Loading...
Loading...

Go to the content (press return)

SETL: A programmable semantic extract-transform-load framework for semantic data warehouses

Author
Deb Nath, R.; Hose, K.; Bach, T.; Romero, O.
Type of activity
Journal article
Journal
Information systems
Date of publication
2017-08-01
Volume
68
First page
17
Last page
43
DOI
https://doi.org/10.1016/j.is.2017.01.005 Open in new window
Repository
http://hdl.handle.net/2117/113594 Open in new window
URL
http://www.sciencedirect.com/science/article/pii/S0306437916302101 Open in new window
Abstract
In order to create better decisions for business analytics, organizations increasingly use external structured, semi-structured, and unstructured data in addition to the (mostly structured) internal data. Current Extract-Transform-Load (ETL) tools are not suitable for this “open world scenario” because they do not consider semantic issues in the integration processing. Current ETL tools neither support processing semantic data nor create a semantic Data Warehouse (DW), a repository of semant...
Citation
Deb Nath, R., Hose, K., Bach, T., Romero, O. SETL: A programmable semantic extract-transform-load framework for semantic data warehouses. "Information systems", 1 Agost 2017, vol. 68, p. 17-43.
Keywords
Data warehouse, ETL, Knowledge base, RDF, Semantic integration, Semantic-aware
Group of research
IMP - Information Modelling and Processing
inLab FIB

Participants

Attachments