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A 3D Visualization of Multiple Time Series on Maps

Sidharth Thakur, Andrew J. Hanson
2010 2010 14th International Conference Information Visualisation  
enhances the user's ability to pose and explore interesting questions about the data.  ...  We present a visualization technique that addresses some of the challenges involved in visually exploring and analyzing the distributions of geo-spatial time-varying data.  ...  We would like to thank our colleagues at Renci and NCSU for providing valuable feedback and interesting data sets to work with.  ... 
doi:10.1109/iv.2010.54 dblp:conf/iv/ThakurH10 fatcat:ih64l6unzzhwbdd67w7f7x7m5e

Exploration of Interesting Dense Regions in Spatial Data [article]

Placido A. Souza Neto and Francisco B. Silva Junior and Felipe F. Pontes and Behrooz Omidvar-Tehrani
2019 arXiv   pre-print
In this paper, we define, formalize and explore Interesting Dense Regions (IDRs) which capture preferences of analysts, in order to automatically find interesting spatial highlights.  ...  The approach consists of observing mouse moves (as a means of analyst's interaction) and also the explicit analyst's interaction with data points in order to discover interesting spatial regions with dense  ...  ); • We define and formalize the concept of Interesting Dense Regions (IDRs), a polygon-based approach to explore and highlight spatial data; • We propose an efficient greedy approach to compute highlights  ... 
arXiv:1903.04049v1 fatcat:6idqrlecfzarpipettfg3p3x7a

An Interactive Approach for Exploration of Flows Through Direction-Based Filtering

Katerina Vrotsou, Georg Fuchs, Natalia Andrienko, Gennady Andrienko
2017 Journal of Geovisualization and Spatial Analysis  
The approach is based on a flow-specific interaction technique for filtering the data by direction, that enables an analyst to successively identify underlying spatial arrangement patterns.  ...  This paper is concerned with the representation and exploration of flows, defined as spatial interactions between geographic locations.  ...  Conflict of interest On behalf of all authors, the corresponding author states that there is no conflict of interest.  ... 
doi:10.1007/s41651-017-0001-7 fatcat:yr7lrkfyl5ekxmmmvedkfztgze

Visual Data Mining in Large Geospatial Point Sets

D.A. Keim, C. Panse, M. Sips, S.C. North
2004 IEEE Computer Graphics and Applications  
His research interests include visual data mining on large spatial data, spatial data transformation, information visualization, and advanced visual interfaces.  ...  A PixelMaps overview of geospatial data reveals subsets with interesting structures by allocating larger display areas to dense regions with many potentially interesting subsets and smaller areas to less  ...  Further information on visual analysis of massive geospatial data sets, as well as an implementation of the PixelMaps algorithm and Waldo, is available at the Pix-elMaps Project Web site at http://dbvis.inf.uni-konstanz  ... 
doi:10.1109/mcg.2004.41 pmid:15628099 fatcat:g4hcmaw2arhipkkk5qxsma3y2i

Iterative Exploration of Big Brain Network Data

Florian Ganglberger, Nicolas Swoboda, Lisa Frauenstein, Joanna Kaczanowska, Wulf Haubensak, Katja Bühler
2018 Eurographics Workshop on Visual Computing for Biomedicine  
On-demand queries on spatial gene expression and connectivity data enable an interactive dissection of dense network graphs - with of billion-edges on voxel-resolution - in real-time based on their spatial  ...  This creates a need for joint exploration of spatial data, such as gene expression patterns, whole brain gene co-expression correlation, structural and functional connectivities together with neuroanatomical  ...  Exploring the data on different scales: Operating region-wise on the data (for example a region-wise network graph) depends on spatial hierarchy.  ... 
doi:10.2312/vcbm.20181231 dblp:conf/vcbm/GanglbergerSFKH18 fatcat:ozx2v3bpprajvi7rgfwgol5b5i

Data Vases: 2D and 3D Plots for Visualizing Multiple Time Series [chapter]

Sidharth Thakur, Theresa-Marie Rhyne
2009 Lecture Notes in Computer Science  
One challenge associated with the visualization of time-dependent data is to develop graphical representations that are effective for exploring multiple time-varying quantities.  ...  In addition, we extended our method to three dimensions for visualizing time-dependent data on cartographic maps.  ...  Data vases grew out of a visualization framework that was developed with NCSU's Institute for Emerging Issues. We thank Steve Chall and Chris Williams for their contributions.  ... 
doi:10.1007/978-3-642-10520-3_89 fatcat:f7smo2aj3fbntdqq62oafvbjtu

Mining Volunteered Geographic Information datasets with heterogeneous spatial reference

Sadiq Hussain, G.C. Hazarika
2011 International Journal of Advanced Computer Science and Applications  
This area can be defined as efficiently discovering interesting patterns from large data sets.  ...  However, these methods cannot directly be applied to a spatiotemporal sequence because of the fuzziness of spatial locations in the sequence.  ...  This is either because they are 1) densely clustered (and thus may represent a local/regional pattern on a large scale) or 2) they are widely distributed (and thus may represent a pattern on a small scale  ... 
doi:10.14569/specialissue.2011.010319 fatcat:37733sl44bf5xegs5p7dr5b4eu

