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6 Research products

  • Digital Humanities and Cultural Heritage
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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: Klenk, Dominik;

    This upload belongs to the paper "Rapid and Reproducible Reconstruction of Ancient Architecture by Procedural Generation", to appear in the CHNT 26 Proceedings. The paper uses the 3D-reconstruction of the "Great Hall" of Karakorum as a case-study. Since the “Great Hall” is an almost completely destroyed building, a possible reconstruction turns out to be quite difficult. The aim was therefore to develop a method with which existing research and theories as well as connections to other architectural styles can be incorporated into the reconstruction. Accordingly, many different variants come into question for a possible reconstruction. Therefore, it is important that hypotheses are not tested on the basis of a single reconstruction, but that it is possible to visualise and discuss several different hypotheses in a short time. Such a method can be created with the help of a procedural generation. In order to implement possible hypotheses as a 3D model with this method, it is important that the generation of the 3D model can be influenced with the help of changeable parameters. In the paper the connections to the Chinese architecture are explained, as well as related works and theories are taken up, which pursued similar approaches and goals. Furthermore, the procedure of reconstruction is explained, and the method of procedural generation is illustrated by the parameter-controlled creation of the structural system of a Chinese-style building. This repository contains the pythons script, which implements a blender-panel to control the reconstruction of a medieval Chinese-style building with different user-defined parameters. To be completely sure that the script will work as expected it is recommended to use the Blender version 3.0.0, because it was developed to work with this version. To use the Blender Panel, it is necessary to import the script via the “Scripting” tab. Inside the “Scripting” tab it is possible to add the script with the folder icon above the text editor. After the script was added, the source code should be visible inside the text editor area. Once the script has been added successfully it needs to be executed with the arrow icon above the text editor. If the script was executed successfully, the panel should be visible in the 3D-Viewport of the “Layout” tab in the “Sidebar” labelled as “Tempel”. It is necessary to use the “Object-Mode” and if the “Sidebar” is not visible, it is possible to open it with the “N”-Key or with the small arrow in the upper right corner. The panel should now be visible as shown in Figure 6. Before it is possible to generate buildings with the panel it is important to add the path to the Blender-File, which includes the individual components used for the generation, as file path via the folder icon inside the panel. Now the individual parameters can be changed at will, and the possible reconstruction can be generated with a click on the “Generierung starten”-Button at the bottom of the panel.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao ZENODOarrow_drop_down
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    ZENODO
    Software . 2023
    Data sources: ZENODO
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    ZENODO
    Software . 2023
    Data sources: Datacite
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao ZENODOarrow_drop_down
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      ZENODO
      Software . 2023
      Data sources: ZENODO
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      ZENODO
      Software . 2023
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Ehlers, Dajana; Kampf, Julia; Ihnen, Greta; Neuhaus, Lara Alyssa; +2 Authors

    Was ist Puls? Wann lebte Ramses II.? Und welche Länder bereisten die Wikinger? Alles Fragen die durch einen Besuch im Museum geklärt werden können. Doch was passiert, wenn nach einem langen Arbeitstag diese Fragen zwischen dir und deinem wohlverdienten Feierabend stehen? Komm zu uns ins Museum, lerne verschiedene Epochen in kurzen Alltagsmomenten kennen und entkomme aus dem Museum! Du bist in einem historischen Museum angestellt und nach einem viel zu langen Arbeitstag zwischen Objekten, Museumskonzepten und Recherche hast du die Zeit völlig aus den Augen verloren. Dein Chef und alle anderen haben dich vergessen und einfach eingeschlossen. Nun musst du versuchen einen Code für den Ausgang zu finden. Hierfür reist du mental zu den Römern, Ägyptern und Wikingern, meisterst Level in dem du das Alltagsleben der verschiedenen Kulturen nachempfindest. Gleichzeitig kannst du im Museum mehr über den Kontext der Geschichten und den Objekten, mit denen du interagierst, erfahren. Es öffnet dir den Blick, weg von den glitzernden „Sensationsfunden“, reißerischen Abenteuern und Zaubereien mit dem Pinsel, hin zu den Menschen wie du und ich. Die Erfahrungen reichen vom Handwerk, der Religion bis hin zum Essen. Vielleicht gehst du deinen nächsten Museumsbesuch etwas anders an und wirst nicht mehr nur von den Münzen und Waffen angezogen, sondern auch vom Mühlstein und den möglichen Personen, die dahinterstehen! Made with Unity More information on the accompanying university website.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: José, Calvo Tello;

