|Title:||Affect in Information Systems: A Knowledge Organization System Approach to Documenting Visitor-Artwork Experiences|
|Publication:||MW2019: MuseWeb 2019|
Viewers of artworks exhibited in museums and galleries are known to experience felt reactions to art objects and exhibitions in a way that constitutes an important dimension of the public function of museums, complementary to their role as sites of learning and community. The ability of artworks to elicit such affective response is widely recognized, yet remains absent from museum documentation systems, standards, and methods. It is impossible to continue to ignore the gulf between the information that the museum wants to present to its publics, and the information that the museum collects and stores in its information systems.
In this paper, based on my Master’s thesis (Canning, 2018), I discuss the development of a conceptual framework for the notion of affect in experiences of artworks within the art museum, and its manifestation in museum information systems and standards—namely, the inclusion of affective metadata, involving both a data model and corresponding taxonomy of affective terms. This system should be able to reliably represent the diversity and complexity of information related to the affective dimensions of the art-viewing experience. In addition to initial system development, I discuss the process and results of an empirical visitor-response study conducted to validate the proposed model, and the revisions and future work that came to light as a result of this study. In particular, I discuss the notion of empathy and connection-making that occurred between research participants and the artworks selected for the study. I conclude by examining how this process could be incorporated into the proposed model, and discuss the complexities in doing so.