An investigation of the basis of representation of aesthetic objects held in collections in museums
Citation:REEVES, MARIAN, An investigation of the basis of representation of aesthetic objects held in collections in museums, Trinity College Dublin.School of Computer Science & Statistics, 2019
MRV-PHD-FinalThesis-Submitted.pdf (Reviewed by External and Internal examiners) 4.791Mb
The design of robust databases for storing data about aesthetic objects is a major challenge, as manifested through discussions on metadata standards about these objects. These databases play a key role in the visualisation and conservation of cultural heritage, for instance. The access to such databases from a variety of users presents a significant opportunity for a number of stakeholders, including the general public, policy makers and art gallery curators. The attributes and associated (many) values associated with these objects can also be ascertained from experts in art history and museum curators. A method for acquiring such data from these sources, metadata standards and domain experts is presented in this thesis together with a prototype database that demonstrates how value can be added through this method, particularly knowledge acquisition from domain experts. Domain experts responsible for the preservation of collections in their care, consult diverse resources when conducting their research, including primary sources of artist archives. These primary sources contain unique, private and contemporaneous materials and potentially provide valuable background and contextual information about the artist, his methods and the artworks. The prototype system developed for this study combines aesthetic objects and related artist's archives to provide a more comprehensive representation than is typically available. The system was specified with the help of domain experts and tested with their help. Issues related to knowledge representation of aesthetic objects like ontological antecedents on one hand and provenance of such objects are also discussed.
Author: REEVES, MARIAN
Publisher:Trinity College Dublin. School of Computer Science & Statistics. Discipline of Computer Science
Type of material:Thesis
Availability:Full text available