Difference between revisions of "Template:Article of the week"

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(Updated article of the week text.)
(Updated article of the week text.)
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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Tab3 Brandão Information2016 7-4.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Tab3 Brandão Information2016 7-4.png|240px]]</div>
'''"[[Journal:A benchmarking analysis of open-source business intelligence tools in healthcare environments|A benchmarking analysis of open-source business intelligence tools in healthcare environments]]"'''
'''"[[Journal:A robust, format-agnostic scientific data transfer framework|A robust, format-agnostic scientific data transfer framework]]"'''


In recent years, a wide range of business intelligence (BI) technologies have been applied to different areas in order to support the decision-making process. BI enables the extraction of knowledge from the data stored. The healthcare industry is no exception, and so BI applications have been under investigation across multiple units of different institutions. Thus, in this article, we intend to analyze some open-source/free BI tools on the market and their applicability in the clinical sphere, taking into consideration the general characteristics of the [[Clinical laboratory|clinical environment]]. For this purpose, six BI tools were selected, analyzed, and tested in a practical environment. Then, a comparison metric and a ranking were defined for the tested applications in order to choose the one that best applies to the extraction of useful knowledge and clinical data in a healthcare environment. Finally, a pervasive BI platform was developed using a real case in order to prove the tool's viability. ('''[[Journal:A benchmarking analysis of open-source business intelligence tools in healthcare environments|Full article...]]''')<br />
The olog approach of Spivak and Kent is applied to the practical development of data transfer frameworks, yielding simple rules for construction and assessment of data transfer standards. The simplicity, extensibility and modularity of such descriptions allows discipline experts unfamiliar with complex ontological constructs or toolsets to synthesize multiple pre-existing standards, potentially including a variety of file formats, into a single overarching ontology. These ontologies nevertheless capture all scientifically-relevant prior knowledge, and when expressed in machine-readable form are sufficiently expressive to mediate translation between legacy and modern data formats. A format-independent programming interface informed by this ontology consists of six functions, of which only two handle data. Demonstration software implementing this interface is used to translate between two common diffraction image formats using such an ontology in place of an intermediate format. ('''[[Journal:A robust, format-agnostic scientific data transfer framework|Full article...]]''')<br />
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Revision as of 20:33, 16 January 2017

Tab3 Brandão Information2016 7-4.png

"A robust, format-agnostic scientific data transfer framework"

The olog approach of Spivak and Kent is applied to the practical development of data transfer frameworks, yielding simple rules for construction and assessment of data transfer standards. The simplicity, extensibility and modularity of such descriptions allows discipline experts unfamiliar with complex ontological constructs or toolsets to synthesize multiple pre-existing standards, potentially including a variety of file formats, into a single overarching ontology. These ontologies nevertheless capture all scientifically-relevant prior knowledge, and when expressed in machine-readable form are sufficiently expressive to mediate translation between legacy and modern data formats. A format-independent programming interface informed by this ontology consists of six functions, of which only two handle data. Demonstration software implementing this interface is used to translate between two common diffraction image formats using such an ontology in place of an intermediate format. (Full article...)

Recently featured:

A benchmarking analysis of open-source business intelligence tools in healthcare environments
openBIS ELN-LIMS: An open-source database for academic laboratories
Health literacy and health information technology adoption: The potential for a new digital divide