Viewer Tagging in Art Museums: Comparisons to Concepts and Vocabularies of Art Museum Visitors

Abstract

As one important experiment in the social or user-generated classification of online cultural heritage resources collections, art museums are leading the effort to elicit keyword descriptions of artwork images from online museum visitors. The motivations for having online viewerspresumably largely non-art-specialists-describe art images are (a) to generate keywords for image and object records in museum information retrieval systems in a cost-effective way and (b) to engage online visitors with the artworks and with each other by inviting visitors to express themselves and share their descriptions of artworks. This paper explores the question of how effective non-specialist art keyworders can be in capturing ("tagging") potentially useful concepts and terms for use in art information retrieval systems. To do this, the paper compares evidence from art museum visitor studies which describe how non-specialist art viewers react to and describe artworks and use museum-supplied information in their initial encounters with artworks.A theoretical model of artwork interpretation derived from art museum visitor research provides a framework with which to examine both the activity and the products of artwork tagging for image and information retrieval.

Expert and adolescent interpretive approaches in a national art museum

“…In the gallery setting, this need is apparent in the visitors' engagement with individual artwork and their search for information in labels and previous knowledge to explore a deeper meaning. This finding supports Smith's (2006) claim that visitors feel a need for more information in order to engage on higher levels of art inquiry, at iconographic and iconological levels (Panofsky 1975). The social context triggered the group's search for new information, created a shared interpretive vocabulary and fostered joint orientation to specific aspects of works.…”

“…Understanding such tensions is particularly relevant in view of the development of gallery technologies and the democratising potential of social media currently explored in museums' communication designs. Studies of art museums' experiments with visitor labelling in exhibits (Parry, Ortiz-Williams, and Sawyer 2007) and crowd-sourced tagging of collection databases are examples of approaches to bridging semantic gaps (Smith 2006). A found that museum professionals positively evaluated the usefulness of the non-specialist perspective on artworks, and that understanding interpretation through the eyes of the visitors made it possible to adapt practices as necessary (Trant 2006).…”

Linking and clustering artworks using social tags: Revitalizing crowd‐sourced information on cultural collections

“…In addition, as the number of social tags grows rapidly, it is easy for users to get lost, leading to low findability (Karampinas & Triantafillou, 2012;Quintarelli, Resmini, & Rosati, 2007;Stock, 2007). This undermines the role of social tags as a meaningful bridge (Smith, 2006). Bar-Ilan, Shoham, Idan, Miller, and Shachak (2008) proposed that structured tags can help overcome these limitations by facilitating a deeper understanding about contents compared to the conventional tag cloud, which is an unstructured set of tags.…”

“…This involves looking at the online collection-digital representation of artworks, books, documents, historical remains, etc.-and adding keyword metadata that they associate with each object. This provides new information about the collection and improves its accessibility, thus opening up a channel for the public to communicate with the museum's information and knowledge system like never before (Cairns, 2013;Chae & Kim, 2011b;Smith, 2006). However, the great popularity that social tagging systems have enjoyed in museums since the late 2000s seems to be faltering recently.…”

Folksonomy and information retrieval

“…This non‐textual information (as well as some fictional texts) consists not only of one single level of aboutness as, e.g., scientific articles. According to Erwin Panofsky (2006) there are three different semantic levels of interpretation for artwork (Smith, 2006, p. 9). We will explain Panofsky's theory by giving an example of a photo found in Flickr (fig.…”