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Visual analytics for large networks: theory, art and practice

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References

  1. Barabási, Albert-László. (2013) Network Science. Phil. Trans. R. Soc. A.3712012037520120375. Google ScholarGoogle ScholarCross RefCross Ref
  2. Bailey, B. J., Lilja, A., Strong, C., Moline, K., Kavallaris, M., Hughes, R. T., & McGhee, J. (2019, November). Multi-User Immersive Virtual Reality Prototype for Collaborative Visualization of Microscopy Image Data. In The 17th International Conference on Virtual-Reality Continuum and its Applications in Industry (pp. 1--2).Google ScholarGoogle Scholar
  3. Branchaud, D., Muskovic, W., Kavallaris, M., Filonik, D., & Bednarz, T. (2018). Visual microscope for massive genomics datasets, expanded perception and interaction. In ACM SIGGRAPH 2018 Posters (pp. 1--2).Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Cordeil, M., Dwyer, T, Klein, K., Laha, B., Marriott, K., & Thomas, B. H. (2016). Immersive collaborative analysis of network connectivity: CAVE-style or head-mounted display?. IEEE transactions on visualization and computer graphics, 23(1), 441--450.Google ScholarGoogle Scholar
  5. CSIRO's Data61, StellarGraph, https://www.stellargraph.io/Google ScholarGoogle Scholar
  6. Di Biase, D. (1990). Visualization in the Earth Sciences. Earth and Mineral Sciences, Bulletin of the College of Earth and Mineral Sciences, Pennsylvania State University, 59, 13--18.Google ScholarGoogle Scholar
  7. Domo, Inc., Data Never Sleeps 8.0, https://www.domo.com/learn/data-never-sleeps-8.Google ScholarGoogle Scholar
  8. Drogemuller, A., Cunningham, A., Walsh, J., Cordeil, M., Ross, W., & Thomas, B. (2018, October). Evaluating navigation techniques for 3d graph visualizations in virtual reality. In 2018 International Symposium on Big Data Visual and Immersive Analytics (BDVA) (pp. 1--10). IEEE.Google ScholarGoogle ScholarCross RefCross Ref
  9. Dutot, A., Guinand, F., Olivier, D., & Pigné, Y. (2007, October). Graphstream: A tool for bridging the gap between complex systems and dynamic graphs. In Emergent Properties in Natural and Artificial Complex Systems. Satellite Conference within the 4th European Conference on Complex Systems (ECCS '2007).Google ScholarGoogle Scholar
  10. Filonik, D., Rittenbruch, M., & Foth, M. (2016, March). DataChopin: A collaborative interface for data visualisation and composition on large interactive screens. In conference; 2016-03-18.Google ScholarGoogle Scholar
  11. Filonik, D. (2017). Participatory data analytics: Designing visualisation and composition interfaces for collaborative sensemaking on large interactive screens (Doctoral dissertation, Queensland University of Technology).Google ScholarGoogle Scholar
  12. Filonik, D., & Bednarz, T. (2018). Visual analytics of big networks: novel approaches for exploring complex networks in big data. In SIGGRAPH Asia 2018 Courses (pp. 1--96).Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Filonik, D., Feng, T, Sun, K., Nock, R., Collins, A., & Bednarz, T. (2019). Non-Euclidean Embeddings for Graph Analytics and Visualisation. In SIGGRAPH Asia 2019 Posters (pp. 1--2).Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Hlawatsch, M., Burch, M., & Weiskopf, D. (2014). Visual adjacency lists for dynamic graphs. IEEE transactions on visualization and computer graphics, 20(11), 1590--1603.Google ScholarGoogle ScholarCross RefCross Ref
  15. Holten, D. and Van Wijk, J.J. (2009), Force-Directed Edge Bundling for Graph Visualization. Computer Graphics Forum, 28: 983--990. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Hughes, R. T., Strong, C., & McGhee, J. (2019). Vox-Cells: Voxel-based visualization of volume data for enhanced understanding and exploration in Virtual Reality (VR). In ACM SIGGRAPH 2019 Posters (pp. 1--2).Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Hughes, T., Hyun, Y. & Liberies, D.A. Visualising very large phylogenetic trees in three dimensional hyperbolic space. BMC Bioinformatics 5, 48 (2004). Google ScholarGoogle ScholarCross RefCross Ref
