Search (43 results, page 1 of 3)

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Abstract

Generally, Computer Science (CS) classifications are inconsistent in taxonomy strategies. t is necessary to develop CS taxonomy research to combine its historical perspective, its current knowledge and its predicted future trends - including all breakthroughs in information and communication technology. In this paper we have analyzed the ACM Computing Classification System (CCS) by means of visualization maps. The important achievement of current work is an effective visualization of classified documents from the ACM Digital Library. From the technical point of view, the innovation lies in the parallel use of analysis units: (sub)classes and keywords as well as a spherical 3D information surface. We have compared both the thematic and semantic maps of classified documents and results presented in Table 1. Furthermore, the proposed new method is used for content-related evaluation of the original scheme. Summing up: we improved an original ACM classification in the Computer Science domain by means of visualization.

Date

22. 7.2010 19:36:46

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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

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

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

Science maps are visual representations of the structure and dynamics of scholarly knowl­edge. They aim to show how fields, disciplines, journals, scientists, publications, and scientific terms relate to each other. Science mapping is the body of methods and techniques that have been developed for generating science maps. This entry is an introduction to science maps and science mapping. It focuses on the conceptual, theoretical, and methodological issues of science mapping, rather than on the mathematical formulation of science mapping techniques. After a brief history of science mapping, we describe the general procedure for building a science map, presenting the data sources and the methods to select, clean, and pre-process the data. Next, we examine in detail how the most common types of science maps, namely the citation-based and the term-based, are generated. Both are based on networks: the former on the network of publications connected by citations, the latter on the network of terms co-occurring in publications. We review the rationale behind these mapping approaches, as well as the techniques and methods to build the maps (from the extraction of the network to the visualization and enrichment of the map). We also present less-common types of science maps, including co-authorship networks, interlocking editorship networks, maps based on patents' data, and geographic maps of science. Moreover, we consider how time can be represented in science maps to investigate the dynamics of science. We also discuss some epistemological and sociological topics that can help in the interpretation, contextualization, and assessment of science maps. Then, we present some possible applications of science maps in science policy. In the conclusion, we point out why science mapping may be interesting for all the branches of meta-science, from knowl­edge organization to epistemology.

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Abstract

The goal of Open Knowledge Maps is to create a visual interface to the world's scientific knowledge. The base for this visual interface consists of so-called knowledge maps, which enable the exploration of existing knowledge and the discovery of new knowledge. Our open source knowledge mapping software applies a mixture of summarization techniques and similarity measures on article metadata, which are iteratively chained together. After processing, the representation is saved in a database for use in a web visualization. In the future, we want to create a space for collective knowledge mapping that brings together individuals and communities involved in exploration and discovery. We want to enable people to guide each other in their discovery by collaboratively annotating and modifying the automatically created maps.

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Abstract

Techniques for multidimensional scaling visualize objects as points in a low-dimensional metric map. As a result, the visualizations are subject to the fundamental limitations of metric spaces. These limitations prevent multidimensional scaling from faithfully representing non-metric similarity data such as word associations or event co-occurrences. In particular, multidimensional scaling cannot faithfully represent intransitive pairwise similarities in a visualization, and it cannot faithfully visualize "central" objects. In this paper, we present an extension of a recently proposed multidimensional scaling technique called t-SNE. The extension aims to address the problems of traditional multidimensional scaling techniques when these techniques are used to visualize non-metric similarities. The new technique, called multiple maps t-SNE, alleviates these problems by constructing a collection of maps that reveal complementary structure in the similarity data. We apply multiple maps t-SNE to a large data set of word association data and to a data set of NIPS co-authorships, demonstrating its ability to successfully visualize non-metric similarities.

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Abstract

Using Google Earth, Google Maps, and/or network visualization programs such as Pajek, one can overlay the network of relations among addresses in scientific publications onto the geographic map. The authors discuss the pros and cons of various options, and provide software (freeware) for bridging existing gaps between the Science Citation Indices (Thomson Reuters) and Scopus (Elsevier), on the one hand, and these various visualization tools on the other. At the level of city names, the global map can be drawn reliably on the basis of the available address information. At the level of the names of organizations and institutes, there are problems of unification both in the ISI databases and with Scopus. Pajek enables a combination of visualization and statistical analysis, whereas the Google Maps and its derivatives provide superior tools on the Internet.

Object

Google Maps

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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