    This is the code and data for following article: * Calvo Tello, José. 2023 (accepted). ‘Where Are Romance Studies Heading? A Bibliographic Data Science Analysis Using Regression’. Edited by Nanette Rißler-Pipika, Jan Rohden, and José Calvo Tello. Apropos [Perspektiven Auf Die Romania].

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Schumacher, Mareike K.;

    In diesem Repository finden Sie einen Raum-Classifier, der mit dem StanfordNER kompatibel ist, sowie dazugehörige Trainingsdaten. Die Datei "Raum320000_18-21_ner-model" ist ein Raum-Classifier mit sieben Unterkategorien, die mit dem StanfordNER kompatibel sind. Die Datei "Raum320000_18-21_ner-model_ohneMetaphern" entält den gleichen Classifier mit sechs Raum-Kategorien (Metaphern sind hier weggelassen). Die Kategorien sind: Ort Relation relationeles Verb Raumhinweis Raumbeschreibung Raumthema Raummetapher Die Datei "Raum320000_18-21_ner-model_ohneMetaphern" ist die empfohlene Version zur Anwendung. Beide Classifier können wie folgt verwendet werden: Laden Sie sich die Classifier herunter Laden Sie sich das Named-Entity-Recognition-Tool StanfordNER herunter Öffnen Sie den Stanford-Named-Entity-Recognizer wie auf der Seite der Stanford NLP Group beschrieben Laden Sie über "Classifier" > "Load CRF from file" den Raum-Classifier in das Tool Wählen Sie über "File" > "Open File" ein Dokument, in dem Raumausdrücke annotiert werden sollen Klicken Sie auf "Run" Die annotierten Daten können über "File" > "Save tagged file as" gespeichert und weiter verwendet werden. Die Annotationskategorien des Raum-Classifiers erreichen unterschiedliche Erkennungsquoten. Eine detaillierte Übersicht der Gesamterkennunggenauigkeit (F1-Score) der einzelnen Kategorien finden Sie im Unterordner "Modell Testreihen". Im Unterordner "Testreihen mit 7 Kategorien" sind im Dokument "7 Kategorien NER-Test Übersicht.xlsx" ausführliche Tests des gesamten Traningsprozesses dokumentiert. Getestet wurde mit acht Testtexten aus vier Jahrhunderten. Durchschnittswerte finden sich im Tabellenblatt "einige Durchschnittswerte". Die abschließenden Tests der finalen Classifier finden sich in den Zeilen 20 und 21. Werte für die einzelnen Testtexte aus den Jahrhunderten 18-21 sind in den anderen Tabellenblättern verzeichnet. Die annotierten Testtexte können - so weit das urheberrechtlich möglich ist, aus dem Unterordner "annotierte Testtexte" heruntergeldane werden. Hierin finden Sie sechs annotierte Texte in Tabellenform aus den Jahrhunderten 18-20 (die nicht gemeinfreien Texte aus dem 21. Jahrhundert können hier nicht zugänglich gemacht werden). Außerdem in diesem Repository zu finden sind: die Dokumentation von Tests eines ersten, nicht implementierten Modells (Ordner "Vorabtests - nicht implementierte Varianten") Anzahl der Annotationen im Trainingskorpus (im Ordner "Testreihen mit 7 Kategorien") Imformationen und Daten zum Trainig des Raum-Classifiers finden sich im Ordner "Training CRF-Classifier". Hierin ist eine Auflistung der Texte im Trainingskorpus enthalten. Aus jedem der aufgelisteten Texte wurden 4.000 Tokens direkt vom Anfang entnommen und ins Trainingskorpus integriert. Das Trainingskorpus besteht insgesamt aus 320.000 Tokens aus 80 Romanen aus vier Jahrhunderten (18-21). Annotierte Trainingsdaten im Tabellenformat TSV (kompatibel mit dem StanfordNER-Tool) finden sich im Unterordner "Trainingsdaten". Die Trainingsdaten aus dem 20. und 21. Jahrhundert enthalten urheberrechtlich geschütztes Material und können darum nicht öffentlich zugänglich gemacht werden. Die Trainingsdaten aus dem 18. und 19. Jahrhundert können jahrhundertweise heruntergeladen werden. Sowohl die Variante mit als auch die ohne Metaphern steht zur Nachnutzung zur Verfügung. Das Trainingskorpus umfasst 80.000 Tokens / Jahrhundert. Informationen zu den im Raum-Classifier implementierten Features können in der Properties-Datei "Raum.prop" eingesehen werden.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Software . 2021
    Data sources: ZENODO
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Software . 2021
      Data sources: ZENODO
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/

