{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:40:02Z","timestamp":1760218802548,"version":"build-2065373602"},"reference-count":37,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2014,6,3]],"date-time":"2014-06-03T00:00:00Z","timestamp":1401753600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Informatics"],"abstract":"<jats:p>As we move into the big data era, data grows not just in size, but also in complexity, containing a rich set of attributes, including location and time information, such as data from mobile devices (e.g., smart phones), natural disasters (e.g., earthquake and hurricane), epidemic spread, etc. We are motivated by the rising challenge and build a visualization tool for exploring generic spatiotemporal data, i.e., records containing time location information and numeric attribute values. Since the values often evolve over time and across geographic regions, we are particularly interested in detecting and analyzing the anomalous changes over time\/space. Our analytic tool is based on geographic information system and is combined with spatiotemporal data mining algorithms, as well as various data visualization techniques, such as anomaly grids and anomaly bars superimposed on the map. We study how effective the tool may guide users to find potential anomalies through demonstrating and evaluating over publicly available spatiotemporal datasets. The tool for spatiotemporal anomaly analysis and visualization is useful in many domains, such as security investigation and monitoring, situation awareness, etc.<\/jats:p>","DOI":"10.3390\/informatics1010100","type":"journal-article","created":{"date-parts":[[2014,6,3]],"date-time":"2014-06-03T11:15:50Z","timestamp":1401794150000},"page":"100-125","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Analyzing Spatiotemporal Anomalies through Interactive Visualization"],"prefix":"10.3390","volume":"1","author":[{"given":"Tao","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Computer Science, Central Michigan University, Mount Pleasant, MI 48859, USA"}]},{"given":"Qi","family":"Liao","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Central Michigan University, Mount Pleasant, MI 48859, USA"}]},{"given":"Lei","family":"Shi","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, 100190, China"}]},{"given":"Weishan","family":"Dong","sequence":"additional","affiliation":[{"name":"IBM Research, Beijing, 100193, China"}]}],"member":"1968","published-online":{"date-parts":[[2014,6,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Von Landesberger, T., Bremm, S., Andrienko, N., Andrienko, G., and Tekusova, M. (2012, January 14\u201319). Visual analytics methods for categoric spatio-temporal data. Proceedings of the IEEE Conference on Visual Analytics Science and Technology (VAST), Seattle, WA, USA.","DOI":"10.1109\/VAST.2012.6400553"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1145\/846170.846173","article-title":"A bibliography of temporal, spatial and spatio-temporal data mining research","volume":"1","author":"Roddick","year":"1999","journal-title":"SIGKDD Explor. Newsl."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"39","DOI":"10.5121\/ijcses.2012.3104","article-title":"Spatiotemporal data mining: Issues, tasks and applications","volume":"3","author":"Rao","year":"2012","journal-title":"Int. J. Comput. Sci. Eng. Surv."},{"key":"ref_4","unstructured":"Tsoukatos, I., and Gunopulos, D. (2001, January 12\u201315). Efficient mining of spatiotemporal patterns. Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases (SSTD \u201901), Redondo Beach, CA, USA."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Mamoulis, N., Cao, H., Kollios, G., Hadjieleftheriou, M., Tao, Y., and Cheung, D.W. (2004, January 22\u201325). Mining, indexing, and querying historical spatiotemporal data. Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD \u201904), Seattle, WA, USA.","DOI":"10.1145\/1014052.1014080"},{"key":"ref_6","unstructured":"Mennis, J., and Liu, J.W. (2003, January 8\u201310). Mining association rules in spatio-temporal data. Proceedings of the Seventh International Conference on GeoComputation, Southampton, UK."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1016\/j.jvlc.2007.02.006","article-title":"Exploratory spatio-temporal data mining and visualization","volume":"18","author":"Compieta","year":"2007","journal-title":"J. Vis. Lang. Comput."},{"key":"ref_8","unstructured":"N\u00f6llenburg, M. (2006). Human-Centered Visualization Environments, Springer."