Search (17 results, page 1 of 1)

  • × theme_ss:"Visualisierung"
  • × year_i:[2010 TO 2020}
  1. Soylu, A.; Giese, M.; Jimenez-Ruiz, E.; Kharlamov, E.; Zheleznyakov, D.; Horrocks, I.: Towards exploiting query history for adaptive ontology-based visual query formulation (2014) 0.03 
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    Abstract
    Grounded on real industrial use cases, we recently proposed an ontology-based visual query system for SPARQL, named OptiqueVQS. Ontology-based visual query systems employ ontologies and visual representations to depict the domain of interest and queries, and are promising to enable end users without any technical background to access data on their own. However, even with considerably small ontologies, the number of ontology elements to choose from increases drastically, and hence hinders usability. Therefore, in this paper, we propose a method using the log of past queries for ranking and suggesting query extensions as a user types a query, and identify emerging issues to be addressed.
    Source
    Metadata and semantics research: 8th Research Conference, MTSR 2014, Karlsruhe, Germany, November 27-29, 2014, Proceedings. Eds.: S. Closs et al
  2. Brantl, M.; Ceynowa, K.; Meiers, T.; Wolf, T.: Visuelle Suche in historischen Werken (2017) 0.01 
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    Abstract
    Die Bayerische Staatsbibliothek (BSB) zählt mit ihrem Bestand von knapp 11 Mio. Bänden zu den bedeutendsten Universalbibliotheken der Welt. Bereits 1,2 Mio. Werke sind digitalisiert, was die BSB zur größten digitalen Kulturinstitution in Deutschland macht. Dieser digitale Bestand umfasst vorwiegend urheberrechtsfreie Werke vom 8. bis ins 20. Jahrhundert, von der mittelalterlichen Bibelhandschrift bis zur Boulevardzeitung der 1920er-Jahre. Diese Vielfalt des zu digitalisierenden schriftlichen Kulturerbes und das hohe Tempo der Massendigitalisierung in den letzten Jahren haben ihren Preis - die inhaltliche Erschließung der Werke hinkt hinterher, insbesondere bei Werken, die nicht mittels Optical Character Recognition-Verfahren (OCR) automatisiert maschinenlesbar transformiert und zugänglich gemacht werden können. Dies gilt insbesondere für mittelalterliche Handschriften, Alte Druck- und Spezialbestände. Deshalb blieb auch der reichhaltige, in diesen Werken verborgene Bildbestand für den Nutzer weitestgehend verborgen und konnte lediglich durch das Durchblättern am Bildschirm entdeckt werden. Dies war Motivation für die Bayerische Staatsbibliothek, gemeinsam mit dem Fraunhofer Heinrich-Hertz-Institut in Berlin ein System zur ähnlichkeitsbasierten Bildsuche aufzubauen, welches sämtliche Bildinhalte aller 1,2 Mio. Digitalisate automatisch identifiziert. Hierbei werden mittels morphologischer Verfahren Bilder aus den Buchseiten extrahiert, die danach aufgrund von Farb- und Kantenmerkmalen klassifiziert werden. Bilder "ohne Informationswert" werden mit Hilfe von Methoden aus dem Bereich des maschinellen Lernens herausgefiltert. Damit konnten aus den digitalisierten Werken der BSB bislang mehr als 43 Mio. einzelne Bilder identifiziert werden, die mittels einer hochperformanten Suchmaschine über eine frei verfügbare Web-Applikation dem Anwender direkt zur Verfügung stehen. Dank der Vielfalt und Reichhaltigkeit der indexierten Bestände spricht dieses Angebot nicht nur Historiker und Buchwissenschaftler an, sondern Interessierte aus den unterschiedlichsten Fachrichtungen. Die Ähnlichkeitssuche stellt dabei unbekannte, ungewöhnliche und oftmals überraschende Bezüge zwischen unterschiedlichsten Werken her.
