Understanding the causality inherent in networks of biological pathways is an active area of research for systems biologists, cancer researchers, and drug designers. ReactionFlow explores the use of animation within novel network visualizations of biological pathways to enable a number of tasks related to representing and analyzing causality, including: finding components that are downstream and/or upstream from a particular protein or biochemical reaction; finding the shortest path between two proteins in a network or subnetwork; identifying feedback loops within a pathway; and simluating the effect of perturbing the network by “knocking out” a protein or protein complex. This technique, developed by Tuan Dang in collaboration with Paul Murray, Jillian Aurisano, and Angus Forbes, was presented at BioVis’15. Source code can be found at the Creative Coding Research Group code repository.
BRAINtrinsic is a novel VR-compatible visualization application that enables users to interactively explore the human brain connectome and its intrinsic topology. It enables a user to reconstruct and analyze the intrinsic geometry of brain data, that is, the topological space where the brain connectivity natively resides (independent of neuroanatomy). The utility of this intrinsic geometry could lead to a greater distinction of differences not only in clinical cohorts, but possibly in the future to monitor longitudinal changes in individual brains in order to better deliver precision medicine. BRAINtrinsic was developed by Giorgio Conte in collaboration with Angus Forbes, Alex Leow, Allen Ye, Olusola Ajilore, and others affilated with the Collaborative Neuroimaging Environment for Connectomics (CoNECt@UIC), and has been presented at BIH’15 and revised for journal publication in Brain Informatics.
The density of points within multidimensional clusters can impact the effective representation of distances and grouping when projecting data from higher dimensions onto a lower dimensional space. This collaboration from Ronak Etemadpour and Angus Forbes examines the use of motion to retain an accurate representation of the point density of clusters that might otherwise be lost when a multidimensional dataset is projected into a 2D space. We study how users interpret motion in 2D scatterplots and investigate whether or not they are able to effectively interpret the point density of the clusters through motion. Specifically, we consider different types of density-based motion, where the magnitude of the motion is directly related to the density of the clusters. This research was presented at BigData’14 and VDA’15, and an article was recently accepted for publication in SAGE Information Visualization.
BranchingSets is a novel interactive visualization technique for augmenting node-link diagrams with information about the categories that both nodes and links belong to. Our technique enables user-driven methods to procedurally navigate the graph topology as well as to interactively inspect complex, hierarchical data associated with individual nodes. Developed by Francesco Paduano in collaboration with Angus Forbes, BranchingSets has been applied to biological pathway networks as well as co-authorship networks. The biology pathway network use case was presented at BioVis’15 in Dublin, Ireland.
Studying the behavior of individual members in communities of dynamic networks can help neuroscientists understand how interactions between neurons in brain networks change over time. Visualizing those temporal features is challenging, especially for networks embedded within spatial structures, such as brain networks. Two projects led by Chihua Ma, Animated dual-representation and SwordPlots, provide visual analytics tools to better understand how the functional behavior of the brain changes over time, how such behaviors are related to the spatial structure of the brain, and how communities of neurons with similar functionality evolve over time. The first project was presented at EuroVis’15 and incorporates interactive animated dual-representation of the connectivity between brain regions as it changes over time. The enhanced node-link diagram and distance matrix visualizations are coordinated, each serving as interfaces for each other to better enable visual analytics tasks using dynamic brain network data. The second project was recently accepted for publication in the Journal of Imaging Science and Technology; it provides a novel interactive multi-view visualization system to assist neuroscientists in their exploration of dynamic brain networks from multiple perspectives. These projects are collaborations with the computer scientists Tanya Berger-Wolf, Robert Kenyon, and Angus Forbes of UIC, and the neuroscientist Daniel Llano of UIUC.
