The State‐of‐the‐Art of Set Visualization

Alsallakh, Bilal; Micallef, Luana; Aigner, Wolfgang; Hauser, Helwig; Miksch, Silvia; Rodgers, Peter

doi:10.1111/cgf.12722

Cited by 99 publications

(93 citation statements)

References 120 publications

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“…Options for visualization: The visualization of uncertainty in sets did not receive much attention up to now [38]. For the visualization of fuzzy sets it has been suggested to position data points on rings with a different diameter within a circular set area, based on their probability [39], or to vary the opacity of the set area accordingly [40,41].…”

Section: Set-typed Uncertaintymentioning

confidence: 99%

Exhibiting Uncertainty: Visualizing Data Quality Indicators for Cultural Collections

2019

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Uncertainty is a standard condition under which large parts of art-historical and curatorial knowledge creation and communication are operating. In contrast to standard levels of data quality in non-historical research domains, historical object and knowledge collections contain substantial amounts of uncertain, ambiguous, contested, or plainly missing data. Visualization approaches and interfaces to cultural collections have started to represent data quality and uncertainty metrics, yet all existing work is limited to representations for isolated metadata dimensions only. With this article, we advocate for a more systematic, synoptic and self-conscious approach to uncertainty visualization for cultural collections. We introduce omnipresent types of data uncertainty and discuss reasons for their frequent omission by interfaces for galleries, libraries, archives and museums. On this basis we argue for a coordinated counter strategy for uncertainty visualization in this field, which will also raise the efforts going into complex interface design and conceptualization. Building on the PolyCube framework for collection visualization, we showcase how multiple uncertainty representation techniques can be assessed and coordinated in a multi-perspective environment. As for an outlook, we reflect on both the strengths and limitations of making the actual wealth of data quality questions transparent with regard to different target and user groups.

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Section: Set-typed Uncertaintymentioning

confidence: 99%

Exhibiting Uncertainty: Visualizing Data Quality Indicators for Cultural Collections

2019

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“…Alsallakh et al [2] provide a comprehensive review of set visualizations, and categorize them into several groups based on their visual characteristics and the type of tasks they can support. Some of these visualizations aim to show the relationships between individual elements of the sets of interest, while others aggregate the set elements into their respective sets and then show the relationships between the sets themselves.…”

Section: Set Visualizationsmentioning

confidence: 99%

“…Some of these visualizations aim to show the relationships between individual elements of the sets of interest, while others aggregate the set elements into their respective sets and then show the relationships between the sets themselves. These aggregation-based techniques are highly scalable in the number of set elements they can represents [2], and therefore, they are better suited for tasks dealing with sets of large cardinality (set size), which is very important for the tasks we envisage for time-sets.…”

Section: Set Visualizationsmentioning

confidence: 99%

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Visualizing narrative patterns in online news media

Koivunen-Niemi

Masoodian

2019

Multimed Tools Appl

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News media play an important role in shaping social reality, and their multimedia narrative content, in particular, can have widespread repercussions in the public's perception of past and present phenomena. Being able to visually track changes in media coverage over time could offer the potential for aiding social change, as well as furthering accountability in journalism. In this paper, we explore how visualizations could be used to examine differences in online media narrative patterns over time and across publications. While there are existing means of visualizing such narrative patterns over time, few address the aspect of co-occurrence of variables in media content. Comparing co-occurrences of variables chronologically can be more useful in identifying patterns and possible biases in media coverage than simply counting the individual occurrences of those variables independently. Here, we present a visualization, called time-sets, which has been designed to support temporal comparisons of such co-occurrences. We also describe an interactive prototype tool we have developed based on time-sets for analysis of multimedia news datasets, using an illustrative case study of news articles published on three online sources over several years. We then report on a user study we have conducted to evaluate the time-sets visualization, and discuss its findings. Keywords Temporal visualization • Co-occurrence visualization • Multimedia content • Time-sets • Visual design • Journalism 1 Introduction Many of the, now iconic, visualizations designed by the likes of William Playfair, Charles Joseph Minard, and Florence Nightingale (for examples of their work see [1]) were originally created and used for raising public awareness of social, political, economic, and other such issues. Similarly, since the early days of widespread newspaper publications in the late 1800s, visualizations-particularly statistical graphs [11]-have been used along with text Masood Masoodian

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“…To allow for effective exploration and analysis of such data, visualization is often used. Indeed, drawing hypergraphs relates to set visualization, an active subfield of information visualization (see the recent survey of Alsallakh et al [3]). Various methods have been developed to visualize set systems for elements fixed in (geo)spatial positions, such as Bubble Sets [8], LineSets [2], Kelp Diagrams [9] and Kelp Fusion [17].…”

Section: Introductionmentioning

confidence: 99%

Short Plane Supports for Spatial Hypergraphs

Castermans

Garderen

Meulemans

et al. 2018

Lecture Notes in Computer Science

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A graph G = (V, E) is a support of a hypergraph H = (V, S) if every hyperedge induces a connected subgraph in G. Supports are used for certain types of hypergraph visualizations. In this paper we consider visualizing spatial hypergraphs, where each vertex has a fixed location in the plane. This is the case, e.g., when modeling set systems of geospatial locations as hypergraphs. By applying established aesthetic quality criteria we are interested in finding supports that yield plane straight-line drawings with minimum total edge length on the input point set V . We first show, from a theoretical point of view, that the problem is NP-hard already under rather mild conditions as well as a negative approximability results. Therefore, the main focus of the paper lies on practical heuristic algorithms as well as an exact, ILP-based approach for computing short plane supports. We report results from computational experiments that investigate the effect of requiring planarity and acyclicity on the resulting support length. Further, we evaluate the performance and trade-offs between solution quality and speed of several heuristics relative to each other and compared to optimal solutions.

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The State‐of‐the‐Art of Set Visualization

Cited by 99 publications

References 120 publications

Exhibiting Uncertainty: Visualizing Data Quality Indicators for Cultural Collections

Exhibiting Uncertainty: Visualizing Data Quality Indicators for Cultural Collections

Visualizing narrative patterns in online news media

Short Plane Supports for Spatial Hypergraphs

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