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Enabling collaborative GeoVisual analytics: Systems, techniques, and research challenges
Author(s) -
GarcíaChapeton Gustavo Adolfo,
Ostermann Frank Olaf,
By Rolf A.,
Kraak MennoJan
Publication year - 2018
Publication title -
transactions in gis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.721
H-Index - 63
eISSN - 1467-9671
pISSN - 1361-1682
DOI - 10.1111/tgis.12344
Subject(s) - multidisciplinary approach , analytics , identification (biology) , computer science , visual analytics , data science , collaboration , domain (mathematical analysis) , work (physics) , knowledge management , visualization , engineering , data mining , mechanical engineering , mathematical analysis , social science , botany , mathematics , sociology , biology
Collaboration across disciplines is recognized as one of the great challenges for research in visual analysis of geographic information (GeoVisual Analytics, GVA). Considering the increasing availability of geodata and the complexity of analytical problems, the need to advance the support for collaborative work is becoming more pressing and prominent. This article contributes to this objective by reviewing the state‐of‐the‐art of the support for collaborative work in GVA systems and by identifying research challenges and proposing strategies to address them. We conducted a systematic review, resulting in the identification of 13 collaborative systems, 6 distinct collaborative techniques, and 3 research challenges. We conclude that GVA is moving toward more effective support of multidisciplinary and cross‐domain collaborative analysis. However, to materialize this potential, research is needed to improve the support for hybrid collaborative scenarios, cross‐device collaboration, and support for time‐critical and long‐term analysis.