PathwayMatrix is a visualization tool that presents the binary relations between proteins in the pathway via the use of an interactive adjacency matrix. We provide filtering, lensing, clustering, and brushing and linking capabilities in order to present relevant details about proteins within a pathway network, enabling systems biologists and cancer researchers to find patterns in the relationships and reactions between proteins and protein complexes. PathwayMatrix, developed by Tuan Dang in collaboration with Angus Forbes and Paul Murray, was presented at BioVis’15; source code can be found at the Creative Coding Research Group code repository.
Halos in a dark sky visualizes dark matter halo merger trees and their evolution through space and time. The prototype web application enables users to interact with individual halos within these trees in order to perform a range of visual analysis tasks, including: identifying the substructure and superstructure of the halos; observing the movement of halos across a custom range of time steps; and comparing the branching attributes of multiple trees. Central to our application is the ability to navigate the halos by interactively “jumping” from tree to tree. By clearly marking halos that have “tributaries” — that is, that split off into multiple halos or merge with one or more halos — the user can traverse the complex structure of the universe. The application is publicly available online and runs at interactive rates on the browser using hardware-accelerated graphics. Halos in a dark sky, developed by Kyle Almryde and Angus Forbes, won Honorable Mention in the 2015 IEEE SciVis Contest, “Visualizing the Universe”.
The use of electronic health records (EHRs) in clinical environments provides new opportunities for clinicians to integrate data analyses into their practice. While having access to these records has many benefits, the act of recording, retrieving, and analyzing this data can nonetheless introduce communication issues, as navigating and interpreting large amounts of heterogeneous data can be difficult, and conclusions can be hard to validate. In collaboration with Jane Carrington and Mihai Surdeanu from the University of Arizona, Angus Forbes created a series of integrated visual interfaces to help nurses document and reason about patient data and about clinicians’ understanding of patient data. The interfaces present the output of a predictive algorithm that makes use of historical EHR data, patient vital signs, and nurse handoff reports in order to classify a patient in terms of their likelihood of experiencing clinical events. Furthermore, the interfaces enable the nurses to quickly explore the original data and to examine other nurses’ interpretation of patient activity during previous shifts. This work, funded by the National Institutes of Health as part of the NSF/NIH Smart and Connected Health Program, has been presented at TextVis’13, and an implementation developed by Alessandro Chetta and Angus Forbes was introduced at VAHC’15, and is currently being evaluated in the context of real-world healthcare situations.
Passive wayfinding devices, such as signs, maps, schedules and arrival time displays are essential parts of most successful, modern public transit networks. In contrast with contemporary transit navigation software, passive wayfinding devices accept no input but, rather, instead provide the user with the information needed to make their own way to their destination. In this paper, we describe a new type of passive wayfinding device: a fully enriched animated, ambient display. Our design makes use of a novel animation strategy to aid travelers in route planning tasks. To provide an initial validation of our design choices, we have conducted a pilot study that assesses a usage scenario demonstrating how our visualization can be used to facilitate effective urban wayfinding in the City of Chicago and elsewhere. The prototype application, TransitTrace, was developed by Massimo De Marchi in collaboration with Jakob Eriksson and Angus Forbes and presented at ACM SIGSPATIAL’15.
Visualizing and analyzing the relationships between taxonomic entities represented in multiple input classifications is both challenging and required due to recurrent new discoveries and inferences of taxa and their phylogenetic relationships. Despite the availability of numerous visualization techniques, the large size of hierarchical classifications and complex relations between taxonomic entities generated during a multi-taxonomy alignment process requires new visualizations. ProvenanceMatrix is a novel tool allowing end users (taxonomists, ecologists, phylogeneticists) to explore and comprehend the outcomes of taxonomic alignments. ProvenanceMatrix, developed by Tuan Dang in collaboration with Nico Franz, Bertram Ludascher, and Angus Forbes, has been evaluated on taxonomic classifications of various sizes, from a few to hundreds of taxonomic entities and hundreds of thousands of relationships. It was presented at VOILA’15, the ISWC Workshop on Visualizations and User Interfaces for Ontologies and Linked Data.
