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To understand the visible and hidden SF history in the Universe, it is crucial to analyze multiwavelength data in a unified manner.
Within this framework, a data model called the Network Analytics ER model (NAER) is developed, which enables us to manage and analyze network data in a unified way.
Starting from a multitude of new parameters coming from the architecture, engineering and construction domain like materials, thermal properties, building layout and orientation, as well as miscellaneous external data, it also integrates conventional data in a unified way.
Developing an application (e.g. the ones presented on the OTN Hub) or using data from more than one pilot city or a region requires having the data in a unified (harmonized) structure.
The broad adoption of clinical decision support systems within clinical practice has been hampered mainly by the difficulty in expressing domain knowledge and patient data in a unified formalism.
Two fields of interest, in vitro or in vivo, have evolved in parallel, but the interconnection of the data in a unified scheme is tricky, so the determination of the initial events and the main actors involved in this cascade is difficult.
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This cohort can integrate patient supplied, primary and secondary care data into a unified data model.
We developed, as a part of the data loader, a unified data transformation module to perform such translations.
These data suggest a unified model for how Vpx and Vpr exploit DCAF1 to promote viral replication.
The integration of product and process models in a unified data model could provide the means by which information could be shared between High Energy Physics (HEP) groups throughout the system lifecycle from design through to production.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com