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Abstract

This paper introduces a new approach to the design of classification schemes for complex work domains to help structure the knowledge domains in databases for single users and multiple users in co-operative work. Ecological work based classification schemes are designed on the basis of an empirical analysis of the invariant structures of the work domain and of the information needs of its actors. Invariant structures of a work domain can be explicit or implicit (hidden structures). The invariant structures are identified through empirical analysis of field studies in work domains, guided by the use of a means ends abstraction hierarchy. This hierarchy provides a model for analyzing, or-ganizing and relating different levels of properties within a work domain. The resulting structure is an ecological classification scheme, comprising the different dimensions or categories of domain information that needs to be available for an actor to make a decision. Contrary to traditional classification systems which usually are designed from one particular point of view (a single discipline, paradigm or purpose), ecological classification schemes provide a transparent and structured information environment in which actors can navigate freely according to their current perspectives of work and subjective preferences

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Source

Knowledge organization and the global information society: Proceedings of the 8th International ISKO Conference 13-16 July 2004, London, UK. Ed.: I.C. McIlwaine

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Abstract

Collaborative integration of knowledge in distributed and cross-disciplinary work domains poses a number of challenges to classification, comprising: 1) how to analyze the actors' current practice of integration of knowledge and 2) how to model consistent semantic support of diverse interpretive perspectives among the actors. This paper introduces a cognitive systems engineering approach to modelling collaborative integration of knowledge in work domains. A generic means-ends model provides a theoretical foundation for mapping the territory of collaborative work. A decision task model captures the actors' distributed decision-making in integration of knowledge. The problem of collaborative integration of knowledge in a distributed web-based film collaboratory is explored through an empirical case of collaborative film indexing. The empirical study identified a lack of tools for consistent support of integration of knowledge. The means-ends model and the decision task model guided the design of a conceptual structure of the common workspace of film indexing. The paper concludes with a proposal for further work an models for integration of knowledge through ecological classification schemes. 1. Introduction Current work practice and knowledge production to an increasing degree involves actors from different disciplines, cultures and organisations. Additionally, current work practice not only relies an authoritative orderings of knowledge, but also relies an the dynamism of the actors' ongoing collaborative integration of knowledge, i.e. their shared interpretations of knowledge, exchange of perspectives and joint knowledge production. Consequently, in order to support the actors' ongoing collaborative integration of knowledge, the design of support tools, like classification schemes, must address not only the order of knowledge, but also the situational contexts where collaborative integration of knowledge occurs. This paper introduces an ecological approach to integration of knowledge across boundaries in distributed collaboratory work environments, which is founded an (a) work domain analysis (b) the development of models for collaborative integration of knowledge. The work domain analysis is based an means-ends analysis of the territory of work and the actors' information needs during decision making. The result is conceptual structures of collaborative work that can be used to create collaborative classification schemes. Previous work an design of ecological classification schemes proposed that such schemes should be based an a finegrained empirical analysis of actors' collaborative decision tasks in order to identify the knowledge produced and needed by the actors (Pejtersen & Albrechtsen, 2000).