56 research outputs found
What Exactly is an Insight? A Literature Review
Insights are often considered the ideal outcome of visual analysis sessions.
However, there is no single definition of what an insight is. Some scholars
define insights as correlations, while others define them as hypotheses or aha
moments. This lack of a clear definition can make it difficult to build
visualization tools that effectively support insight discovery. In this paper,
we contribute a comprehensive literature review that maps the landscape of
existing insight definitions. We summarize key themes regarding how insight is
defined, with the goal of helping readers identify which definitions of insight
align closely with their research and tool development goals. Based on our
review, we also suggest interesting research directions, such as synthesizing a
unified formalism for insight and connecting theories of insight to other
critical concepts in visualization research.Comment: Technical report. arXiv admin note: text overlap with
arXiv:2206.0476
Enhancing Personal Informatics Through Social Sensemaking
Personal informatics practices are increasingly common, with a range of consumer technologies available to support, largely individual, interactions with data (e.g., performance measurement and activity/health monitoring). In this paper, we explore the concept of social sensemaking. In contrast to high-level statistics, we posit that social networking and reciprocal sharing of fine-grained self-tracker data can provide valuable context for individuals in making sense of their data. We present the design of an online platform called Citizense Makers (CM), which facilitates group sharing, annotating and discussion of self-tracker data. In a field trial of CM, we explore design issues around willingness to share data reciprocally; the importance of familiarity between individuals; and understandings of common activities in contextualising one's own data
Information Visualisation for Project Management: Case Study of Bath Formula Student Project
This paper contributes to a better understanding and design of dashboards for monitoring of engineering projects based on the projects’ digital footprint and user-centered design approach. The paper presents an explicit insight-based framework for the evaluation of dashboard visualisations and compares the performance of two groups of student engineering project managers against the framework: a group with the dashboard visualisations and a group without the dashboard. The results of our exploratory study demonstrate that student project managers who used the dashboard generated more useful information and exhibited more complex reasoning on the project progress, thus informing knowledge of the provision of information to engineers in support of their project understanding
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Comparing and Improving the Design of Physical Activity Data Visualizations
Heart disease is a leading cause of death in the United States, and older adults are at highest risk of being diagnosed with heart disease. Consistent physical exercise is an effective means of deterring onset of heart disease, and physical activity tracking devices can inspire greater activity in older adults. However, physical activity tracking device abandonment is quite common due to limitations on what can be learned from the activity data that is collected. Better data visualization of physical data presents an opportunity to surpass these limitations. In this thesis, a task-based human subject study was performed with three different data visualizations to gain insight into how the format of physical activity data visualizations impact older adults’ abilities to infer meaning from physical activity data. Participants (n = 30) interacted with a prototype data visualization as well as two data visualizations from popular fitness tracking applications (Fitbit and Strava) and used these visualizations to complete 11 tasks. Results from these tasks show each visualization was able to facilitate users answer some task questions effectively, though no visualizations exhibited strong performance across all tasks. From the successes and shortcomings of each visualization, three key design recommendations for the design of data visualizations for physical activity data were made: 1) make exact values available, 2) summarize data at multiple timescales, and 3) ensure accessibility for the entire population of users
Self-reflection and personal physicalization construction
Self-reflection is a central goal of personal informatics systems, and constructing visualizations from physical tokens has been found to help people reflect on data. However, so far, constructive physicalization has only been studied in lab environments with provided datasets. Our qualitative study investigates the construction of personal physicalizations in people's domestic environments over 2-4 weeks. It contributes an understanding of (1) the process of creating personal physicalizations, (2) the types of personal insights facilitated, (3) the integration of self-reflection in the physicalization process, and (4) its benefits and challenges for self-reflection. We found that in constructive personal physicalization, data collection, construction and self-reflections are deeply intertwined. This extends previous models of visualization creation and data-driven self-reflection. We outline how benefits such as reflection through manual construction, personalization, and presence in everyday life can be transferred to a wider set of digital and physical systems.Postprin
Flexible and Mindful Self-Tracking: Design Implications from Paper Bullet Journals
Digital self-tracking technologies offer many potential
benefits over self-tracking with paper notebooks. However,
they are often too rigid to support people’s practical and
emotional needs in everyday settings. To inform the design
of more flexible self-tracking tools, we examine bullet
journaling: an analogue and customisable approach for
logging and reflecting on everyday life. Analysing a corpus
of paper bullet journal photos and related conversations on
Instagram, we found that individuals extended and adapted
bullet journaling systems to their changing practical and
emotional needs through: (1) creating and combining
personally meaningful visualisations of different types of
trackers, such as habit, mood, and symptom trackers; (2)
engaging in mindful reflective thinking through design
practices and self-reflective strategies; and (3) posting
photos of paper journals online to become part of a selftracking
culture of sharing and learning. We outline two
interrelated design directions for flexible and mindful selftracking:
digitally extending analogue self-tracking and
supporting digital self-tracking as a mindful design practice
Characterizing the Quality of Insight by Interactions: A Case Study
Understanding the quality of insight has become increasingly important with the trend of allowing users to post comments during visual exploration, yet approaches for qualifying insight are rare. This article presents a case study to investigate the possibility of characterizing the quality of insight via the interactions performed. To do this, we devised the interaction of a visualization tool—MediSyn—for insight generation. MediSyn supports five types of interactions: selecting, connecting, elaborating, exploring, and sharing. We evaluated MediSyn with 14 participants by allowing them to freely explore the data and generate insights. We then extracted seven interaction patterns from their interaction logs and correlated the patterns to four aspects of insight quality. The results show the possibility of qualifying insights via interactions. Among other findings, exploration actions can lead to unexpected insights; the drill-down pattern tends to increase the domain values of insights. A qualitative analysis shows that using domain knowledge to guide exploration can positively affect the domain value of derived insights. We discuss the study’s implications, lessons learned, and future research opportunities.Peer reviewe
Insight provenance for spatiotemporal visual analytics: Theory, review, and guidelines
Research on provenance, which focuses on different ways to describe and record the history of changes and advances made throughout an analysis process, is an integral part of visual analytics. This paper focuses on providing the provenance of insight and rationale through visualizations while emphasizing, first, that this entails a profound understanding of human cognition and reasoning and that, second, the special nature of spatiotemporal data needs to be acknowledged in this process. A recently proposed human reasoning framework for spatiotemporal analysis, and four guidelines for the creation of visualizations that provide the provenance of insight and rationale published in relation to that framework, work as a starting point for this paper. While these guidelines are quite abstract, this paper set out to create a set of more concrete guidelines. On the basis of a review of available provenance solutions, this paper identifies a set of key features that are of relevance when providing the provenance of insight and rationale and, on the basis of these features, produces a new set of complementary guidelines that are more practically oriented than the original ones. Together, these two sets of guidelines provide both a theoretical and practical approach to the problem of providing the provenance of insight and rationale. Providing these kinds of guidelines represents a new approach in provenance research
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