Search (93 results, page 1 of 5)

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Abstract

QVIZ will research and create a framework for visualizing and querying archival resources by a time-space interface based on maps and emergent knowledge structures. The framework will also integrate social software, such as wikis, in order to utilize knowledge in existing and new communities of practice. QVIZ will lead to improved information sharing and knowledge creation, easier access to information in a user-adapted context and innovative ways of exploring and visualizing materials over time, between countries and other administrative units. The common European framework for sharing and accessing archival information provided by the QVIZ project will open a considerably larger commercial market based on archival materials as well as a richer understanding of European history.

Content

Vortrag anlässlich des Workshops: "Extending the multilingual capacity of The European Library in the EDL project Stockholm, Swedish National Library, 22-23 November 2007".

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Abstract

The "Screen Design Manual" provides designers of interactive media with a practical working guide for preparing and presenting information that is suitable for both their target groups and the media they are using. It describes background information and relationships, clarifies them with the help of examples, and encourages further development of the language of digital media. In addition to the basics of the psychology of perception and learning, ergonomics, communication theory, imagery research, and aesthetics, the book also explores the design of navigation and orientation elements. Guidelines and checklists, along with the unique presentation of the book, support the application of information in practice.

Classification

ST 253 Informatik / Monographien / Software und -entwicklung / Web-Programmierwerkzeuge (A-Z)

Content

From the contents:.- Basics of screen design.- Navigation and orientation.- Information.- Screen layout.Interaction.- Motivation.- Innovative prospects.- Appendix.Glossary.- Literature.- Index

Date

22. 3.2008 14:29:25

LCSH

Information display systems / Formatting

RVK

ST 253 Informatik / Monographien / Software und -entwicklung / Web-Programmierwerkzeuge (A-Z)

Subject

Information display systems / Formatting

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Abstract

This article describes the latest development of a generic approach to detecting and visualizing emerging trends and transient patterns in scientific literature. The work makes substantial theoretical and methodological contributions to progressive knowledge domain visualization. A specialty is conceptualized and visualized as a time-variant duality between two fundamental concepts in information science: research fronts and intellectual bases. A research front is defined as an emergent and transient grouping of concepts and underlying research issues. The intellectual base of a research front is its citation and co-citation footprint in scientific literature - an evolving network of scientific publications cited by research-front concepts. Kleinberg's (2002) burst-detection algorithm is adapted to identify emergent research-front concepts. Freeman's (1979) betweenness centrality metric is used to highlight potential pivotal points of paradigm shift over time. Two complementary visualization views are designed and implemented: cluster views and time-zone views. The contributions of the approach are that (a) the nature of an intellectual base is algorithmically and temporally identified by emergent research-front terms, (b) the value of a co-citation cluster is explicitly interpreted in terms of research-front concepts, and (c) visually prominent and algorithmically detected pivotal points substantially reduce the complexity of a visualized network. The modeling and visualization process is implemented in CiteSpace II, a Java application, and applied to the analysis of two research fields: mass extinction (1981-2004) and terrorism (1990-2003). Prominent trends and pivotal points in visualized networks were verified in collaboration with domain experts, who are the authors of pivotal-point articles. Practical implications of the work are discussed. A number of challenges and opportunities for future studies are identified.

Date

22. 7.2006 16:11:05

Source

Journal of the American Society for Information Science and Technology. 57(2006) no.3, S.359-377

