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With the rise of short-form video platforms and the increasing availability of data, we see the potential for people to share short-form videos embedded with data in situ (e.g., daily steps when running) to increase the credibility and expressiveness of their stories. However, creating and sharing such videos in situ is challenging since it involves multiple steps and skills (e.g., data visualization creation and video editing), especially for amateurs. By conducting a formative study (N=10) using three design probes, we collected the motivations and design requirements. We then built VisTellAR, a mobile AR authoring tool, to help amateur video creators embed data visualizations in short-form videos in situ. A two-day user study shows that participants (N=12) successfully created various videos with data visualizations in situ and they confirmed the ease of use and learning. AR pre-stage authoring was useful to assist people in setting up data visualizations in reality with more designs in camera movements and interaction with gestures and physical objects to storytelling.

Non-fungible tokens (NFTs) can certify the authenticity and scarcity of digital assets on the blockchain. There is an urgent need to identify impact attributes from various potential factors and further evaluate NFT collectibles. Nevertheless, the task is challenging due to the massive amount of heterogeneous and multi-modal data (e.g., social media text, numerical transaction data, and images) in NFT transactions. To this end, we present an interactive visual analytics system, NFTeller, that provides a dual-centric perspective analysis of NFT transactions. The system i) summarizes the temporal evolution and correlation of transaction patterns and dynamic impact attributes of NFT collection projects; ii) presents an augmented chord diagram with a radial stacked bar chart for exploring the co-collected projects and co-occurring whale accounts. We derive in-depth insights from case studies on a real data set to evaluate the systems' effectiveness and usability. © 2023 IEEE.

Non-fungible tokens (NFTs) have recently gained widespread popularity as an alternative investment. However, the lack of assessment criteria has caused intense volatility in NFT marketplaces. Identifying attributes impacting the market performance of NFT collectibles is crucial but challenging due to the massive amount of heterogeneous and multi-modal data in NFT transactions, e.g., social media texts, numerical trading data, and images. To address this challenge, we introduce an interactive dual-centric visual analytics system, NFTeller, to facilitate users' analysis. First, we collaborate with five domain experts to distill static and dynamic impact attributes and collect relevant data. Next, we derive six analysis tasks and develop NFTeller to present the evolution of NFT transactions and correlate NFTs' market performance with impact attributes. Notably, we create an augmented chord diagram with a radial stacked bar chart to explore intersections between NFT collection projects and whale accounts. Finally, we conduct three case studies and interview domain experts to evaluate the effectiveness and usability of this system. As such, we gain in-depth insights into assessing NFT collectibles and detecting opportune moments for investment. © 2023 ACM.

With the aim of better teaching effectiveness in programing courses, this study provides a framework to easily understand students' coding progress using the data which is produced while they are coding. In particular, we explore the methods to find students who get stuck at coding and make little progress. In HTML courses for programing novices, we collected code revision history including the amount of code update and save times of students. In this paper, we discuss the usefulness of code revision history to understand students' coding progress by describing coding patterns revealed by the analysis of the data, characteristics of coding progress and scalability for programing courses.

Data visualization is powerful in persuading an audience. However, when it is done poorly or maliciously, a visualization may become misleading or even deceiving. Visualizations give further strength to the dissemination of misinformation on the Internet. The visualization research community has long been aware of visualizations that misinform the audience, mostly associated with the terms “lie” and “deceptive.” Still, these discussions have focused only on a handful of cases. To better understand the landscape of misleading visualizations, we open-coded over one thousand real-world visualizations that have been reported as misleading. From these examples, we discovered 74 types of issues and formed a taxonomy of misleading elements in visualizations. We found four directions that the research community can follow to widen the discussion on misleading visualizations: (1) informal fallacies in visualizations, (2) exploiting conventions and data literacy, (3) deceptive tricks in uncommon charts, and (4) understanding the designers' dilemma. This work lays the groundwork for these research directions, especially in understanding, detecting, and preventing them.