Knowl. Org. 44(2017)No.7 R. Szostak. A Grammatical Approach to Subject Classification in Museums 494 A Grammatical Approach to Subject Classification in Museums Rick Szostak University of Alberta, Department of Economics, Tory Building 9-18, Edmonton, Alberta, T6G 2H4, CANADA, <rszostak@ualberta.ca> Rick Szostak is Professor and Chair of Economics at the University of Alberta. He is the author of fifteen books and fifty journal articles in economics, history, interdisciplinary studies, information science, and several other fields. He has studied the theory and practice of interdisciplinarity for two decades and has emphasized in the last decade the ways in which knowledge organization systems might better facilitate interdisciplinary research and teaching. He has long argued that a phenomenon-based synthetic approach to classification is both feasible and desirable; he has more recently stressed the use of grammatical construction in performing that synthesis. He re- cently co-authored Interdisciplinary Knowledge Organization. He has created the Basic Concepts Classification (BCC), and is engaged in efforts to evaluate the BCC and compare it to other classification systems. Szostak, Rick. 2017. “A Grammatical Approach to Subject Classification in Museums.” Knowledge Organization 44, no. 7: 494-505. 26 references. Abstract: Several desiderata of a system of subject classification for museums are identified. The limitations of existing approaches are reviewed. It is argued that an approach which synthesizes basic concepts within a grammatical structure can achieve the goals of subject classification in museums while addressing diverse challenges. The same approach can also be applied in galleries, archives, and libraries. The approach is described in some detail and examples are provided of its application. The article closes with brief discussions of thesauri and linked open data. Received: 9 June 2017; Revised: 5 September 2017; Accepted 10 September 2017 Keywords: Subject classification; Museums; Basic concepts; Grammar; Facets 1.0 Introduction This paper seeks to address two key challenges in knowl- edge organization for museums. First, it is often recog- nized in the literature that it would be advantageous to utilize the same knowledge organization system (KOS) across the entire GLAM sector since users increasingly search across galleries, libraries, archives, and museums. McMarty (2014, 615) for example, argues that museums, libraries, and archives now face a very similar set of user expectations as a result of each developing an online presence; he cites a number of conferences and special issues of journals focused on how to respond. Yet, the KOSs developed for libraries are often thought to be ill- suited to the classification of objects. Second, museums often have limited resources to devote to classification, and often do not have staff trained in knowledge organi- zation. Museum training has tended to focus on under- standing the artifacts rather than knowledge organiza- tion—though of course there has always been some in- terest in and familiarity with knowledge organization in museums (Urban 2014). We would want, then, a KOS that is capable of addressing both objects and docu- ments, and yet is easy for both cataloguer and user to navigate. The solution that will be proposed involves a synthetic and grammatical approach to subject headings. This would allow cataloguers in museums, archives, and librar- ies to move fairly directly from a sentence in an existing object or document description to a synthetic subject string that orders terms grammatically. Though objects and documents differ in many ways, they are each com- monly described—by publishers, authors, or curators—in a few sentences. Users in turn can move fairly directly from a query stated as a sentence to the most relevant subject string. Since object descriptions, document de- scriptions, and user queries are all formulated in sen- tences, there is obvious value in using sentence structure also in the subject headings that mediate among these. The next section of this paper provides more detail on the challenges of museum classification. The succeeding section then addresses the present state of museum clas- sification and foreshadows the potential advantages of a new approach. We are then able to expand on the nature of a synthetic and grammatical approach to classification that addresses the challenges identified. Examples are https://doi.org/10.5771/0943-7444-2017-7-494 Generiert durch IP '3.215.190.136', am 26.11.2021, 01:38:54. Das Erstellen und Weitergeben von Kopien dieses PDFs ist nicht zulässig.