    CRF-Classifier für automatische Annotation männlicher, weiblicher und neutraler Genderzuschreibungen in deutschsprachiger Literatur. Der Gender-Classifier kann mit dem Stanford Named Entity Recognizer zusammen genutzt werden. Das Modell wurde mit einem Trainingskorpus folgender Zusammensetzung trainiert: ca. 100.000 Tokens aus 25 Novellen des deutschen Novellenschatzes ca. 40.000 Tokens aus 10 Romanen des 18. Jahrhunderts ca. 40.000 Tokens aus 10 Romanen des 19. Jahrhunderts ca. 40.000 Tokens aus 10 Romanen des 20. Jahrhunderts ca. 40.000 Tokens aus 10 Romanen des 21. Jahrhunderts ca. 20.000 Tokens aus 5 Dramen des 18. Jahrhunderts ca. 20.000 Tokens aus 5 Dramen des 19. Jahrhunderts ca. 20.000 Tokens aus 5 Dramen des 20. Jahrhunderts ca. 7.000 Figurennamen aus 500 Dramen des 17.-20. Jahrhunderts (bereitgestellt von https://dracor.org) Getestet wurde das Modell mit 6 Novellen aus dem deutschen Novellenschatz, 8 Romanen aus den Jahrhunderten 18-21 und 3 Dramen von Caroline von Günderrode (1805), das Modell erreichte in den Tests einen durchschnittlichen overall F1-Score von 78,09%. Die Erkennung von Genderzuschreibungen in Novellen des 19. Jahrhunderts ist mit einem durchschnittlichen overall F1-Score von 85,52% am besten. In Romanen des 18.-21. Jahrhunderts beträgt die durchschnittliche Gesamterkennungsgenauigkeit (F1-Score) 72,83%. In Ausschnitten aus drei Dramen von Caroline von Günderode (publiziert 1805) erreicht der Gender-Classifier einen F1-Score von 75,53% Der Classifier wird laufend weiter entwickelt. Es handelt sich um eine Open-Beta-Version. Geplant ist z.B. die Aufnahme weiterer Gender-Kategorien, die nicht in das Binärschema männlich-weiblich fallen. Der Classifier wurde im Projekt m*w entwickelt. Der Classifier kann wie folgt verwendet werden: Laden Sie sich den Classifier herunter Laden Sie sich das Named-Entity-Recognition-Tool StanfordNER herunter Öffnen Sie den Stanford-Named-Entity-Recognizer wie auf der Webseite der Stanford NLP Group beschrieben Laden Sie über "Classifier" > "Load CRF from file" den Gender-Classifier in das Tool Wählen Sie über "File" > "Open File" ein Dokument, in dem Genderzuschreibungen annotiert werden sollen Klicken Sie auf "Run" Die annotierten Daten können über "File" > "Save tagged file as" gespeichert und weiter verwendet werden.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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    Authors: Simmler, Severin;

    An important step in the quantitative analysis of narrative texts is the automatic recognition of references to figures, a special case of the generic NLP problem of Named Entity Recognition (NER). Usually NER models are not designed for literary texts resulting in poor recall. This Neural Network Model is the continuation of the work of Jannidis et al. and used in this easy-to-use package for the programming language Python.

