Search (60 results, page 1 of 3)

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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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Date

1. 2.2016 18:25:22

Series

Lecture notes in computer science ; 9398

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Content

Bill Howe and his colleagues at the University of Washington, in Seattle, decided to find out. First, they trained a computer algorithm to distinguish between various sorts of figures-which they defined as diagrams, equations, photographs, plots (such as bar charts and scatter graphs) and tables. They exposed their algorithm to between 400 and 600 images of each of these types of figure until it could distinguish them with an accuracy greater than 90%. Then they set it loose on the more-than-650,000 papers (containing more than 10m figures) stored on PubMed Central, an online archive of biomedical-research articles. To measure each paper's influence, they calculated its article-level Eigenfactor score-a modified version of the PageRank algorithm Google uses to provide the most relevant results for internet searches. Eigenfactor scoring gives a better measure than simply noting the number of times a paper is cited elsewhere, because it weights citations by their influence. A citation in a paper that is itself highly cited is worth more than one in a paper that is not.
As the team describe in a paper posted (http://arxiv.org/abs/1605.04951) on arXiv, they found that figures did indeed matter-but not all in the same way. An average paper in PubMed Central has about one diagram for every three pages and gets 1.67 citations. Papers with more diagrams per page and, to a lesser extent, plots per page tended to be more influential (on average, a paper accrued two more citations for every extra diagram per page, and one more for every extra plot per page). By contrast, including photographs and equations seemed to decrease the chances of a paper being cited by others. That agrees with a study from 2012, whose authors counted (by hand) the number of mathematical expressions in over 600 biology papers and found that each additional equation per page reduced the number of citations a paper received by 22%. This does not mean that researchers should rush to include more diagrams in their next paper. Dr Howe has not shown what is behind the effect, which may merely be one of correlation, rather than causation. It could, for example, be that papers with lots of diagrams tend to be those that illustrate new concepts, and thus start a whole new field of inquiry. Such papers will certainly be cited a lot. On the other hand, the presence of equations really might reduce citations. Biologists (as are most of those who write and read the papers in PubMed Central) are notoriously mathsaverse. If that is the case, looking in a physics archive would probably produce a different result.
Dr Howe and his colleagues do, however, believe that the study of diagrams can result in new insights. A figure showing new metabolic pathways in a cell, for example, may summarise hundreds of experiments. Since illustrations can convey important scientific concepts in this way, they think that browsing through related figures from different papers may help researchers come up with new theories. As Dr Howe puts it, "the unit of scientific currency is closer to the figure than to the paper." With this thought in mind, the team have created a website (viziometrics.org (http://viziometrics.org/) ) where the millions of images sorted by their program can be searched using key words. Their next plan is to extract the information from particular types of scientific figure, to create comprehensive "super" figures: a giant network of all the known chemical processes in a cell for example, or the best-available tree of life. At just one such superfigure per paper, though, the citation records of articles containing such all-embracing diagrams may very well undermine the correlation that prompted their creation in the first place. Call it the ultimate marriage of chart and science.

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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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Content

One of a series of three publications influenced by the travelling exhibit Places & Spaces: Mapping Science, curated by the Cyberinfrastructure for Network Science Center at Indiana University. - Additional materials can be found at http://http://scimaps.org/atlas2. Erweitert durch: Börner, Katy. Atlas of Science: Visualizing What We Know.

