Laura Tateosian


2017 Blending tools for a Smooth Introduction to 3D Geovisualization Laura Tateosian, Payam Tabrizian, IEEE Visualization - 2nd Pedagogy of Data Visualization Workshop
2017 GazeGIS: A Gaze-based Reading
and Dynamic Geographic Information System.
Tateosian, L., Glatz, M., Shukunobe, M., and Chopra, P. Visualization and Mathematics, Springer Berlin
2016 Python for ArcGIS Tateosian; Springer Books, New York, NY.
2014 GIS-Based Analysis of Coastal Lidar Time-Series Hardin, Mitasova, Tateosian, Overton; Springer Books
2013 Visualizations of Coastal Terrain Time-series Tateosian, Mitasova, Thakur, Hardin, Russ, and Blundell; Information Visualization
2013 Summary Visualizations for Coastal Spatial-Temporal Dynamics (extended paper) Thakur, Tateosian, Mitasova, Hardin, and Overton, M.; International Journal for Uncertainty Quantification
2012 Who’s Watching Your Food? A Flexible Framework for Public Health Monitoring. Tateosian, L., Supak, S., Luo, H., Fang, K., Harrell, J., Harrelson, C., Bailey, A., and Devine; Transactions in GIS
2011 Summary Visualizations for Coastal Spatial-Temporal Dynamics (short paper). Thakur, S., Tateosian, L. G., Hardin, E., Mitasova, H., and Overton, M. IEEE Working with Uncertainty
2010 TanGeoMS: Tangible geospatial modeling system Tateosian, Mitasova, Harmon, Fogleman, Weaver, Harmon; TVCG
2007 Engaging Viewers Through Nonphotorealistic Visualizations Tateosian, Healey, Enns; NPAR
2006 Investigating Aesthetic Visualizations Tateosian; Ph.D. Dissertation
2006 Stevens Dot Patterns for 2D Flow Visualization Tateosian, Dennis, Healey; APGV
2005 Designing a Visualization Framework for Multidimensional Data Dennis, Kocherlakota, Sawant, Tateosian, Healey; IEEE CG&A
2004 Perceptually-Based Brush Strokes for Nonphotorealistic Visualization Healey, Enns, Tateosian, Remple; ACM TOG
2002 Nonphotorealistic Visualization of Multidimensional Datasets Tateosian; M.S. Thesis


2017 Interactive Visualizations of Conflict Economies Amindarbari, R., Shukunobe, M., and Tateosian, L.
2017 Py4All: Innovative feedback tool for students of geospatial programming Tateosian, L., Bader, S., Huckaby, B., Dunnagan, C., and Webster, J.
2016 Representing Time on Story Telling Maps Tateosian, L., Glatz, M. and Shukunobe, M.
2013 Visualizing Coastal Tourism and Landscape Change. Thakur, S., Tateosian, L., Mitasova, H. and Hardin, E.
2011 Visualizing Coastal Spatial-Temporal Dynamics Tateosian, L. G., Thakur, S., Hardin, E., Mitasova, H., and Overton, M.
2010 Exploring Topographic Change Impacts with a Tangible Geospatial Modeling System Weaver, di Leo, Mitasova, Tateosian; Binghamton Geomorphology Symposium
2009 Multivariate Visualization of Continuous Datasets, a User Study Hagh-Shenas, Kim, Tateosian, Healey; IEEE InfoVis


2005 Characterizing Aesthetic Visualizations Tateosian; NCSU Dissertation Proposal
2004 NPR: Art Enhancing Computer Graphics Tateosian, Healey; NCSU CSTR


      Blending tools for a Smooth Introduction to 3D Geovisualization
      [PDF, 635KB][Presentation 10/1/2017][Bibtex]

      Gathering data and practical examples for teaching 3D geovisualization can be time-consuming for instructors. We present a set of innovative, ready-to-adopt materials on 3D geovisualization for terrains. These material show how 3D visualization tools, Blender and SketchFab, can enable students to build 3D interactive visualizations of landscapes. With these tools, rapidly generating visualizations and experimenting with key graphics components, such as texture and lighting, does not require an extensive programming background. Written instructions and videos explain how to create and customize the visualization of a landscape with various surface properties. Additionally, step-by-step labs guide students through the process of creating their own 3D landscape visualization. These materials provide hands-on experience with a practical application of 3D visualization and expose students to several common types of geospatial data.

