Generative AI for Visualization: Opportunities and Challenges.

Recent developments in artificial intelligence (AI) and machine learning (ML) have led to the creation of powerful generative AI methods and tools capable of producing text, code, images, and other media in response to user prompts. Significant interest in the technology has led to speculation about what fields, including visualization, can be augmented or replaced by such approaches. However, there remains a lack of understanding about which visualization activities may be particularly suitable for the application of generative AI.

The Curse of Performative User Studies.

Computer graphics research frequently evaluates research outputs with user studies, often through online crowdworking platforms. When performed carefully and thoughtfully, studies on human behavior and preferences provide valuable insights, useful for both developing and evaluating new tools. Yet, I argue that many of the current studies are performative: they result from reviewers' expectation that "papers should have some evaluation," not from careful thought about the value and usefulness of the studies themselves.

How to Evaluate If Collaborative Augmented Reality Speaks to Its Users.

Augmented reality (AR) is increasingly considered to support scenarios of co-located and remote collaboration. Thus far, the core goal has been advancing the supporting technologies and assessing how they perform to inform design and development, thus providing support toward their maturity. Nevertheless, while understanding the performance and impact of supporting technology is indisputable groundwork, we argue that the field needs to adopt a framework that moves from answering questions about the proposed methods and technologies to a more holistic view, also encompassing collaboration.

Can Image Data Facilitate Reproducibility of Graphics and Visualizations? Toward a Trusted Scientific Practice.

Reproducibility is a cornerstone of good scientific practice; however, the ongoing "reproducibility crisis" shows that we still need to improve the way we are doing research currently. Reproducibility is crucial because it enables both the comparison to existing techniques as well as the composition and improvement of existing approaches. It can also increase trust in the respective results, which is paramount for adoption in further research and applications.

Notebooks for Data Analysis and Visualization: Moving Beyond the Data.

Notebooks are a relatively new way of analyzing data and creating visualizations. They differ from the common graphical user interfaces used for visualization tools in many ways, and have their own strengths and weaknesses. In particular, they allow easy sharing, experimentation, and collaboration, and provide context about the data for different kinds of users.

Affective Virtual Reality: How to Design Artificial Experiences Impacting Human Emotions.

Computer graphics is-in many cases-about visualizing what you cannot see. However, virtual reality (VR), from its beginnings, aimed at stimulating all human senses: not just the visual channel. Moreover, this set of multisensory stimuli allows users to feel present and able to interact with the virtual environment.

Looking Into a Future Which Hopefully Will Not Become Reality: How Computer Graphics Can Impact Our Behavior-A Study of the Potential of VR.

Humans tendency to engage in behaviors that are harmful to themselves, the environment, and the society has always been present on a personal and collective level. However, the concern for this kind of phenomena is increasing, as demographic and economic growth is amplifying its impact on people health, economies, and ecosystems. As a consequence, we have seen the rise of research fields as design for behavior change, with a growing interest in the use of tools as persuasive technologies, serious games and interactive systems to affect people awareness, attitude, and behavior.

Understanding Failure Mode Effect Analysis Data Using Interactive Visual Analytics.

Providing actionable insights through interactive visual analytics is essential to effective decision making. Yet, many complex systems engineering (SE) domains still lack such tools. Design reviews are often still based on static snapshots of data, without any dynamic interaction, data curation, and view creation capabilities to answer salient analysis questions.

Graphicle: Exploring Units, Networks, and Context in a Blended Visualization Approach.

Many real-world datasets are large, multivariate, and relational in nature and relevant associated decisions frequently require a simultaneous consideration of both attributes and connections. Existing visualization systems and approaches, however, often make an explicit trade-off between either affording rich exploration of individual data units and their attributes or exploration of the underlying network structure. In doing so, important analysis opportunities and insights are potentially missed.

MAQUI: Interweaving Queries and Pattern Mining for Recursive Event Sequence Exploration.

Exploring event sequences by defining queries alone or by using mining algorithms alone is often not sufficient to support analysis. Analysts often interweave querying and mining in a recursive manner during event sequence analysis: sequences extracted as query results are used for mining patterns, patterns generated are incorporated into a new query for segmenting the sequences, and the resulting segments are mined or queried again. To support flexible analysis, we propose a framework that describes the process of interwoven querying and mining.

Duet: Helping Data Analysis Novices Conduct Pairwise Comparisons by Minimal Specification.

Data analysis novices often encounter barriers in executing low-level operations for pairwise comparisons. They may also run into barriers in interpreting the artifacts (e.g.

Chronodes: Interactive Multifocus Exploration of Event Sequences.

The advent of mobile health (mHealth) technologies challenges the capabilities of current visualizations, interactive tools, and algorithms. We present Chronodes, an interactive system that unifies data mining and human-centric visualization techniques to support explorative analysis of longitudinal mHealth data. Chronodes extracts and visualizes frequent event sequences that reveal chronological patterns across multiple participant timelines of mHealth data.

Graphiti: Interactive Specification of Attribute-Based Edges for Network Modeling and Visualization.

Network visualizations, often in the form of node-link diagrams, are an effective means to understand relationships between entities, discover entities with interesting characteristics, and to identify clusters. While several existing tools allow users to visualize pre-defined networks, creating these networks from raw data remains a challenging task, often requiring users to program custom scripts or write complex SQL commands. Some existing tools also allow users to both visualize and model networks.

A Visual Analytics Approach to Understanding Care Process Variation and Conformance.

With greater pressures of providing high-quality care at lower cost due to a changing financial and policy environment, the ability to understand variations in care delivery and associated outcomes and act upon this understanding is of critical importance. Building on prior work in visualizing health-care event sequences and in collaboration with our clinical partner, we describe our process in developing a multiple, coordinated visualization system that helps identify and analyze care processes and their conformance to existing care guidelines. We demonstrate our system using data of 5,784 pediatric emergency department visits over a 13-month period for which asthma was the primary diagnosis.

Understanding variations in pediatric asthma care processes in the emergency department using visual analytics.

Health care delivery processes consist of complex activity sequences spanning organizational, spatial, and temporal boundaries. Care is human-directed so these processes can have wide variations in cost, quality, and outcome making systemic care process analysis, conformance testing, and improvement challenging. We designed and developed an interactive visual analytic process exploration and discovery tool and used it to explore clinical data from 5784 pediatric asthma emergency department patients.

Visual business ecosystem intelligence: lessons from the field.

Macroscopic insight into business ecosystems is becoming increasingly important. With the emergence of new digital business data, opportunities exist to develop rich, interactive visual-analytics tools. Georgia Institute of Technology researchers have been developing and implementing visual business ecosystem intelligence tools in corporate settings.

Understanding interfirm relationships in business ecosystems with interactive visualization.

Business ecosystems are characterized by large, complex, and global networks of firms, often from many different market segments, all collaborating, partnering, and competing to create and deliver new products and services. Given the rapidly increasing scale, complexity, and rate of change of business ecosystems, as well as economic and competitive pressures, analysts are faced with the formidable task of quickly understanding the fundamental characteristics of these interfirm networks. Existing tools, however, are predominantly query- or list-centric with limited interactive, exploratory capabilities.