Search (73 results, page 3 of 4)

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Abstract

This study proposes an approach for visualizing knowledge structures that creates a "research-focused parallelship network," "keyword co-occurrence network," and a knowledge map to visualize Sci-Tech policy research structure. A total of 1,125 Sci-Tech policy-related papers (873 journal papers [78%], 205 conference papers [18%], and 47 review papers [4%]) have been retrieved from the Web of Science database for quantitative analysis and mapping. Different network and contour maps based on these 1,125 papers can be constructed by choosing different information as the main actor, such as the paper title, the institute, the country, or the author keywords, to reflect Sci-Tech policy research structures in micro-, meso-, and macro-levels, respectively. The quantitative way of exploring Sci-Tech policy research papers is investigated to unveil important or emerging Sci-Tech policy implications as well as to demonstrate the dynamics and visualization of the evolution of Sci-Tech policy research.

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Abstract

Visualization of scientific results using networks has become popular in scientometric research. We provide base maps for Mendeley reader count data using the publication year 2012 from the Web of Science data. Example networks are shown and explained. The reader can use our base maps to visualize other results with the VOSViewer. The proposed overlay maps are able to show the impact of publications in terms of readership data. The advantage of using our base maps is that it is not necessary for the user to produce a network based on all data (e.g., from 1 year), but can collect the Mendeley data for a single institution (or journals, topics) and can match them with our already produced information. Generation of such large-scale networks is still a demanding task despite the available computer power and digital data availability. Therefore, it is very useful to have base maps and create the network with the overlay technique.

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Abstract

In this article, we propose a graph-based interactive bibliographic information retrieval system-GIBIR. GIBIR provides an effective way to retrieve bibliographic information. The system represents bibliographic information as networks and provides a form-based query interface. Users can develop their queries interactively by referencing the system-generated graph queries. Complex queries such as "papers on information retrieval, which were cited by John's papers that had been presented in SIGIR" can be effectively answered by the system. We evaluate the proposed system by developing another relational database-based bibliographic information retrieval system with the same interface and functions. Experiment results show that the proposed system executes the same queries much faster than the relational database-based system, and on average, our system reduced the execution time by 72% (for 3-node query), 89% (for 4-node query), and 99% (for 5-node query).

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Abstract

Although extremely useful for visualizing high-dimensional data, t-SNE plots can sometimes be mysterious or misleading. By exploring how it behaves in simple cases, we can learn to use it more effectively. We'll walk through a series of simple examples to illustrate what t-SNE diagrams can and cannot show. The t-SNE technique really is useful-but only if you know how to interpret it.

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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.

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Abstract

Since their beginnings, bibliographic information systems have been displaying results in the form of long, textual lists. With the development of new data models and computer technologies, the need for new approaches to present and interact with bibliographic data has slowly been maturing. To investigate how this could be accomplished, a prototype system, FrbrVis1, was designed to present work families within a bibliographic information system using information visualization. This paper reports on two user studies, a controlled and an observational experiment, that have been carried out to assess the Functional Requirements for Bibliographic Records (FRBR)-based against an existing system as well as to test four different hierarchical visual layouts. The results clearly show that FrbrVis offers better performance and user experience compared to the baseline system. The differences between the four hierarchical visualizations (Indented tree, Radial tree, Circlepack, and Sunburst) were, on the other hand, not as pronounced, but the Indented tree and Sunburst design proved to be the most successful, both in performance as well as user perception. The paper therefore not only evaluates the application of a visual presentation of bibliographic work families, but also provides valuable results regarding the performance and user acceptance of individual hierarchical visualization techniques.

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Abstract

Documents in rich text corpora usually contain multiple facets of information. For example, an article about a specific disease often consists of different facets such as symptom, treatment, cause, diagnosis, prognosis, and prevention. Thus, documents may have different relations based on different facets. Powerful search tools have been developed to help users locate lists of individual documents that are most related to specific keywords. However, there is a lack of effective analysis tools that reveal the multifaceted relations of documents within or cross the document clusters. In this paper, we present FacetAtlas, a multifaceted visualization technique for visually analyzing rich text corpora. FacetAtlas combines search technology with advanced visual analytical tools to convey both global and local patterns simultaneously. We describe several unique aspects of FacetAtlas, including (1) node cliques and multifaceted edges, (2) an optimized density map, and (3) automated opacity pattern enhancement for highlighting visual patterns, (4) interactive context switch between facets. In addition, we demonstrate the power of FacetAtlas through a case study that targets patient education in the health care domain. Our evaluation shows the benefits of this work, especially in support of complex multifaceted data analysis.

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Abstract

In the information science literature, recent studies have used patent databases and patent classification information to construct network maps of patent technology classes. In such a patent technology map, almost all pairs of technology classes are connected, whereas most of the connections between them are extremely weak. This observation suggests the possibility of filtering the patent network map by removing weak links. However, removing links may reduce the explanatory power of the network on inventor or organization diversification. The network links may explain the patent portfolio diversification paths of inventors and inventing organizations. We measure the diversification explanatory power of the patent network map, and present a method to objectively choose an optimal tradeoff between explanatory power and removing weak links. We show that this method can remove a degree of arbitrariness compared with previous filtering methods based on arbitrary thresholds, and also identify previous filtering methods that created filters outside the optimal tradeoff. The filtered map aims to aid in network visualization analyses of the technological diversification of inventors, organizations, and other innovation agents, and potential foresight analysis. Such applications to a prolific inventor (Leonard Forbes) and company (Google) are demonstrated.