      Tateosian, L., and Tabrizian, P. (2017) "Blending tools for a smooth introduction to 3D geovisualization." In IEEE Visualization Workshop, Pedagogy of Data Visualization Workshop (PDVW) Proceedings, 2017.



      GazeGIS: A Gaze-based Reading and Dynamic Geographic Information System.
      [PDF, 9.47MB][Bibtex]

      Location is an important component of a narrative. Mapped place names provide vital geographical, economic, historical, political, and cultural context for the text. Online sources such as news articles, travel logs, and blogs frequently refer to geographic locations, but often these are not mapped. When a map is provided, the reader is still responsible for matching references in the text with map positions. As they read a place name within the text, readers must locate its map position, then find their place again in the text to resume reading, and repeat this for each toponym. We propose a gaze-based reading and dynamic geographic information system (GazeGIS) which uses eye tracking and geoparsing to enable a more cohesive reading experience by dynamically mapping locations just as they are encountered within the text. We developed a prototype GazeGIS application and demonstrated its application to several narrative passages. We conducted a study in which participants read text passages using the system and evaluated their experience. We also explored an application for intelligence analysis and discuss how experts in this domain envision its use. Layman and intelligence expert evaluations indicate a positive reception for this new reading paradigm. This could change the way we read online news and e-books, the way school children study political science and geography, the way officers study military history, the way intelligence analysts consume reports, and the way we plan our next vacation.

      Tateosian, L., Glatz, M., Shukunobe, M., and Chopra, P. (2017) "GazeGIS: A Gaze-based Reading and Dynamic Geographic Information System." In: Burch M., Chuang L., Fisher B., Schmidt A., Weiskopf D. (eds) Eye Tracking and Visualization. ETVIS 2015. Mathematics and Visualization. Springer, Cham. pp. 129-147.



      TanGeoMS: Tangible geospatial modeling system
      [PDF, 4.1MB][ Presentation, 10/29/10][WMV, Supplementary video, 4.1 MB]
      [WMV, Fast Forward, 10/26/10, 1.2MB]

      We present TanGeoMS, a tangible geospatial modeling visualization system that couples a laser scanner, projector, and a flexible physical three-dimensional model with a standard geospatial information system (GIS) to create a tangible user interface for terrain data. TanGeoMS projects an image of real-world data onto a physical terrain model. Users can alter the topography of the model by modifying the clay surface or placing additional objects on the surface. The modified model is captured by an overhead laser scanner then imported into a GIS for analysis and simulation of real-world processes. The results are projected back onto the surface of the model providing feedback on the impact of the modifications on terrain parameters and simulated processes. Interaction with a physical model is highly intuitive, allowing users to base initial design decisions on geospatial data, test the impact of these decisions in GIS simulations, and use the feedback to improve their design. We demonstrate the system on three applications: investigating runoff management within a watershed, assessing the impact of storm surge on barrier islands, and exploring landscape rehabilitation in military training areas.

      Tateosian, L. G., Mitasova, H., Harmon, B. A., Fogleman, B., Weaver, K. and Harmon, R.S. "TanGeoMS: ATangible geospatial modeling system." IEEE Transactions on Visualization and Computer Graphics (Proceedings InfoVis 2010) 16, 6, 1605-1612.



      Engaging Viewers Through Nonphotorealistic Visualizations
      [PDF, 9227K] [Presentation, 8/07/07, 45.5MB][Fast Forward presentation, 8/04/07, 7.4MB][Bibtex]

      Research in human visual cognition suggests that beautiful images can engage the visual system, encouraging it to linger in certain locations in an image and absorb subtle details. By developing aesthetically pleasing visualizations of data, we aim to engage viewers and promote prolonged inspection, which can lead to new discoveries within the data. We present three new visualization techniques that apply painterly rendering styles to vary interpretational complexity (IC), indication and detail (ID), and visual complexity (VC), image properties that are important to aesthetics. Knowledge of human visual perception and psychophysical models of aesthetics provide the theoretical basis for our designs. Computational geometry and nonphotorealistic algorithms are used to preprocess the data and render the visualizations. We demonstrate the techniques with visualizations of real weather and supernova data.

      Tateosian, L. G., Healey, C. G., and Enns, J. T. "Engaging Viewers Through Nonphotorealistic Visualizations." In Proceedings of the 5th International Symposium on Non-Photorealistic Animation and Rendering (San Diego, California, August 04 - 05, 2007). NPAR '07. ACM, New York, NY, 93-102.