Type

a

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Source

Information processing and management. 37(2001) no.4, S.639-657

Type

a

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Date

23. 3.2008 19:10:22

Footnote

Rez. in: JASIST 54(2003) no.9, S.905-906 (C.A. Badurek): "Visual approaches for knowledge discovery in very large databases are a prime research need for information scientists focused an extracting meaningful information from the ever growing stores of data from a variety of domains, including business, the geosciences, and satellite and medical imagery. This work presents a summary of research efforts in the fields of data mining, knowledge discovery, and data visualization with the goal of aiding the integration of research approaches and techniques from these major fields. The editors, leading computer scientists from academia and industry, present a collection of 32 papers from contributors who are incorporating visualization and data mining techniques through academic research as well application development in industry and government agencies. Information Visualization focuses upon techniques to enhance the natural abilities of humans to visually understand data, in particular, large-scale data sets. It is primarily concerned with developing interactive graphical representations to enable users to more intuitively make sense of multidimensional data as part of the data exploration process. It includes research from computer science, psychology, human-computer interaction, statistics, and information science. Knowledge Discovery in Databases (KDD) most often refers to the process of mining databases for previously unknown patterns and trends in data. Data mining refers to the particular computational methods or algorithms used in this process. The data mining research field is most related to computational advances in database theory, artificial intelligence and machine learning. This work compiles research summaries from these main research areas in order to provide "a reference work containing the collection of thoughts and ideas of noted researchers from the fields of data mining and data visualization" (p. 8). It addresses these areas in three main sections: the first an data visualization, the second an KDD and model visualization, and the last an using visualization in the knowledge discovery process. The seven chapters of Part One focus upon methodologies and successful techniques from the field of Data Visualization. Hoffman and Grinstein (Chapter 2) give a particularly good overview of the field of data visualization and its potential application to data mining. An introduction to the terminology of data visualization, relation to perceptual and cognitive science, and discussion of the major visualization display techniques are presented. Discussion and illustration explain the usefulness and proper context of such data visualization techniques as scatter plots, 2D and 3D isosurfaces, glyphs, parallel coordinates, and radial coordinate visualizations. Remaining chapters present the need for standardization of visualization methods, discussion of user requirements in the development of tools, and examples of using information visualization in addressing research problems.
In 13 chapters, Part Two provides an introduction to KDD, an overview of data mining techniques, and examples of the usefulness of data model visualizations. The importance of visualization throughout the KDD process is stressed in many of the chapters. In particular, the need for measures of visualization effectiveness, benchmarking for identifying best practices, and the use of standardized sample data sets is convincingly presented. Many of the important data mining approaches are discussed in this complementary context. Cluster and outlier detection, classification techniques, and rule discovery algorithms are presented as the basic techniques common to the KDD process. The potential effectiveness of using visualization in the data modeling process are illustrated in chapters focused an using visualization for helping users understand the KDD process, ask questions and form hypotheses about their data, and evaluate the accuracy and veracity of their results. The 11 chapters of Part Three provide an overview of the KDD process and successful approaches to integrating KDD, data mining, and visualization in complementary domains. Rhodes (Chapter 21) begins this section with an excellent overview of the relation between the KDD process and data mining techniques. He states that the "primary goals of data mining are to describe the existing data and to predict the behavior or characteristics of future data of the same type" (p. 281). These goals are met by data mining tasks such as classification, regression, clustering, summarization, dependency modeling, and change or deviation detection. Subsequent chapters demonstrate how visualization can aid users in the interactive process of knowledge discovery by graphically representing the results from these iterative tasks. Finally, examples of the usefulness of integrating visualization and data mining tools in the domain of business, imagery and text mining, and massive data sets are provided. This text concludes with a thorough and useful 17-page index and lengthy yet integrating 17-page summary of the academic and industrial backgrounds of the contributing authors. A 16-page set of color inserts provide a better representation of the visualizations discussed, and a URL provided suggests that readers may view all the book's figures in color on-line, although as of this submission date it only provides access to a summary of the book and its contents. The overall contribution of this work is its focus an bridging two distinct areas of research, making it a valuable addition to the Morgan Kaufmann Series in Database Management Systems. The editors of this text have met their main goal of providing the first textbook integrating knowledge discovery, data mining, and visualization. Although it contributes greatly to our under- standing of the development and current state of the field, a major weakness of this text is that there is no concluding chapter to discuss the contributions of the sum of these contributed papers or give direction to possible future areas of research. "Integration of expertise between two different disciplines is a difficult process of communication and reeducation. Integrating data mining and visualization is particularly complex because each of these fields in itself must draw an a wide range of research experience" (p. 300). Although this work contributes to the crossdisciplinary communication needed to advance visualization in KDD, a more formal call for an interdisciplinary research agenda in a concluding chapter would have provided a more satisfying conclusion to a very good introductory text.
With contributors almost exclusively from the computer science field, the intended audience of this work is heavily slanted towards a computer science perspective. However, it is highly readable and provides introductory material that would be useful to information scientists from a variety of domains. Yet, much interesting work in information visualization from other fields could have been included giving the work more of an interdisciplinary perspective to complement their goals of integrating work in this area. Unfortunately, many of the application chapters are these, shallow, and lack complementary illustrations of visualization techniques or user interfaces used. However, they do provide insight into the many applications being developed in this rapidly expanding field. The authors have successfully put together a highly useful reference text for the data mining and information visualization communities. Those interested in a good introduction and overview of complementary research areas in these fields will be satisfied with this collection of papers. The focus upon integrating data visualization with data mining complements texts in each of these fields, such as Advances in Knowledge Discovery and Data Mining (Fayyad et al., MIT Press) and Readings in Information Visualization: Using Vision to Think (Card et. al., Morgan Kauffman). This unique work is a good starting point for future interaction between researchers in the fields of data visualization and data mining and makes a good accompaniment for a course focused an integrating these areas or to the main reference texts in these fields."