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Abstract

We present a novel approach to visually locate bodies of research within the sciences, both at each moment of time and dynamically. This article describes how this approach fits with other efforts to locally and globally map scientific outputs. We then show how these science overlay maps help benchmarking, explore collaborations, and track temporal changes, using examples of universities, corporations, funding agencies, and research topics. We address their conditions of application and discuss advantages, downsides, and limitations. Overlay maps especially help investigate the increasing number of scientific developments and organizations that do not fit within traditional disciplinary categories. We make these tools available online to enable researchers to explore the ongoing sociocognitive transformations of science and technology systems.

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Abstract

This article shows how visual representations have progressively taken the lead over classical language-based models of knowledge organization (KO). The paper adopts a theoretical and historical perspective and focuses on the consequences of the changes in the volume of data generated by data production on the KO models. Until now, data visualization tools have been used mainly by researchers with expertise in textual data processing or in computational linguistics. But now, these tools are accessible to a greater number of users. Thus, there are new issues at stake for KO, other professions and institutions for gathering data that contribute to defining new standards and KO representations.

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Abstract

Many large digital collections are currently organized by subject; although useful, these information organization structures are large and complex and thus difficult to browse. Current online tools and visualization prototypes show small, localized subsets and do not provide the ability to explore the predominant patterns of the overall subject structure. This study describes subject tree modifications that facilitate browsing for documents by capitalizing on the highly uneven distribution of real-world collections. The approach is demonstrated on two large collections organized by the Library of Congress Subject Headings (LCSH) and Medical Subject Headings (MeSH). Results show that the LCSH subject tree can be reduced to 49% of its initial complexity while maintaining access to 83% of the collection, and the MeSH tree can be reduced to 45% of its initial complexity while maintaining access to 97% of the collection. A simple solution to negate the loss of access is discussed. The visual impact is demonstrated by using traditional outline views and a slider control allowing searchers to change the subject structure dynamically according to their needs. This study has implications for the development of information organization theory and human-information interaction techniques for subject trees.

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Abstract

Complex cognitive activities, such as analytical reasoning, problem solving, and sense making, are often performed through the mediation of interactive computational tools. Examples include visual analytics, decision support, and educational tools. Through interaction with visual representations of information at the visual interface of these tools, a joint, coordinated cognitive system is formed. This partnership results in a number of relational properties-those depending on both humans and tools-that researchers and designers must be aware of if such tools are to effectively support the performance of complex cognitive activities. This article presents 10 properties of interactive visual representations that are essential and relational and whose values can be adjusted through interaction. By adjusting the values of these properties, better coordination between humans and tools can be effected, leading to higher quality performance of complex cognitive activities. This article examines how the values of these properties affect cognitive processing and visual reasoning and demonstrates the necessity of making their values adjustable-all of which is situated within a broader theoretical framework concerned with human-information interaction in complex cognitive activities. This framework can facilitate systematic research, design, and evaluation in numerous fields including information visualization, health informatics, visual analytics, and educational technology.

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Abstract

Map-based visualizations of document collections have become popular in recent times. However, most of these visualizations emphasize only geospatial properties of objects, leaving out other ontological properties. In this paper we propose to extend these visualizations to include nongeospatial properties of documents to support users with elementary and synoptic visual tasks. More specifically, additional suitable representations that can enhance the utility of map-based visualizations are discussed. To demonstrate the utility of the proposed solution, we have developed a prototype map-based visualization system using Google Maps (GM), which demonstrates how additional representations can be beneficial.

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Abstract

Purpose - The purpose of this paper is to evaluate the functionality of the particular epistemological schools with regard to the issues of users with visual impairment, to offer a theoretical answer to the question why these issues are not in the center of the interest of information science, and to try to find an epistemological approach that has ambitions to create the theoretical basis for the analysis of the relationship between information and visually impaired users. Design/methodology/approach - The methodological basis of the paper is determined by the selection of the epistemological approach. In order to think about the concept of information and to put it in relation to issues associated with users with visual impairment, a conceptual analysis is applied. Findings - Most of information science theories are based on empiricism and rationalism; this is the reason for their low interest in the questions of visually impaired users. Users with visual disabilities are out of the interest of rationalistic epistemology because it underestimates sensory perception; empiricism is not interested in them paradoxically because it overestimates sensory perception. Realism which fairly reflects such issues is an approach which allows the providing of information to persons with visual disabilities to be dealt with properly. Research limitations/implications - The paper has a speculative character. Its findings should be supported by empirical research in the future. Practical implications - Theoretical questions solved in the paper come from the practice of providing information to visually impaired users. Because practice has an influence on theory and vice versa, the author hopes that the findings included in the paper can serve to improve practice in the field. Social implications - The paper provides theoretical anchoring of the issues which are related to the inclusion of people with disabilities into society and its findings have a potential to support such efforts. Originality/value - This is first study linking questions of users with visual disabilities to highly abstract issues connected to the concept of information.

Type

a

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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".

Type

a