Data Centralization - Biomedical Informatics in Translational Research - page 171

8.6 Summary

In biomedical informatics research, large amounts of data are generated across the
clinical, genomic, and proteomic platforms. To find answers to questions arising
from clinical practices and research exercises, these data need to be centralized, and
data warehousing is one way to do it. Data warehousing has been applied to the
banking, retail, and other industries for many years, but its application to life sci-
ences is relatively new.
In principle, we suggested that the internally generated data be integrated but
external and public data be federated. The importance of developing a
patient-centric modular structure as a middle data tier was discussed, together with
proper handling of the temporal data. Important issues in developing a DW for inte-
grative biomedical informatics research were discussed as well. A real DW example
in a nonprofit integrative biomedical informatics research environment was

provided.
It is expected that after reading this chapter, a user will have a good understand-
ing of the status of DW application to the field of biomedical informatics research
and be able to apply this knowledge to his or her own research environment.

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