Search (152 results, page 1 of 8)

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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.

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

User interfaces (Computer systems)
Information display systems / Formatting

Subject

User interfaces (Computer systems)
Information display systems / Formatting

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Abstract

This study explores how user subject knowledge influences search task processes and outcomes, as well as how search behavior is influenced by subject-oriented information visualization (IV) tools. To enable integrated searches, the proposed WikiMap + integrates search functions and IV tools (i.e., a topic network and hierarchical topic tree) and gathers information from Wikipedia pages and Google Search results. To evaluate the effectiveness of the proposed interfaces, we design subject-oriented tasks and adopt extended evaluation measures. We recruited 48 novices and 48 knowledgeable users, that is, intermediates, for the evaluation. Our results show that novices using the proposed interface demonstrate better search performance than intermediates using Wikipedia. We therefore conclude that our tools help close the gap between novices and intermediates in information searches. The results also show that intermediates can take advantage of the search tool by leveraging the IV tools to browse subtopics, and formulate better queries with less effort. We conclude that embedding the IV and the search tools in the interface can result in different search behavior but improved task performance. We provide implications to design search systems to include IV features adapted to user levels of subject knowledge to help them achieve better task performance.

Date

9.12.2018 16:22:25

Source

Journal of the Association for Information Science and Technology. 69(2018) no.12, S.1428-1445

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LCSH

Information display systems / Congresses

Subject

Information display systems / Congresses

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Abstract

As the volume and breadth of online information is rapidly increasing, ad hoc search systems become less and less efficient to answer information needs of modern users. To support the growing complexity of search tasks, researchers in the field of information developed and explored a range of approaches that extend the traditional ad hoc retrieval paradigm. Among these approaches, personalized search systems and exploratory search systems attracted many followers. Personalized search explored the power of artificial intelligence techniques to provide tailored search results according to different user interests, contexts, and tasks. In contrast, exploratory search capitalized on the power of human intelligence by providing users with more powerful interfaces to support the search process. As these approaches are not contradictory, we believe that they can re-enforce each other. We argue that the effectiveness of personalized search systems may be increased by allowing users to interact with the system and learn/investigate the problem in order to reach the final goal. We also suggest that an interactive visualization approach could offer a good ground to combine the strong sides of personalized and exploratory search approaches. This paper proposes a specific way to integrate interactive visualization and personalized search and introduces an adaptive visualization based search system Adaptive VIBE that implements it. We tested the effectiveness of Adaptive VIBE and investigated its strengths and weaknesses by conducting a full-scale user study. The results show that Adaptive VIBE can improve the precision and the productivity of the personalized search system while helping users to discover more diverse sets of information.

Footnote

Beitrag im Rahmen einer Special section on Human-computer Information Retrieval.

Source

Information processing and management. 49(2013) no.5, S.1139-1164

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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
Knowledge acquisition (Expert systems)

RSWK

Information Retrieval (BVB)

Series

Morgan Kaufmann series in data management systems

Subject

Information Retrieval (BVB)
Information visualization
Knowledge acquisition (Expert systems)

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Abstract

Purpose - The purpose of this paper is to report an investigation into the ways in which Canadian digital library collections have incorporated knowledge organization systems into their search interfaces. Design/methodology/approach - A combination of data-gathering techniques was used. These were as follows: a review of the literature related to the application of knowledge organization systems, deep scanning of Canadian governmental and academic institutions web sites on the web, identify and contact researchers in the area of knowledge organization, and identify and contact people in the governmental organizations who are involved in knowledge organization and information management. Findings - A total of 33 digital collections were identified that have made use of some type of knowledge organization system. Thesauri, subject heading lists and classification schemes were the widely used knowledge organization systems in the surveyed Canadian digital library collections. Research limitations/implications - The target population for this research was limited to governmental and academic digital library collections. Practical implications - An evaluation of the knowledge organization systems interfaces showed that searching, browsing and navigation facilities as well as bilingual features call for improvements. Originality/value - This research contributes to the following areas: digital libraries, knowledge organization systems and services and search interface design.

