Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/168961
Title: Visual mapping art : data visualization & crowdsourcing for an ostensive definition of art
Authors: Ong, Zi Feng
Keywords: Visual arts and music::Arts in general
Library and information science::Libraries::Cataloguing and classification
Issue Date: 2023
Publisher: Nanyang Technological University
Source: 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
Abstract: 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.
URI: https://hdl.handle.net/10356/168961
DOI: 10.32657/10356/168961
Schools: School of Art, Design and Media 
Rights: This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:ADM Theses

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