377","journal-title":"IEEE Comput Graphics Appl"},{"key":"986_CR53","unstructured":"Van Wijk JJ (2005) The value of visualization. In: VIS 05. IEEE visualization. IEEE, pp 79\u201386"},{"issue":"4","key":"986_CR54","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1145\/3092931.3092937","volume":"45","author":"M Vartak","year":"2017","unstructured":"Vartak M, Huang S, Siddiqui T, Madden S, Parameswaran A (2017) Towards visualization recommendation systems. ACM SIGMOD Rec 45(4):34\u201339","journal-title":"ACM SIGMOD Rec"},{"key":"986_CR55","unstructured":"Wang Q, Chen Z, Wang Y, Qu H (2020) Applying machine learning advances to data visualization: a survey on ml4vis. Preprint arXiv:2012.00467"},{"key":"986_CR56","doi-asserted-by":"publisher","DOI":"10.1002\/9781119283089","volume-title":"The big book of dashboards: visualizing your data using real-world business scenarios","author":"S Wexler","year":"2017","unstructured":"Wexler S, Shaffer J, Cotgreave A (2017) The big book of dashboards: visualizing your data using real-world business scenarios. Wiley"},{"issue":"1","key":"986_CR57","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1057\/ivs.2008.27","volume":"9","author":"G Wills","year":"2010","unstructured":"Wills G, Wilkinson L (2010) Autovis: automatic visualization. Inf Vis 9(1):47\u201369","journal-title":"Inf Vis"},{"issue":"1","key":"986_CR58","doi-asserted-by":"publisher","first-page":"649","DOI":"10.1109\/TVCG.2015.2467191","volume":"22","author":"K Wongsuphasawat","year":"2015","unstructured":"Wongsuphasawat K, Moritz D, Anand A, Mackinlay J, Howe B, Heer J (2015) Voyager: exploratory analysis via faceted browsing of visualization recommendations. IEEE Trans Visual Comput Graph 22(1):649\u2013658","journal-title":"IEEE Trans Visual Comput Graph"},{"key":"986_CR59","unstructured":"Wu A, Wang Y, Shu X, Moritz D, Cui W, Zhang H, Zhang D, Qu H (2021) Survey on artificial intelligence approaches for visualization data. Preprint arXiv:2102.01330"},{"key":"986_CR60","doi-asserted-by":"crossref","unstructured":"Wu A, Wang Y, Zhou M, He X, Zhang H, Qu H, Zhang D (2021) Multivision: designing analytical dashboards with deep learning based recommendation. IEEE Trans Vis Comput Graph","DOI":"10.1109\/TVCG.2021.3114826"},{"key":"986_CR61","doi-asserted-by":"publisher","first-page":"1777","DOI":"10.1360\/SSI-2021-0062","volume":"51","author":"J Xia","year":"2021","unstructured":"Xia J, Li J, Chen S (2021) A survey on interdisciplinary research of visualization and artificial intelligence. Sci Sin (Inf) 51:1777\u20131801","journal-title":"Sci Sin (Inf)"},{"issue":"3","key":"986_CR62","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1080\/10106049.2017.1404140","volume":"34","author":"P Zhao","year":"2019","unstructured":"Zhao P, Liu X, Shen J, Chen M (2019) A network distance and graph-partitioning-based clustering method for improving the accuracy of urban hotspot detection. Geocarto Int 34(3):293\u2013315","journal-title":"Geocarto Int"},{"key":"986_CR63","doi-asserted-by":"crossref","unstructured":"Zhou Z, Zhang X, Yang Z, Chen Y, Liu Y, Wen J, Chen B, Zhao Y, Chen W (2020) Visual abstraction of geographical point data with spatial autocorrelations. In: 2020 IEEE conference on visual analytics science and technology (VAST). IEEE, pp 60\u201371","DOI":"10.1109\/VAST50239.2020.00011"},{"key":"986_CR64","doi-asserted-by":"crossref","unstructured":"Zou T, Li W, Liu P, Su X, Huang H, Han Y, Guo X (2018) An overview of geospatial information visualization. In: 2018 IEEE international conference on progress in informatics and computing (PIC). IEEE, pp 250\u2013254","DOI":"10.1109\/PIC.2018.8706332"}],"container-title":["Journal of Visualization"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12650-024-00986-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12650-024-00986-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12650-024-00986-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T14:24:20Z","timestamp":1719843860000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12650-024-00986-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4,16]]},"references-count":64,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2024,8]]}},"alternative-id":["986"],"URL":"https:\/\/doi.org\/10.1007\/s12650-024-00986-y","relation":{},"ISSN":["1343-8875","1875-8975"],"issn-type":[{"value":"1343-8875","type":"print"},{"value":"1875-8975","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,4,16]]},"assertion":[{"value":"30 November 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 February 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 February 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 April 2024","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}