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A Statistical Metadata Model for Simultaneous Manipulation of both Data and Metadata

There is a growing demand for more cost-efficient production processes in Statistical Institutes. One way to address this need is to equip Statistical Information Systems (SIS) with the ability to automatically produce statistical data and metadata of high quality and deliver them to the user via th...

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Bibliographic Details
Published in:Journal of intelligent information systems 2001-12, Vol.17 (2-3), p.169
Main Authors: Papageorgiou, H, Pentaris, Fragkiskos, Theodorou, Eirini, Vardaki, Maria, Petrakos, Michalis
Format: Article
Language:English
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Summary:There is a growing demand for more cost-efficient production processes in Statistical Institutes. One way to address this need is to equip Statistical Information Systems (SIS) with the ability to automatically produce statistical data and metadata of high quality and deliver them to the user via the Internet. Current approaches, although provide for the storage of appropriate metadata, do not use process metadata for guiding the production process. In this paper we present an approach on creating SISs that permits metadata-guided statistical processing based on an object-based, statistical metadata model. The model is not domain specific and can accommodate both microdata and macrodata. We have equipped the model with a set of transformations that can be used to automatically manipulate data and metadata. We show the applicability of transformations with some examples using actual statistical data for R&D expenditures. Finally, we demonstrate how the presented framework can be exploited for the construction of a web site that offers ad hoc query capabilities to the users of statistical data. [PUBLICATION ABSTRACT]
ISSN:0925-9902
1573-7675
DOI:10.1023/A:1012805713392