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Abstract

This article is a programmatic article, which formulates a new approach to information science (IS): domain analysis. This approach states that the most fruitful horizon for IS is to study the knowledge-domains as thought or discourse communities, which are parts of society's division of labor. The article is also a review article, providing a multidisciplinary description of research, illuminating this theoretical view. The first section presents contemporary research in IS, sharing the fundamental viewpoint that IS should be seen as a social rather than as a purely mental discipline. In addition, important predecessors to this view are mentioned and the possibilities as well as the limitations of their approaches are discussed. The second section describes recent transdisciplinary tendencies in the understanding of knowledge. In bordering disciplines to IS, such as educational research, psychology, linguistics, and the philosophy of science, an important new view of knowledge is appearing in the 1990s. This new view of knowledge stresses the social ecological, and content-oriented nature of knowledge. This is opposed to the more formal, computer-like approaches that dominated in the 1980s. The third section compares domain-analysis to other major approaches in IS, such as the cognitive approach. The final section outlines important problems to be investigates, such as how different knowledge-doamins affect the informational value of different subject access points in databases

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Abstract

Work centered design of classification schemes is an emerging area of research which poses particular challenges to domain analysis and scheme construction. A key challenge in work centered design of classification schemes is the evolving semantics of work. This article introduces a work centered approach to the design of classification schemes, based an the framework of cognitive work analysis. We launch collaborative task situations as a new unit of analysis for capturing evolving semantic structures in work domains. An example case from a cognitive work analysis of three national film research archives illustrates the application of the framework for identifying actors' needs for a classification scheme to support collaborative knowledge integration. It is concluded that a main contribution of the new approach is support for empirical analysis and overall design of classification schemes that can serve as material interfaces for actors' negotiations and integration of knowledge perspectives during collaborative work.

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Abstract

Discusses how classification systems have developed to perform the work of articulation in electronic libraries as exemplified by projects involving cooperative design of classificatory structures and democratic classification and indexing. Delineates the stages in this evolution and focuses on the mutual design activity of libraries and users which took place in the development of an enriched multimedia catalogue on the WWW at Ballerup public library in Denmark and on research in england into the democratic indexing of images and fiction. Although recent projects are promising it is important to avoid a mechanistic concept of knowledge and maintain a social view

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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).

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Abstract

In information science, classification systems are conventionally viewed as tools for representing knowledge in the universe of ideas, the human mind, or one or more sets of documents. In this view, developing and maintaining relationships and structures in classification schemes must primarily consider two abstract ingredients: i) a set of concepts for one or more domains; and ii) a (set of) unambiguous structure(s) to articulate the relationships that persist between the various concepts that comprise the classificatory structure. We contend that design decisions pertaining to the structure of a classification system consist of far more than simply creating links between the elements in a particular set of concepts. Ultimately, a simplistic tool view of classifications implies that the construction is little more than a technical task in a very narrow sense: that classificatory concepts are viewed as standard representations of what are assumed to be the central and/or important topics in the knowledge domain(s), and that there is i) an unambiguous Platonic ideal or universal consensus that determines how the links will be generated within a classificatory structure; or, conversely, ii) that there are no general structures and relationships available at all, but that only diverse individual knowledge structures exist, which cannot be reconciled into a general organization of knowledge

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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