| information visualization|
(Alternative names for this keyword)
|Related keyword(s)||visualization, visualization tool|
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information visualization is included as keyword or extra keyword in 0 datasets, 1 tools and 22 publications.
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|Tool||Operating System(s)||Language(s)||Programming language(s)||License||Description||Image|
|Wiki Category Matrix Visualization||Cross-platform||English||Java||Educational Community License||Wiki Category Matrix Visualization is a tool that generates a visual representation of data sizes across topics of a multi-level category hierarchy in matrix form. It provides a "big picture" overview of topics in terms of categorization.|
|Title||Author(s)||Published in||Language||DateThis property is a special property in this wiki.||Abstract||R||C|
|Visualizing large-scale human collaboration in Wikipedia||Biuk-Aghai R.P.
|Future Generation Computer Systems||English||2014||Volunteer-driven large-scale human-to-human collaboration has become common in the Web 2.0 era. Wikipedia is one of the foremost examples of such large-scale collaboration, involving millions of authors writing millions of articles on a wide range of subjects. The collaboration on some popular articles numbers hundreds or even thousands of co-authors. We have analyzed the co-authoring across entire Wikipedias in different languages and have found it to follow a geometric distribution in all the language editions we studied. In order to better understand the distribution of co-author counts across different topics, we have aggregated content by category and visualized it in a form resembling a geographic map. The visualizations produced show that there are significant differences of co-author counts across different topics in all the Wikipedia language editions we visualized. In this article we describe our analysis and visualization method and present the results of applying our method to the English, German, Chinese, Swedish and Danish Wikipedias. We have evaluated our visualization against textual data and found it to be superior in usability, accuracy, speed and user preference. © 2013 Elsevier B.V. All rights reserved.||0||0|
|A novel map-based visualization method based on liquid modelling||Biuk-Aghai R.P.
|ACM International Conference Proceeding Series||English||2013||Many applications produce large amounts of data, and information visualization has been successfully applied to help make sense of this data. Recently geographic maps have been used as a metaphor for visualization, given that most people are familiar with reading maps, and several visualization methods based on this metaphor have been developed. In this paper we present a new visualization method that aims to improve on existing map-like visualizations. It is based on the metaphor of liquids poured onto a surface that expand outwards until they touch each other, forming larger areas. We present the design of our visualization method and an evaluation we have carried out to compare it with an existing visualization. Our new visualization has better usability, leading to higher accuracy and greater speed of task performance.||0||0|
|Visualizing recent changes in Wikipedia||Biuk-Aghai R.P.
|Science China Information Sciences||English||2013||Large wikis such as Wikipedia attract large numbers of editors continuously editing content. It is difficult to observe what editing activity goes on at any given moment, what editing patterns can be observed, and which are the currently active editors and articles. We introduce the design and implementation of an information visualization tool for data streams of recent changes in wikis that aims to address this difficulty. We also show examples of our visualizations from English Wikipedia, and present several patterns of editing activity that we have visually identified using our tool. We have evaluated our tool's usability, accuracy and speed of task performance in comparison with Wikipedia's recent changes page, and have obtained qualitative feedback from users on the pros and cons of our tool. We also present a review of the related literature.||0||0|
|Extracting knowledge from U.S. department of defense freedom of information act requests with social media||Whitmore A.||Government Information Quarterly||English||2012||The Freedom of Information Act (FOIA) has facilitated the release of large amounts of government information that has been of great value to researchers, journalists, and other interested parties. The fraction of this information released in electronic format has been growing as has its volume. While offering great potential for research, large amounts of data disgorged from government information systems can pose challenges to human interpretation and knowledge extraction. Using the Office of the Secretary of Defense/Joint Staff Freedom of Information Act (FOIA) Logs for 2007-2009, this research identifies (1) a process for finding relationships between the FOIA requests through keywords extracted from Wikipedia and (2) a technique for visualizing these relationships in order to provide context and improve understanding when working with born-digital government data.||0||0|
|Feeling the pulse of a wiki: Visualization of recent changes in Wikipedia||Biuk-Aghai R.P.
