-
Leydesdorff, L.: Visualization of the citation impact environments of scientific journals : an online mapping exercise (2007)
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- Abstract
- Aggregated journal-journal citation networks based on the Journal Citation Reports 2004 of the Science Citation Index (5,968 journals) and the Social Science Citation Index (1,712 journals) are made accessible from the perspective of any of these journals. A vector-space model Is used for normalization, and the results are brought online at http://www.leydesdorff.net/jcr04 as input files for the visualization program Pajek. The user is thus able to analyze the citation environment in terms of links and graphs. Furthermore, the local impact of a journal is defined as its share of the total citations in the specific journal's citation environments; the vertical size of the nodes is varied proportionally to this citation impact. The horizontal size of each node can be used to provide the same information after correction for within-journal (self-)citations. In the "citing" environment, the equivalents of this measure can be considered as a citation activity index which maps how the relevant journal environment is perceived by the collective of authors of a given journal. As a policy application, the mechanism of Interdisciplinary developments among the sciences is elaborated for the case of nanotechnology journals.
-
Zou, J.; Thoma, G.; Antani, S.: Unified deep neural network for segmentation and labeling of multipanel biomedical figures (2020)
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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.
-
Samoylenko, I.; Chao, T.-C.; Liu, W.-C.; Chen, C.-M.: Visualizing the scientific world and its evolution (2006)
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- Abstract
- We propose an approach to visualizing the scientific world and its evolution by constructing minimum spanning trees (MSTs) and a two-dimensional map of scientific journals using the database of the Science Citation Index (SCI) during 1994-2001. The structures of constructed MSTs are consistent with the sorting of SCI categories. The map of science is constructed based on our MST results. Such a map shows the relation among various knowledge clusters and their citation properties. The temporal evolution of the scientific world can also be delineated in the map. In particular, this map clearly shows a linear structure of the scientific world, which contains three major domains including physical sciences, life sciences, and medical sciences. The interaction of various knowledge fields can be clearly seen from this scientific world map. This approach can be applied to various levels of knowledge domains.
-
Bornmann, L.; Haunschild, R.: Overlay maps based on Mendeley data : the use of altmetrics for readership networks (2016)
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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.
-
Boyack, K.W.; Wylie, B.N.; Davidson, G.S.: Domain visualization using VxInsight®) [register mark] for science and technology management (2002)
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- Abstract
- Boyack, Wylie, and Davidson developed VxInsight which transforms information from documents into a landscape representation which conveys information on the implicit structure of the data as context for queries and exploration. From a list of pre-computed similarities it creates on a plane an x,y location for each item, or can compute its own similarities based on direct and co-citation linkages. Three-dimensional overlays are then generated on the plane to show the extent of clustering at particular points. Metadata associated with clustered objects provides a label for each peak from common words. Clicking on an object will provide citation information and answer sets for queries run will be displayed as markers on the landscape. A time slider allows a view of terrain changes over time. In a test on the microsystems engineering literature a review article was used to provide seed terms to search Science Citation Index and retrieve 20,923 articles of which 13,433 were connected by citation to at least one other article in the set. The citation list was used to calculate similarity measures and x.y coordinates for each article. Four main categories made up the landscape with 90% of the articles directly related to one or more of the four. A second test used five databases: SCI, Cambridge Scientific Abstracts, Engineering Index, INSPEC, and Medline to extract 17,927 unique articles by Sandia, Los Alamos National Laboratory, and Lawrence Livermore National Laboratory, with text of abstracts and RetrievalWare 6.6 utilized to generate the similarity measures. The subsequent map revealed that despite some overlap the laboratories generally publish in different areas. A third test on 3000 physical science journals utilized 4.7 million articles from SCI where similarity was the un-normalized sum of cites between journals in both directions. Physics occupies a central position, with engineering, mathematics, computing, and materials science strongly linked. Chemistry is farther removed but strongly connected.
-
Haller, S.H.M.: Mappingverfahren zur Wissensorganisation (2002)
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- Date
- 30. 5.2010 16:22:35
-
Platis, N. et al.: Visualization of uncertainty in tag clouds (2016)
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- Date
- 1. 2.2016 18:25:22
-
Börner, K.: Atlas of knowledge : anyone can map (2015)
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- Date
- 22. 1.2017 16:54:03
22. 1.2017 17:10:56
-
Petrovich, E.: Science mapping and science maps (2021)
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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.
-
Trunk, D.: Semantische Netze in Informationssystemen : Verbesserung der Suche durch Interaktion und Visualisierung (2005)
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- Date
- 30. 1.2007 18:22:41
-
Palm, F.: QVIZ : Query and context based visualization of time-spatial cultural dynamics (2007)
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- 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".
-
Thissen, F.: Screen-Design-Handbuch : Effektiv informieren und kommunizieren mit Multimedia (2001)
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- Date
- 22. 3.2008 14:35:21
-
Osinska, V.; Bala, P.: New methods for visualization and improvement of classification schemes : the case of computer science (2010)
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- Date
- 22. 7.2010 19:36:46
-
Jäger-Dengler-Harles, I.: Informationsvisualisierung und Retrieval im Fokus der Infromationspraxis (2013)
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- Date
- 4. 2.2015 9:22:39
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Thissen, F.: Screen-Design-Manual : Communicating Effectively Through Multimedia (2003)
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- Date
- 22. 3.2008 14:29:25
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Chen, C.: CiteSpace II : detecting and visualizing emerging trends and transient patterns in scientific literature (2006)
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- Date
- 22. 7.2006 16:11:05
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Wu, K.-C.; Hsieh, T.-Y.: Affective choosing of clustering and categorization representations in e-book interfaces (2016)
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- Date
- 20. 1.2015 18:30:22
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Wu, I.-C.; Vakkari, P.: Effects of subject-oriented visualization tools on search by novices and intermediates (2018)
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- Date
- 9.12.2018 16:22:25
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Osinska, V.; Kowalska, M.; Osinski, Z.: ¬The role of visualization in the shaping and exploration of the individual information space : part 1 (2018)
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- Date
- 21.12.2018 17:22:13
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Spero, S.: LCSH is to thesaurus as doorbell is to mammal : visualizing structural problems in the Library of Congress Subject Headings (2008)
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- Source
- Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