      Investigating Aesthetic Visualizations
      [PDF, 12.8MB] [Presentation, 12/15/06, 38.4MB][Bibtex]

      Visualizations enable scientists to inspect, interpret, and analyze large multi-dimensional data sets. Effective visualizations are designed to both orient and engage viewers by directing attention in response to a visual stimulus, and then encouraging a viewer's vision to linger at a given image location. Research into human visual perception provides information about how to orient viewers, using salient visual features, such as color, orientation, and flicker. Less is known about how to build engaging visualizations. Increasing the aesthetic merit of visualizations is a promising approach to increasing engagement. Intuition suggests that visualizations with a more aesthetic presentation style will be judged as more artistic, but this is an open problem. In this thesis, we explored an important question pertaining to creating aesthetic visualizations: Is it possible to affect the perceived artistic merit of a scientific visualization?

      To investigate this question, we developed three new painterly visualization techniques, designed to vary different visual qualities important to aesthetics: interpretational complexity (IC), indication and detail (ID), and visual complexity (VC). We conducted four experiments to investigate how these qualities affect the aesthetics. Observers were asked to rank IC, ID, and VC images, together with Master abstract and Impressionist paintings on five questions: artistic merit, pleasure, arousal, meaningfulness, and complexity. Although realistic Impressionist paintings consistently ranked as most artistic, computer visualizations were considered as artistic as and more pleasing than Master abstractionist artwork in certain situations. There was also a significant preference for aesthetic visualizations that used more sophisticated presentation styles. This provides strong evidence that our aesthetic techniques can increase the perceived artistic merit of a visualization, possibly leading to a significant improvement in the visualizations's ability to engage its viewers.

      We applied our experimental techniques to real meteorological and supernova data sets, to explore their capabilities in a real-world setting. Anecdotal feedback from a domain expert in astrophysics was strongly positive, further supporting the theory that enhancing the artistic merit of visualizations is a worthwhile contribution to the scientific community.

      Tateosian, L. G., "Investigating Aesthetic Visualizations." Ph.D. Dissertation (2006), Department of Computer Science, North Carolina State University.



      Stevens Dot Patterns for 2D Flow Visualization
      [PDF, 1523K][Bibtex]

      This paper describes a new technique to visualize 2D flow fields with a sparse collection of dots. A cognitive model proposed by Ken Stevens describes how spatially local configurations of dots are processed in parallel by the low-level visual system to perceive orientations throughout the image. We integrate this model into a visualization algorithm that converts a sparse grid of dots into patterns that capture flow orientations in an underlying flow field. Because our visualizations are based on experimental results from human vision, the patterns are perceptually salient. We describe how our algorithm supports large flow fields that exceed the capabilities of a display device, and demonstrate how to include properties like direction and velocity in our visualizations. We conclude by applying our technique to 2D slices from a simulated supernova collapse.

      Tateosian, L. G., Dennis, B. M., and Healey, C. G. "Stevens Dot Patterns for 2D Flow Visualization." In Third International Symposium on Applied Perception in Graphics and Visualization (Boston, Massachusetts, 2006), pp.93-100.



      Designing a Visualization Framework for Multidimensional Data
      [PDF, 1158K][Bibtex]

      This article describes our initial end-to-end system that starts with data management and continues through assisted visualization design, display, navigation, and user interaction. The purposes of this discussion are to: (1) promote a more comprehensive visualization framework; (2) describe how expertise from human psychophysics, databases, rational logic, and artificial intelligence can be applied to visualization; and (3) illustrate the benefits of a more complete framework using examples from our own experiences.

      Dennis, B. M., Kocherlakota, S. M., Sawant, A. P., Tateosian, L. G., and Healey, C. G. "Designing a Visualization Framework for Multidimensional Data." IEEE Computer Graphics & Applications (Visualization Viewpoints) 25, 6, (2005), 10-15.