|ACM International Conference Proceeding Series||English||2012||Large wikis such as Wikipedia attract large numbers of editors continuously editing content. It is difficult to observe what editing activity goes on at any given moment, what editing patterns can be observed, and which are the currently active editors and articles. We introduce the design and implementation of an information visualization tool for streaming data on recent changes in wikis that aims to address this difficulty, show examples of our visualizations from English Wikipedia, and present several patterns of editing activity that we can visually identify using our tool.||0||0|
|Visualization of Wiki-based collaboration through two-mode network patterns||Modritscher F.
|Proceedings of the 12th IEEE International Conference on Advanced Learning Technologies, ICALT 2012||English||2012||Nowadays Wikis are considered to be a useful tool for teaching and learning. However, well-known Wiki solutions do not provide sufficient facilities for analyzing and exploring networked collaboration. In this paper we present a method for detecting and visualizing structural patterns of collaboration in Wikis. Furthermore we summarize findings from applying our approach on a smaller and two larger datasets. Overall, our method allows characterizing Wikis according to collaboration patterns on the basis of two-mode networks but it also enables users to explore large Wiki corpora and provides visual feedback on content creation.||0||0|
|A link-based visual search engine for Wikipedia||David N. Milne
Ian H. Witten
|Exploring Wikipedia with Hōpara||Milne D.N.
|Proceedings of the ACM/IEEE Joint Conference on Digital Libraries||English||2011||[No abstract available]||0||0|
|Visualization of large category hierarchies||Robert P. Biuk-Aghai
Felix Hon Hou Cheang
|Visual Information Communication - International Symposium||English||2011||Large data repositories such as electronic journal databases, document corpora and wikis often organise their content into categories. Librarians, researchers, and interested users who wish to know the content distribution among different categories face the challenge of analysing large amounts of data. Information visualization can assist the user by shifting the analysis task to the human visual sub-system. In this paper we describe three visualization methods we have implemented, which help users understand category hierarchies and content distribution within large document repositories, and present an evaluation of these visualizations, pointing out each of their relative strengths for communicating information about the underlying category structure.||1||0|
|Visualizing author contribution statistics in Wikis using an edit significance metric||Peter Kin-Fong Fong
Robert P. Biuk-Aghai
|WikiSym||English||2011||Wiki articles tend to be edited multiple times by multiple authors. This makes it difficult to identify individual authors’ contributions by human observation alone. We calculate an edit significance metric, using different weights for different types of edits, which reflect the different value placed on them by wiki community members. We then aggregate edit significance values and present them as visualizations to the user to aid in perceiving extent and patterns of contributions.||4||0|
|Wikipedia category visualization using radial layout||Robert P. Biuk-Aghai
Felix Hon Hou Cheang
|WikiSym||English||2011||Wikipedia is a large and popular daily information source for millions of people. How are articles distributed by topic area, and what is the semantic coverage of Wikipedia? Using manual methods it is impractical to determine this. We present the design of an information visualization tool that produces overview diagrams of Wikipedia’s articles distributed according to category relationships, and show examples of visualizing English Wikipedia.||3||0|
|Wikipedia world map: Method and application of map-like wiki visualization||Pang C.-L.
|WikiSym 2011 Conference Proceedings - 7th Annual International Symposium on Wikis and Open Collaboration||English||2011||Wiki are popular platforms for collaborative editing. In volunteer-driven wikis such as Wikipedia, which attracts millions of authors editing articles on a diverse range of topics, contributors' editing activity results in certain semantic coverage of topic areas. Obtaining an understanding of a given wiki's semantic coverage is not easy. To solve this problem, we have devised a method for visualizing a wiki in a way similar to a geographic map. We have applied our method to Wikipedia, and generated visualizations for several Wikipedia language editions. This paper presents our wiki visualization method and its application.||0||0|
|Wikipedia world map: method and application of map-like wiki visualization||Cheong-Iao Pang
Robert P. Biuk-Aghai
|WikiSym||English||2011||Wiki are popular platforms for collaborative editing. In volunteer-driven wikis such as Wikipedia, which attracts millions of authors editing articles on a diverse range of topics, contributors’ editing activity results in certain semantic coverage of topic areas. Obtaining an understanding of a given wiki’s semantic coverage is not easy. To solve this problem, we have devised a method for visualizing a wiki in a way similar to a geographic map. We have applied our method to Wikipedia, and generated visualizations for several Wikipedia language editions. This paper presents our wiki visualization method and its application.||8||0|
|Interactive visualization and navigation of web search results revealing community structures and bridges||Sallaberry A.
