Visual mapping art : data visualization & crowdsourcing for an ostensive definition of art
Art 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...
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| Format: | Thesis-Master by Research |
| Language: | English |
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Nanyang Technological University
2023
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| Online Access: | https://hdl.handle.net/10356/168961 |
| _version_ | 1824454782574657536 |
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| author | Ong, Zi Feng |
| author2 | Bernhard Johannes Schmitt |
| author_facet | Bernhard Johannes Schmitt Ong, Zi Feng |
| author_sort | Ong, Zi Feng |
| collection | NTU |
| description | Art 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. |
| first_indexed | 2025-02-19T03:27:47Z |
| format | Thesis-Master by Research |
| id | ntu-10356/168961 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T03:27:47Z |
| publishDate | 2023 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1689612023-07-04T01:52:13Z Visual mapping art : data visualization & crowdsourcing for an ostensive definition of art Ong, Zi Feng Bernhard Johannes Schmitt School of Art, Design and Media bjschmitt@ntu.edu.sg Visual arts and music::Arts in general Library and information science::Libraries::Cataloguing and classification Art 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. Master of Arts 2023-06-26T00:34:25Z 2023-06-26T00:34:25Z 2023 Thesis-Master by Research Ong, 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/10356/168961 https://hdl.handle.net/10356/168961 10.32657/10356/168961 en This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). application/pdf Nanyang Technological University |
| spellingShingle | Visual arts and music::Arts in general Library and information science::Libraries::Cataloguing and classification Ong, Zi Feng Visual mapping art : data visualization & crowdsourcing for an ostensive definition of art |
| title | Visual mapping art : data visualization & crowdsourcing for an ostensive definition of art |
| title_full | Visual mapping art : data visualization & crowdsourcing for an ostensive definition of art |
| title_fullStr | Visual mapping art : data visualization & crowdsourcing for an ostensive definition of art |
| title_full_unstemmed | Visual mapping art : data visualization & crowdsourcing for an ostensive definition of art |
| title_short | Visual mapping art : data visualization & crowdsourcing for an ostensive definition of art |
| title_sort | visual mapping art data visualization crowdsourcing for an ostensive definition of art |
| topic | Visual arts and music::Arts in general Library and information science::Libraries::Cataloguing and classification |
| url | https://hdl.handle.net/10356/168961 |
| work_keys_str_mv | AT ongzifeng visualmappingartdatavisualizationcrowdsourcingforanostensivedefinitionofart |