Image or Information? Examining the Nature and Impact of Visualization Perceptual Classification.

How do people internalize visualizations: as images or information? In this study, we investigate the nature of internalization for visualizations (i.e., how the mind encodes visualizations in memory) and how memory encoding affects its retrieval. This exploratory work examines the influence of various design elements on a user's perception of a chart. Specifically, which design elements lead to perceptions of visualization as an image (aims to provide visual references, evoke emotions, express creativity, and inspire philosophic thought) or as information (aims to present complex data, information, or ideas concisely and promote analytical thinking)? Understanding how design elements contribute to viewers perceiving a visualization more as an image or information will help designers decide which elements to include to achieve their communication goals. For this study, we annotated 500 visualizations and analyzed the responses of 250 online participants, who rated the visualizations on a bilinear scale as 'image' or 'information.' We then conducted an in-person study ( n = 101) using a free recall task to examine how the image/information ratings and design elements impacted memory. The results revealed several interesting findings: Image-rated visualizations were perceived as more aesthetically 'appealing,' 'enjoyable,' and 'pleasing.' Information-rated visualizations were perceived as less 'difficult to understand' and more aesthetically 'likable' and 'nice,' though participants expressed higher 'positive' sentiment when viewing image-rated visualizations and felt less 'guided to a conclusion.' The presence of axes and text annotations heavily influenced the likelihood of participants rating the visualization as 'information.' We also found different patterns among participants that were older. Importantly, we show that visualizations internalized as 'images' are less effective in conveying trends and messages, though they elicit a more positive emotional judgment, while 'informative' visualizations exhibit annotation focused recall and elicit a more positive design judgment. We discuss the implications of this dissociation between aesthetic pleasure and perceived ease of use in visualization design.

ChartStory: Automated Partitioning, Layout, and Captioning of Charts into Comic-Style Narratives.

Visual data storytelling is gaining importance as a means of presenting data-driven information or analysis results, especially to the general public. This has resulted in design principles being proposed for data-driven storytelling, and new authoring tools being created to aid such storytelling. However, data analysts typically lack sufficient background in design and storytelling to make effective use of these principles and authoring tools. To assist this process, we present ChartStory for crafting data stories from a collection of user-created charts, using a style akin to comic panels to imply the underlying sequence and logic of data-driven narratives. Our approach is to operationalize established design principles into an advanced pipeline that characterizes charts by their properties and similarities to each other, and recommends ways to partition, layout, and caption story pieces to serve a narrative. ChartStory also augments this pipeline with intuitive user interactions for visual refinement of generated data comics. We extensively and holistically evaluate ChartStory via a trio of studies. We first assess how the tool supports data comic creation in comparison to a manual baseline tool. Data comics from this study are subsequently compared and evaluated to ChartStory's automated recommendations by a team of narrative visualization practitioners. This is followed by a pair of interview studies with data scientists using their own datasets and charts who provide an additional assessment of the system. We find that ChartStory provides cogent recommendations for narrative generation, resulting in data comics that compare favorably to manually-created ones.

PMU Tracker: A Visualization Platform for Epicentric Event Propagation Analysis in the Power Grid.

The electrical power grid is a critical infrastructure, with disruptions in transmission having severe repercussions on daily activities, across multiple sectors. To identify, prevent, and mitigate such events, power grids are being refurbished as 'smart' systems that include the widespread deployment of GPS-enabled phasor measurement units (PMUs). PMUs provide fast, precise, and time-synchronized measurements of voltage and current, enabling real-time wide-area monitoring and control. However, the potential benefits of PMUs, for analyzing grid events like abnormal power oscillations and load fluctuations, are hindered by the fact that these sensors produce large, concurrent volumes of noisy data. In this paper, we describe working with power grid engineers to investigate how this problem can be addressed from a visual analytics perspective. As a result, we have developed PMU Tracker, an event localization tool that supports power grid operators in visually analyzing and identifying power grid events and tracking their propagation through the power grid's network. As a part of the PMU Tracker interface, we develop a novel visualization technique which we term an epicentric cluster dendrogram, which allows operators to analyze the effects of an event as it propagates outwards from a source location. We robustly validate PMU Tracker with: (1) a usage scenario demonstrating how PMU Tracker can be used to analyze anomalous grid events, and (2) case studies with power grid operators using a real-world interconnection dataset. Our results indicate that PMU Tracker effectively supports the analysis of power grid events; we also demonstrate and discuss how PMU Tracker's visual analytics approach can be generalized to other domains composed of time-varying networks with epicentric event characteristics.