|Proceedings - Graphics Interface||English||2010||With the information overload on the Internet, organization and visualization of web search results so as to facilitate faster access to information is a necessity. The classical methods present search results as an ordered list of web pages ranked in terms of relevance to the searched topic. Users thus have to scan text snippets or navigate through various pages before finding the required information. In this paper we present an interactive visualization system for content analysis of web search results. The system combines a number of algorithms to present a novel layout methodology which helps users to analyze and navigate through a collection of web pages. We have tested this system with a number of data sets and have found it very useful for the exploration of data. Different case studies are presented based on searching different topics on Wikipedia through Exalead's search engine.||0||0|
|Model-aware wiki analysis tools: The case of HistoryFlow||Diaz O.
|WikiSym 2010||English||2010||Wikis are becoming mainstream. Studies confirm how wikis are finding their way into organizations. This paper focuses on requirements for analysis tools for corporate wikis. Corporate wikis differ from their grow-up counterparts such as Wikipedia. First, they tend to be much smaller. Second, they require analysis to be customized for their own domains. So far, most analysis tools focus on large wikis where handling efficiently large bulks of data is paramount. This tends to make analysis tools access directly the wiki database. This binds the tool to the wiki engine, hence, jeopardizing customizability and interoperability. However, corporate wikis are not so big while customizability is a desirable feature. This change in requirements advocates for analysis tools to be decoupled from the underlying wiki engines. Our approach argues for characterizing analysis tools in terms of their abstract analysis model (e.g. a graph model, a contributor model). How this analysis model is then map into wiki-implementation terms is left to the wiki administrator. The administrator, as the domain expert, can better assess which is the right terms/granularity to conduct the analysis. This accounts for suitability and interoperability gains. The approach is borne out for HistoryFlow, an IBM tool for visualizing evolving wiki pages and the interactions of multiple wiki authors.||0||0|
|Visualizing empires decline||Cruz P.
|ACM SIGGRAPH 2010 Posters, SIGGRAPH '10||English||2010||This is an information visualization project that narrates the decline of the British, French, Portuguese and Spanish empires during the 19th and 20th centuries. These empires were the main maritime empires in terms of land area during the referred centuries [Wikipedia]. The land area of the empires and its former colonies is continuously represented in the simulation. The size of the empires varies during the simulation as they gain, or lose, territories. The graphic representation forms were selected to attain a narrative that depicts the volatility, instability and dynamics of the expansion and decline of the empires. Furthermore, the graphic representation also aims at emphasizing the contrast between their maximum and current size, and portraying the contemporary heritage and legacy of the empires.||0||0|
|WikipediaViz: Conveying article quality for casual wikipedia readers||Fanny Chevalier
|IEEE Pacific Visualization Symposium 2010, PacificVis 2010 - Proceedings||English||2010||As Wikipedia has become one of the most used knowledge bases worldwide, the problem of the trustworthiness of the information it disseminates becomes central. With WikipediaViz, we introduce five visual indicators integrated to the Wikipedia layout that can keep casual Wikipedia readers aware of important meta-information about the articles they read. The design of WikipediaViz was inspired by two participatory design sessions with expert Wikipedia writers and sociologists who explained the clues they used to quickly assess the trustworthiness of articles. According to these results, we propose five metrics for Maturity and Quality assessment ofWikipedia articles and their accompanying visualizations to provide the readers with important clues about the editing process at a glance. We also report and discuss about the results of the user studies we conducted. Two preliminary pilot studies show that all our subjects trust Wikipedia articles almost blindly. With the third study, we show that WikipediaViz significantly reduces the time required to assess the quality of articles while maintaining a good accuracy.||0||0|
|Vispedia: On-demand data integration for interactive visualization and exploration||Bryan Chan
