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The objective of this work is to assess to what extent data reengineering processes could also take advantage of MDE techniques.
Some approaches and experiences of model-driven software reengineering have recently been presented but they have been focused on the code while data reengineering aspects have been overlooked.
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Detailed provenance information and full traceability of all data and analytical components becomes even more critical in an emerging big-data-driven knowledge reengineering scenario (Hoekstra, 2011; Robbins and Chiesa, 2011).
Information on Reengineering the Clinical Research Enterprise can be obtained from http://nihroadmap.nih.gov/clinicalresearch/overview-translational.asp.asp
Information on Reengineering the Clinical Research Enterprise can be obtained from: http://nihroadmap.nih.gov.
Second was to build on the accomplishments of cloud computing by reengineering the data warehouse to take full advantage of the cloud.
This paper discusses transforming ontological models into non-ontological models of business processes, when the process of articulating different data models is known as reengineering domains.
In contrast to the established network reengineering algorithms from dynamic data, which require time course measurements of phosphorylation, this approach utilizes static data.
For this reason, the data warehouse design has been traditionally considered a reengineering process, guided by requirements, from the data sources.
This week: using mobile to reduce supply chain risk; reengineering with machines; a data science primer for execs.
The concept is based on the functional network re-engineering concept (as described above), but the focus is on the development of additional modules in order to overcome the drawbacks of the hierarchical network reconstruction algorithm in the special case of signalling network reengineering from stimulation-inhibition data.
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