Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/168961
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dc.contributor.authorOng, Zi Fengen_US
dc.date.accessioned2023-06-26T00:34:25Z-
dc.date.available2023-06-26T00:34:25Z-
dc.date.issued2023-
dc.identifier.citationOng, Z. F. (2023). Visual mapping art : data visualization & crowdsourcing for an ostensive definition of art. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/168961en_US
dc.identifier.urihttps://hdl.handle.net/10356/168961-
dc.description.abstractArt categorization is challenging (Novitz, 1996; Ziff, 1953) because definitions of art vary throughout art history and amongst different philosophical schools. (Adajian, 2018, Tatarkiewicz, 1980). The purpose of this research is not to join these art historical and philosophical discussions, but to build a perceptible, practicable component that could be used by the public through applying the ostensible definitions of art as an exploratory, statistical database. This research will build the framework to categorize forms of art in a database as the practical component. The core data will be gathered from existing art databases, such as the Library of Congress (LCC) (Class-N - Fine Arts) and the Universal Decimal Classification (UDC) (73/76 Various arts & crafts); and controlled vocabulary systems such as Art & Architecture Thesaurus (AAT). The core data will be utilized as a framework for crowdsourcing, with Human Intelligence Tasks (HIT) implemented on Amazon Mechanical Turk (MTurk) to increase the number of art forms in the database to include less prevalent art forms. As an endpoint of this research, the data obtained through the process of existing art database extraction and crowdsourcing will be shown through a network visualization on a website as a practical component for the public to observe the classification of art in a graphical fashion.en_US
dc.language.isoenen_US
dc.publisherNanyang Technological Universityen_US
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).en_US
dc.subjectVisual arts and music::Arts in generalen_US
dc.subjectLibrary and information science::Libraries::Cataloguing and classificationen_US
dc.titleVisual mapping art : data visualization & crowdsourcing for an ostensive definition of arten_US
dc.typeThesis-Master by Researchen_US
dc.contributor.supervisorBernhard Johannes Schmitten_US
dc.contributor.schoolSchool of Art, Design and Mediaen_US
dc.description.degreeMaster of Artsen_US
dc.identifier.doi10.32657/10356/168961-
dc.contributor.supervisoremailbjschmitt@ntu.edu.sgen_US
item.fulltextWith Fulltext-
item.grantfulltextopen-
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