Edgeless Graph: A New Graph-Based Information Visualization Technique

2021 ◽  
pp. 451-461
Author(s):  
Mahipal Jadeja ◽  
Rahul Muthu
Keyword(s):  
Information Visualization ◽  
Visualization Technique

Dust & Magnet: Multivariate Information Visualization Using a Magnet Metaphor

2005 ◽  
Vol 4 (4) ◽  
pp. 239-256 ◽  
Author(s):  
Ji Soo Yi ◽  
Rachel Melton ◽  
John Stasko ◽  
Julie A. Jacko
Keyword(s):  
General Population ◽  
Information Visualization ◽  
Real World ◽  
Daily Life ◽  
Information Age ◽  
Visualization Tool ◽  
Visualization Technique ◽  
Visualization Techniques

The use of multivariate information visualization techniques is intrinsically difficult because the multidimensional nature of data cannot be effectively presented and understood on real-world displays, which have limited dimensionalities. However, the necessity to use these techniques in daily life is increasing as the amount and complexity of data grows explosively in the information age. Thus, multivariate information visualization techniques that are easier to understand and more accessible are needed for the general population. In order to meet this need, the present paper proposes Dust & Magnet, a multivariate information visualization technique using a magnet metaphor and various interactive techniques. The intuitive magnet metaphor and subsequent interactions facilitate the ease of learning this multivariate information visualization technique. A visualization tool such as Dust & Magnet has the potential to increase the acceptance of and utility for multivariate information by a broader population of users who are not necessarily knowledgeable about multivariate information visualization techniques.

scholarly journals Information Visualization from the Perspective of Big Data Analysis and Fusion

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xiang Lin
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Information Visualization ◽  
Big Data Analysis ◽  
Experimental Results ◽  
Data Sources ◽  
Visualization Technique ◽  
Data Volume ◽  
Data Environment ◽  
Information Association

In the big data environment, the visualization technique has been increasingly adopted to mine the data on library and information (L&I), with the diversification of data sources and the growth of data volume. The previous research into the information association of L&I visualization network rarely tries to construct such a network or explore the information association of the network. To overcome these defects, this paper explores the visualization of L&I from the perspective of big data analysis and fusion. Firstly, the authors analyzed the topology of the L&I visualization network and calculated the metrics for the construction of L&I visualization topology map. Next, the importance of meta-paths of the L&I visualization network was calculated. Finally, a complex big data L&I visualization network was established, and the associations between information nodes were analyzed in detail. Experimental results verify the effectiveness of the proposed algorithm.

EmojiText: An Information Visualization Technique for Analyzing Phrases and Sentiments

2021 ◽  
Author(s):  
Iuri Costa ◽  
Rodrigo Lima ◽  
Carlos Gustavo Resque dos Santos ◽  
Bianchi Serique Meiguins ◽  
Anderson Gregorio Marques Soares ◽  
...  
Keyword(s):  
Information Visualization ◽  
Visualization Technique

scholarly journals Information Visualization from the Perspective of Big Data Analysis and Fusion

2021 ◽  
Vol 20 ◽  
pp. 352-361
Author(s):  
Xiang Lin
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Information Visualization ◽  
Information Fusion ◽  
Big Data Analysis ◽  
Data Sources ◽  
Visualization Technique ◽  
Network Layout ◽  
Data Volume ◽  
Data Environment

In the big data environment, the visualization technique has been increasingly adopted to mine the data on library and information (L&I), with the diversification of data sources and the growth of data volume. However, there are several defects with the research on information association of L&I visualization network: the lack of optimization of network layout algorithms, and the absence of L&I information fusion and comparison in multiple disciplines, in the big data environment. To overcome these defects, this paper explores the visualization of L&I from the perspective of big data analysis and fusion. Firstly, the authors analyzed the topology of the L&I visualization network, and calculated the metrics for the construction of L&I visualization topology map. Next, the importance of meta-paths of the L&I visualization network was calculated. Finally, a complex big data L&I visualization network was established, and the associations between information nodes were analyzed in details. Experimental results verify the effectiveness of the proposed algorithm