Stretch projections allow users to interactively interrogate multivariate datasets in real-time by “stretching” data into data onto a two-dimensional display. The position of each element is based on a linear combination of variables determined by the analyst. The technique is particularly relevant to geotemporal data, where geography and time interact with a number of other variables. A protoype application, Stretch Plot, was used to visually explore a large dataset related to traveling musicians. Data include the date and geographic location of performances given by over 3000 musicians over the span of four years. In addition, social and demographic data – such as median household income and racial distributions – was collected based on the geographic coordinates of each performance location. The technique was created by Paul Murray in collaboration with Angus Forbes and the StretchPlot application was presented at VAST’14 and MapInteract’14.
This collaboration with Saiph Savage and Tobias Höllerer presents a system that automatically classifies social network data in order to support a user’s directed social queries and, furthermore, that allows the user to quickly verify the accuracy of the classifications. We model a user’s friends’ interests in particular topics through the creation of a crowd-sourced knowledge base comprised of terms related to user-specified semantic categories. Using this model, our system makes it possible to quickly identify friends who have a high probability of being able to answer particular questions or of having a shared interested in particular topics. This work was presented at TextVis’12.
The Natural materials browser is a tablet application created in collaboration with the materials scientist Tony Fast. The application enables a user to interact with volumetric datasets created from a series of natural materials samples. The data samples— high resolution meso-scale volumetric images of nutshells gathered via micro-computed tomography— are envisioned as “virtual specimens” presented many orders of magnitude larger than their characteristic length scale. The user, initially placed in the center of the volumetric dataset and facing orthogonally toward the original 2D image slices, uses a tablet as a magic lens to view and navigate the data via physical rotation and multitouch gestures. The user has simultaneous access to multiple representations of the datasets from any angle or position, and an additional viewport provides real-time, spatial statistics on the current view of the currently loaded dataset. The Natural materials browser was first presented at IEEE VIS in 2013.
Tag River is a visualization that presents a detailed comparative overview between mutiple users’ content within a particular time period; and providing a trend summarization over a range of time spans. The summarization is displayed using vertically-adjacent polygonal regions in which the area represents some facet of quantitative information. A series of animated tag clouds are used to provide more detailed content for each user, changing over time to provide an indication of the coherence of context between time segments. The concurrent representation of both multivariate and temporal data can be cycled though programmatically or navigated interactively. Tag river is a collaboration with Basak Alper and Tobias Höllerer and was presented at TextVis’11.
Stereoscopic highlighting, developed in collaboration with Basak Alper, Tobias Höllerer, and JoAnn Kuchera-Morin, is a novel technique that helps to answer accessibility and adjacency queries when interacting with a node-link diagram. The technique utilizes stereoscopic depth to highlight regions of interest in a 2D graph by projecting these parts onto a plane closer to the viewpoint of the user. This technique aims to isolate and magnify specific portions of the graph that need to be explored in detail without resorting to other highlighting techniques, such as color or motion, which can then be reserved to encode other data attributes. This mechanism of stereoscopic highlighting also enables focus+context views by juxtaposing a detailed image of a region of interest with the overall graph, which is visualized at a further depth with correspondingly less detail. The stereoscopic highlighting technique was presented at InfoVis’11 and later published in IEEE Transactions on Visualization and Computer Graphics.
Behaviorism is a software framework that faciliates the creation of new visualizations. It allows a wide range of flexibility when working with dynamic information on visual, temporal, and ontological levels, but at the same time provides appropriate abstractions that allow developers to create prototypes quickly, which can then easily be turned into robust systems. The core of the framework is a set of three interconnected graphs, each with associated operators: a scene graph for high-performance 3D rendering, a data graph for different layers of semantically-linked heterogeneous data, and a timing graph for sophisticated control of scheduling, interaction, and animation. In particular, the timing graph provides a unified system to add behaviors to both data and visual elements, as well as to the behaviors themselves. Behaviorism has been used to create a wide range of visualization and media arts projects. It was presented at InfoVis’10 and later published in the IEEE Transactions on Visualization and Computer Graphics.