Die Wissenschaft befindet sich in einer Auffindbarkeitskrise. Obwohl durch die Open Access-Bewegung Forschungsergebnisse besser zugänglich geworden sind, wird ein signifikanter Teil der Outputs nicht nachgenutzt. Einen großen Anteil an der Krise haben die Tools, die für die Literatursuche verwendet werden. Angesichts von drei Millionen Veröffentlichungen pro Jahr sind klassische Ansätze, wie etwa listenbasierte Suchmaschinen, nicht mehr ausreichend. Open Knowledge Maps hat es sich zum Ziel gesetzt, die Auffindbarkeit wissenschaftlichen Wissens zu verbessern. Dafür betreibt die gemeinnützige Organisation aus Österreich die weltweit größte visuelle Suchmaschine für Forschung. Das Grundprinzip besteht darin, Wissenslandkarten für die Literatursuche zu nutzen. Diese geben einen Überblick über ein Forschungsfeld und ermöglichen so einen schnelleren Einstieg in die Literatur. Open Knowledge Maps basiert auf den Prinzipien von Open Science: Inhalte, Daten und Software werden unter einer freien Lizenz veröffentlicht. Dadurch entsteht eine offene, wiederverwendbare Infrastruktur; Lock-In-Effekte, wie sie bei proprietären Systemen auftreten, werden vermieden. Open Knowledge Maps arbeitet seit Beginn eng mit Bibliotheken und BibliothekarInnen als ExpertInnen für Wissensorganisation und -verwaltung zusammen. Im Rahmen eines konsortialen Fördermodells werden Bibliotheken nun eingeladen, das System stärker mitzugestalten - unter anderem bei wichtigen Zukunftsthemen wie der besseren Auffindbarkeit von Datensätzen.

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Abstract

Describes the use of concept maps as one of the semantic tools employed in the ADEPT (Alexandria Digital Earth Prototype) Digital Learning Environment (DLE) for teaching undergraduate classes. The graphic representation of the conceptualizations is derived from the knowledge in stronglystructured models (SSMs) of concepts represented in one or more knowledge bases. Such knowledge bases function as a source of "reference" information about concepts in a given context, including information about their scientific representation, scientific semantics, manipulation, and interrelationships to other concepts.

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Abstract

The idea of constructing science maps based on bibliographic data has intrigued researchers for decades, and various techniques have been developed to map the structure of research disciplines. Most science mapping studies use a single method. However, as research fields have various properties, a valid map of a field should actually be composed of a set of maps derived from a series of investigations using different methods. That leads to the question of what can be learned from a combination-triangulation-of these different science maps. In this paper we propose a method for triangulation, using the example of water science. We combine three different mapping approaches: journal-journal citation relations (JJCR), shared author keywords (SAK), and title word-cited reference co-occurrence (TWRC). Our results demonstrate that triangulation of JJCR, SAK, and TWRC produces a more comprehensive picture than each method applied individually. The outcomes from the three different approaches can be associated with each other and systematically interpreted to provide insights into the complex multidisciplinary structure of the field of water research.

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Abstract

Data from multiple knowledge organization systems are combined to provide a global overview of the content holdings of a small personal library. Subject headings and classification data are used to effectively map the combined book and topic space of the library. While harvested and manipulated by hand, the work reveals issues and potential solutions when using automated techniques to produce topic maps of much larger libraries. The small library visualized consists of the thirty-nine, digital, English language books found in the Osama Bin Laden (OBL) compound in Abbottabad, Pakistan upon his death. As this list of books has garnered considerable media attention, it is worth providing a visual overview of the subject content of these books - some of which is not readily apparent from the titles. Metadata from subject headings and classification numbers was combined to create book-subject maps. Tree maps of the classification data were also produced. The books contain 328 subject headings. In order to enhance the base map with meaningful thematic overlay, library holding count data was also harvested (and aggregated from duplicates). This additional data revealed the relative scarcity or popularity of individual books.

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Abstract

An event is a specific occurrence involving participants, which is a typed, n-ary association of entities or other events, each identified as a participant in a specific semantic role in the event (Pyysalo et al. 2012; Linguistic Data Consortium 2005). Event types may vary across domains. Representing relationships between events can facilitate the understanding of knowledge in complex systems (such as economic systems, human body, social systems). In the simplest form, an event can be represented as Entity A <Relation> Entity B. This paper evaluates several knowledge organization and visualization models and tools, such as concept maps (Cmap), topic maps (Ontopia), network analysis models (Gephi), and ontology (Protégé), then proposes an event relationship model that aims to integrate the strengths of these models, and can represent complex knowledge expressed in events and their relationships.

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Abstract

Science mapping aims to build bibliometric maps that describe how specific disciplines, scientific domains, or research fields are conceptually, intellectually, and socially structured. Different techniques and software tools have been proposed to carry out science mapping analysis. The aim of this article is to review, analyze, and compare some of these software tools, taking into account aspects such as the bibliometric techniques available and the different kinds of 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

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 Hypertext mit seinem Point- und Klickverfahren an. Die Visualisierung erfolgt als Netzstruktur aus Punkten und Linien. Es werden die Anwendungsbeispiele Wissensnetz im Brockhaus multimedial, WordSurfer der Firma BiblioMondo, SpiderSearch der Firma BOND und Topic Maps Visualization in dandelon.com und im Portal Informationswissenschaft der Firma AGI - Information Management Consultants vorgestellt.

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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

Displaying aspects of "aboutness" by means of non-verbal representations, such as notations, symbols, or icons, or through rich visual displays, such as those of topic maps, can facilitate meaning-making, putting information in context, and situating it relative to other information. As the design of displays of web-enabled information has struggled to keep pace with a bourgeoning body of digital content, increasingly innovative approaches to organizing search results have warranted greater attention. Using Worldmapper as an example, this paper examines cartograms - a derivative of the data map which adds dimensionality to the geographic positioning of information - as one approach to representing and managing subject content, and to tracking the diffusion of knowledge across place and time.