Date

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

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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

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Footnote

Rez. in: JASIST 56(2005) no.10, S.1126-1128 (P.K. Nayar): "How Images Think is an exercise both in philosophical meditation and critical theorizing about media, images, affects, and cognition. Burnett combines the insights of neuroscience with theories of cognition and the computer sciences. He argues that contemporary metaphors - biological or mechanical - about either cognition, images, or computer intelligence severely limit our understanding of the image. He suggests in his introduction that "image" refers to the "complex set of interactions that constitute everyday life in image-worlds" (p. xviii). For Burnett the fact that increasing amounts of intelligence are being programmed into technologies and devices that use images as their main form of interaction and communication-computers, for instance-suggests that images are interfaces, structuring interaction, people, and the environment they share. New technologies are not simply extensions of human abilities and needs-they literally enlarge cultural and social preconceptions of the relationship between body and mind. The flow of information today is part of a continuum, with exceptional events standing as punctuation marks. This flow connects a variety of sources, some of which are continuous - available 24 hours - or "live" and radically alters issues of memory and history. Television and the Internet, notes Burnett, are not simply a simulated world-they are the world, and the distinctions between "natural" and "non-natural" have disappeared. Increasingly, we immerse ourselves in the image, as if we are there. We rarely become conscious of the fact that we are watching images of events-for all perceptioe, cognitive, and interpretive purposes, the image is the event for us. The proximity and distance of viewer from/with the viewed has altered so significantly that the screen is us. However, this is not to suggest that we are simply passive consumers of images. As Burnett points out, painstakingly, issues of creativity are involved in the process of visualization-viewwes generate what they see in the images. This involves the historical moment of viewing-such as viewing images of the WTC bombings-and the act of re-imagining. As Burnett puts it, "the questions about what is pictured and what is real have to do with vantage points [of the viewer] and not necessarily what is in the image" (p. 26). In his second chapter Burnett moves an to a discussion of "imagescapes." Analyzing the analogue-digital programming of images, Burnett uses the concept of "reverie" to describe the viewing experience. The reverie is a "giving in" to the viewing experience, a "state" in which conscious ("I am sitting down an this sofa to watch TV") and unconscious (pleasure, pain, anxiety) processes interact. Meaning emerges in the not-always easy or "clean" process of hybridization. This "enhances" the thinking process beyond the boundaries of either image or subject. Hybridization is the space of intelligence, exchange, and communication.
Moving an to virtual images, Burnett posits the existence of "microcultures": places where people take control of the means of creation and production in order to makes sense of their social and cultural experiences. Driven by the need for community, such microcultures generate specific images as part of a cultural movement (Burnett in fact argues that microcultures make it possible for a "small cinema of twenty-five seats to become part of a cultural movement" [p. 63]), where the process of visualization-which involves an awareness of the historical moment - is central to the info-world and imagescapes presented. The computer becomms an archive, a history. The challenge is not only of preserving information, but also of extracting information. Visualization increasingly involves this process of picking a "vantage point" in order to selectively assimilate the information. In virtual reality systems, and in the digital age in general, the distance between what is being pictured and what is experienced is overcome. Images used to be treated as opaque or transparent films among experience, perception, and thought. But, now, images are taken to another level, where the viewer is immersed in the image-experience. Burnett argues-though this is hardly a fresh insight-that "interactivity is only possible when images are the raw material used by participants to change if not transform the purpose of their viewing experience" (p. 90). He suggests that a work of art, "does not start its life as an image ... it gains the status of image when it is placed into a context of viewing and visualization" (p. 90). With simulations and cyberspace the viewing experience has been changed utterly. Burnett defines simulation as "mapping different realities into images that have an environmental, cultural, and social form" (p. 95). However, the emphasis in Burnett is significant-he suggests that interactivity is not achieved through effects, but as a result of experiences attached to stories. Narrative is not merely the effect of technology-it is as much about awareness as it is about Fantasy. Heightened awareness, which is popular culture's aim at all times, and now available through head-mounted displays (HMD), also involves human emotions and the subtleties of human intuition.