LCSH

Information visualization

RSWK

Information Retrieval (BVB)

Subject

Information Retrieval (BVB)
Information visualization

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Abstract

Semantische Netze unterstützen den Suchvorgang im Information Retrieval. Sie bestehen aus relationierten Begriffen und helfen dem Nutzer das richtige Vokabular zur Fragebildung zu finden. Eine leicht und intuitiv erfassbare Darstellung und eine interaktive Bedienungsmöglichkeit optimieren den Suchprozess mit der Begriffsstruktur. Als Interaktionsform bietet sich Hy-pertext mit dem etablierte Point- und Klickverfahren an. Eine Visualisierung zur Unterstützung kognitiver Fähigkeiten kann durch eine Darstellung der Informationen mit Hilfe von Punkten und Linien erfolgen. Vorgestellt wer-den die Anwendungsbeispiele Wissensnetz im Brockhaus multimedial, WordSurfer der Firma BiblioMondo, SpiderSearch der Firma BOND und Topic Maps Visualization in dandelon.com und im Portal Informationswis-senschaft der Firma AGI - Information Management Consultants.

Date

30. 1.2007 18:22:41

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Abstract

This study explores an image-based retrieval interface for drug information, focusing on usability for a specific population - seniors. Qualitative, task-based interviews examined participants' health information behaviors and documented search strategies using an existing database (www.drugs.com) and a new prototype that uses similarity-based clustering of pill images for retrieval. Twelve participants (aged 65 and older), reflecting a diversity of backgrounds and experience with Web-based resources, located pill information using the interfaces and discussed navigational and other search preferences. Findings point to design features (e.g., image enlargement) that meet seniors' needs in the context of other health-related information-seeking strategies (e.g., contacting pharmacists).

Source

Journal of the American Society for Information Science and Technology. 58(2007) no.11, S.1610-1617

Type

a

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Abstract

A visual thesaurus system and method for displaying a selected term in association with its one or more meanings, other words to which it is related, and further relationship information. The results of a search are presented in a directed graph that provides more information than an ordered list. When a user selects one of the results, the display reorganizes around the user's search allowing for further searches, without the interruption of going to additional pages.

Content

Traditional print reference guides often have two methods of finding information: an order (alphabetical for dictionaries and encyclopedias, by subject hierarchy in the case of thesauri) and indices (ordered lists, with a more complete listing of words and concepts, which refers back to original content from the main body of the book). A user of such traditional print reference guides who is looking for information will either browse through the ordered information in the main body of the reference book, or scan through the indices to find what is necessary. The advent of the computer allows for much more rapid electronic searches of the same information, and for multiple layers of indices. Users can either search through information by entering a keyword, or users can browse through the information through an outline index, which represents the information contained in the main body of the data. There are two traditional user interfaces for such applications. First, the user may type text into a search field and in response, a list of results is returned to the user. The user then selects a returned entry and may page through the resulting information. Alternatively, the user may choose from a list of words from an index. For example, software thesaurus applications, in which a user attempts to find synonyms, antonyms, homonyms, etc. for a selected word, are usually implemented using the conventional search and presentation techniques discussed above. The presentation of results only allows for a one-dimensional order of data at any one time. In addition, only a limited number of results can be shown at once, and selecting a result inevitably leads to another page-if the result is not satisfactory, the users must search again. Finally, it is difficult to present information about the manner in which the search results are related, or to present quantitative information about the results without causing confusion. Therefore, there exists a need for a multidimensional graphical display of information, in particular with respect to information relating to the meaning of words and their relationships to other words. There further exists a need to present large amounts of information in a way that can be manipulated by the user, without the user losing his place. And there exists a need for more fluid, intuitive and powerful thesaurus functionality that invites the exploration of language.

