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Data Governance by Neera Bhansali

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93
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Semantic Analytics and Ontologies
O. Takaki, N. Izumi, K. Murata, and K. Hasida
CONTENTS
Introduction ......................................................................................................94
Ontology ............................................................................................................95
Denition of Ontologies ............................................................................ 96
Purposes for Constructing Ontologies .................................................... 96
Construction of Ontologies ........................................................................98
Concepts (Classes) ..................................................................................98
Properties (Slots) .................................................................................... 99
Axioms .................................................................................................. 100
Representation of Linguistic Vocabulary on a Semantic Web ............ 100
RDF (Resource Description Framework) .......................................... 101
RDFS (Resource Description Framework Schema) .........................101
OWL (Web Ontology Language) ........................................................103
Semantic Analytics .........................................................................................104
Semantic Analysis Based on Natural Language Text ............................106
Semantic Analysis Based on ConditionalExpression of
Graph-Based Representation ...................................................................107
Semantic Analytics on a Semantic Web ..................................................108
A Framework for Denition and Calculation of Quality Indications .....108
Quality Indicators ......................................................................................109
Overview of QI-Framework ..................................................................... 110
Outline of QI-RS ........................................................................................111
Medical Service Ontology ........................................................................112
Outline of MSO Concepts ...................................................................112
Patients ...................................................................................................112
Events .....................................................................................................114
States of Patients ....................................................................................115
Main Relations in MSO ........................................................................115
94  •  O. Takaki, N. Izumi, K. Murata, and K. Hasida
INTRODUCTION
is chapter explains semantic analytics in data governance (DG) by
introducing a framework to dene quality indicators and to calculate
their values based on medical databases, where quality indicators are
measures of medical service quality, which are represented by numerical
values . Most importantly, we introduce an ontology called Medical
Service Ontology (MSO) as an example of an ontology that plays the
central role in semantic analytics.
Semantic analytics plays an important role in DG. e term semantic
analytics in this chapter refers to a technique used for semantically
analyzing, retrieving, integrating, or managing data resources in several
databases and on the Internet using ontologies. In fact, it is one of DG’s
primary roles to manage and utilize the data accumulated by an organiza-
tion and to use that data for the organizational decision making. However,
for this purpose, it is essential to be able to deal with data in an integrated
manner beyond dierences in data formats or expressions. Semantic
analytics judges the semantic identity or similarity between data beyond
syntactic dierences, making it possible to collectively deal with the same
or similar data from data resources in various formats. Moreover, ontolo-
gies are important as the fundamental tools of current semantic analysis.
We here explain a role of ontology in semantic analytics by natural lan-
guage processing (NLP). NLP is an area of research and application that
explores how computers can be used to understand and manipulate natu-
ral language text or speech to do useful things [Chowdhury, 2003]. NLP
can be regarded as a basic theory of semantic analytics. Knowledge used
in the four stages of analysis in NLP—morphological analysis, syntactic
analysis, semantic analysis, and context analysis—can roughly be divided
Objective Graphs and Quantifying Concepts ........................................ 117
Objective Graphs ..................................................................................117
Quantifying Concepts ..........................................................................117
Example of a Quality Indicator in QI-RS ..........................................117
Related Work .................................................................................................. 120
Conclusions .....................................................................................................121
Acknowledgement .......................................................................................... 121
References ........................................................................................................ 121

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