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1016\/S1045-926X(03)00046-6","article-title":"Exploratory spatio-temporal visualization: An analytical review","volume":"14","author":"Andrienko","year":"2003","journal-title":"J. Vis. Lang. Comput."},{"key":"ref_10","unstructured":"Oliveira, M., Baptista, C., and Falcao, A. (February,, January 30). A Web-Based Environment for Analysis and Visualization of Spatio-Temporal Data Provided by OGC Services. Proceedings of the Fourth International Conference on Advanced Geographic Information Systems, Applications, and Services, Valencia, Spain."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2649","DOI":"10.1109\/TVCG.2012.291","article-title":"Whisper: Tracing the spatiotemporal process of information diffusion in real time","volume":"18","author":"Cao","year":"2012","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1044","DOI":"10.1109\/TVCG.2010.197","article-title":"Stacking graphic elements to avoid over-plotting","volume":"16","author":"Dang","year":"2010","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"ref_13","unstructured":"Tominski, C., Schulze-Wollgast, P., and Schumann, H. (2005, January 6\u20138). 3D Information Visualization for Time Dependent Data on Maps. Proceedings of the Ninth International Conference on Information Visualisation, London, UK."},{"key":"ref_14","unstructured":"Dong, W., Zhang, X., Li, L., Sun, C., Shi, L., and Sun, W. (2002). Detecting Irregularly Shaped Significant Spatial and Spatio-Temporal Clusters, SDM. SIAM\/Omnipress."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/2945.981847","article-title":"Information visualization and visual data mining","volume":"8","author":"Keim","year":"2002","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1559\/152304001782173952","article-title":"The integration of geographic visualization with knowledge discovery in databases and geocomputation","volume":"28","author":"Gahegan","year":"2001","journal-title":"Cartogr. Geogr. Inf. Sci."},{"key":"ref_17","unstructured":"Andrienko, N., Andrienko, G., and Gatalsky, P. (2000, January 25\u201327). Towards Exploratory Visualization of Spatio-Temporal Data. Proceedings of the 3rd AGILE Conference on Geographic Information Science, Helsinki\/Espoo, Finland."},{"key":"ref_18","unstructured":"Weiskopf, D., Schramm, F., Erlebacher, G., and Ertl, T. (2005, January 23\u201328). Particle and Texture Based Spatiotemporal Visualization of Time-Dependent Vector Fields. Proceedings of IEEE Visualization (VIS 05), Minneapolis, MN, USA."},{"key":"ref_19","first-page":"4","article-title":"HyperSmooth: A system for interactive spatial analysis via potential maps","volume":"5373","author":"Plumejeaud","year":"2008","journal-title":"Web Wirel. Geogr. Inf. Syst."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Chae, J., Thom, D., Bosch, H., Jang, Y., Maciejewski, R., Ebert, D.S., and Ertl, T. (2012, January 14\u201319). Spatiotemporal Social Media Analytics for Abnormal Event Detection and Examination using Seasonal-Trend Decomposition. Proceedings of the IEEE Conference on Visual Analytics Science and Technology (VAST), Seattle, WA, USA.","DOI":"10.1109\/VAST.2012.6400557"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Andrienko, G.L., Andrienko, N.V., Rinzivillo, S., Nanni, M., Pedreschi, D., and Fosca, G. (2009, January 11\u201316). Interactive Visual Clustering of Large Collections of Trajectories. Proceedings of the IEEE Conference on Visual Analytics Science and Technology (VAST), Atlantic City, NJ, USA.","DOI":"10.1109\/VAST.2009.5332584"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2565","DOI":"10.1109\/TVCG.2012.265","article-title":"Stacking-based visualization of trajectory attribute data","volume":"18","author":"Tominski","year":"2012","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"ref_23","unstructured":"Kapler, T., and Wright, W. (2004, January 10\u201312). GeoTime Information Visualization. Proceedings of the IEEE Symposium on Information Visualization ( INFOVIS \u201904), Austin, TX, USA."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1109\/38.946631","article-title":"Information availability in 2D and 3D displays","volume":"21","author":"Smallman","year":"2001","journal-title":"IEEE Comput. Graph. Appl."},{"key":"ref_25","unstructured":"Shepherd, I.D.H. (2008). Geographic Visualization: Concepts, Tools and Applications, John Wiley & Sons. Chapter 10."