ACM Home Page
Please provide us with feedback. Feedback
Using AutoMed metadata in data warehousing environments
Full text PdfPdf (271 KB)
Source Data Warehousing and OLAP archive
Proceedings of the 6th ACM international workshop on Data warehousing and OLAP table of contents
New Orleans, Louisiana, USA
SESSION: Maintenance and workload table of contents
Pages: 86 - 93  
Year of Publication: 2003
ISBN:1-58113-727-3
Authors
Hao Fan  School of Computer Science and Information Systems, Birkbeck College, University of London
Alexandra Poulovassilis  School of Computer Science and Information Systems, Birkbeck College, University of London
Sponsors
SIGIR: ACM Special Interest Group on Information Retrieval
ACM: Association for Computing Machinery
SIGMIS: ACM Special Interest Group on Management Information Systems
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 7,   Downloads (12 Months): 92,   Citation Count: 1
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues   peer to peer  

Tools and Actions: Review this Article  
Save this Article to a Binder    Display Formats: BibTex  EndNote ACM Ref   
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/956060.956076
What is a DOI?

ABSTRACT

What kind of metadata can be used for expressing the multiplicity of data models and the data transformation and integration processes in data warehousing environments? How can this metadata be further used for supporting other data warehouse activities? We examine how these questions are addressed by AutoMed, a system for expressing data transformation and integration processes in heterogeneous database environments.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

1
 
2
3
 
4
D. Calvanese, G. Giacomo, M. Lenzerini, D. Nardi, and R. Rosati. A principled approach to data integration and reconciliation in data warehousing. In Proc. DMDW'99, 1999.
5
 
6
7
 
8
H. Fan. Incremental view maintenance and data lineage tracing in heterogeneous database environments. In Proc. BNCOD'02 PhD Summer School, Sheffied, pages 14--21, 2002.
 
9
H. Fan and A. Poulovassilis. Tracing data lineage using schema transformation pathways. In Knowledge Transformation for the Semantic Web, pages 64--79. IOS Press, 2003.
10
 
11
Holger Hinrichs and Thomas Aden. An {ISO 9001: 2000 compliant quality management system for data integration in data warehouse systems. In Proc. DMDW'01, 2001.
 
12
B. Hsemann, J. Lechtenbürger, and G. Vossen. Conceptual data warehouse modeling. In Proc. DMDW'00, 2000.
 
13
E. Jasper, N. Tong, P. McBrien, and A. Poulovassilis. View generation and optimisation in the AutoMed data integration framework. Technical report, AutoMed Project, 2003.
 
14
 
15
P. McBrien and A. Poulovassilis. Data integration by Bi-directional schema transfformation rules In Proc. ICDE'03, 2003.
 
16
D. Moody and M. Kortink. From enterprise models to dimensional models: a methodology for data warehouse and data mart design. In Proc. DMDW'00, 2000.
 
17
Erhard Rahm and Hong Hai Do. Data cleaning: Problems and current approaches. IEEE Data Engineering Bulletin, 23(4):3--13, 2000.
 
18
19
 
20
A. Tsois, N. Karayannidis, and T. Sellis. MAC: Conceptual data modeling for OLAP. In Proc. DMDW'01, 2001.
21
 
22


Collaborative Colleagues:
Hao Fan: colleagues
Alexandra Poulovassilis: colleagues

Peer to Peer - Readers of this Article have also read: