Many real world data can be modeled by a graph with a set of nodes interconnected to each other by multiple relationships. Such a rich graph is called multilayer graph or network. Providing useful visualization tools ...
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Many real world data can be modeled by a graph with a set of nodes interconnected to each other by multiple relationships. Such a rich graph is called multilayer graph or network. Providing useful visualization tools to support the query process for such graphs is challenging. Although many approaches have addressed the visual query construction, few efforts have been done to provide a contextualized exploration of query results and suggestion strategies to refine the original query. This is due to several issues such as i) the size of the graphs ii) the large number of retrieved results and iii) the way they can be organized to facilitate their exploration. In this article, we present VERTIGo, a novel visual platform to query, explore and support the analysis of large multilayer graphs. VERTIGo provides coordinated views to navigate and explore the large set of retrieved results at different granularity levels. In addition, the proposed system supports the refinement of the query by visual suggestions to guide the user through the exploration process. Two examples and a user study demonstrate how VERTIGo can be used to perform visualanalysis (query, exploration, and suggestion) on real world multilayer networks.
This paper focuses on the fundamental role played by annotations to support provenance analysis in visualexploration processes of large datasets. Particularly, we investigate the use of annotations during the visual ...
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ISBN:
(纸本)9783031099175;9783031099168
This paper focuses on the fundamental role played by annotations to support provenance analysis in visualexploration processes of large datasets. Particularly, we investigate the use of annotations during the visualexploration of semantic datasets assisted by chained visualization techniques. In this paper, we identify three potential uses of annotations: (i) documenting findings (including errors in the dataset), (ii) supporting collaborative reasoning among teammates, and (iii) analysing provenance during the exploratory process. To demonstrate the feasibility of our approach, we implemented it as a tool support, while illustrating its usage and effectiveness through a series of use case scenarios. We identify the attributes and meta-data that describe the dependencies between annotations and visual representations, and we illustrate these dependencies through a domain-specific model.
This paper defines, analyzes, and discusses the emerging genre of visualization atlases. We currently witness an increase in web-based, data-driven initiatives that call themselves "atlases" while explaining...
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This paper defines, analyzes, and discusses the emerging genre of visualization atlases. We currently witness an increase in web-based, data-driven initiatives that call themselves "atlases" while explaining complex, contemporary issues through data and visualizations: climate change, sustainability, AI, or cultural discoveries. To understand this emerging genre and inform their design, study, and authoring support, we conducted a systematic analysis of 33 visualization atlases and semi-structured interviews with eight visualization atlas creators. Based on our results, we contribute (1) a definition of a visualization atlas as a compendium of (web) pages aimed at explaining and supporting exploration of data about a dedicated topic through data, visualizations and narration. (2) a set of design patterns of 8 design dimensions, (3) insights into the atlas creation from interviews and (4) the definition of 5 visualization atlas genres. We found that visualization atlases are unique in the way they combine i) exploratory visualization, ii) narrative elements from data-driven storytelling and iii) structured navigation mechanisms. They target a wide range of audiences with different levels of domain knowledge, acting as tools for study, communication, and discovery. We conclude with a discussion of current design practices and emerging questions around the ethics and potential real-world impact of visualization atlases, aimed to inform the design and study of visualization atlases.
Survey data often encompasses many variables, making it challenging to identify complex relationships. Parallel coordinates visualization offers a powerful solution for exploring these relationships. We propose a web-...
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This paper presents a novel 3D system for human motion analysis - Motion datavisualization and Annotation (MoViAn). Designed to provide a comprehensive visual representation of 3D human motion data, MoViAn incorporat...
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ISBN:
(纸本)9798400704857
This paper presents a novel 3D system for human motion analysis - Motion datavisualization and Annotation (MoViAn). Designed to provide a comprehensive visual representation of 3D human motion data, MoViAn incorporates detailed visualization of gaze direction, hand movements, and object interactions, alongside an interactive interface for efficient data annotation. A user study involving eight participants indicates that MoViAn enables users to thoroughly explore and annotate human motion data, with System Usability Scale (SUS) results demonstrating a satisfactory usability level. The contribution of this paper lies in the development of an interactive and usable data analytics tool aimed at deepening the understanding of human behaviors and intentions in various creative, cognitive, and physical activities that ultimately can facilitate the design and creation of innovative tools that enhance human life in multiple domains.
Recent developments in sensor technology have enabled real-time data acquisition, high-frequency and multimodal data capturing thus underlying the need for monitoring physical or operational conditions in various aspe...
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With the vigorous development of big data technology, the application of data mining program to complete quantitative prediction and evaluation of mineral resources has become a new trend in the development of mineral...
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The paper presents a recommender algorithm for visualanalysis based on data field Schema and Aggregation, and developed an automated dataanalysis solution recommendation system (AutoEDA) in conjunction with the Expl...
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data-centric NLP is a highly iterative process requiring careful exploration of text data throughout entire model development life-cycle. Unfortunately, existing dataexploration tools are not suitable to support data...
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ISBN:
(纸本)9781450394161
data-centric NLP is a highly iterative process requiring careful exploration of text data throughout entire model development life-cycle. Unfortunately, existing dataexploration tools are not suitable to support data-centric NLP because of workfow discontinuity and lack of support for unstructured text. In response, we propose Weedle, a seamless and customizable exploratory text analysis system for data-centric NLP. Weedle is equipped with built-in text transformation operations and a suite of visualanalysis features. With its widget, users can compose customizable dashboards interactively and programmatically in computational notebooks.
This paper investigates the application of mobile robotic platforms for visualdata capture in infrastructure inspection tasks. The captured data offer significant value for both manual and automated inspection proces...
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ISBN:
(纸本)9798331516246;9798331516239
This paper investigates the application of mobile robotic platforms for visualdata capture in infrastructure inspection tasks. The captured data offer significant value for both manual and automated inspection processes. It can produce detailed visual information for human inspectors and serve as input for automated systems to detect anomalies or assist inspectors through computer-aided analysis. Additionally, these data can be integrated into the robot navigation system for real-time path optimisation. A critical challenge in optimising data capture is highlighted: balancing the desired precision with the time invested in inspections. The study explores this tradeoff by analysing the impact of motion blur on measurement errors. Capturing high-quality images with minimal motion blur necessitates slower inspection speeds. The findings suggest that for extensive inspection areas, prioritising mid-range object distances can optimise data capture, as errors increase at a slower pace at these distances compared to closer or farther ranges. This research paves the way for further advancements. Future areas of exploration include evaluating noise reduction techniques, incorporating real-world complexities into testing environments, and investigating the impact of capture speed on machine learning algorithms.
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