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1145\/245882.245901","article-title":"3D geographic network displays","volume":"25","author":"Cox","year":"1996","journal-title":"ACM Sigmod Record"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Moore, J.H., Lari, R.C., Hill, D., Hibberd, P.L., and Madan, J.C. (2011). Human microbiome visualization using 3D technology. Pac. Symp. Biocomput., 154\u2013164.","DOI":"10.1142\/9789814335058_0017"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"696","DOI":"10.1109\/TVCG.2008.194","article-title":"An evaluation of space time cube representation of spatiotemporal patterns","volume":"15","author":"Kristensson","year":"2009","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Choudhury, S., Kodagoda, N., Nguyen, P., Rooney, C., Attfield, S., Xu, K., Zheng, Y., Wong, B., Chen, R., and Slabbert, G.M. (2012, January 14\u201319). M-Sieve: A Visualisation Tool for Supporting Network Security Analysts: VAST 2012 Mini Challenge 1 Award: \u201cSubject Matter Expert\u2019s Award\u201d. Proceedings of the IEEE Conference on Visual Analytics Science and Technology (VAST 2012) Challenge Workshop (VisWeek\u201912), Seattle, WA, USA.","DOI":"10.1109\/VAST.2012.6400524"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Kachkaev, A., Dillingham, I., Beecham, R., Goodwin, S., Ahmed, N., and Slingsby, A. (2012, January 14\u201319). Monitoring the Health of Computer Networks with Visualization: VAST 2012 Mini Challenge 1 Award: \u201cEfficient use of Visualization\u201d. Proceedings of the IEEE Conference on Visual Analytics Science and Technology (VAST 2012) Challenge Workshop (VisWeek\u201912), Seattle, WA, USA.","DOI":"10.1109\/VAST.2012.6400522"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Zhang, T., Liao, Q., and Shi, L. (2012, January 14\u201319). 3D Anomaly Bar Visualization for Large-scale Network: VAST 2012 Mini Challenge 1. Proceedings of the IEEE Conference on Visual Analytics Science and Technology (VAST 2012) Challenge Workshop (VisWeek\u201912), Seattle, WA, USA.","DOI":"10.1109\/VAST.2012.6400511"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Kalnis, P., Mamoulis, N., and Bakiras, S. (2005, January 22\u201324). On Discovering Moving Clusters in Spatio-Temporal Data. Proceedings of the 9th international conference on Advances in Spatial and Temporal Databases (SSTD\u201905), Angra dos Reis, Brazil.","DOI":"10.1007\/11535331_21"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Andrienko, G., Andrienko, N., Hurter, C., Rinzivillo, S., and Wrobel, S. (2011, January 23\u201328,). From Movement Tracks through Events to Places: Extracting and Characterizing Significant Places from Mobility Data. Proceedings of the IEEE Conference on Visual Analytics Science and Technology (VAST), Providence, RI, USA.","DOI":"10.1109\/VAST.2011.6102454"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Crnovrsanin, T., Muelder, C., Correa, C., and Ma, K.L. (2009, January 11\u201316). Proximity-based Visualization of Movement Trace Data. Proceedings of the IEEE Conference on Visual Analytics Science and Technology (VAST), Atlantic City, NJ, USA.","DOI":"10.1109\/VAST.2009.5332593"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1481","DOI":"10.1080\/03610929708831995","article-title":"A spatial scan statistic","volume":"26","author":"Kulldoff","year":"1997","journal-title":"Commun. Stat.-Theory Methods"},{"key":"ref_36","unstructured":"Mohammadi, S.H., Janeja, P.V., and Gangopadhyay, A. (May,, January 30). Discretized Spatio-Temporal Scan Window. Proceedings of the Ninth SIAM International Conference on Data Mining, Sparks, NV, USA."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1377","DOI":"10.2105\/AJPH.88.9.1377","article-title":"A space-time scan statistic and brain cancer in Los Alamos","volume":"88","author":"Kulldorff","year":"1998","journal-title":"Am. J. Public Health"}],"container-title":["Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2227-9709\/1\/1\/100\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:12:04Z","timestamp":1760217124000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2227-9709\/1\/1\/100"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,6,3]]},"references-count":37,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2014,6]]}},"alternative-id":["informatics1010100"],"URL":"https:\/\/doi.org\/10.3390\/informatics1010100","relation":{},"ISSN":["2227-9709"],"issn-type":[{"type":"electronic","value":"2227-9709"}],"subject":[],"published":{"date-parts":[[2014,6,3]]}}}