|SIGMOD-PODS'09 - Proceedings of the International Conference on Management of Data and 28th Symposium on Principles of Database Systems||English||2009||Wikipedia is an example of the large, collaborative, semi-structured data sets emerging on the Web. Typically, before these data sets can be used, they must transformed into structured tables via data integration. We present Vispedia, a Web-based visualization system which incorporates data integration into an iterative, interactive data exploration and analysis process. This reduces the upfront cost of using heterogeneous data sets like Wikipedia. Vispedia is driven by a keyword-query-based integration interface implemented using a fast graph search. The search occurs interactively over DBpedia's semantic graph of Wikipedia, without depending on the existence of a structured ontology. This combination of data integration and visualization enables a broad class of non-expert users to more effectively use the semi-structured data available on the Web.||0||0|
|Visualization of Interactions in Collaborative Writing||Robert P. Biuk-Aghai
|International Conference on Digital Ecosystems and Technologies||English||February 2008||Wikis have become an important component of a collaboration infrastructure, particularly in loosely-coupled and self-organizing settings such as those of digital ecosystems. We report on our use of wikis in the education doman to support collaborative creative writing, as well as collaborative translation. This paper presents an analysis and visualization tool that we have developed as an aid for assessing both the process and the outcome of these collaborative writing tasks.||16||1|
|Vispedia*: Interactive visual exploration of wikipedia data via search-based integration||Bryan Chan
|IEEE Transactions on Visualization and Computer Graphics||English||2008||Wikipedia is an example of the collaborative, semi-structured data sets emerging on the Web. These data sets have large, non-uniform schema that require costly data integration into structured tables before visualization can begin. We present Vispedia, a Web-based visualization system that reduces the cost of this data integration. Users can browse Wikipedia, select an interesting data table, then use a search interface to discover, integrate, and visualize additional columns of data drawn from multiple Wikipedia articles. This interaction is supported by a fast path search algorithm over DBpedia, a semantic graph extracted from Wikipedia's hyperlink structure. Vispedia can also export the augmented data tables produced for use in traditional visualization systems. We believe that these techniques begin to address the "long tail" of visualization by allowing a wider audience to visualize a broader class of data. We evaluated this system in a first-use formative lab study. Study participants were able to quickly create effective visualizations for a diverse set of domains, performing data integration as needed.||0||0|
|The analysis and visualization of entries in Wiki services||Jakub Gawryjolek
|Advances in Soft Computing||English||2007||The use of online collaboration environments has become exceptionally widespread over the past decade. One of the most popular styles of collaboration are the "wik" web sites. They have attracted attention because of their policy of letting anyone become an editor. This paper presents the technique for the analysis and visualization of Wikipedia - the largest wiki in existence. Specifically, it concentrates on some activity patterns of its contributors. First, a new visualization and analysis tool named JWikiVis is presented. Second, with the use of this software, some interesting user behaviors are described. Finally, text classification algorithms are applied in order to determine some patterns observed in individual wiki pages as well as in the entire service.||0||0|
|Visualizing Co-Authorship Networks in Online Wikipedia||Robert P. Biuk-Aghai||International Symposium on Communications and Information Technologies||English||2006||The Wikipedia online user-contributed encyclopedia has rapidly become a highly popular and widely used online reference source. However, perceiving the complex relationships in the network of articles and other entities in Wikipedia is far from easy. We introduce the notion of using co-authorship of articles to determine relationship between articles, and present the WikiVis information visualization system which visualizes this and other types of relationships in the Wikipedia database in 3D graph form. A 3D star layout and a 3D nested cone tree layout are presented for displaying relationships between entities and between categories, respectively. A novel 3D pinboard layout is presented for displaying search results||1||1|