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Abstract

Advanced technology has resulted in the generation of about one million terabytes of information every year. Ninety-reine percent of this is available in digital format (Keim, 2001). More information will be generated in the next three years than was created during all of previous human history (Keim, 2001). Collecting information is no longer a problem, but extracting value from information collections has become progressively more difficult. Various search engines have been developed to make it easier to locate information of interest, but these work well only for a person who has a specific goal and who understands what and how information is stored. This usually is not the Gase. Visualization was commonly thought of in terms of representing human mental processes (MacEachren, 1991; Miller, 1984). The concept is now associated with the amplification of these mental processes (Card, Mackinlay, & Shneiderman, 1999). Human eyes can process visual cues rapidly, whereas advanced information analysis techniques transform the computer into a powerful means of managing digitized information. Visualization offers a link between these two potent systems, the human eye and the computer (Gershon, Eick, & Card, 1998), helping to identify patterns and to extract insights from large amounts of information. The identification of patterns is important because it may lead to a scientific discovery, an interpretation of clues to solve a crime, the prediction of catastrophic weather, a successful financial investment, or a better understanding of human behavior in a computermediated environment. Visualization technology shows considerable promise for increasing the value of large-scale collections of information, as evidenced by several commercial applications of TreeMap (e.g., http://www.smartmoney.com) and Hyperbolic tree (e.g., http://www.inxight.com) to visualize large-scale hierarchical structures. Although the proliferation of visualization technologies dates from the 1990s where sophisticated hardware and software made increasingly faster generation of graphical objects possible, the role of visual aids in facilitating the construction of mental images has a long history. Visualization has been used to communicate ideas, to monitor trends implicit in data, and to explore large volumes of data for hypothesis generation. Imagine traveling to a strange place without a map, having to memorize physical and chemical properties of an element without Mendeleyev's periodic table, trying to understand the stock market without statistical diagrams, or browsing a collection of documents without interactive visual aids. A collection of information can lose its value simply because of the effort required for exhaustive exploration. Such frustrations can be overcome by visualization.
Visualization can be classified as scientific visualization, software visualization, or information visualization. Although the data differ, the underlying techniques have much in common. They use the same elements (visual cues) and follow the same rules of combining visual cues to deliver patterns. They all involve understanding human perception (Encarnacao, Foley, Bryson, & Feiner, 1994) and require domain knowledge (Tufte, 1990). Because most decisions are based an unstructured information, such as text documents, Web pages, or e-mail messages, this chapter focuses an the visualization of unstructured textual documents. The chapter reviews information visualization techniques developed over the last decade and examines how they have been applied in different domains. The first section provides the background by describing visualization history and giving overviews of scientific, software, and information visualization as well as the perceptual aspects of visualization. The next section assesses important visualization techniques that convert abstract information into visual objects and facilitate navigation through displays an a computer screen. It also explores information analysis algorithms that can be applied to identify or extract salient visualizable structures from collections of information. Information visualization systems that integrate different types of technologies to address problems in different domains are then surveyed; and we move an to a survey and critique of visualization system evaluation studies. The chapter concludes with a summary and identification of future research directions.

Source

Annual review of information science and technology. 39(2005), S.139-177

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a

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Abstract

This paper seeks to provide a brief overview of those developments which have taken the theory and practice of image and video retrieval into the digital age. Drawing on a voluminous literature, the context in which visual information retrieval takes place is followed by a consideration of the conceptual and practical challenges posed by the representation and recovery of visual material on the basis of its semantic content. An historical account of research endeavours in content-based retrieval, directed towards the automation of these operations in digital image scenarios, provides the main thrust of the paper. Finally, a look forwards locates visual information retrieval research within the wider context of content-based multimedia retrieval.