ConceptExplainer: Interactive Explanation for Deep Neural Networks from a Concept Perspective.

Traditional deep learning interpretability methods which are suitable for model users cannot explain network behaviors at the global level and are inflexible at providing fine-grained explanations. As a solution, concept-based explanations are gaining attention due to their human intuitiveness and their flexibility to describe both global and local model behaviors. Concepts are groups of similarly meaningful pixels that express a notion, embedded within the network's latent space and have commonly been hand-generated, but have recently been discovered by automated approaches. Unfortunately, the magnitude and diversity of discovered concepts makes it difficult to navigate and make sense of the concept space. Visual analytics can serve a valuable role in bridging these gaps by enabling structured navigation and exploration of the concept space to provide concept-based insights of model behavior to users. To this end, we design, develop, and validate CONCEPTEXPLAINER, a visual analytics system that enables people to interactively probe and explore the concept space to explain model behavior at the instance/class/global level. The system was developed via iterative prototyping to address a number of design challenges that model users face in interpreting the behavior of deep learning models. Via a rigorous user study, we validate how CONCEPTEXPLAINER supports these challenges. Likewise, we conduct a series of usage scenarios to demonstrate how the system supports the interactive analysis of model behavior across a variety of tasks and explanation granularities, such as identifying concepts that are important to classification, identifying bias in training data, and understanding how concepts can be shared across diverse and seemingly dissimilar classes.

Atrazine exposure in zebrafish induces aberrant genome-wide methylation.

Atrazine (ATZ) is the second most common agricultural herbicide used in the United States and is an endocrine disrupting chemical (EDC). Developmental exposure to ATZ can lead to significant behavioral and morphological alterations in exposed animals and their progeny suggesting the involvement of an epigenetic mechanism. Specific epigenetic mechanisms responsible for these alterations, however, are yet to be elucidated. In this study, we exposed zebrafish embryos to 0, 0.3, 3, or 30 ppb (µg/L) of ATZ from 1 to 72 h post fertilization (hpf). Chemical exposure was ceased and zebrafish maintained until 9 months post fertilization (mpf), when whole-genome bisulfite sequencing (WGBS) was performed to assess the effects of embryonic ATZ exposure on DNA methylation in female fish brains. The number of differentially methylated genes (DMGs) increased with increasing treatment concentration. DMGs were enriched in neurological pathways with extensive methylation changes consistently observed in neuroendocrine pathways. Specifically, DMGs with methylation changes in promoter regions showed hypomethylation in estrogen receptor signaling and hypermethylation in androgen signaling. DMGs with methylation changes in genebody were primarily enriched for mitochondrion-related pathways associated with healthy aging. Integrated analysis with transcriptomic data at 9 mpf exhibited a similar trend identifying CABLES1 and NDUFA4 as shared targets at all concentrations. We then compared the predicted upstream regulators of transcriptomic changes with DMGs and identified CALML3 as a common upstream regulator at both 0.3 and 30 ppb that exhibit significant methylation changes. Collectively, our study identified long-lasting DNA methylation changes in genome after embryonic ATZ exposure and elucidated potential gene targets whose aberrant methylation features may drive alterations in gene transcription in long-term.

PMUVis : A Large-Scale Platform to Assist Power System Operators in a Smart Grid.

