Reflections on the evolution of the Jigsaw visual analytics system

2013 ◽  
Vol 13 (4) ◽  
pp. 336-345 ◽  
Author(s):  
Carsten Görg ◽  
Zhicheng Liu ◽  
John Stasko
Keyword(s):  
Visual Analytics ◽  
Important Task ◽  
Design And Development ◽  
Document Collections ◽  
Over Time

Analyzing and understanding collections of textual documents is an important task for professional analysts and a common everyday scenario for nonprofessionals. We have developed the Jigsaw visual analytics system to support these types of sensemaking activities. Jigsaw’s development benefited significantly from the existence of the VAST Contest/Challenge that provided (1) diverse document collections to use as examples, (2) controlled exercises with a set of analytic tasks and solutions for judging results, and (3) visibility and publicity to help communicate our ideas to others. This article describes our participation in a series of VAST Contest/Challenge efforts and how this participation helped influence Jigsaw’s design and development. We describe how the system’s capabilities have evolved over time, and we identify the particular lessons that we learned by participating in the challenges.

Using the Building Blocks

2010 ◽  
Vol 2 (3) ◽  
pp. 43-55
Author(s):  
Joe Lamantia
Keyword(s):  
Building Blocks ◽  
Design Framework ◽  
Design And Development ◽  
Over Time

This article is a case study that explores the use of the Building Blocks portal design framework over a series of enterprise portal projects spanning several years. This article describes the business contexts that shaped each portal as it was designed, showing the use and reuse of design and development elements based on the Building Blocks. This article discusses the changes and adaptations that shaped the elements of the Building Blocks design framework over time.

scholarly journals Story Tracker: Incremental visual text analytics of news story development

2013 ◽  
Vol 12 (3-4) ◽  
pp. 308-323 ◽  
Author(s):  
Miloš Krstajić ◽  
Mohammad Najm-Araghi ◽  
Florian Mansmann ◽  
Daniel A Keim
Keyword(s):  
Visual Analytics ◽  
Time Windows ◽  
Clustering Algorithms ◽  
Temporal Analysis ◽  
Online News ◽  
Full Detail ◽  
News Story ◽  
The Past ◽  
Split And Merge ◽  
Over Time

Online news sources produce thousands of news articles every day, reporting on local and global real-world events. New information quickly replaces the old, making it difficult for readers to put current events in the context of the past. The stories about these events have complex relationships and characteristics that are difficult to model: they can be weakly or strongly related or they can merge or split over time. In this article, we present a visual analytics system for temporal analysis of news stories in dynamic information streams, which combines interactive visualization and text mining techniques to facilitate the analysis of similar topics that split and merge over time. Text clustering algorithms extract stories from online news streams in consecutive time windows and identify similar stories from the past. The stories are displayed in a visualization, which (1) sorts the stories by minimizing clutter and overlap from edge crossings, (2) shows their temporal characteristics in different time frames with different levels of detail, and (3) allows incremental updates of the display without recalculating the past data. Stories can be interactively filtered by their duration and connectivity in order to be explored in full detail. To demonstrate the system’s capabilities for detailed dynamic text stream exploration, we present a use case with real news data about the Arabic Uprising in 2011.

The Understanding of Spatial-Temporal Behaviors

2018 ◽  
pp. 1344-1354
Author(s):  
Yu-Jin Zhang
Keyword(s):  
Computer Vision ◽  
Image Understanding ◽  
Research Field ◽  
Cutting Edge ◽  
Important Task ◽  
Temporal Behavior ◽  
Time And Space ◽  
Behavior Understanding ◽  
Fast Development ◽  
Over Time

This chapter introduces a cutting-edge research field of computer vision and image understanding – the spatial-temporal behavior understanding. The main concepts, the focus of research, the typical technology, the fast development, etc. of this new field in recent years are overviewed. An important task in computer vision and image understanding is to analyze the scene through image operation on the image of scene in order to guide the action. To do this, one needs to locate the objects in the scene, and to determine how they change its position, attitude, speed and relationships in the space over time. In short, it is to grasp the action in time and space, to determine the purpose of the operation, and thus to understand the semantics of the information they passed. This is refereed as the understanding of spatial-temporal behaviors.

scholarly journals StanceVis Prime: visual analysis of sentiment and stance in social media texts

2020 ◽  
Vol 23 (6) ◽  
pp. 1015-1034
Author(s):  
Kostiantyn Kucher ◽  
Rafael M. Martins ◽  
Carita Paradis ◽  
Andreas Kerren
Keyword(s):  
Social Media ◽  
Visual Analytics ◽  
Visual Analysis ◽  
Research Problem ◽  
Data Sources ◽  
Data Series ◽  
Text Documents ◽  
Document Collections ◽  
Social Media Data ◽  
Media Data