Source

Online information review. 29(2005) no.6, S.604-620

Theme

Information Gateway

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Abstract

Purpose The purpose of this paper is to examine whether and how a methodological coupling of visualisations of trace data and interview methods can be utilised for information practices studies. Design/methodology/approach Trace data visualisation enquiry is suggested as the coupling of visualising exported data from an information system and using these visualisations as basis for interview guides and elicitation in information practices research. The methodology is illustrated and applied through a small-scale empirical study of a citizen science project. Findings The study found that trace data visualisation enquiry enabled fine-grained investigations of temporal aspects of information practices and to compare and explore temporal and geographical aspects of practices. Moreover, the methodology made possible inquiries for understanding information practices through trace data that were discussed through elicitation with participants. The study also found that it can aid a researcher of gaining a simultaneous overarching and close picture of information practices, which can lead to theoretical and methodological implications for information practices research. Originality/value Trace data visualisation enquiry extends current methods for investigating information practices as it enables focus to be placed on the traces of practices as recorded through interactions with information systems and study participants' accounts of activities.

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Abstract

Geospatial information technologies revolutionize the way we have traditionally approached navigation and browsing in information systems. Colorful graphics, statistical summaries, geospatial relationships of underlying collections make them attractive for text retrieval systems. This paper examines the nature of georeferenced information in academic library catalogs organized according to the Library of Congress Classification (LCC) with the goal of understanding their implications for geovisualization of library collections.

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Abstract

LyberWorld is a prototype IR user interface. It implements visualizations of an abstract information space: fulltext. The video demonstrates a visual user interface for the probabilistic fulltext retrieval system INQUERY. Visualizations are used to communicate information search and browsing activities in a natural way by applying metaphors of spatial navigation in abstract information spaces. Visualization tools for exploring information spaces and judging relevance of information items are introduced and an example session demonstrates the prototype. The presence of a spatial model in the user's mind is regarded as an essential contribution towards natural interaction and reduction of cognitive costs during retrieval dialogues.

Source

Proceeding CHI '95 Conference Companion on Human Factors in Computing Systems

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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]

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Content

1. Introduction Web search engines and digital libraries usually expect the users to use search terms that most accurately represent their information needs. Finding the most appropriate search terms to represent an information need is an age old problem in information retrieval. Keyword or phrase search may produce good search results as long as the search terms or phrase(s) match those used by the authors and have been chosen for indexing by the concerned information retrieval system. Since this does not always happen, a large number of false drops are produced by information retrieval systems. The retrieval results become worse in very large systems that deal with millions of records, such as the Web search engines and digital libraries. Vocabulary control tools are used to improve the performance of text retrieval systems. Thesauri, the most common type of vocabulary control tool used in information retrieval, appeared in the late fifties, designed for use with the emerging post-coordinate indexing systems of that time. They are used to exert terminology control in indexing, and to aid in searching by allowing the searcher to select appropriate search terms. A large volume of literature exists describing the design features, and experiments with the use, of thesauri in various types of information retrieval systems (see for example, Furnas et.al., 1987; Bates, 1986, 1998; Milstead, 1997, and Shiri et al., 2002).

Source

Knowledge organization and the global information society: Proceedings of the 8th International ISKO Conference 13-16 July 2004, London, UK. Ed.: I.C. McIlwaine

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Date

22. 1.2017 16:54:03
22. 1.2017 17:10:56

LCSH

Information visualization

Subject

Information visualization

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Abstract

This investigation tested the designer assumption that VIBE is a tool for an expert user and asked: what are the effects of user expertise on usability when VIBE's non-traditional interface is compared with a more traditional text-based interface? Three user groups - novices, online searching experts, and VIBE system experts - totaling 31 participants, were asked to use and compare VIBE to a more traditional text-based system, askSam. No significant differences were found; however, significant performance differences were found for some tasks on the two systems. Participants understood the basic principles underlying VIBE although they generally favored the askSam system. The findings suggest that VIBE is a learnable system and its components have pragmatic application to the development of visualized information retrieval systems. Further research is recommended to maximize the retrieval potential of IR visualization systems.

