Visual analysis of time-series similarities for anomaly detection in sensor networks

Computer Graphics Forum

Volumn 33, Issue 3, 2014, Pages 401-410

  Steiger, Martin ^a   Bernard, Jürgen ^a   Mittelstädt, Sebastian ^b   Lücke Tieke, Hendrik ^a   Keim, Daniel ^b   May, Thorsten ^a   Kohlhammer, Jörn ^a  

^a FRAUNHOFER IGD   (Germany)

^b UNIVERSITY OF KONSTANZ   (Germany)

Author keywords

C.2.3 Computer Communication Networks : Network Operations Network monitoring; Categories and Subject Descriptors (according to ACM CCS):; H.5.2 Information Interfaces and Presentation : User Interfaces User centered design; I.3.6 Computer Graphics : Methodology and Techniques Interaction techniques

Indexed keywords

COMPUTER GRAPHICS; INFORMATION SYSTEMS; PATIENT MONITORING; SENSOR NETWORKS; SOFTWARE DESIGN; TIME SERIES; USER INTERFACES;

ANOMALY DETECTION; DESCRIPTORS; H.5.2 [INFORMATION INTERFACES AND PRESENTATION]: USER INTERFACES; I.3.6 [COMPUTER GRAPHICS]: METHODOLOGY AND TECHNIQUES - INTERACTION TECHNIQUES; INFORMATION VISUALIZATION; INTERACTION TECHNIQUES; NETWORK OPERATIONS; TOPOLOGICAL NETWORKS;

TIME SERIES ANALYSIS;

EID: 84904414173     PISSN: 01677055     EISSN: 14678659     Source Type: Journal    
DOI: 10.1111/cgf.12396     Document Type: Article

References (37)