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    Software . 2019
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6 Research products
  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: Klenk, Dominik;

    This upload belongs to the paper "Rapid and Reproducible Reconstruction of Ancient Architecture by Procedural Generation", to appear in the CHNT 26 Proceedings. The paper uses the 3D-reconstruction of the "Great Hall" of Karakorum as a case-study. Since the “Great Hall” is an almost completely destroyed building, a possible reconstruction turns out to be quite difficult. The aim was therefore to develop a method with which existing research and theories as well as connections to other architectural styles can be incorporated into the reconstruction. Accordingly, many different variants come into question for a possible reconstruction. Therefore, it is important that hypotheses are not tested on the basis of a single reconstruction, but that it is possible to visualise and discuss several different hypotheses in a short time. Such a method can be created with the help of a procedural generation. In order to implement possible hypotheses as a 3D model with this method, it is important that the generation of the 3D model can be influenced with the help of changeable parameters. In the paper the connections to the Chinese architecture are explained, as well as related works and theories are taken up, which pursued similar approaches and goals. Furthermore, the procedure of reconstruction is explained, and the method of procedural generation is illustrated by the parameter-controlled creation of the structural system of a Chinese-style building. This repository contains the pythons script, which implements a blender-panel to control the reconstruction of a medieval Chinese-style building with different user-defined parameters. To be completely sure that the script will work as expected it is recommended to use the Blender version 3.0.0, because it was developed to work with this version. To use the Blender Panel, it is necessary to import the script via the “Scripting” tab. Inside the “Scripting” tab it is possible to add the script with the folder icon above the text editor. After the script was added, the source code should be visible inside the text editor area. Once the script has been added successfully it needs to be executed with the arrow icon above the text editor. If the script was executed successfully, the panel should be visible in the 3D-Viewport of the “Layout” tab in the “Sidebar” labelled as “Tempel”. It is necessary to use the “Object-Mode” and if the “Sidebar” is not visible, it is possible to open it with the “N”-Key or with the small arrow in the upper right corner. The panel should now be visible as shown in Figure 6. Before it is possible to generate buildings with the panel it is important to add the path to the Blender-File, which includes the individual components used for the generation, as file path via the folder icon inside the panel. Now the individual parameters can be changed at will, and the possible reconstruction can be generated with a click on the “Generierung starten”-Button at the bottom of the panel.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao ZENODOarrow_drop_down
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    ZENODO
    Software . 2023
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    ZENODO
    Software . 2023
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao ZENODOarrow_drop_down
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      Software . 2023
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      Software . 2023
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Ehlers, Dajana; Kampf, Julia; Ihnen, Greta; Neuhaus, Lara Alyssa; +2 Authors

    Was ist Puls? Wann lebte Ramses II.? Und welche Länder bereisten die Wikinger? Alles Fragen die durch einen Besuch im Museum geklärt werden können. Doch was passiert, wenn nach einem langen Arbeitstag diese Fragen zwischen dir und deinem wohlverdienten Feierabend stehen? Komm zu uns ins Museum, lerne verschiedene Epochen in kurzen Alltagsmomenten kennen und entkomme aus dem Museum! Du bist in einem historischen Museum angestellt und nach einem viel zu langen Arbeitstag zwischen Objekten, Museumskonzepten und Recherche hast du die Zeit völlig aus den Augen verloren. Dein Chef und alle anderen haben dich vergessen und einfach eingeschlossen. Nun musst du versuchen einen Code für den Ausgang zu finden. Hierfür reist du mental zu den Römern, Ägyptern und Wikingern, meisterst Level in dem du das Alltagsleben der verschiedenen Kulturen nachempfindest. Gleichzeitig kannst du im Museum mehr über den Kontext der Geschichten und den Objekten, mit denen du interagierst, erfahren. Es öffnet dir den Blick, weg von den glitzernden „Sensationsfunden“, reißerischen Abenteuern und Zaubereien mit dem Pinsel, hin zu den Menschen wie du und ich. Die Erfahrungen reichen vom Handwerk, der Religion bis hin zum Essen. Vielleicht gehst du deinen nächsten Museumsbesuch etwas anders an und wirst nicht mehr nur von den Münzen und Waffen angezogen, sondern auch vom Mühlstein und den möglichen Personen, die dahinterstehen! Made with Unity More information on the accompanying university website.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: José, Calvo Tello;

    This is the code and data for following article: * Calvo Tello, José. 2023 (accepted). ‘Where Are Romance Studies Heading? A Bibliographic Data Science Analysis Using Regression’. Edited by Nanette Rißler-Pipika, Jan Rohden, and José Calvo Tello. Apropos [Perspektiven Auf Die Romania].