Abstract Text visualization and visual text analytics methods have been successfully applied for various tasks related to the analysis of individual text documents and large document collections such as summarization of main topics or identification of events in discourse. Visualization of sentiments and emotions detected in textual data has also become an important topic of interest, especially with regard to the data originating from social media. Despite the growing interest in this topic, the research problem related to detecting and visualizing various stances, such as rudeness or uncertainty, has not been adequately addressed by the existing approaches. The challenges associated with this problem include the development of the underlying computational methods and visualization of the corresponding multi-label stance classification results. In this paper, we describe our work on a visual analytics platform, called StanceVis Prime, which has been designed for the analysis of sentiment and stance in temporal text data from various social media data sources. The use case scenarios intended for StanceVis Prime include social media monitoring and research in sociolinguistics. The design was motivated by the requirements of collaborating domain experts in linguistics as part of a larger research project on stance analysis. Our approach involves consuming documents from several text stream sources and applying sentiment and stance classification, resulting in multiple data series associated with source texts. StanceVis Prime provides the end users with an overview of similarities between the data series based on dynamic time warping analysis, as well as detailed visualizations of data series values. Users can also retrieve and conduct both distant and close reading of the documents corresponding to the data series. We demonstrate our approach with case studies involving political targets of interest and several social media data sources and report preliminary user feedback received from a domain expert. Graphic abstract

scholarly journals Visual Exploration of Energy Use in EU 28: Dynamics, Patterns, Policies

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7532
Author(s):  
George Halkos ◽  
Kyriaki Tsilika
Keyword(s):  
Energy Consumption ◽  
Visual Analytics ◽  
Energy Use ◽  
Visual Exploration ◽  
Dependence Structure ◽  
Low Carbon ◽  
Pollution Effects ◽  
Cross Sectional ◽  
Systematic Analysis ◽  
Over Time

The paper places emphasis on primary energy resources, their covariation, and their correlation with socioeconomic factors and aims to provide a systematic analysis of their development over time. The analysis uses evidence from European Union (EU) country-level data and is based on visual analytics techniques. Different results from the same territories show that energy consumption does not always reflect or is due to climatological or meteorological conditions. Extensive use of visualization is adopted as a means of contributing to the understanding of energy use, some involved problems and concepts, and energy consumption trends over time. We present an approach that addresses the informatics challenges based on the integration of visualization software, data integration, and cluster analysis. Our cross-sectional energy review advocates that EU energy leaders are moving towards a low-carbon economy. The correlations of energy variables with economic and pollution effects are stronger in greater levels of energy use, which means that energy use has an obvious impact on economic growth and the environment. Visual and automated methods employed for the analysis, reveal the direction, the strength, and the nature of the dependence structure, in clusters covering the range of energy use in EU 28 countries.

The Understanding of Spatial-Temporal Behaviors

2019 ◽  
pp. 392-405
Author(s):  
Yu-Jin Zhang
Keyword(s):  
Computer Vision ◽  
Image Understanding ◽  
Research Field ◽  
Cutting Edge ◽  
Important Task ◽  
Temporal Behavior ◽  
Time And Space ◽  
Behavior Understanding ◽  
Fast Development ◽  
Over Time

This chapter introduces a cutting-edge research field of computer vision and image understanding – the spatial-temporal behavior understanding. The main concepts, the focus of research, the typical technology, the fast development, etc. of this new field in recent years are overviewed. An important task in computer vision and image understanding is to analyze the scene through image operation on the image of scene in order to guide the action. To do this, one needs to locate the objects in the scene, and to determine how they change its position, attitude, speed, and relationships in the space over time. In short, it is to grasp the action in time and space, to determine the purpose of the operation, and thus to understand the semantics of the information they passed. This is referred ti as the understanding of spatial-temporal behaviors.

Using the Building Blocks

2012 ◽  
pp. 259-271
Author(s):  
Joe Lamantia
Keyword(s):  
Building Blocks ◽  
Design Framework ◽  
Design And Development ◽  
Over Time

This article is a case study that explores the use of the Building Blocks portal design framework over a series of enterprise portal projects spanning several years. This article describes the business contexts that shaped each portal as it was designed, showing the use and reuse of design and development elements based on the Building Blocks. This article discusses the changes and adaptations that shaped the elements of the Building Blocks design framework over time.

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