The sixth chapter looks at this interfacing of humans and machines and begins with a series of questions. The crucial one, to my mind, is this: "Does the distinction between humans and technology contribute to a lack of understanding of the continuous interrelationship and interdependence that exists between humans and all of their creations?" (p. 125) Burnett suggests that to use biological or mechanical views of the computer/mind (the computer as an input/output device) Limits our understanding of the ways in which we interact with machines. He thus points to the role of language, the conversations (including the one we held with machines when we were children) that seem to suggest a wholly different kind of relationship. Peer-to-peer communication (P2P), which is arguably the most widely used exchange mode of images today, is the subject of chapter seven. The issue here is whether P2P affects community building or community destruction. Burnett argues that the trope of community can be used to explore the flow of historical events that make up a continuum-from 17th-century letter writing to e-mail. In the new media-and Burnett uses the example of popular music which can be sampled, and reedited to create new compositions - the interpretive space is more flexible. Private networks can be set up, and the process of information retrieval (about which Burnett has already expended considerable space in the early chapters) involves a lot more of visualization. P2P networks, as Burnett points out, are about information management. They are about the harmony between machines and humans, and constitute a new ecology of communications. Turning to computer games, Burnett looks at the processes of interaction, experience, and reconstruction in simulated artificial life worlds, animations, and video images. For Burnett (like Andrew Darley, 2000 and Richard Doyle, 2003) the interactivity of the new media games suggests a greater degree of engagement with imageworlds. Today many facets of looking, listening, and gazing can be turned into aesthetic forms with the new media. Digital technology literally reanimates the world, as Burnett demonstrates in bis concluding chapter. Burnett concludes that images no longer simply represent the world-they shape our very interaction with it; they become the foundation for our understanding the spaces, places, and historical moments that we inhabit. Burnett concludes his book with the suggestion that intelligence is now a distributed phenomenon (here closely paralleling Katherine Hayles' argument that subjectivity is dispersed through the cybernetic circuit, 1999). There is no one center of information or knowledge. Intersections of human creativity, work, and connectivity "spread" (Burnett's term) "intelligence through the use of mediated devices and images, as well as sounds" (p. 221).
Burnett's work is a useful basic primer an the new media. One of the chief attractions here is his clear language, devoid of the jargon of either computer sciences or advanced critical theory. This makes How Images Think an accessible introduction to digital cultures. Burnett explores the impact of the new technologies an not just image-making but an image-effects, and the ways in which images constitute our ecologies of identity, communication, and subject-hood. While some of the sections seem a little too basic (especially where he speaks about the ways in which we constitute an object as an object of art, see above), especially in the wake of reception theory, it still remains a starting point for those interested in cultural studies of the new media. The Gase Burnett makes out for the transformation of the ways in which we look at images has been strengthened by his attention to the history of this transformation-from photography through television and cinema and now to immersive virtual reality systems. Joseph Koemer (2004) has pointed out that the iconoclasm of early modern Europe actually demonstrates how idolatory was integral to the image-breakers' core belief. As Koerner puts it, "images never go away ... they persist and function by being perpetually destroyed" (p. 12). Burnett, likewise, argues that images in new media are reformed to suit new contexts of meaning-production-even when they appear to be destroyed. Images are recast, and the degree of their realism (or fantasy) heightened or diminished-but they do not "go away." Images do think, but-if I can parse Burnett's entire work-they think with, through, and in human intelligence, emotions, and intuitions. Images are uncanny-they are both us and not-us, ours and not-ours. There is, surprisingly, one factual error. Burnett claims that Myron Kreuger pioneered the term "virtual reality." To the best of my knowledge, it was Jaron Lanier who did so (see Featherstone & Burrows, 1998 [1995], p. 5)."