scholarly journals Visualizing Populated Ontologies with OntoTrix

2013 ◽  
Vol 9 (4) ◽  
pp. 17-40 ◽  
Author(s):  
Benjamin Bach ◽  
Emmanuel Pietriga ◽  
Ilaria Liccardi
Keyword(s):  
Social Network ◽  
Information Visualization ◽  
Adjacency Matrix ◽  
Network Visualization ◽  
Visualization Technique ◽  
Matrix Representations ◽  
Level Data ◽  
Complex Graph ◽  
Visualization Techniques ◽  
Different Parts

Research on visualizing Semantic Web data has yielded many tools that rely on information visualization techniques to better support the user in understanding and editing these data. Most tools structure the visualization according to the concept definitions and interrelations that constitute the ontology’s vocabulary. Instances are often treated as somewhat peripheral information, when considered at all. These instances, that populate ontologies, represent an essential part of any knowledge base. Understanding instance-level data might be easier for users because of their higher concreteness, but instances will often be orders of magnitude more numerous than the concept definitions that give them machine-processable meaning. As such, the visualization of instance-level data poses different but real challenges. The authors present a visualization technique designed to enable users to visualize large instance sets and the relations that connect them. This visualization uses both node-link and adjacency matrix representations of graphs to visualize different parts of the data depending on their semantic and local structural properties. The technique was originally devised for simple social network visualization. The authors extend it to handle the richer and more complex graph structures of populated ontologies, exploiting ontological knowledge to drive the layout of, and navigation in, the representation embedded in a smooth zoomable environment.

scholarly journals A Visualization Technique to Support Searching Filtering

2019 ◽  
Vol 255 ◽  
pp. 05003
Author(s):  
Mohammad Najah Mehdi ◽  
Abdul Rahim Ahmad ◽  
Roslan Ismail
Keyword(s):  
Literature Review ◽  
Information Visualization ◽  
Web Sites ◽  
Search Engines ◽  
Information Overload ◽  
Visual Representation ◽  
Exploratory Search ◽  
Visualization Technique ◽  
Data Overload

This paper discusses the need for an integrative literature review on Information Visualization for exploratory search particularly in handling data overload. The paper analyses many applications and web sites across disciplines. Certain search engines incorporate visualization to allow for better understanding of the information and at the same time reduce information overload. Current search engines use the query and response (lookup) process. Exploratory search allows for open-ended search. Visual representation is one feature in exploratory search that can be used to improve the overall search. The main contribution of this paper is the review of previous exploratory-search-based works, the utilised features as well as its existing applications, visualizations as the mechanism for developing filters to narrow down the results of searching. Many studies have shown that replacing traditional search engines with exploratory search by using the features of exploratory search can reduce the data overload.

GeoTime Information Visualization

2005 ◽  
Vol 4 (2) ◽  
pp. 136-146 ◽  
Author(s):  
Thomas Kapler ◽  
William Wright
Keyword(s):  
Association Analysis ◽  
Information Visualization ◽  
Three Dimensional ◽  
Potential Utility ◽  
Visualization Technique ◽  
Aggregation Methods ◽  
Common Task ◽  
Business Analysis ◽  
Over Time

Analyzing observations over time and geography is a common task, but typically requires multiple, separate tools. The objective of our research has been to develop a method to visualize, and work with, the spatial inter-connectedness of information over time and geography within a single, highly interactive three-dimensional (3-D) view. A novel visualization technique for displaying and tracking events, objects and activities within a combined temporal and geospatial display has been developed. This technique has been implemented as a demonstrable prototype called GeoTime in order to determine potential utility. Capabilities include descriptive events and relationships, association analysis, event aggregation methods and geo-located linked charting. Initial evaluations have been with military users. However, we believe the concept is applicable to a variety of government and business analysis tasks.

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