How to Write a Visualization Survey Paper: A Starting Point

McNabb, Liam; Laramee, Robert S.

doi:10.2312/eged.20191026

Cited by 6 publications

(2 citation statements)

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“…In our meta‐survey, we map the landscape of survey papers with a specific focus on the visualization of graphs and networks in more detail than McNabb and Laramee [ ML17 ] and this work is, to our knowledge, the first comprehensive meta‐survey in network visualization. We also acknowledge the useful guide by McNabb and Laramee [ ML19 ] about writing survey papers in visualization, which gave us suggestions used in the writing of this paper.…”

Section: A Roadmap For Network Visualizationmentioning

confidence: 99%

Are We There Yet? A Roadmap of Network Visualization from Surveys to Task Taxonomies

Filipov

Arleo

Miksch

2023

Computer Graphics Forum

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Networks are abstract and ubiquitous data structures, defined as a set of data points and relationships between them. Network visualization provides meaningful representations of these data, supporting researchers in understanding the connections, gathering insights, and detecting and identifying unexpected patterns. Research in this field is focusing on increasingly challenging problems, such as visualizing dynamic, complex, multivariate, and geospatial networked data. This ever‐growing, and widely varied, body of research led to several surveys being published, each covering one or more disciplines of network visualization. Despite this effort, the variety and complexity of this research represents an obstacle when surveying the domain and building a comprehensive overview of the literature. Furthermore, there exists a lack of clarification and uniformity between the terminology used in each of the surveys, which requires further effort when mapping and categorizing the plethora of different visualization techniques and approaches. In this paper, we aim at providing researchers and practitioners alike with a “roadmap” detailing the current research trends in the field of network visualization. We design our contribution as a meta‐survey where we discuss, summarize, and categorize recent surveys and task taxonomies published in the context of network visualization. We identify more and less saturated disciplines of research and consolidate the terminology used in the surveyed literature. We also survey the available task taxonomies, providing a comprehensive analysis of their varying support to each network visualization discipline and by establishing and discussing a classification for the individual tasks. With this combined analysis of surveys and task taxonomies, we provide an overarching structure of the field, from which we extrapolate the current state of research and promising directions for future work.

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Section: A Roadmap For Network Visualizationmentioning

confidence: 99%

Are We There Yet? A Roadmap of Network Visualization from Surveys to Task Taxonomies

Filipov

Arleo

Miksch

2023

Computer Graphics Forum

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“…We will contextualize our survey within the state of the art and existing literature in this section. Regarding surveys in information visualization (InfoVis) in general, McNabb and Laramee provided a survey of surveys [ ML19 ] while Rees and Laramee published a survey of information visualization books [ RL19 ]. In these surveys, more papers about specific interaction idioms or visualizations can be found, that are commonly used in InfoVis in general and VPSE specifically.…”

Section: Related Workmentioning

confidence: 99%

Visual Parameter Space Exploration in Time and Space

Piccolotto

Bögl

Miksch

2023

Computer Graphics Forum

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Computational models, such as simulations, are central to a wide range of fields in science and industry. Those models take input parameters and produce some output. To fully exploit their utility, relations between parameters and outputs must be understood. These include, for example, which parameter setting produces the best result (optimization) or which ranges of parameter settings produce a wide variety of results (sensitivity). Such tasks are often difficult to achieve for various reasons, for example, the size of the parameter space, and supported with visual analytics. In this paper, we survey visual parameter space exploration (VPSE) systems involving spatial and temporal data. We focus on interactive visualizations and user interfaces. Through thematic analysis of the surveyed papers, we identify common workflow steps and approaches to support them. We also identify topics for future work that will help enable VPSE on a greater variety of computational models.

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