Source

Information science in transition, Ed.: A. Gilchrist

Type

a

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Abstract

The study adopts a naturalistic approach to investigate users' interaction with a browsable MeSH (medical subject headings) display designed to facilitate query construction for the PubMed bibliographic database. The purpose of the study is twofold: first, to test the usefulness of a browsable interface utilizing the principle of faceted classification; and second, to investigate users' preferred query submission methods in different problematic situations. An interface that incorporated multiple query submission methods - the conventional single-line query box as well as methods associated the faceted classification display was constructed. Participants' interactions with the interface were monitored remotely over a period of 10 weeks; information about their problematic situations and information retrieval behaviors were also collected during this time. The traditional controlled experiment was not adequate in answering the author's research questions; hence, the author provides his rationale for a naturalistic approach. The study's findings show that there is indeed a selective compatibility between query submission methods provided by the MeSH display and users' problematic situations. The query submission methods associated with the display were found to be the preferred search tools when users' information needs were vague and the search topics unfamiliar. The findings support the theoretical proposition that users engaging in an information retrieval process with a variety of problematic situations need different approaches. The author argues that rather than treat the information retrieval system as a general purpose tool, more attention should be given to the interaction between the functionality of the tool and the characteristics of users' problematic situations.

Source

Journal of the American Society for Information Science and Technology. 58(2007) no.13, S.1998-2006

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Abstract

The importance of information visualization as a means of transforming data into visual, understandable form is now embraced across university campuses and research institutes world-wide. Yet, the role of designers in this field of activity is often overlooked by the dominant scientific and technological interests in data visualization, and a corporate culture reliant on off-the-shelf visualization tools. This article is an attempt to describe the value of design thinking in information visualization with reference to Horst Rittel's ([1988]) definition of disorderly reasoning, and to frame design as a critical act of translating between scientific, technical, and aesthetic interests.

Footnote

Beitrag im Schwerpunktthema "Perspectives on design: information technologies and creative practices"

Source

Journal of the American Society for Information Science and Technology. 60(2009) no.9, S.1877-1882

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a

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Abstract

The authors introduce an information visualization model, WebStar, for hyperlink-based information systems. Hyperlinks within a hyperlink-based document can be visualized in a two-dimensional visual space. All links are projected within a display sphere in the visual space. The relationship between a specified central document and its hyperlinked documents is visually presented in the visual space. In addition, users are able to define a group of subjects and to observe relevance between each subject and all hyperlinked documents via movement of that subject around the display sphere center. WebStar allows users to dynamically change an interest center during navigation. A retrieval mechanism is developed to control retrieved results in the visual space. Impact of movement of a subject on the visual document distribution is analyzed. An ambiguity problem caused by projection is discussed. Potential applications of this visualization model in information retrieval are included. Future research directions on the topic are addressed.

Source

Information processing and management. 41(2005) no.4, S.1003-1018

Type

a

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Abstract

This book is the outcome of the Dagstuhl Seminar on "Information Visualization - Human-Centered Issues in Visual Representation, Interaction, and Evaluation" held at Dagstuhl Castle, Germany, from May 28 to June 1, 2007. Information Visualization (InfoVis) is a relatively new research area, which focuses on the use of visualization techniques to help people understand and analyze data.This book documents and extends the findings and discussions of the various sessions in detail. The seven contributions cover the most important topics: Part I is on general reflections on the value of information visualization; evaluating information visualizations; theoretical foundations of information visualization; teaching information visualization. Part II deals with specific aspects on creation and collaboration: engaging new audiences for information visualization; process and pitfalls in writing information visualization research papers; and visual analytics: definition, process, and challenges.

Content

Inhalt: Part I. General Reflections The Value of Information Visualization / Jean-Daniel Fekete, Jarke J van Wijk, John T. Stasko, Chris North Evaluating Information Visualizations / Sheelagh Carpendale Theoretical Foundations of Information Visualization / Helen C. Purchase, Natalia Andrienko, T.J. Jankun-Kelly, Matthew Ward Teaching Information Visualization / Andreas Kerren, John T. Stasko, Jason Dykes Part II. Specific Aspects Creation and Collaboration: Engaging New Audiences for Information Visualization / Jeffrey Heer, Frank van Ham, Sheelagh Carpendale, Chris Weaver, Petra Isenberg Process and Pitfalls in Writing Information Visualization Research Papers / Tamara Munzner Visual Analytics: Definition, Process, and Challenges / Daniel Keim, Gennady Andrienko, Jean-Daniel Fekete, Carsten Görg, Jörn Kohlhammer, Guy Melancon

Editor

Kerren, A. u.a.

