{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T19:32:14Z","timestamp":1772652734738,"version":"3.50.1"},"reference-count":9,"publisher":"Association for Computing Machinery (ACM)","issue":"Spring","license":[{"start":{"date-parts":[[2015,4,30]],"date-time":"2015-04-30T00:00:00Z","timestamp":1430352000000},"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":["SIGWEB Newsl."],"published-print":{"date-parts":[[2015,4,30]]},"abstract":"<jats:p>The research field of spatial scientometrics is dedicated to measuring and analyzing science with spatial components (e.g., location, place, mapping). It involves the study of spatial patterns, impacts and trends of scientific activities (e.g., co-publication, citation, academic mobility) based on bibliographic databases. Because of the dynamic nature of this field, researchers from interdisciplinary\/multidisciplinary domains constantly contribute qualitative, quantitative and computational approaches and technologies into scientometric analysis. This article aims to giving a brief overview about this field by analyzing the publications in (spatial) scientometrics collected from the Scopus database and introduces recent frontier researches which integrate advanced spatial analysis and geovisualization with Semantic Web technologies.<\/jats:p>","DOI":"10.1145\/2749279.2749284","type":"journal-article","created":{"date-parts":[[2015,5,1]],"date-time":"2015-05-01T17:49:08Z","timestamp":1430502548000},"page":"1-9","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["\"Towards a frontier of spatial scientometric studies\" by SONG Gao with Martin Vesely as coordinator"],"prefix":"10.1145","volume":"2015","author":[{"given":"Song","family":"Gao","sequence":"first","affiliation":[{"name":"University of California, Santa Barbara"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2015,4,30]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Atlas of science: Visualizing what we know","author":"B\u00f6rner K.","unstructured":"B\u00f6rner , K. 2010. 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A linked-data-driven web portal for learning analytics: Data enrichment, interactive visualization, and knowledge discovery. In Proceedings of Learning Analytics and Knowledge Workshops 2014, Indianapolis, IN, USA. 1--6."},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.5555\/2590208.2590209"},{"key":"e_1_2_1_9_1","volume-title":"Proceedings of the 7th International Conference on Geographic Information Science","volume":"7478","author":"Kessler C.","unstructured":"Kessler , C. , Janowicz , K. , and Kauppinen , T . 2012. spatial@linkedscience - exploring the research field of giscience with linked data . In Proceedings of the 7th International Conference on Geographic Information Science , Columbus, OH, USA, N. Xiao, M. P. Kwan, M. F. Goodchild, and S. Shekhar, Eds. LNCS , vol. 7478 . Springer, Heidelberg, 102--115. Kessler, C., Janowicz, K., and Kauppinen, T. 2012. spatial@linkedscience - exploring the research field of giscience with linked data. 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