Electric transmission power grids are being revamped with the widespread deployment of GPS-enabled phasor measurement units (PMUs) for real-time wide-area monitoring and control via precise, time-synchronized measurements of voltage and current. Large, concurrently produced volumes of noisy data hinder PMU usability, particularly for the analysis of power oscillation and load fluctuation events in the grid. We examine visualization challenges for events in the electric power grid and develop PMUVis, a visualization platform that supports scalable analysis of grid network topology and anomalous events in near time. PMUVis incorporates a novel FFT-based approach over raw and temporally aggregated data to examine oscillation event propagation through the grid network. We validate PMUVis with expert reviews and a case study and discuss how visualization can be leveraged to enhance real-time spatiotemporal grid analysis by advancing operator capabilities.

Umbra: A Visual Analysis Approach for Defense Construction Against Inference Attacks on Sensitive Information.

Collecting and analyzing anonymous personal information is required as a part of data analysis processes, such as medical diagnosis and restaurant recommendation. Such data should ostensibly be stored so that specific individual information cannot be disclosed. Unfortunately, inference attacks-integrating background knowledge and intelligent models-hinder classic sanitization techniques like syntactic anonymity and differential privacy from exhaustively protecting sensitive information. As a solution, we introduce a three-stage approach empowered within a visual interface, which depicts underlying inference behaviors via a Bayesian Network and supports a customized defense against inference attacks from unknown adversaries. In particular, our approach visually explains the process details of the underlying privacy preserving models, allowing users to verify if the results sufficiently satisfy the requirements of privacy preservation. We demonstrate the effectiveness of our approach through two case studies and expert reviews.

Bmi1 Augments Proliferation and Survival of Cortical Bone-Derived Stem Cells after Injury through Novel Epigenetic Signaling via Histone 3 Regulation.

Ischemic heart disease can lead to myocardial infarction (MI), a major cause of morbidity and mortality worldwide. Multiple stem cell types have been safely transferred into failing human hearts, but the overall clinical cardiovascular benefits have been modest. Therefore, there is a dire need to understand the basic biology of stem cells to enhance therapeutic effects. Bmi1 is part of the polycomb repressive complex 1 (PRC1) that is involved in different processes including proliferation, survival and differentiation of stem cells. We isolated cortical bones stem cells (CBSCs) from bone stroma, and they express significantly high levels of Bmi1 compared to mesenchymal stem cells (MSCs) and cardiac-derived stem cells (CDCs). Using lentiviral transduction, Bmi1 was knocked down in the CBSCs to determine the effect of loss of Bmi1 on proliferation and survival potential with or without Bmi1 in CBSCs. Our data show that with the loss of Bmi1, there is a decrease in CBSC ability to proliferate and survive during stress. This loss of functionality is attributed to changes in histone modification, specifically histone 3 lysine 27 (H3K27). Without the proper epigenetic regulation, due to the loss of the polycomb protein in CBSCs, there is a significant decrease in cell cycle proteins, including Cyclin B, E2F, and WEE as well as an increase in DNA damage genes, including ataxia-telangiectasia mutated (ATM) and ATM and Rad3-related (ATR). In conclusion, in the absence of Bmi1, CBSCs lose their proliferative potential, have increased DNA damage and apoptosis, and more cell cycle arrest due to changes in epigenetic modifications. Consequently, Bmi1 plays a critical role in stem cell proliferation and survival through cell cycle regulation, specifically in the CBSCs. This regulation is associated with the histone modification and regulation of Bmi1, therefore indicating a novel mechanism of Bmi1 and the epigenetic regulation of stem cells.

Pre-differentiation exposure to low-dose of atrazine results in persistent phenotypic changes in human neuronal cell lines.