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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.

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Abstract

User interfaces for digital information discovery often require users to click around and read a lot of text in order to find the text they want to read-a process that is often frustrating and tedious. This is exacerbated because of the limited amount of text that can be displayed on a computer screen. To improve the user experience of computer mediated information discovery, information visualization techniques are applied to the digital library context, while retaining traditional information organization concepts. In this article, the "virtual (book) spine" and the virtual spine viewer are introduced. The virtual spine viewer is an application which allows users to visually explore large information spaces or collections while also allowing users to hone in on individual resources of interest. The virtual spine viewer introduced here is an alpha prototype, presented to promote discussion and further work. Information discovery changed radically with the introduction of computerized library access catalogs, the World Wide Web and its search engines, and online bookstores. Yet few instances of these technologies provide a user experience analogous to walking among well-organized, well-stocked bookshelves-which many people find useful as well as pleasurable. To put it another way, many of us have heard or voiced complaints about the paucity of "online browsing"-but what does this really mean? In traditional information spaces such as libraries, often we can move freely among the books and other resources. When we walk among organized, labeled bookshelves, we get a sense of the information space-we take in clues, perhaps unconsciously, as to the scope of the collection, the currency of resources, the frequency of their use, etc. We also enjoy unexpected discoveries such as finding an interesting resource because library staff deliberately located it near similar resources, or because it was miss-shelved, or because we saw it on a bookshelf on the way to the water fountain.
When our experience of information discovery is mediated by a computer, we neither move ourselves nor the monitor. We have only the computer's monitor to view, and the keyboard and/or mouse to manipulate what is displayed there. Computer interfaces often reduce our ability to get a sense of the contents of a library: we don't perceive the scope of the library: its breadth, (the quantity of materials/information), its density (how full the shelves are, how thorough the collection is for individual topics), or the general audience for the materials (e.g., whether the materials are appropriate for middle school students, college professors, etc.). Additionally, many computer interfaces for information discovery require users to scroll through long lists, to click numerous navigational links and to read a lot of text to find the exact text they want to read. Text features of resources are almost always presented alphabetically, and the number of items in these alphabetical lists sometimes can be very long. Alphabetical ordering is certainly an improvement over no ordering, but it generally has no bearing on features with an inherent non-alphabetical ordering (e.g., dates of historical events), nor does it necessarily group similar items together. Alphabetical ordering of resources is analogous to one of the most familiar complaints about dictionaries: sometimes you need to know how to spell a word in order to look up its correct spelling in the dictionary. Some have used technology to replicate the appearance of physical libraries, presenting rooms of bookcases and shelves of book spines in virtual 3D environments. This approach presents a problem, as few book spines can be displayed legibly on a monitor screen. This article examines the role of book spines, call numbers, and other traditional organizational and information discovery concepts, and integrates this knowledge with information visualization techniques to show how computers and monitors can meet or exceed similar information discovery methods. The goal is to tap the unique potentials of current information visualization approaches in order to improve information discovery, offer new services, and most important of all, improve user satisfaction. We need to capitalize on what computers do well while bearing in mind their limitations. The intent is to design GUIs to optimize utility and provide a positive experience for the user.

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Abstract

Many real-world domains can be represented as large node-link graphs: backbone Internet routers connect with 70,000 other hosts, mid-sized Web servers handle between 20,000 and 200,000 hyperlinked documents, and dictionaries contain millions of words defined in terms of each other. Computational manipulation of such large graphs is common, but previous tools for graph visualization have been limited to datasets of a few thousand nodes. Visual depictions of graphs and networks are external representations that exploit human visual processing to reduce the cognitive load of many tasks that require understanding of global or local structure. We assert that the two key advantages of computer-based systems for information visualization over traditional paper-based visual exposition are interactivity and scalability. We also argue that designing visualization software by taking the characteristics of a target user's task domain into account leads to systems that are more effective and scale to larger datasets than previous work. This thesis contains a detailed analysis of three specialized systems for the interactive exploration of large graphs, relating the intended tasks to the spatial layout and visual encoding choices. We present two novel algorithms for specialized layout and drawing that use quite different visual metaphors. The H3 system for visualizing the hyperlink structures of web sites scales to datasets of over 100,000 nodes by using a carefully chosen spanning tree as the layout backbone, 3D hyperbolic geometry for a Focus+Context view, and provides a fluid interactive experience through guaranteed frame rate drawing. The Constellation system features a highly specialized 2D layout intended to spatially encode domain-specific information for computational linguists checking the plausibility of a large semantic network created from dictionaries. The Planet Multicast system for displaying the tunnel topology of the Internet's multicast backbone provides a literal 3D geographic layout of arcs on a globe to help MBone maintainers find misconfigured long-distance tunnels. Each of these three systems provides a very different view of the graph structure, and we evaluate their efficacy for the intended task. We generalize these findings in our analysis of the importance of interactivity and specialization for graph visualization systems that are effective and scalable.