  3. Kraker, P.; Schramm, M.; Kittel, C.: Open knowledge maps : visuelle Literatursuche basierend auf den Prinzipien von Open Science (2019) 0.01 
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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.
  4. Seeliger, F.: ¬A tool for systematic visualization of controlled descriptors and their relation to others as a rich context for a discovery system (2015) 0.01 
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    Abstract
    The discovery service (a search engine and service called WILBERT) used at our library at the Technical University of Applied Sciences Wildau (TUAS Wildau) is comprised of more than 8 million items. If we were to record all licensed publications in this tool to a higher level of articles, including their bibliographic records and full texts, we would have a holding estimated at a hundred million documents. A lot of features, such as ranking, autocompletion, multi-faceted classification, refining opportunities reduce the number of hits. However, it is not enough to give intuitive support for a systematic overview of topics related to documents in the library. John Naisbitt once said: "We are drowning in information, but starving for knowledge." This quote is still very true today. Two years ago, we started to develop micro thesauri for MINT topics in order to develop an advanced indexing of the library stock. We use iQvoc as a vocabulary management system to create the thesaurus. It provides an easy-to-use browser interface that builds a SKOS thesaurus in the background. The purpose of this is to integrate the thesauri in WILBERT in order to offer a better subject-related search. This approach especially supports first-year students by giving them the possibility to browse through a hierarchical alignment of a subject, for instance, logistics or computer science, and thereby discover how the terms are related. It also supports the students with an insight into established abbreviations and alternative labels. Students at the TUAS Wildau were involved in the developmental process of the software regarding the interface and functionality of iQvoc. The first steps have been taken and involve the inclusion of 3000 terms in our discovery tool WILBERT.
  5. Platis, N. et al.: Visualization of uncertainty in tag clouds (2016) 0.00 
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    Date
    1. 2.2016 18:25:22
  6. Börner, K.: Atlas of knowledge : anyone can map (2015) 0.00 
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    Date
    22. 1.2017 16:54:03
    22. 1.2017 17:10:56
  7. Osinska, V.; Bala, P.: New methods for visualization and improvement of classification schemes : the case of computer science (2010) 0.00 
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    Date
    22. 7.2010 19:36:46
  8. Jäger-Dengler-Harles, I.: Informationsvisualisierung und Retrieval im Fokus der Infromationspraxis (2013) 0.00 
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    Date
    4. 2.2015 9:22:39
  9. Osiñska, V.: Visual analysis of classification scheme (2010) 0.00 
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    Date
    6. 1.2011 19:29:12
  10. Mercun, T.; Zumer, M.; Aalberg, T.: Presenting bibliographic families : Designing an FRBR-based prototype using information visualization (2016) 0.00 
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    Date
    15. 4.2016 14:29:41
  11. Wen, B.; Horlings, E.; Zouwen, M. van der; Besselaar, P. van den: Mapping science through bibliometric triangulation : an experimental approach applied to water research (2017) 0.00 
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    16.11.2017 13:29:12
  12. Wu, K.-C.; Hsieh, T.-Y.: Affective choosing of clustering and categorization representations in e-book interfaces (2016) 0.00 
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    Date
    20. 1.2015 18:30:22
  13. Wu, I.-C.; Vakkari, P.: Effects of subject-oriented visualization tools on search by novices and intermediates (2018) 0.00 
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    Date
    9.12.2018 16:22:25
  14. Osinska, V.; Kowalska, M.; Osinski, Z.: ¬The role of visualization in the shaping and exploration of the individual information space : part 1 (2018) 0.00 
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    Date
    21.12.2018 17:22:13
  15. Wu, I.-C.; Vakkari, P.: Supporting navigation in Wikipedia by information visualization : extended evaluation measures (2014) 0.00 
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    Date
    8. 4.2015 16:20:29
  16. Batorowska, H.; Kaminska-Czubala, B.: Information retrieval support : visualisation of the information space of a document (2014) 0.00 
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    Source
    Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
  17. Graphic details : a scientific study of the importance of diagrams to science (2016) 0.00 
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    Content
    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.

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