      Perceptually-Based Brush Strokes for Nonphotorealistic Visualization
      [PDF, 4243K][Bibtex]

      An important problem in the area of computer graphics is the visualization of large, complex information spaces. Datasets of this type have grown rapidly in recent years, both in number and in size. Images of the data stored in these collections must support rapid and accurate exploration and analysis. This paper presents a method for constructing visualizations that are both effective and aesthetic. Our approach uses techniques from master paintings and human perception to visualize a multidimensional dataset. Individual data elements are drawn with one or more brush strokes that vary their appearance to represent the element's attribute values. The result is a nonphotorealistic visualization of information stored in the dataset. Our research extends existing glyph-based and nonphotorealistic techniques by applying perceptual guidelines to build an effective representation of the underlying data. The nonphotorealistic properties the strokes employ are selected from studies of the history and theory of Impressionist art. We show that these properties are similar to visual features that are detected by the low-level human visual system. This correspondence allows us to manage the strokes to produce perceptually salient visualizations. Psychophysical experiments confirm a strong relationship between the expressive power of our nonphotorealistic properties and previous findings on the use of perceptual color and texture patterns for data display. Results from these studies are used to produce effective nonphotorealistic visualizations. We conclude by applying our techniques to a large, multidimensional weather dataset to demonstrate their viability in a practical, real-world setting.

      Healey, C. G., Enns, J. T., Tateosian, L. G., and Remple, M. "Perceptually-Based Brush Strokes for Nonphotorealistic Visualization." ACM Transactions on Graphics 23, 1, (2004), 64-96.



      Nonphotorealistic Visualization of Multidimensional Datasets
      [PDF, 1210K] [Presentation, 12/19/02, 7573K][Bibtex]

      The huge quantities of data that are being recorded annually need to be organized and analyzed. The datasets often consist of a large number of elements, each associated with multiple attributes. Our objective is to create effective, aesthetically appealing multidimensional visualizations. By mapping element attributes to carefully chosen visual features, such visualizations support exploration, encourage prolonged inspection, and facilitate discovery of unexpected data characteristics and relationships.

      We present a new visualization technique that uses “painted” brush strokes to represent data elements of large multidimensional datasets. Each element’s attributes controls the visual features of one or more brushstrokes. To pursue aesthetic appeal, we draw inspiration from the Impressionist style of painting and apply rendering techniques from nonphotorealistic graphics. We construct our mappings to harness the strengths of the human visual system. The resulting displays are nonphotorealistic visualizations of the information in the datasets.

      Studies confirm that existing guidelines based on human visual perception apply to our painterly styles. Additional studies investigate the artistic appeal of our visualizations, along with the emotional and visual features that influence aesthetic judgments. Finally, we use the results of these studies to combine painterly styles to build a tool which creates visualizations that are both effective and aesthetic and we apply our method to a real-world dataset.

      Tateosian, L. G., "Nonphotorealistic Visualization of Multidimensional Datasets." Master's Thesis (2002), Department of Computer Science, North Carolina State University.



      Characterizing Aesthetic Visualizations
      [PDF, 2225K] [Presentation, 4/26/05, 21MB]

      Exploiting aesthetics to improve the effectiveness of visualizations has not yet been explored in depth by the visualization community. This report describes a proposal to vary visual qualities derived from models of aesthetics to investigate the affect on visualizations. Visualization scientists would like to engage viewers to encourage exploration. A promising approach to engage viewers is to enhance the aesthetic appeal of the visualization. Psychologists believe that aesthetic judgement can be characterized by a number of emotional and cognitive properties. This project aims to identify some qualities that can be varied in visualizations to influence aesthetic judgment. The properties identified by psychologists provide a good starting point. In this proposal, I present three visual qualities, related to these properties. I propose to conduct studies in which these three qualities are varied, to analyze results statistically, and then to seek ways to vary these qualities in a visualization while maintaining perceptual salience.

      Tateosian, L. G. "Characterizing Aesthetic Visualizations" NCSU Dissertation Proposal, Department of Computer Science, North Carolina State University.



      NPR: Art Enhancing Computer Graphics
      [PDF, 2164K][Presentation, 12/19/03, 19MB][Bibtex]

      Nonphotorealistic rendering is a field in computer science in which scientists apply artistic techniques to enhance computer graphics. This paper addresses the interrogatives what, how, and why, about NPR. The discussion expands on what NPR is and what kinds of projects are being done in NPR, specifically it focuses on three issues: two large problems in NPR, simulating pen-and-ink illustration and simulating painting, and last the application of NPR to visualization. Exploring these topics thoroughly provides some specific answers to how these effects are accomplished. Throughout the paper various motivations for using NPR are revealed, including the application of NPR to visualization (as evidence of why). Our lab is interested in applying NPR techniques to visualization, so the paper concludes with some conjecture on how to verify the efficacy of this goal.

      Tateosian, L. G. and Healey, C. G. "NPR: Art Enhancing Computer Graphics." Technical Report TR-2004-17 (2004), Department of Computer Science, North Carolina State University.


      Last Modified by Laura G. Tateosian (1/4/11)