Semantic Analytics and Ontologies - Data Governance: Creating Value from Information Assets - page 108

the fourth section, we will introduce a method for calculating the quality
indicator value and the semantic analytics of quality indicators from con-
ditional statements where the representation is close to a natural language.
Semantic Analytics on a Semantic Web
The essence of semantic analytics on a semantic web is to detect semantic
associations in information over the Internet, analyze them from every point
of view, and organize them. Here, semantic associations are “meaningful
and relevant complex relationships between entities, events and concepts”
[Aleman-Meza et al., 2005]. Semantic associations help figure out or char-
acterize a lot of entities on the Web as those carrying inherent meanings.
For semantic associations over information in certain languages, one
can give more formal definitions to semantic associations based on the
languages. For example, in [Anyanwu and Sheth, 2003], semantic associa-
tions in an RDF graph are given a formal definition that two entities e1
and en are semantically associated if there exists a sequence e1, p1, e2, p2,
e3, …, en-1, pn-1, en in an RDF graph where ei, 1 ≤ i ≤ n, are entities and
pj, 1 ≤ j < n, are properties (see also [Aleman-Meza et al., 2005]).
Semantic associations enable the analyzing of data on the Web at the
semantic level and the utilization of the data for more sophisticated purposes
including data checking, ranking, retrieving, discovering hidden patterns
of data, and detecting inconsistency in data. For example, [Aleman-Meza
et al., 2005] apply semantic association to the insider threat application,
which involves validation of legitimate access of documents. On the other
hand, [Aleman-Meta et al., 2006] and [Aleman-Meta et al., 2008] address
conflict of interest detection by using semantic association. Furthermore,
[Anyanwu, Maduko, and Sheth, 2005] rank search results on a semantic
web that have complex relationships based on semantic association.
A FRAMEWORK FOR DEFINITION AND
CALCULATION OF QUALITY INDICATIONS
In this section, we will introduce a representation system of quality indi-
cators that is based on MSO as an example of ontology and semantic
analytics for data governance in the medical service domain.