Gaining overview with transient focus+context maps

References

• Baudisch, P., & Rosenholtz, R. (2003). Halo: a technique for visualizing off-screen objects. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI '03 (pp. 481–488). Association for Computing Machinery.
   Google Scholar
• Bostock, M. (2020). D3 data-driven documents.
   Google Scholar
• Brodkorb, F., Kuijper, A., Andrienko, G., Andrienko, N., & Von Landesberger, T. (2016). Overview with details for exploring geo-located graphs on maps. Information Visualization, 15(3), 214–237. https://doi.org/https://doi.org/10.1177/1473871615597077
   Google Scholar
• Butkiewicz, T., Dou, W., Wartell, Z., Ribarsky, W., & Chang, R. (2008). Multi-focused geospatial analysis using probes. IEEE Transactions on Visualization and Computer Graphics, 14(6), 1165–1172. https://doi.org/https://doi.org/10.1109/TVCG.2008.149
   Google Scholar
• Carpendale, M. S. T., Cowperthwaite, D. J., & Fracchia, F. D. (1997). Making distortions comprehensible. In Proceedings of the 1997 IEEE Symposium on Visual Languages (pp. 36–45). IEEE Institute of Electrical and Electronic Engineers.
   Google Scholar
• Carpendale, S., Light, J., & Pattison, E. (2004). Achieving higher magnification in context. In Proceedings of the 17th Annual ACM Symposium on UIST (pp. 71–80). Association for Computing Machinery.
   Google Scholar
• Ceneda, D., Gschwandtner, T., & Miksch, S. (2019). A review of guidance approaches in visual data analysis: a multifocal perspective. Computer Graphics Forum, 38(3), 861–879. https://doi.org/https://doi.org/10.1111/cgf.2019.38.issue-3
   Google Scholar
• Cockburn, A., Karlson, A., & Bederson, B. B. (2008). A review of overview+ detail, zooming, and focus+ context interfaces. ACM Computing Surveys (CSUR), 41(1), 1–31. https://doi.org/https://doi.org/10.1145/1456650.1456652
   Google Scholar
• Cox, D. A., Chugh, J. S., Gutwin, C., & Greenberg, S. (1998). The usability of transparent overview layers. In CHI 98 Conference Summary on Human Factors in Computing Systems (pp. 301–302). Association for Computing Machinery.
   Google Scholar
• Elmqvist, N., Henry, N., Riche, Y., & Fekete, J.-D. (2008). Melange: space folding for multi-focus interaction. In Proceedings of the SIGCHI CHI (pp. 1333–1342). Association for Computing Machinery.
   Google Scholar
• Furnas, G. W. (2006). A fisheye follow-up: further reflections on focus+ context. In Proceedings of the SIGCHI CHI (pp. 999–1008). Association for Computing Machinery.
   Google Scholar
• Ghani, S., Riche, N. H., & Elmqvist, N. (2011). Dynamic insets for context-aware graph navigation. Computer Graphics Forum, 30(3), 861–870. https://doi.org/https://doi.org/10.1111/cgf.2011.30.issue-3
   Google Scholar
• Gustafson, S., Baudisch, P., Gutwin, C., & Irani, P. (2008). Wedge: clutter-free visualization of off-screen locations. In Proceedings of the SIGCHI CHI (pp. 787–796). Association for Computing Machinery.
   Google Scholar
• Hadlak, S., Schulz, H., & Schumann, H. (2011). In situ exploration of large dynamic networks. IEEE Transactions on Visualization and Computer Graphics, 17(12), 2334–2343. https://doi.org/https://doi.org/10.1109/TVCG.2011.213
   Google Scholar
• Hauser, H. (2006). Generalizing focus+ context visualization. In Scientific Visualization: The Visual Extraction of Knowledge from Data (pp. 305–327). Springer.
   Google Scholar
• Horak, T., Mathisen, A., Klokmose, C. N., Dachselt, R., & Elmqvist, N. (2019). Vistribute: distributing interactive visualizations in dynamic multi-device setups. In Proceedings of the CHI (pp. 1–13). Association for Computing Machinery.
