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<rdf:RDF xmlns:community="http://www.bibsonomy.org/ontologies/2008/05/community#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:admin="http://webns.net/mvcb/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:syn="http://purl.org/rss/1.0/modules/syndication/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" xmlns:cc="http://web.resource.org/cc/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" xmlns:swrc="http://swrc.ontoware.org/ontology#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns="http://purl.org/rss/1.0/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xml:base="https://puma.ub.uni-stuttgart.de/user/markusjohn/visualization"><owl:Ontology rdf:about=""><rdfs:comment>PUMA publications for /user/markusjohn/visualization</rdfs:comment><owl:imports rdf:resource="http://swrc.ontoware.org/ontology/portal"/></owl:Ontology><rdf:Description rdf:about="https://puma.ub.uni-stuttgart.de/bibtex/2e85bd57d174a86079fc058c54cb81262/markusjohn"><owl:sameAs rdf:resource="/uri/bibtex/2e85bd57d174a86079fc058c54cb81262/markusjohn"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#Article"/><swrc:date>Mon Feb 12 15:04:02 CET 2018</swrc:date><swrc:journal>Digital Humanities, Montreal, Canada, August 8-11, 2017</swrc:journal><swrc:title>Interactive Visual Exploration of the Regesta Imperii</swrc:title><swrc:year>2017</swrc:year><swrc:keywords>Digital Humanities; Text Visualization </swrc:keywords><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="Markus John"/></rdf:_1><rdf:_2><swrc:Person swrc:name="Christian Richter"/></rdf:_2><rdf:_3><swrc:Person swrc:name="Steffen Koch"/></rdf:_3><rdf:_4><swrc:Person swrc:name="Andreas Kuczera"/></rdf:_4><rdf:_5><swrc:Person swrc:name="Thomas Ertl"/></rdf:_5></rdf:Seq></swrc:author></rdf:Description><rdf:Description rdf:about="https://puma.ub.uni-stuttgart.de/bibtex/2165cbdc68a3b67c55a4a5e3d4896845e/markusjohn"><owl:sameAs rdf:resource="/uri/bibtex/2165cbdc68a3b67c55a4a5e3d4896845e/markusjohn"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#InProceedings"/><swrc:date>Mon Feb 12 15:00:59 CET 2018</swrc:date><swrc:address>Cham</swrc:address><swrc:booktitle>Computer Vision, Imaging and Computer Graphics Theory and Applications</swrc:booktitle><swrc:pages>220--241</swrc:pages><swrc:publisher><swrc:Organization swrc:name="Springer International Publishing"/></swrc:publisher><swrc:title>Visual Analysis of Character and Plot Information Extracted from Narrative Text</swrc:title><swrc:year>2017</swrc:year><swrc:keywords>Visualization </swrc:keywords><swrc:abstract>The study of novels and the analysis of their plot, characters and other information entities are complex and time-consuming tasks in literary science. The digitization of literature and the proliferation of electronic books provide new opportunities to support these tasks with visual abstractions. Methods from the field of computational linguistics can be used to automatically extract entities and their relations from digitized novels. However, these methods have known limitations, especially when applied to narrative text that does often not follow a common schema but can have various forms. Visualizations can address the limitations by providing visual clues to show the uncertainty of the extracted information, so that literary scholars get a better idea of the accuracy of the methods. In addition, interaction can be used to let users control and adapt the extraction and visualization methods according to their needs. This paper presents ViTA, a web-based approach that combines automatic analysis methods with effective visualization techniques. Different views on the extracted entities are provided and relations between them across the plot are indicated. Two usage scenarios show successful applications of the approach and demonstrate its benefits and limitations. Furthermore, the paper discusses how uncertainty might be represented in the different views and how users can be enabled to adapt the automatic methods.</swrc:abstract><swrc:hasExtraField><swrc:Field swrc:value="978-3-319-64870-5" swrc:key="isbn"/></swrc:hasExtraField><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="Markus John"/></rdf:_1><rdf:_2><swrc:Person swrc:name="Steffen Lohmann"/></rdf:_2><rdf:_3><swrc:Person swrc:name="Steffen Koch"/></rdf:_3><rdf:_4><swrc:Person swrc:name="Michael W{\&#034;o}rner"/></rdf:_4><rdf:_5><swrc:Person swrc:name="Thomas Ertl"/></rdf:_5></rdf:Seq></swrc:author><swrc:editor><rdf:Seq><rdf:_1><swrc:Person swrc:name="Jos{\&#039;e} Braz"/></rdf:_1><rdf:_2><swrc:Person swrc:name="Nadia Magnenat-Thalmann"/></rdf:_2><rdf:_3><swrc:Person swrc:name="Paul Richard"/></rdf:_3><rdf:_4><swrc:Person swrc:name="Lars Linsen"/></rdf:_4><rdf:_5><swrc:Person swrc:name="Alexandru Telea"/></rdf:_5><rdf:_6><swrc:Person swrc:name="Sebastiano Battiato"/></rdf:_6><rdf:_7><swrc:Person swrc:name="Francisco Imai"/></rdf:_7></rdf:Seq></swrc:editor></rdf:Description><rdf:Description rdf:about="https://puma.ub.uni-stuttgart.de/bibtex/279820e1562a3b7af96d90ebb328ba161/markusjohn"><owl:sameAs rdf:resource="/uri/bibtex/279820e1562a3b7af96d90ebb328ba161/markusjohn"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#Article"/><swrc:date>Mon Mar 06 16:42:45 CET 2017</swrc:date><swrc:journal>IEEE Transactions on Visualization and Computer Graphics</swrc:journal><swrc:title>DocuCompass: Effective Exploration of Document Landscapes</swrc:title><swrc:year>2017</swrc:year><swrc:keywords>analytics, document focus+context interaction mining, myown techniques, text visual visualization </swrc:keywords><swrc:abstract>The creation of interactive visualization to analyze text documents has gained an impressive momentum in recent years.
This is not surprising in the light of massive and still increasing amounts of available digitized texts.
Websites, social media, news wire, and digital libraries are just few examples of the diverse text sources whose visual analysis and exploration offers new opportunities to effectively mine and manage the information and knowledge hidden within them.
A popular visualization method for large text collections is to represent each document by a glyph in 2D space.
These landscapes can be the result of optimizing pairwise distances in 2D to represent document similarities, or they are provided directly as meta data, such as geo-locations.
For well-defined information needs, suitable interaction methods are available for these spatializations.
However, free exploration and navigation on a level of abstraction between a labeled document spatialization and reading single documents is largely unsupported.
As a result, vital foraging steps for task-tailored actions, such as selecting subgroups of documents for detailed inspection, or subsequent sense-making steps are hampered.
To fill in this gap, we propose DocuCompass, a focus+context approach based on the lens metaphor.
It comprises multiple methods to characterize local groups of documents, and to efficiently guide exploration based on users&#039; requirements.
DocuCompass thus allows for effective interactive exploration of document landscapes without disrupting the mental map of users by changing the layout itself.
We discuss the suitability of multiple navigation and characterization methods for different spatializations and texts.
Finally, we provide insights generated through user feedback and discuss the effectiveness of our approach.</swrc:abstract><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="Florian Heimerl"/></rdf:_1><rdf:_2><swrc:Person swrc:name="Markus John"/></rdf:_2><rdf:_3><swrc:Person swrc:name="Qi Han"/></rdf:_3><rdf:_4><swrc:Person swrc:name="Steffen Koch"/></rdf:_4><rdf:_5><swrc:Person swrc:name="Thomas Ertl"/></rdf:_5></rdf:Seq></swrc:author></rdf:Description></rdf:RDF>