Editorial of the special issue on quantified self and personal informatics

In recent years, we witnessed the spreading of a plethora of wearable and mobile technologies allowing for a continuous and “transparent” gathering of personal data [...

Geospatial big data and cartography : research challenges and opportunities for making maps that matter

Geospatial big data present a new set of challenges and opportunities for cartographic researchers in technical, methodological, and artistic realms. New computational and technical paradigms for cartography are accompanying the rise of geospatial big data. Additionally, the art and science of cartography needs to focus its contemporary efforts on work that connects to outside disciplines and is grounded in problems that are important to humankind and its sustainability. Following the development of position papers and a collaborative workshop to craft consensus around key topics, this article presents a new cartographic research agenda focused on making maps that matter using geospatial big data. This agenda provides both long-term challenges that require significant attention as well as short-term opportunities that we believe could be addressed in more concentrated studies.PostprintPeer reviewe

A visual exploration of cybersecurity concepts

Funding: This research was funded by the UK EPSRC under grant EP/N028228/1 (PACTMAN).Cybersecurity-related concepts can be difficult to explain or summarise. The complexity associated with these concepts is compounded by the impact of rapid technological changes and the contextual nature of the meaning ascribed to the various themes. Since visual imagery is often employed in articulation and explanation, we conducted a study in which we asked participants to sketch their understanding of cybersecurity concepts. Based on an analysis of these sketches and subsequent discussions with participants, we make the case for the use of sketching and visuals as a tool for cybersecurity research. Our collection of sketches and icons can further serve as the seed for a visual vocabulary for cybersecurity-related interfaces and communication

The Influence of Visual Provenance Representations on Strategies in a Collaborative Hand-off Data Analysis Scenario

Conducting data analysis tasks rarely occur in isolation. Especially in intelligence analysis scenarios where different experts contribute knowledge to a shared understanding, members must communicate how insights develop to establish common ground among collaborators. The use of provenance to communicate analytic sensemaking carries promise by describing the interactions and summarizing the steps taken to reach insights. Yet, no universal guidelines exist for communicating provenance in different settings. Our work focuses on the presentation of provenance information and the resulting conclusions reached and strategies used by new analysts. In an open-ended, 30-minute, textual exploration scenario, we qualitatively compare how adding different types of provenance information (specifically data coverage and interaction history) affects analysts' confidence in conclusions developed, propensity to repeat work, filtering of data, identification of relevant information, and typical investigation strategies. We see that data coverage (i.e., what was interacted with) provides provenance information without limiting individual investigation freedom. On the other hand, while interaction history (i.e., when something was interacted with) does not significantly encourage more mimicry, it does take more time to comfortably understand, as represented by less confident conclusions and less relevant information-gathering behaviors. Our results contribute empirical data towards understanding how provenance summarizations can influence analysis behaviors.Comment: to be published in IEEE Vis 202

Visualizing Source Code as Comics Using Generative AI

The architecture and inner structure of software is often only implicitly available in the form of its source code and thus not tangible and intuitively easy to understand for non-programmers and laymen. Our goal is to create visualizations as automatically as possible, with which such people can nevertheless understand the software or parts of the software and get a feel for the structure of the software and how its methods work. Especially for newcomers to software projects, for management or even for students and pupils, it can be helpful to get a non-technical insight into the software. We use the concept of visualizing information as comics to present aspects of the software as strikingly as possible, as comics are an effective way to present complex systems and interrelationships for certain target groups. For this purpose, we present a method to generate comics from source code. Our semi-automated process is based on generating a prompt for an LLM from source code, which in turn generates a prompt for a comic image generation using the text-to-image model Stable Diffusion. We show that generative AI methods can be used to rapidly generate human-compatible artistic representations from source code. However, further research is needed to validate the understandability of the results

ToonNote: Improving Communication in Computational Notebooks Using Interactive Data Comics

Computational notebooks help data analysts analyze and visualize datasets, and share analysis procedures and outputs. However, notebooks typically combine code (e.g., Python scripts), notes, and outputs (e.g., tables, graphs). The combination of disparate materials is known to hinder the comprehension of notebooks, making it difficult for analysts to collaborate with other analysts unfamiliar with the dataset. To mitigate this problem, we introduce ToonNote, a JupyterLab extension that enables the conversion of notebooks into “data comics.” ToonNote provides a simplified view of a Jupyter notebook, highlighting the most important results while supporting interactive and free exploration of the dataset. This paper presents the results of a formative study that motivated the system, its implementation, and an evaluation with 12 users, demonstrating the effectiveness of the produced comics. We discuss how our findings inform the future design of interfaces for computational notebooks and features to support diverse collaborators