Exposures to organic pesticides, particularly during a developmental window, have been associated with various neurodegenerative diseases later in life. Atrazine (ATZ), one of the most used pesticides in the U.S., is suspected to be associated with increased neurodegeneration later in life but few studies assessed the neurotoxicity of developmental ATZ exposure using human neuronal cells. Here, we exposed human SH-SY5Y cells to 0.3, 3, and 30 ppb of ATZ prior to differentiating them into dopaminergic-like neurons in ATZ-free medium to mimic developmental exposure. The differentiated neurons exhibit altered neurite outgrowth and SNCA pathology depending on the ATZ treatment doses. Epigenome changes, such as decreases in 5mC (for 0.3 ppb only), H3K9me3, and H3K27me3 were observed immediately after exposure. These alterations persist in a compensatory manner in differentiated neurons. Specifically, we observed significant reductions in 5mC and H3K9me3, as well as, an increase in H3K27me3 in ATZ-exposed cells after differentiation, suggesting substantial chromatin rearrangements after developmental ATZ exposure. Transcriptional changes of relevant epigenetic enzymes were also quantified but found to only partially explain the observed epigenome alteration. Our results thus collectively suggest that exposure to low-dose of ATZ prior to differentiation can result in long-lasting changes in epigenome and increase risks of SNCA-related Parkinson's Disease.

Low dose lead exposure induces alterations on heterochromatin hallmarks persisting through SH-SY5Y cell differentiation.

Lead (Pb) is a commonly found heavy metal due to its historical applications. Recent studies have associated early-life Pb exposure with the onset of various neurodegenerative disease. The molecular mechanisms of Pb conferring long-term neurotoxicity, however, is yet to be elucidated. In this study, we explored the persistency of alteration in epigenetic marks that arise from exposure to low dose of Pb using a combination of image-based and gene expression analysis. Using SH-SY5Y as a model cell line, we observed significant alterations in global 5-methycytosine (5 mC) and histone 3 lysine 27 tri-methylation (H3K27me3) and histone 3 lysine 9 tri-methylation (H3K9me3) levels in a dose-dependent manner immediately after Pb exposure. The changes are partially associated with alterations in epigenetic enzyme expression levels. Long term culturing (14 days) after cease of exposure revealed persistent changes in 5 mC, partial recovery in H3K9me3 and overcompensation in H3K27me3 levels. The observed alterations in H3K9me3 and H3K27me3 are reversed after neuronal differentiation, while reduction in 5 mC levels are amplified with significant changes in patterns as identified via texture clustering analysis. Moreover, correlation analysis demonstrates a strong positive correlation between trends of 5 mC alteration after differentiation and neuronal morphology. Collectively, our results suggest that exposure to low dose of Pb prior to differentiation can result in persistent epigenome alterations that can potentially be responsible for the observed phenotypic changes. Our work reveals that Pb induced changes in epigenetic repressive marks can persist through neuron differentiation, which provides a plausible mechanism underlying long-term neurotoxicity associated with developmental Pb-exposure.

Profiling epigenetic changes in human cell line induced by atrazine exposure.

How environmental chemicals can affect and exert their toxic effect at a molecular level has gained significant interest in recent years, not only for understanding their immediate health implications over exposed individuals, but also for their subsequent progeny. Atrazine (ATZ) is a commonly used herbicide in the U.S. and a long-suspected endocrine disrupting chemical. The molecular mechanism conferring long-term adverse health outcomes, however, remain elusive. Here, we explored changes in epigenetic marks that arise after exposure to ATZ at selected doses using image-based analysis coupled with data clustering. Significant decreases in methylated CpG (meCpG) and histone 3 lysine 9 tri-methylated (H3K9me3) were observed in the selected human cell line with a clear spatial preference. Treating cells with ATZ leads to the loss of a subpopulation of cells with high meCpG levels as identified in our clustering and histogram analysis. A similar trend was observed in H3K9me3 potentially attributing to the cross-talking between meCpG and H3K9me3. Changes in meCpG are likely to be associated with alterations in epigenetic enzyme expression levels regulating meCpG and persist after the removal of ATZ source which collectively provide a plausible mechanism for long-term ATZ-induced toxicity.