   Google Scholar
• Hornbæk, K., & Hertzum, M. (2011). The notion of overview in information visualization. International Journal of Human-Computer Studies, 69(7-8), 509–525. https://doi.org/https://doi.org/10.1016/j.ijhcs.2011.02.007
   Google Scholar
• Jäckle, D., Stoffel, F., Kwon, B. C., Sacha, D., Stoffel, A., & Keim, D. A. (2015). Ambient grids: maintain context-awareness via aggregated off-screen visualization. In Eurographics Conference on Visualization (EuroVis) 2015 (pp. 55–59). The Eurographics Association.
   Google Scholar
• Jakobsen, M. R., & Hornbæk, K. (2007). Transient visualizations. In Proceedings of the 19th OZCHI '07 (pp. 69–76). Association for Computing Machinery.
   Google Scholar
• Jakobsen, M. R., & Hornbæk, K. (2012). Transient or permanent fisheye views: a comparative evaluation of source code interfaces. Information Visualization, 11(2), 151–167. https://doi.org/https://doi.org/10.1177/1473871611405643
   Google Scholar
• Javed, W., Ghani, S., & Elmqvist, N. (2012). Polyzoom: multiscale and multifocus exploration in 2d visual spaces. In Proceedings of the SIGCHI CHI (pp. 287–296). Association for Computing Machinery.
   Google Scholar
• Jul, S., & Furnas, G. W. (1998). Critical zones in desert fog: aids to multiscale navigation. In Proceedings of the 11th Annual ACM Symposium on UIST (pp. 97–106). Association for Computing Machinery.
   Google Scholar
• Kerpedjiev, P., Abdennur, N., Lekschas, F., McCallum, C., Dinkla, K., Strobelt, H., Luber, J. M., Ouellette, S. B., Azhir, A., Kumar, N., Hwang, J., Lee, S., Alver, B. H., Pfister, H., Mirny, L. A., Park, P. J., & Gehlenborg, N. (2018). Higlass: web-based visual exploration and analysis of genome interaction maps. Genome Biology, 19(1), 1–12. https://doi.org/https://doi.org/10.1186/s13059-018-1486-1
   Google Scholar
• Lee, C., Kim, Y., Jin, S., Kim, D., Maciejewski, R., Ebert, D., & Ko, S. (2020). A visual analytics system for exploring, monitoring, and forecasting road traffic congestion. IEEE Transactions on Visualization and Computer Graphics, 26(11), 3133–3146. https://doi.org/https://doi.org/10.1109/TVCG.2945
   Google Scholar
• Lekschas, F., Bach, B., Kerpedjiev, P., Gehlenborg, N., & Pfister, H. (2018). Hipiler: visual exploration of large genome interaction matrices with interactive small multiples. IEEE Transactions on Visualization and Computer Graphics, 24(1), 522–531. https://doi.org/https://doi.org/10.1109/TVCG.2017.2745978
   Google Scholar
• Lekschas, F., Behrisch, M., Bach, B., Kerpedjiev, P., Gehlenborg, N., & Pfister, H. (2020). Pattern-driven navigation in 2d multiscale visualizations with scalable insets. IEEE Transactions on Visualization and Computer Graphics, 26(1), 611–621. https://doi.org/https://doi.org/10.1109/TVCG.2019.2934555
   Google Scholar
• Lieberman, H. (1994). Powers of ten thousand: navigating in large information spaces. In Proceedings of the 7th Annual ACM Symposium on UIST (pp. 15–16). Association for Computing Machinery.
   Google Scholar
• Lienert, C., Weingartner, R., & Hurni, L. (2009). Real-time visualization in operational hydrology through web-based cartography. Cartography and Geographic Information Science, 36(1), 45–58. https://doi.org/https://doi.org/10.1559/152304009787340188
   Google Scholar
• MacEachren, A. M., Gahegan, M., Pike, W., Brewer, I., Cai, G., Lengerich, E., & Hardistry, F. (2004). Geovisualization for knowledge construction and decision support. IEEE Computer Graphics and Applications, 24(1), 13–17. https://doi.org/https://doi.org/10.1109/MCG.2004.1255801
   Google Scholar
• Marai, G. E. (2015). Visual scaffolding in integrated spatial and nonspatial analysis. In: E. Bertini and J. C. Roberts (Eds.), EuroVis Workshop on Visual Analytics (EuroVA) (pp. 13–15). The Eurographics Association.
   Google Scholar
• Miau, D., & Feiner, S. (2018). Spacetokens: interactive map widgets for location-centric interactions. In Proceedings of the 2018 CHI (pp. 1–12). Association for Computing Machinery.
