Category: Publications

Topoinvis TTK Hackathon: Experiences, Lessons Learned, and Perspectives

Posted on October 10, 2020April 16, 2024 by paul.a.rosen

This paper documents the organization, the execution, and the results of the Topology ToolKit (TTK) hackathon that took place at the TopoInVis 2019 conference. The primary goal of the hackathon was to promote TTK in our research community as a unified software development platform for topology-based data analysis algorithms. Continue reading

Modeling The Influence Of Visual Density On Cluster Perception In Scatterplots Using Topology

Posted on August 23, 2020April 16, 2024 by paul.a.rosen

We present a multi-stage user study focusing on 4 factors—distribution size of clusters, number of points, size ofpoints, and opacity of points—that influence cluster identification in scatterplots. From these parameters, we have constructed 2 models, a distance-based model, and a density-based model, using the merge tree data structure from Topological Data Analysis. Our analysis demonstrates that these factors play an important role in the number of clusters perceived, and it verifies that the distance-based and density-based models can reasonably estimate the number of clusters a user observes.

Linesmooth: An Analytical Framework For Evaluating The Effectiveness Of Smoothing Techniques On Line Charts

Posted on August 23, 2020April 16, 2024 by paul.a.rosen

We present a comprehensive framework for evaluating line chart smoothing methods under a variety of visual analytics tasks. The framework is based on 8 measures of the line smoothing effectiveness tied to 8 low-level visual analytics tasks. We analyze 12 methods coming from 4 commonly used classes of line chart smoothing---rank filters, convolutional filters, frequency domain filters, and subsampling. Continue reading

Topolines: Topological Smoothing For Line Charts

Posted on May 1, 2020April 16, 2024 by paul.a.rosen

We present TopoLines, a method for smoothing line charts using techniques from Topological Data Analysis. The design goal of TopoLines is to maintain prominent peaks in the data while minimizing any residual error. We evaluate TopoLines for 2 visual analytics tasks by comparing to 5 popular line smoothing methods with data from 4 application domains.

Leveraging Peer Feedback To Improve Visualization Education

Posted on February 11, 2020April 16, 2024 by paul.a.rosen

In this paper, we discuss the construction and application of peer review in a computer science visualization course, including: projects that reuse code and visualizations in a feedback-guided, continual improvement process and a peer review rubric to reinforce key course concepts. Continue reading

Persistent Homology Guided Force-Directed Graph Layouts

Posted on October 11, 2019April 16, 2024 by paul.a.rosen

In this paper, we leverage persistent homology features of an undirected graph as derived information for interactive manipulation of force-directed layouts. We first discuss how to efficiently extract 0-dimensional persistent homology features from both weighted and unweighted undirected graphs. We then introduce the interactive persistence barcode used to manipulate the force-directed graph layout by adding and removing contracting and repulsing forces generated by the persistent homology features, eventually selecting the set of persistent homology features that most improve the layout. Continue reading

Visual Inspection Of Dbs Efficacy

Posted on October 11, 2019April 16, 2024 by paul.a.rosen

A key problem in Deep Brain Stimulation (DBS) is determining the optimal parameters for clinical outcome. Current knowledge does not provide a complete deterministic model of DBS neurophysiology. While multiple parameters may influence clinical outcomes in DBS, this paper explores spatial correlation of volume of tissue activated (VTA) to Unified Parkinson's Disease Rating Scale (UPDRS) scores. Continue reading

You Can’T Publish Replication Studies (And How To Anyways) : Position Paper

Posted on October 9, 2019April 16, 2024 by paul.a.rosen

In this position paper, we define three methods -- re-evaluation, expansion, and specialization -- for embedding a replication study into a novel published work. Within this context, we provide a non-exhaustive case study on replications of Cleveland and McGill's seminal work on graphical perception. Continue reading

Propagate And Pair: A Single-Pass Approach To Critical Point Pairing In Reeb Graphs

Posted on October 2, 2019April 16, 2024 by paul.a.rosen

Pairing critical points enables forming topological fingerprints, known as persistence diagrams, that provides insights into the structure and noise in data. In this paper, we discuss two algorithmic approaches for pairing critical points in Reeb graphs, first a multipass approach, followed by a new single-pass algorithm, called Propagate and Pair. Continue reading

Topologically-Guided Image Enhancement

Posted on October 1, 2019April 16, 2024 by paul.a.rosen

In this paper, we leverage the contour tree to extract a hierarchical representation of the topology of an image. We propose 4 topology-aware transfer functions for editing features of the image using local topological properties, instead of global image properties. Continue reading