1. Andrienko G., Andrienko N., Demsar U., Dransch D., Dykes J., Fabrikant S.I., Jern M., Kraak M.-J., Schumann H., Tominski C.,: Space, Time and Visual Analytics. Int. J. Geogr. Inf. Sci. 24, 10 (Oct. 2010), 1577-1600. doi: 10.1080/13658816.2010.508043. 3
2. Aigner W., Miksch S., Schumann H., Tominski C.,: Visualization of Time-Oriented Data. Springer, London, UK, 2011. doi: 10.1007/978-0-85729-079-3. 3
3. Bögl M., Aigner W., Filzmoser P., Lammarsch T., Miksch S., Rind A.,: Visual Analytics for Model Selection in Time Series Analysis. IEEE Trans. Vis. Comput. Graph. 19, 12 (2013), 2237-2246. 3
4. Berndt D.J., Clifford J.,: Using Dynamic Time Warping to Find Patterns in Time Series. In KDD workshop (1994), vol. 10/16, Seattle, WA, pp. 359-370. 4
5. Brandes U., Pich C.,: An Experimental Study on Distance-Based Graph Drawing. In Graph Drawing, vol. 5417 of Lecture Notes in Computer Science. Springer, 2009, pp. 218-229. doi: 10.1007/978-3-642-00219-9-21. 3
6. Bernard J., Ruppert T., Goroll O., May T., Kohlhammer J.,: Visual-Interactive Preprocessing of Time Series Data. In SIGRAD (2012), pp. 39-48. 3
7. Bernard J., Ruppert T., Scherer M., Kohlhammer J., Schreck T.,: Content-based Layouts for Exploratory Metadata Search in Scientific Research Data. In Proc. of the Joint Conference on Digital Libraries (2012), JCDL, ACM, pp. 139-148. doi: 10.1145/2232817.2232844. 3
8. Bertini E., Tatu A., Keim D.A.,: Quality Metrics in High-Dimensional Data Visualization: An Overview and Systematization. IEEE Symposium on Information Visualization (InfoVis) 17, 12 (Dec. 2011), pages 2203-2212. 3
9. Bernard J., von Landesberger T., Bremm S., Schreck T.,: Micro-Macro Views for Visual Trajectory Cluster Analysis. In IEEE Symposium on Visualization (2009). 6
10. Bremm S., von Landesberger T., Bernard J., Schreck T.,: Assisted descriptor selection based on visual comparative data analysis. In Computer Graphics Forum (2011), vol. 30/3, Wiley Online Library, pp. 891-900. 6
11. Bernard J., Wilhelm N., Krüger B., May T., Schreck T., Kohlhammer J.,: MotionExplorer: Exploratory Search in Human Motion Capture Data Based on Hierarchical Aggregation. IEEE Transactions on Visualization and Computer Graphics 19, 12 (2013), 2257-2266. 4
12. Bernard J., Wilhelm N., Scherer M., May T., Schreck T.,: TimeSeriesPaths: Projection-Based Explorative Analysis of Multivarate Time Series Data. Journal of WSCG 20, 2 (2012), 97-106. 3
13. Collins C., Penn G., Carpendale S.,: Bubble sets: Revealing set relations with isocontours over existing visualizations. Visualization and Computer Graphics, IEEE Transactions on 15, 6 (2009), 1009-1016. 9
14. Ding H., Trajcevski G., Scheuermann P., Wang X., Keogh E.,: Querying and Mining of Time Series Data: Experimental Comparison of Representations and Distance Measures. Proc. VLDB Endow. 1, 2 (Aug. 2008), 1542-1552. 3
15. Fu T.-C.,: A Review on Time Series Data Mining. Eng. Appl. Artif. Intell. 24, 1 (Feb. 2011), 164-181. doi: 10.1016/j.engappai.2010.09.007. 3
16. Hinton G.E., Roweis S.T.,: Stochastic neighbor embedding. In Advances in neural information processing systems (2002), pp. 833-840. 3
17. Hadlak S., Schumann H., Cap C.H., Wollenberg T.,: Supporting the Visual Analysis of Dynamic Networks by Clustering associated Temporal Attributes. Visualization and Computer Graphics, IEEE Transactions on 19, 12 (2013), 2267-2276. doi: 10.1109/TVCG.2013.198. 3, 4
18. Jain A.K., Dubes R.C.,: Algorithms for clustering data. Prentice-Hall, Inc., Upper Saddle River, NJ, USA, 1988. 5
19. Joia P., Paulovich F.V., Coimbra D., Cuminato J.A., Nonato L.G.,: Local affine multidimensional projection. IEEE Transactions on Visualization and Computer Graphics 17, 12 (2011), 2563-2571. 3, 4
20. Janetzko H., Stoffel F., Mittelstädt S., Keim D.A.,: Anomaly Detection for Visual Analytics of Power Consumption Data. Computer & Graphics 38 (2014), 27-37. 3
21. Keim D.,: Designing pixel-oriented visualization techniques: Theory and applications. IEEE Transactions on Visualization and Computer Graphics 6, 1 (2000). 6
22. Kruskal J.,: Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika 29, 1 (1964), 1-27. doi: 10.1007/BF02289565. 3
23. Lee J.A., Verleysen M.,: Unsupervised dimensionality reduction: Overview and recent advances. In The International Joint Conference on Neural Networks (2010), pp. 1-8. 3
24. Nöllenburg M., Wolff A.,: A Mixed-Integer Program for Drawing High-Quality Metro Maps. In Graph Drawing, vol. 3843 of Lecture Notes in Computer Science. Springer, 2006, pp. 321-333. doi: 10.1007/11618058-29. 4, 6
25. Salvador S., Chan P.,: Toward accurate dynamic time warping in linear time and space. Intelligent Data Analysis 11, 5 (2007), 561-580. 4
26. Stoffel F., Fischer F., Keim D.A.,: Finding anomalies in time-series using visual correlation for interactive root cause analysis. In Proceedings of the Tenth Workshop on Visualization for Cyber Security (New York, USA, 2013), VizSec '13, ACM, pp. 65-72. doi: 10.1145/2517957.2517966. 3
27. Shi L., Liao Q., He Y., Li R., Striegel A., Su Z.,: SAVE: Sensor anomaly visualization engine. In IEEE Conference on Visual Analytics Science and Technology (VAST) (2011), pp. 201-210. doi: 10.1109/VAST.2011.6102458. 3
28. Saraiya P., Lee P., North C.,: Visualization of graphs with associated timeseries data. In Information Visualization, 2005. INFOVIS 2005. IEEE Symposium on (2005), pp. 225-232. doi: 10.1109/INFVIS.2005.1532151. 3
29. Sips M., Neubert B., Lewis J.P., Hanrahan P.,: Selecting good views of high-dimensional data using class consistency. Computer Graphics Forum 28, 3 (2009), 831-838. doi: 10.1111/j.1467-8659.2009.01467.x. 3, 4
30. Schreck T., Panse C.,: A new metaphor for projection-based visual analysis and data exploration. Proc. SPIE 6495 (2007). doi: 10.1117/12.697879. 7, 9
31. Torgerson W.S.,: Multidimensional scaling: I. Theory and Method. Psychometrika 17, 4 (1952), 401-419. doi: 10.1007/BF02288916. 3
32. Tominski C., Schumann H.,: Enhanced Interactive Spiral Display. In Proceedings of the Annual SIGRAD Conference, Special Theme: Interactivity (2008), Linköping University Electronic Press, pp. 53-56. 3
33. Van Wijk J.J., Van Selow E.R.,: Cluster and Calendar Based Visualization of Time Series Data. In Proceedings of the Symposium on Information Visualization (Washington, DC, USA, 1999), INFOVIS, IEEE Computer Society, pp. 4-9. 3, 7
34. Ward M.O., Guo Z.,: Visual Exploration of Time-series Data with Shape Space Projections. In Proceedings of the Eurographics Conference on Visualization (2011), EuroVis, Eurographics Association, pp. 701-710. doi: 10.1111/j.1467-8659.2011.01919.x. 3
35. Wong P.C., Schneider K., Mackey P., Foote H., Chin G., Guttromson R., Thomas J.,: A Novel Visualization Technique for Electric Power Grid Analytics. IEEE Transactions on Visualization and Computer Graphics 15, 3 (2009), 410-423. doi: 10.1109/TVCG.2008.197. 3
36. Zhao J., Forer P., Harvey A.S.,: Activities, ringmaps and geovisualization of large human movement fields. Information Visualization 7, 3-4 (2008), 198-209. 3
37. Ziegler H., Nietzschmann T., Keim D.,: Visual Exploration and Discovery of Atypical Behavior in Financial Time Series Data using Two-Dimensional Colormaps. In Information Visualization, 2007. IV '07. 11th International Conference (2007), pp. 308-315. doi: 10.1109/IV.2007.124. 6