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Abstract

In the last few years, there is an increasing interest to generate visual representations of very large scientific domains. A methodology based on the combined use of ISI-JCR category cocitation and social networks analysis through the use of the Pathfinder algorithm has demonstrated its ability to achieve high quality, schematic visualizations for these kinds of domains. Now, the next step would be to generate these scientograms in an on-line fashion. To do so, there is a need to significantly decrease the run time of the latter pruning technique when working with category cocitation matrices of a large dimension like the ones handled in these large domains (Pathfinder has a time complexity order of O(n4), with n being the number of categories in the cocitation matrix, i.e., the number of nodes in the network). Although a previous improvement called Binary Pathfinder has already been proposed to speed up the original algorithm, its significant time complexity reduction is not enough for that aim. In this paper, we make use of a different shortest path computation from classical approaches in computer science graph theory to propose a new variant of the Pathfinder algorithm which allows us to reduce its time complexity in one order of magnitude, O(n3), and thus to significantly decrease the run time of the implementation when applied to large scientific domains considering the parameter q = n - 1. Besides, the new algorithm has a much simpler structure than the Binary Pathfinder as well as it saves a significant amount of memory with respect to the original Pathfinder by reducing the space complexity to the need of just storing two matrices. An experimental comparison will be developed using large networks from real-world domains to show the good performance of the new proposal.

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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

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Date

22. 3.2008 14:29:25

LCSH

User interfaces (Computer systems)

Subject

User interfaces (Computer systems)

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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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Issue

Sponsored by IEEE Computer Society Technical Committee on Visualization and Graphics.

LCSH

Computer graphics / Congresses
Computer vision / Congresses

Subject

Computer graphics / Congresses
Computer vision / Congresses

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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

Recent efforts in biomedical visual question answering (VQA) research rely on combined information gathered from the image content and surrounding text supporting the figure. Biomedical journals are a rich source of information for such multimodal content indexing. For multipanel figures in these journals, it is critical to develop automatic figure panel splitting and label recognition algorithms to associate individual panels with text metadata in the figure caption and the body of the article. Challenges in this task include large variations in figure panel layout, label location, size, contrast to background, and so on. In this work, we propose a deep convolutional neural network, which splits the panels and recognizes the panel labels in a single step. Visual features are extracted from several layers at various depths of the backbone neural network and organized to form a feature pyramid. These features are fed into classification and regression networks to generate candidates of panels and their labels. These candidates are merged to create the final panel segmentation result through a beam search algorithm. We evaluated the proposed algorithm on the ImageCLEF data set and achieved better performance than the results reported in the literature. In order to thoroughly investigate the proposed algorithm, we also collected and annotated our own data set of 10,642 figures. The experiments, trained on 9,642 figures and evaluated on the remaining 1,000 figures, show that combining panel splitting and panel label recognition mutually benefit each other.

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Abstract

Document retrieval is a highly interactive process dealing with large amounts of information. Visual representations can provide both a means for managing the complexity of large information structures and an interface style well suited to interactive manipulation. The system we have designed utilizes visually displayed graphic structures and a direct manipulation interface style to supply an integrated environment for retrieval. A common visually displayed network structure is used for query, document content, and term relations. A query can be modified through direct manipulation of its visual form by incorporating terms from any other information structure the system displays. An associative thesaurus of terms and an inter-document network provide information about a document collection that can complement other retrieval aids. Visualization of these large data structures makes use of fisheye views and overview diagrams to help overcome some of the inherent difficulties of orientation and navigation in large information structures.

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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.

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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".