GraphProtector: A Visual Interface for Employing and Assessing Multiple Privacy Preserving Graph Algorithms.

Analyzing social networks reveals the relationships between individuals and groups in the data. However, such analysis can also lead to privacy exposure (whether intentionally or inadvertently): leaking the real-world identity of ostensibly anonymous individuals. Most sanitization strategies modify the graph's structure based on hypothesized tactics that an adversary would employ. While combining multiple anonymization schemes provides a more comprehensive privacy protection, deciding the appropriate set of techniques-along with evaluating how applying the strategies will affect the utility of the anonymized results-remains a significant challenge. To address this problem, we introduce GraphProtector, a visual interface that guides a user through a privacy preservation pipeline. GraphProtector enables multiple privacy protection schemes which can be simultaneously combined together as a hybrid approach. To demonstrate the effectiveness of GraphProtector, we report several case studies and feedback collected from interviews with expert users in various scenarios.

MeetingVis: Visual Narratives to Assist in Recalling Meeting Context and Content.

In team-based workplaces, reviewing and reflecting on the content from a previously held meeting can lead to better planning and preparation. However, ineffective meeting summaries can impair this process, especially when participants have difficulty remembering what was said and what its context was. To assist with this process, we introduce MeetingVis, a visual narrative-based approach to meeting summarization. MeetingVis is composed of two primary components: (1) a data pipeline that processes the spoken audio from a group discussion, and (2) a visual-based interface that efficiently displays the summarized content. To design MeetingVis, we create a taxonomy of relevant meeting data points, identifying salient elements to promote recall and reflection. These are mapped to an augmented storyline visualization, which combines the display of participant activities, topic evolutions, and task assignments. For evaluation, we conduct a qualitative user study with five groups. Feedback from the study indicates that MeetingVis effectively triggers the recall of subtle details from prior meetings: all study participants were able to remember new details, points, and tasks compared to an unaided, memory-only baseline. This visual-based approaches can also potentially enhance the productivity of both individuals and the whole team.

Synteny Explorer: An Interactive Visualization Application for Teaching Genome Evolution.

Rapid advances in biology demand new tools for more active research dissemination and engaged teaching. This paper presents Synteny Explorer, an interactive visualization application designed to let college students explore genome evolution of mammalian species. The tool visualizes synteny blocks: segments of homologous DNA shared between various extant species that can be traced back or reconstructed in extinct, ancestral species. We take a karyogram-based approach to create an interactive synteny visualization, leading to a more appealing and engaging design for undergraduate-level genome evolution education. For validation, we conduct three user studies: two focused studies on color and animation design choices and a larger study that performs overall system usability testing while comparing our karyogram-based designs with two more common genome mapping representations in an educational context. While existing views communicate the same information, study participants found the interactive, karyogram-based views much easier and likable to use. We additionally discuss feedback from biology and genomics faculty, who judge Synteny Explorer's fitness for use in classrooms.

Temporal Summary Images: An Approach to Narrative Visualization via Interactive Annotation Generation and Placement.

Visualization is a powerful technique for analysis and communication of complex, multidimensional, and time-varying data. However, it can be difficult to manually synthesize a coherent narrative in a chart or graph due to the quantity of visualized attributes, a variety of salient features, and the awareness required to interpret points of interest (POls). We present Temporal Summary Images (TSIs) as an approach for both exploring this data and creating stories from it. As a visualization, a TSI is composed of three common components: (1) a temporal layout, (2) comic strip-style data snapshots, and (3) textual annotations. To augment user analysis and exploration, we have developed a number of interactive techniques that recommend relevant data features and design choices, including an automatic annotations workflow. As the analysis and visual design processes converge, the resultant image becomes appropriate for data storytelling. For validation, we use a prototype implementation for TSIs to conduct two case studies with large-scale, scientific simulation datasets.