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Schumacher, Mareike K.;

    In diesem Repository finden Sie einen Raum-Classifier, der mit dem StanfordNER kompatibel ist, sowie dazugehörige Trainingsdaten. Die Datei "Raum320000_18-21_ner-model" ist ein Raum-Classifier mit sieben Unterkategorien, die mit dem StanfordNER kompatibel sind. Die Datei "Raum320000_18-21_ner-model_ohneMetaphern" entält den gleichen Classifier mit sechs Raum-Kategorien (Metaphern sind hier weggelassen). Die Kategorien sind: Ort Relation relationeles Verb Raumhinweis Raumbeschreibung Raumthema Raummetapher Die Datei "Raum320000_18-21_ner-model_ohneMetaphern" ist die empfohlene Version zur Anwendung. Beide Classifier können wie folgt verwendet werden: Laden Sie sich die Classifier herunter Laden Sie sich das Named-Entity-Recognition-Tool StanfordNER herunter Öffnen Sie den Stanford-Named-Entity-Recognizer wie auf der Seite der Stanford NLP Group beschrieben Laden Sie über "Classifier" > "Load CRF from file" den Raum-Classifier in das Tool Wählen Sie über "File" > "Open File" ein Dokument, in dem Raumausdrücke annotiert werden sollen Klicken Sie auf "Run" Die annotierten Daten können über "File" > "Save tagged file as" gespeichert und weiter verwendet werden. Die Annotationskategorien des Raum-Classifiers erreichen unterschiedliche Erkennungsquoten. Eine detaillierte Übersicht der Gesamterkennunggenauigkeit (F1-Score) der einzelnen Kategorien finden Sie im Unterordner "Modell Testreihen". Im Unterordner "Testreihen mit 7 Kategorien" sind im Dokument "7 Kategorien NER-Test Übersicht.xlsx" ausführliche Tests des gesamten Traningsprozesses dokumentiert. Getestet wurde mit acht Testtexten aus vier Jahrhunderten. Durchschnittswerte finden sich im Tabellenblatt "einige Durchschnittswerte". Die abschließenden Tests der finalen Classifier finden sich in den Zeilen 20 und 21. Werte für die einzelnen Testtexte aus den Jahrhunderten 18-21 sind in den anderen Tabellenblättern verzeichnet. Die annotierten Testtexte können - so weit das urheberrechtlich möglich ist, aus dem Unterordner "annotierte Testtexte" heruntergeldane werden. Hierin finden Sie sechs annotierte Texte in Tabellenform aus den Jahrhunderten 18-20 (die nicht gemeinfreien Texte aus dem 21. Jahrhundert können hier nicht zugänglich gemacht werden). Außerdem in diesem Repository zu finden sind: die Dokumentation von Tests eines ersten, nicht implementierten Modells (Ordner "Vorabtests - nicht implementierte Varianten") Anzahl der Annotationen im Trainingskorpus (im Ordner "Testreihen mit 7 Kategorien") Imformationen und Daten zum Trainig des Raum-Classifiers finden sich im Ordner "Training CRF-Classifier". Hierin ist eine Auflistung der Texte im Trainingskorpus enthalten. Aus jedem der aufgelisteten Texte wurden 4.000 Tokens direkt vom Anfang entnommen und ins Trainingskorpus integriert. Das Trainingskorpus besteht insgesamt aus 320.000 Tokens aus 80 Romanen aus vier Jahrhunderten (18-21). Annotierte Trainingsdaten im Tabellenformat TSV (kompatibel mit dem StanfordNER-Tool) finden sich im Unterordner "Trainingsdaten". Die Trainingsdaten aus dem 20. und 21. Jahrhundert enthalten urheberrechtlich geschütztes Material und können darum nicht öffentlich zugänglich gemacht werden. Die Trainingsdaten aus dem 18. und 19. Jahrhundert können jahrhundertweise heruntergeladen werden. Sowohl die Variante mit als auch die ohne Metaphern steht zur Nachnutzung zur Verfügung. Das Trainingskorpus umfasst 80.000 Tokens / Jahrhundert. Informationen zu den im Raum-Classifier implementierten Features können in der Properties-Datei "Raum.prop" eingesehen werden.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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    Software . 2021
