• Archives of design research
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• v.12 no.4
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• pp.231-241
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• 1999

This study propose to analyze the design method and the form elements of museums, of works by Richard Meier, and through the analysis, spacial characteristics of museums will be understood. The museum works of Richard Meier, as an exhibition space, not only display the art works efficiently, but they also offer visitors the opportunity to experience the art of architecture, as a cultural space. Richard Meier, when working on the projects, has utilized the design methods and the architectural language, learned from Mies van der Rohe and Le Corbusier, resourcefully. Having the structural grid as basis, the rational rectangular forms were intended for exhibition space, while the circular and partial circular forms of geometry were utilized in formative space. This was able to maintain the balance between functional and formative space. In the museums of his works, the ramp and the glass wall separated from the structure become very important means of expression. The ramps, not only make people to enjoy the interior and exterior of museum, but also able them to see the works of art from different distances and angles repeatedly and the large glass wall reveals the various shapes of interior to exterior. In comparing with the design method and language of two masters mentioned, the design principles and elements, developed by Meier were applied to the site plans, exhibition space planning and elevations to manifest its originality. The design concept, derived from the urban fabric and historical buildings around, gave harmony to the museum with its surroundings, and employing the deformed axis brought variation and the effect of diversion to the site plan. The exhibition space is much vitalized by the well arrangement of various exhibition fixtures in the museum. The exhibion fixtures, which the partitions, shelves, miches, and stages were put together in flexibility, play multiple roles as partitions dividing spaces, as furniture displaying art works, and as elements creating forms. The systematically arranged fixtures, also produce several visual axes and centers, which have visitors appreciate the works of art in various perspectives, hence create a unique environment.

• Journal of the Korean Society for information Management
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• v.31 no.2
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• pp.57-77
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• 2014

As co-authorship has been prevalent within science communities, counting the credit of co-authors appropriately is an important consideration, particularly in the context of identifying the knowledge structure of fields with author-based analysis. The purpose of this study is to compare the characteristics of co-author credit counting methods by utilizing correlations, multidimensional scaling, and pathfinder networks. To achieve this purpose, this study analyzed a dataset of 2,014 journal articles and 3,892 cited authors from the Journal of the Architectural Institute of Korea: Planning & Design from 2003 to 2008 in the field of Architecture in Korea. In this study, six different methods of crediting co-authors are selected for comparative analyses. These methods are first-author counting (m1), straight full counting (m2), and fractional counting (m3), proportional counting with a total score of 1 (m4), proportional counting with a total score between 1 and 2 (m5), and first-author-weighted fractional counting (m6). As shown in the data analysis, m1 and m2 are found as extreme opposites, since m1 counts only first authors and m2 assigns all co-authors equally with a credit score of 1. With correlation and multidimensional scaling analyses, among five counting methods (from m2 to m6), a group of counting methods including m3, m4, and m5 are found to be relatively similar. When the knowledge structure is visualized with pathfinder network, the knowledge structure networks from different counting methods are differently presented due to the connections of individual links. In addition, the internal validity shows that first-author-weighted fractional counting (m6) might be considered a better method to author clustering. Findings demonstrate that different co-author counting methods influence the network results of knowledge structure and a better counting method is revealed for author clustering.