Dynamic Network Plaid

Network data that changes over time can be very useful for studying a wide range of important phenomena, from how social network connections change to epidemiology. However, it is challenging to analyze, especially if it has many actors, connections or if the covered timespan is large with rapidly changing links (e.g., months of changes with changes at second resolution). In these analyses one would often like to compare many periods of time to others, without having to look at the full timeline. To support this kind of analysis we designed and implemented a technique and system to visualize this dynamic data. The Dynamic Network Plaid (DNP) is designed for large displays and based on user-generated interactive timeslicing on the dynamic graph attributes and on linked provenance-preserving representations. We present the technique, interface and the design/evaluation with a group of public health researchers investigating non-suicidal self-harm picture sharing in Instagram

Development of E-Comic Based on Local Wisdom to Improve Scientific Literacy

This research is the development of local wisdom-based e-comics to increase scientific literacy. Learning media can help achieve learning objectives. This study aims to develop e-comic learning media based on local wisdom to improve scientific literacy in grade IV elementary school. The type of research used is Research and Development with the ADDIE development model namely Analyze, Design, Development, Implementation, and Evaluation. This study used test subjects by carrying out validity tests on media experts, material experts, learning experts and the responses of ten fourth grade elementary school students. Data collection using a questionnaire instrument. Research data were analyzed by means of descriptive quantitative and descriptive qualitative. The results of the media expert validator are categorized as very valid. The results of the material expert validator are categorized as very valid. The results of the learning expert validator are categorized as very valid. As well as the results of the responses of ten fourth grade elementary school students categorized as very valid. The overall results of the validator test are categorized as very valid so that e-comic media based on local wisdom can be used with learning alternative energy sources in grade IV Elementary School Science lessons

Sea of Genes: Combining Animation and Narrative Strategies to Visualize Metagenomic Data for Museums

We examine the application of narrative strategies to present a complex and unfamiliar metagenomics dataset to the public in a science museum. Our dataset contains information about microbial gene expressions that scientists use to infer the behavior of microbes. This exhibit had three goals: to inform (the) public about microbes' behavior, cycles, and patterns; to link their behavior to the concept of gene expression; and to highlight scientists' use of gene expression data to understand the role of microbes. To address these three goals, we created a visualization with three narrative layers, each layer corresponding to a goal. This study presented us with an opportunity to assess existing frameworks for narrative visualization in a naturalistic setting. We present three successive rounds of design and evaluation of our attempts to engage visitors with complex data through narrative visualization. We highlight our design choices and their underlying rationale based on extant theories. We conclude that a central animation based on a curated dataset could successfully achieve our first goal, i.e., to communicate the aggregate behavior and interactions of microbes. We failed to achieve our second goal and had limited success with the third goal. Overall, this study highlights the challenges of telling multi-layered stories and the need for new frameworks for communicating layered stories in public settings.Comment: This manuscript has been accepted to VIS 2020 and TVCG 9 pages 2 reference

Archival Vagabonds: 20th-Century American Fiction and the Archive in Novelistic Practice

My research explores the interplay between the archival and aesthetic sensibilities of novelists not typically associated with archival practices--Claude McKay, Richard Wright, Ralph Ellison, and Jack Kerouac. In juxtaposing their dual roles as public novelists and private archivists, I expose how their literary practices echo with core concepts in archival theory and position the novel as an alternative and superior site of historical preservation. Drawing on my experience as an archivist, I argue that the twentieth-century American novel's concern with inclusivity, preservation and posterity parallels archival science's changing approach to ephemera, arrangement, and diversity. The role of the archive in my work is both methodological and thematic: first, my own research incorporates these authors' cache of research materials, correspondence, drafts, diaries, and aborted or unpublished pieces, obtained during my visits to their various repositories. Second, I extricate the role of the archival in their fictions, and trace how their research, documentation, and classification practices inform their experiments with the novel form. I propose that all these vagabond masters of novelistic craft throw into relief the archive's positivist fallibility while also stressing its creative mutability