Pixel based visual data mining of geo-spatial data

Daniel A. Keim, Christian Panse, Mike Sips, Stephen C. North
2004 Computers & graphics  
Spatial data mining, or the discovery of interesting patterns in such databases, is an important capability in the development of database systems.  ...  Visual data mining applies human visual perception to the exploration of large data sets.  ...  The rescaling reduces the size of virtually empty regions and reallocates unused pixels to dense regions.  ... 
doi:10.1016/j.cag.2004.03.022 fatcat:eupsifsxcbhmjpqt57gh3q6qoy

Multilevel Visualization of Travelogue Trajectory Data

Yongsai Ma, Yang Wang, Guangluan Xu, Xianqing Tai
2018 ISPRS International Journal of Geo-Information  
The data characteristic of a single travelogue are different from multiple travelogues.  ...  The variety and volume of trajectory data make it very hard to directly find patterns contained within them.  ...  Conflicts of Interest: The authors declare no conflicts of interest.  ... 
doi:10.3390/ijgi7010012 fatcat:ttiwvrqalvew7gulsmogtsjmiq

Fancies and Fallacies of Spatial Sampling With Transcranial Magnetic Stimulation (TMS)

Luigi Cattaneo
2018 Frontiers in Psychology  
Concluding, the spatial frequency of the brain signal is dependent exclusively on the behavioral task that I chose to explore the effects of TMS.  ...  On the contrary, adding a micro-array of dense sampling allows constant coverage of the target region in all subjects.  ...  Conflict of Interest Statement: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest  ... 
doi:10.3389/fpsyg.2018.01171 pmid:30026721 pmcid:PMC6042252 fatcat:r7aw452jsrhppgzeqcjrsskiei

linus: Conveniently explore, share and present large-scale biological trajectory data from a web browser [article]

Johannes Waschke, Mario Hlawitschka, Kerim Anlas, Vikas Trivedi, Ingo Roeder, Jan Huisken, Nico Scherf
2020 bioRxiv   pre-print
In biology we encounter large-scale trajectory data, but exploring and communicating patterns in such data is often a cumbersome task.  ...  Ideally, such data should be provided with an interactive visualisation in one concise package so that we can create and test hypotheses collaboratively.  ...  The user can define spatial regions of interest (ROIs) and iteratively refine them in order to highlight trajectories of interest and to download them as CSV files for subsequent analysis.  ... 
doi:10.1101/2020.04.17.043323 fatcat:oszbnx7jjndalhb5klzcyawwgm

Towards Visual Analytics for Multi-Sensor Analysis of Remote Sensing Archives [article]

Daniel Eggert, Mike Sips, Patrick Köthur
2016 Workshop on Visualisation in Environmental Sciences (EnvirVis)  
To better detect and study processes on the Earth's surface, scientists want to combine various satellite data and extract potentially interesting patterns from the combined data.  ...  To demonstrate the utility of our visual exploration solution, we use a real-world scenario: the assessment and selection of scenes in order to study the change of forest cover in Europe.  ...  Scientists conduct multi-sensor analysis to answer a particular question for a specific region of interest (ROI).  ... 
doi:10.2312/envirvis.20161100 dblp:conf/envirvis-ws/EggertSK16 fatcat:qblt4d73q5f6lf67id5flk7nwq

Multiple Uncertainties in Time-Variant Cosmological Particle Data

Steve Haroz, Kwan-Liu Ma, Katrin Heitmann
2008 2008 IEEE Pacific Visualization Symposium  
Obtaining this insight can necessitate visualizing the many relationships among temporal, spatial, and other dimensionalities of data and its uncertainties.  ...  We utilize multiple views for interactive dataset exploration and selection of important features, and we apply those techniques to the unique challenges of cosmological particle datasets.  ...  Department of Energy through the SciDAC program with Agreement No. DE-FC02-06ER25777. Thanks to the Cosmic Data ArXiv for making the datasets publicly available.  ... 
doi:10.1109/pacificvis.2008.4475478 dblp:conf/apvis/HarozMH08 fatcat:3rt2uxlni5fk5nahl3q4hzzcgi

Integrating Randomization and Discrimination for Classifying Human-Object Interaction Activities [chapter]

Aditya Khosla, Bangpeng Yao, Li Fei-Fei
2014 Human-Centered Social Media Analytics  
be explored for finegrained image classification.  ...  It is interesting to observe that computer vision research has followed a similar trajectory.  ...  It is interesting to note that despite the randomization and the algorithm having no prior information, it is able to locate the region of interest reliably.  ... 
doi:10.1007/978-3-319-05491-9_5 fatcat:2rmnayfpgjdp7envy6vsj4pgqa

Visual Data Mining of Large Spatial Data Sets [chapter]

Daniel A. Keim, Christian Panse, Mike Sips
2003 Lecture Notes in Computer Science  
Extraction of interesting knowledge from large spatial databases is an important task in the development of spatial database systems.  ...  Visual data mining applies human visual perception to the exploration of large data sets.  ...  There are several approaches to coping with dense spatial data already in common use [11] . One widely used method is a 2.5D visualization showing data points aggregated up to map regions.  ... 
doi:10.1007/978-3-540-39845-5_17 fatcat:wddmfeikgvh7pb4muj4wqeaulq
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