DocumentCode
3134536
Title
An integrated metadata model for statistical data collection and processing
Author
Vardaki, Maria ; Papageorgiou, H.
Author_Institution
Dept. of Public Adm., Panteion Univ., Athens, Greece
fYear
2004
fDate
21-23 June 2004
Firstpage
363
Lastpage
372
Abstract
An integrated, semantically rich statistical metadata model is designed to cover the major stages of the statistical information processing (data collection and analysis including harmonization, processing of data and metadata and dissemination/output phases), which can minimize complexity of data warehousing environments and compatibility problems between distributed statistical information systems (SIS). The semantics of the model are analyzed, describing each part of the statistical processing. In addition, process metadata (operators) for automatic manipulation of both data and metadata are also defined over their common domain as well as logistic metadata for the location and format of data. Furthermore, we discuss how the proposed framework can facilitate actual information entry and analysis into a SIS. Finally, we demonstrate in a case study how the suggested metadata model can be implemented and integrated into a modern metadata-enabled SIS, thus standardizing the processing environment and assuring the quality of statistical results.
Keywords
data acquisition; data models; data warehouses; distributed databases; information analysis; meta data; statistical databases; automatic data manipulation; compatibility problems; complexity minimization; data analysis; data dissemination; data format; data harmonization; data location; data output; data warehousing environments; distributed statistical information systems; information analysis; integrated metadata model; logistic metadata; metadata manipulation; metadata-enabled SIS; model semantics; process metadata; process operators; statistical data collection; statistical data processing; Conference management; Databases;
fLanguage
English
Publisher
ieee
Conference_Titel
Scientific and Statistical Database Management, 2004. Proceedings. 16th International Conference on
ISSN
1099-3371
Print_ISBN
0-7695-2146-0
Type
conf
DOI
10.1109/SSDM.2004.1311232
Filename
1311232
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