RSWK

Information / Visualisierung / Aufsatzsammlung

Subject

Information / Visualisierung / Aufsatzsammlung

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Abstract

Computers have become our companions in many of the activities we pursue in our life. They assist us, in particular, in searching relevant information that is needed to perform a variety of tasks, from professional usage to personal entertainment. They hold this information in a huge number of heterogeneous sources, either dedicated to a specific user community (e.g., enterprise databases) or maintained for the general public (e.g., websites and digital libraries). Whereas progress in basic information technology is nowadays capable of guaranteeing effective information management, information retrieval and dissemination has become a core issue that needs further accomplishments to achieve user satisfaction. The research communities in databases, information retrieval, information visualization, and human-computer interaction have already largely investigated these domains. However, the technical environment has so dramatically evolved in recent years, inducing a parallel and very significant evolution in user habits and expectations, that new approaches are definitely needed to meet current demand. One of the most evident and significant changes is the human-computer interaction paradigm. Traditional interactions relayed an programming to express user information requirements in formal code and an textual output to convey to users the information extracted by the system. Except for professional data-intensive application frameworks, still in the hands of computer speciahsts, we have basically moved away from this pattern both in terms of expressing information requests and conveying results. The new goal is direct interaction with the final user (the person who is looking for information and is not necessarily familiar with computer technology). The key motto to achieve this is "go visual." The well-known high bandwidth of the human-vision channel allows both recognition and understanding of large quantities of information in no more than a few seconds. Thus, for instance, if the result of an information request can be organized as a visual display, or a sequence of visual displays, the information throughput is immensely superior to the one that can be achieved using textual support. User interaction becomes an iterative query-answer game that very rapidly leads to the desired final result. Conversely, the system can provide efficient visual support for easy query formulation. Displaying a visual representation of the information space, for instance, lets users directly point at the information they are looking for, without any need to be trained into the complex syntax of current query languages. Alternatively, users can navigate in the information space, following visible paths that will lead them to the targeted items. Again, thanks to the visual support, users are able to easily understand how to formulate queries and they are likely to achieve the task more rapidly and less prone to errors than with traditional textual interaction modes.
The two facets of "going visual" are usually referred to as visual query systems, for query formulation, and information visualization, for result display. Visual Query Systems (VQSs) are defined as systems for querying databases that use a visual representation to depict the domain of interest and express related requests. VQSs provide both a language to express the queries in a visual format and a variety of functionalities to facilitate user-system interaction. As such, they are oriented toward a wide spectrum of users, especially novices who have limited computer expertise and generally ignore the inner structure of the accessed database. Information visualization, an increasingly important subdiscipline within the field of Human-Computer Interaction (HCI), focuses an visual mechanisms designed to communicate clearly to the user the structure of information and improve an the cost of accessing large data repositories. In printed form, information visualization has included the display of numerical data (e.g., bar charts, plot charts, pie charts), combinatorial relations (e.g., drawings of graphs), and geographic data (e.g., encoded maps). In addition to these "static" displays, computer-based systems, such as the Information Visualizer and Dynamic Queries, have coupled powerful visualization techniques (e.g., 3D, animation) with near real-time interactivity (i.e., the ability of the system to respond quickly to the user's direct manipulation commands). Information visualization is tightly combined with querying capabilities in some recent database-centered approaches. More opportunities for information visualization in a database environment may be found today in data mining and data warehousing applications, which typically access large data repositories. The enormous quantity of information sources an the World-Wide Web (WWW) available to users with diverse capabilities also calls for visualization techniques. In this article, we survey the main features and main proposals for visual query systems and touch upon the visualization of results mainly discussing traditional visualization forms. A discussion of modern database visualization techniques may be found elsewhere. Many related articles by Daniel Keim are available at http://www. informatik.uni-halle.de/dbs/publications.html.