   Google Scholar
• Mittelstaedt, S., Spretke, D., Sacha, D., Keim, D. A., Heyder, B., & Kopp, J. (2013). Visual analytics for critical infrastructures. In: International ETG-Congress 2013; Symposium 1: Security in Critical Infrastructures Today (pp. 1–8). VDE Verlag.
   Google Scholar
• Moscovich, T., Chevalier, F., Henry, N., Pietriga, E., & Fekete, J.-D. (2009). Topology-aware navigation in large networks. In Proceedings of the SIGCHI CHI (pp. 2319–2328). Association for Computing Machinery.
   Google Scholar
• Pietriga, E., & Appert, C. (2008). Sigma lenses: focus-context transitions combining space, time and translucence. In Proceedings of the SIGCHI CHI (pp. 1343–1352). Association for Computing Machinery.
   Google Scholar
• Pindat, C., Pietriga, E., Chapuis, O., & Puech, C. (2012). Jellylens: content-aware adaptive lenses. In Proceedings of the 25th annual ACM symposium on UIST (pp. 261–270). Association for Computing Machinery.
   Google Scholar
• Plumlee, M., & Ware, C. (2003). Integrating multiple 3d views through frame-of-reference interaction. In Proceedings International Conference on CMV 2003 (pp. 34–43). IEEE Institute of Electrical and Electronic Engineers.
   Google Scholar
• Plumlee, M. D., & Ware, C. (2006). Zooming versus multiple window interfaces: cognitive costs of visual comparisons. ACM TOCHI, 13(2), 179–209. https://doi.org/https://doi.org/10.1145/1165734.1165736
   Google Scholar
• Poco, J., Dasgupta, A., Wei, Y., Hargrove, W., Schwalm, C., Cook, R., Bertini, E., & Silva, C. (2014). Similarityexplorer: a visual inter-comparison tool for multifaceted climate data. Computer Graphics Forum, 33(3), 341–350. https://doi.org/https://doi.org/10.1111/cgf.12390
   Google Scholar
• Roberts, J. C., Al-maneea, H., Butcher, P. W. S., Lew, R., Rees, G., Sharma, N., & Frankenberg-Garcia, A. (2019). Multiple views: different meanings and collocated words. Computer Graphics Forum, 38(3), 79–93. https://doi.org/https://doi.org/10.1111/cgf.2019.38.issue-3
   Google Scholar
• Saidi, H., Serrano, M., & Dubois, E. (2016). Investigating the effects of splitting detailed views in overview+detail interfaces. In Proceedings of the 18th International Conference on MobileHCI (pp. 180–184). Association for Computing Machinery.
   Google Scholar
• Schwanbeck, J., Kan, C., Bühlmann, A., Etter, S., Kummer, D., Morf, S., & von Wattenwyl, N. (2018). Hydrometrische netze – einzugsgebiete und datenreihen. In Daten- und Analyseplattform. Hydrologischer Atlas der Schweiz.
   Google Scholar
• Tominski, C. (2016). Comparing: reducing costs of visual comparison. In Proceedings of the Eurographics / IEEE VGTC Conference on Visualization: Short Papers (pp. 137–141). Eurographics Association.
   Google Scholar
• Valsecchi, F., Abrate, M., Bacciu, C., Tesconi, M., & Marchetti, A. (2015). Linked data maps: providing a visual entry point for the exploration of datasets. IESD@ ISWC.
   Google Scholar
• Wang Baldonado, M. Q., Woodruff, A., & Kuchinsky, A. (2000). Guidelines for using multiple views in information visualization. In Proceedings of the AVI (pp. 110–119). Association for Computing Machinery.
   Google Scholar
• Ware, C., & Lewis, M. (1995). The dragmag image magnifier. In Conference Companion on Human Factors in Computing Systems (pp. 407–408). Association for Computing Machinery.
   Google Scholar
• Zellweger, P. T., Mackinlay, J. D., Good, L., Stefik, M., & Baudisch, P. (2003). City lights: contextual views in minimal space. In CHI '03 Extended Abstracts on Human Factors in Computing Systems (pp. 838–839). Association for Computing Machinery.
   Google Scholar
• Zhao, J., Wigdor, D., & Balakrishnan, R. (2013). Trailmap: facilitating information seeking in a multi-scale digital map via implicit bookmarking. In Proceedings of the SIGCHI CHI (pp. 3009–3018). Association for Computing Machinery.
   Google Scholar