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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

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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Abstract

Je mehr Informationen gleichzeitig, übersichtlich dargestellt und überwacht werden können, desto höher wird der Informations-Nutzen für einen Besucher oder potentiellen Kunden von ihnen sein. Da wir in einer Zeit der Informationsüberflutung leben, hilft uns das Information-Panel in Zukunft als multimediales Informationssystem. Ein Interface ist in unserem heutigen multimedialen Umfeld ein Bestandteil eines Systems, das dem Austausch von Informationen dient. Durch Information-Panels (sog. I-Panels) kann der Mensch mit Geräten interagieren, indem er sich wahlweise die für ihn masßgeschneiderten Informationen darstellen lässt. Für den Interface-Theoretiker Artur P. Schmidt können Information-Panels heute als eine Art Enzyklopädie für Informationen und Nachrichten aller Art dienen, wie sein Internet-Projekt "Der Wissensnavigator" belegt. Das Vorbild für multimediale Panels ist die geordnete Verbindung von Inhalten. Das Information-Panel als MenschMaschine-Interface kann zum "Punkt der Begegnung" oder "Kopplung zwischen zwei oder mehr Systemen" werden. Es übernimmt eine Übersetzung- und Vermittlungsfunktion.

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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

Icon system could represent an efficient solution for collective iconic categorization of knowledge by providing graphical interpretation. Their pictorial characters assist visualizing the structure of text to become more understandable beyond vocabulary obstacle. In this paper we are proposing a Knowledge Engineering (KM) based iconic representation approach. We assume that these systematic icons improve collective knowledge management. Meanwhile, text (constructed under our knowledge management model - Hypertopic) helps to reduce the diversity of graphical understanding belonging to different users. This "position paper" also prepares to demonstrate our hypothesis by an "iconic social tagging" experiment which is to be accomplished in 2011 with UTT students. We describe the "socio semantic web" information portal involved in this project, and a part of the icons already designed for this experiment in Sustainability field. We have reviewed existing theoretical works on icons from various origins, which can be used to lay the foundation of robust "icons systems".

Content

Vgl.: http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5928690. Vgl. auch: Special Issue on CTS 2011 at Elsevier's Future Generation Computer Systems Journal - http://www.elsevier.com/wps/find/journaldescription.cws_home/505611/description)

Source

Collaboration Technologies and Systems (CTS), 2011 International Conference on Collaboration Technologies and Systems (CTS 2011), May 23-27, 2011,The Sheraton University City Hotel, Philadelphia, Pennsylvania, USA

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Abstract

We sought to understand how users interpret meanings of symbols commonly used in information systems, especially how icons are processed by the brain. We investigated Chinese and English speakers' processing of 4 types of visual stimuli: icons, pictures, Chinese characters, and English words. The goal was to examine, via functional magnetic resonance imaging (fMRI) data, the hypothesis that people cognitively process icons as logographic words and to provide neurological evidence related to human-computer interaction (HCI), which has been rare in traditional information system studies. According to the neuroimaging data of 19 participants, we conclude that icons are not cognitively processed as logographical words like Chinese characters, although they both stimulate the semantic system in the brain that is needed for language processing. Instead, more similar to images and pictures, icons are not as efficient as words in conveying meanings, and brains (people) make more effort to process icons than words. We use this study to demonstrate that it is practicable to test information system constructs such as elements of graphical user interfaces (GUIs) with neuroscience data and that, with such data, we can better understand individual or group differences related to system usage and user-computer interactions.

Source

Journal of the Association for Information Science and Technology. 66(2015) no.4, S.702-720

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Abstract

Purpose - Despite the importance of bibliographic information systems for discovering and exploring library resources, some of the core functionality that should be provided to support users in their information seeking process is still missing. Investigating these issues, the purpose of this paper is to design a solution that would fulfil the missing objectives. Design/methodology/approach - Building on the concepts of a work family, functional requirements for bibliographic records (FRBR) and information visualization, the paper proposes a model and user interface design that could support a more efficient and user-friendly presentation and navigation in bibliographic information systems. Findings - The proposed design brings together all versions of a work, related works, and other works by and about the author and shows how the model was implemented into a FrbrVis prototype system using hierarchical visualization layout. Research limitations/implications - Although issues related to discovery and exploration apply to various material types, the research first focused on works of fiction and was also limited by the selected sample of records. Practical implications - The model for presenting and interacting with FRBR-based data can serve as a good starting point for future developments and implementations. Originality/value - With FRBR concepts being gradually integrated into cataloguing rules, formats, and various bibliographic services, one of the important questions that has not really been investigated and studied is how the new type of data would be presented to users in a way that would exploit the true potential of the changes.