Source

Encyclopedia of library and information science. Vol.72, [=Suppl.35]

Type

a

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Abstract

This article explores the aesthetic design criteria that should be incorporated into the information visualization of a taxonomy intended for use by children. Seven elementary-school students were each asked to represent their ideas in drawings for visualizing a taxonomy. Their drawings were analyzed according to six criteria - balance, equilibrium, symmetry, unity, rhythm, and economy - identified as aesthetic measures in previous research. The drawings revealed the presence of all six measures, and three - unity, equilibrium, and rhythm - were found to play an especially important role. It is therefore concluded that an aesthetic design for an information visualization for young users should incorporate all six measures.

Source

Journal of the American Society for Information Science and Technology. 60(2009) no.9, S.1808-1822

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a

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Abstract

This review describes experimental designs (users, search tasks, measures, etc.) used by 31 controlled user studies of information visualization (IV) tools for textual information retrieval (IR) and a meta-analysis of the reported statistical effects. Comparable experimental designs allow research designers to compare their results with other reports, and support the development of experimentally verified design guidelines concerning which IV techniques are better suited to which types of IR tasks. The studies generally use a within-subject design with 15 or more undergraduate students performing browsing to known-item tasks on sets of at least 1,000 full-text articles or Web pages on topics of general interest/news. Results of the meta-analysis (N = 8) showed no significant effects of the IV tool as compared with a text-only equivalent, but the set shows great variability suggesting an inadequate basis of comparison. Experimental design recommendations are provided which would support comparison of existing IV tools for IR usability testing.

Source

Journal of the American Society for Information Science and Technology. 59(2008) no.6, S.1012-1024

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a

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Abstract

The goal of information visualization (IV) is to amplify human cognition through computer-generated, interactive, and visual data representation. By combining the computational power with human perceptional and associative capabilities, IV will make it easier for users to navigate through large amounts of information, discover patterns or hidden structures of the information, and understand semantics of the information space. This entry reviews the history and background of IV and discusses its basic principles with pointers to relevant resources. The entry also summarizes major IV techniques and toolkits and shows various examples of IV applications.

Source

Encyclopedia of library and information sciences. 3rd ed. Ed.: M.J. Bates

Type

a

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Abstract

In this article and two other articles which conceptualize a future stage of the research program (Leide, Cole, Large, & Beheshti, submitted for publication; Cole, Leide, Large, Beheshti, & Brooks, in preparation), we map-out a domain novice user's encounter with an IR system from beginning to end so that appropriate classification-based visualization schemes can be inserted into the encounter process. This article describes the visualization of a navigation classification scheme only. The navigation classification scheme uses the metaphor of a ship and ship's navigator traveling through charted (but unknown to the user) waters, guided by a series of lighthouses. The lighthouses contain mediation interfaces linking the user to the information store through agents created for each. The user's agent is the cognitive model the user has of the information space, which the system encourages to evolve via interaction with the system's agent. The system's agent is an evolving classification scheme created by professional indexers to represent the structure of the information store. We propose a more systematic, multidimensional approach to creating evolving classification/indexing schemes, based on where the user is and what she is trying to do at that moment during the search session.

Source

Information processing and management. 39(2003) no.6, S.923-940

Type

a

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Abstract

Purpose - To describe how information visualization can be used in the design of interface tools for large-scale repositories. Design/methodology/approach - One challenge for designers in the context of large-scale repositories is to create interface tools that help users find specific information of interest. In order to be most effective, these tools need to leverage the cognitive characteristics of the target users. At the Los Alamos National Laboratory, the authors' target users are scientists and engineers who can be characterized as higher-order, analytical thinkers. In this paper, the authors describe a visualization tool they have created for making the authors' large-scale digital object repositories more usable for them: SearchGraph, which facilitates data set analysis by displaying search results in the form of a two- or three-dimensional interactive scatter plot. Findings - Using SearchGraph, users can view a condensed, abstract visualization of search results. They can view the same dataset from multiple perspectives by manipulating several display, sort, and filter options. Doing so allows them to see different patterns in the dataset. For example, they can apply a logarithmic transformation in order to create more scatter in a dense cluster of data points or they can apply filters in order to focus on a specific subset of data points. Originality/value - SearchGraph is a creative solution to the problem of how to design interface tools for large-scale repositories. It is particularly appropriate for the authors' target users, who are scientists and engineers. It extends the work of the first two authors on ActiveGraph, a read-write digital library visualization tool.

Theme

Information Gateway

Type

a