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    CRF-Classifier für automatische Annotation männlicher, weiblicher und neutraler Genderzuschreibungen in deutschsprachiger Literatur. Der Gender-Classifier kann mit dem Stanford Named Entity Recognizer zusammen genutzt werden. Das Modell wurde mit einem Trainingskorpus folgender Zusammensetzung trainiert: ca. 100.000 Tokens aus 25 Novellen des deutschen Novellenschatzes ca. 40.000 Tokens aus 10 Romanen des 18. Jahrhunderts ca. 40.000 Tokens aus 10 Romanen des 19. Jahrhunderts ca. 40.000 Tokens aus 10 Romanen des 20. Jahrhunderts ca. 40.000 Tokens aus 10 Romanen des 21. Jahrhunderts ca. 20.000 Tokens aus 5 Dramen des 18. Jahrhunderts ca. 20.000 Tokens aus 5 Dramen des 19. Jahrhunderts ca. 20.000 Tokens aus 5 Dramen des 20. Jahrhunderts ca. 7.000 Figurennamen aus 500 Dramen des 17.-20. Jahrhunderts (bereitgestellt von https://dracor.org) Getestet wurde das Modell mit 6 Novellen aus dem deutschen Novellenschatz, 8 Romanen aus den Jahrhunderten 18-21 und 3 Dramen von Caroline von Günderrode (1805), das Modell erreichte in den Tests einen durchschnittlichen overall F1-Score von 78,09%. Die Erkennung von Genderzuschreibungen in Novellen des 19. Jahrhunderts ist mit einem durchschnittlichen overall F1-Score von 85,52% am besten. In Romanen des 18.-21. Jahrhunderts beträgt die durchschnittliche Gesamterkennungsgenauigkeit (F1-Score) 72,83%. In Ausschnitten aus drei Dramen von Caroline von Günderode (publiziert 1805) erreicht der Gender-Classifier einen F1-Score von 75,53% Der Classifier wird laufend weiter entwickelt. Es handelt sich um eine Open-Beta-Version. Geplant ist z.B. die Aufnahme weiterer Gender-Kategorien, die nicht in das Binärschema männlich-weiblich fallen. Der Classifier wurde im Projekt m*w entwickelt. Der Classifier kann wie folgt verwendet werden: Laden Sie sich den Classifier herunter Laden Sie sich das Named-Entity-Recognition-Tool StanfordNER herunter Öffnen Sie den Stanford-Named-Entity-Recognizer wie auf der Webseite der Stanford NLP Group beschrieben Laden Sie über "Classifier" > "Load CRF from file" den Gender-Classifier in das Tool Wählen Sie über "File" > "Open File" ein Dokument, in dem Genderzuschreibungen annotiert werden sollen Klicken Sie auf "Run" Die annotierten Daten können über "File" > "Save tagged file as" gespeichert und weiter verwendet werden.

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    Authors: Simmler, Severin;

    An important step in the quantitative analysis of narrative texts is the automatic recognition of references to figures, a special case of the generic NLP problem of Named Entity Recognition (NER). Usually NER models are not designed for literary texts resulting in poor recall. This Neural Network Model is the continuation of the work of Jannidis et al. and used in this easy-to-use package for the programming language Python.

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    ZENODO
    Software . 2019
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Software . 2019
    Data sources: ZENODO
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      ZENODO
      Software . 2019
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      ZENODO
      Software . 2019
      Data sources: ZENODO
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