  18. Jayawickrama, Thamindu Dilshan. (2021). https://towardsdatascience.com/community-detection-algorithms-9bd8951e7daeGoogle ScholarGoogle Scholar
  19. Kister, U., Klamka, K., Tominski, C., & Dachselt, R. (2017, June). GraSp: Combining Spatially-aware Mobile Devices and a Display Wall for Graph Visualization and Interaction. In Computer Graphics Forum (Vol. 36, No. 3, pp. 503--514).Google ScholarGoogle Scholar
  20. Keim, Daniel & Kohlhammer, Jörn & Ellis, Geoffrey & Mansmann, Florian. (2010). Mastering The Information Age - Solving Problems with Visual Analytics.Google ScholarGoogle Scholar
  21. Kotlarek, J., Kwon, O. H., Ma, K. L, Eades, P., Kerren, A., Klein, K., & Schreiber, F. (2020, June). A Study of Mental Maps in Immersive Network Visualization. In 2020 IEEE Pacific Visualization Symposium (PacificVis) (pp. 1--10). IEEE.Google ScholarGoogle ScholarCross RefCross Ref
  22. Kumar, A., Kushwah, S., & Manjhvar, A. (2016). A Review on Link Prediction in Social Network. International Journal of Grid and Distributed Computing, 9, 43--50.Google ScholarGoogle ScholarCross RefCross Ref
  23. Kwon, O., Muelder, C., Lee, K., & Ma, K. (2016). A Study of Layout, Rendering, and Interaction Methods for Immersive Graph Visualization. IEEE Transactions on Visualization and Computer Graphics, 22, 1802--1815.Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Lamping, John & Rao, Ramana. (1996). Visualizing large trees using the hyperbolic browser. 388--389. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Liu, Mark. (2016) http://www.drmarkliu.com/noneuclideanGoogle ScholarGoogle Scholar
  26. Lubin, Noa. (2019). https://towardsdatascience.com/node2vec-graph-embedding-method-f306ac87004eGoogle ScholarGoogle Scholar
  27. Milgram, P., & Kishino, F. (1994). A taxonomy of mixed reality visual displays. IEICE TRANSACTIONS on Information and Systems, 77(12), 1321--1329.Google ScholarGoogle Scholar
  28. Petri G., Expert P., Turkheimer F., Carhart-Harris R., Nutt D., Hellyer P. J. and Vaccarino F. 2014. Homological scaffolds of brain functional networks. J. R. Soc. Interface.112014087320140873. Google ScholarGoogle ScholarCross RefCross Ref
  29. Shneiderman, B. (1996). The eyes have it: A task by data type taxonomy for information visualizations. Visual Languages, 1996. Proceedings., IEEE Symposium on (p./pp. 336--343),.Google ScholarGoogle ScholarCross RefCross Ref
  30. Shin, Minjeong, Alasdair Tran, Siqi Wu, Alexander Mathews, Rong Wang, Georgiana Lyall, and Lexing Xie. "AttentionFlow: Visualising Influence in Networks of Time Series." In Proceedings of the 14th ACM International Conference on Web Search and Data Mining 2021.Google ScholarGoogle Scholar
  31. Silver, Nate. (2021). FiveThirtyEight, https://www.fivethirtyeight.com.Google ScholarGoogle Scholar
  32. Stevens, S. S. (1946). On the theory of scales of measurement. Science, 103, 677--680.Google ScholarGoogle ScholarCross RefCross Ref
  33. Tran, Alasdair, Alexander Mathews, Cheng Soon Ong, and Lexing Xie. "Radflow: A recurrent, aggregated, and decomposable model for networks of time series." The Web Conference (2021).Google ScholarGoogle Scholar
  34. Veeramachaneni, K., Arnaldo, I., Korrapati, V., Bassias, C., & Li, K. (2016, April). AI^ 2: training a big data machine to defend. In 2016 IEEE 2nd International Conference on Big Data Security on Cloud (BigDataSecurity), IEEE International Conference on High Performance and Smart Computing (HPSC), and IEEE International Conference on Intelligent Data and Security (IDS) (pp. 49--54). IEEE.Google ScholarGoogle Scholar
  35. Ware, C. (2012). Information Visualization: Perception for Design. Amsterdam: Morgan Kaufmann. ISBN: 978-0-12-381464-7Google ScholarGoogle ScholarDigital LibraryDigital Library

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    cover image ACM Conferences
    SIGGRAPH '21: ACM SIGGRAPH 2021 Courses
    August 2021
    2220 pages
    ISBN:9781450383615
    DOI:10.1145/3450508

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