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From B ig D ata to Knowledge: An Ontological Approach to B ig D ata Analytics
Author(s) -
Kuiler Erik W.
Publication year - 2014
Publication title -
review of policy research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.832
H-Index - 45
eISSN - 1541-1338
pISSN - 1541-132X
DOI - 10.1111/ropr.12077
Subject(s) - analytics , ontology , computer science , domain (mathematical analysis) , semantics (computer science) , data science , data analysis , knowledge management , data mining , programming language , mathematics , mathematical analysis , philosophy , epistemology
The introduction of B ig D ata sets in the healthcare domain has presented opportunities to engage in analytics of very large sets containing both structured and unstructured data. With advances in information technology ( IT ), these data sets have become available from diverse sources at greatly increased rates. The availability of B ig D ata sets has introduced complexities that we must address, not only in terms of semantics and analytics but also in terms of data management, storage, and distribution. Currently, the capabilities to ingest, analyze, and manage multipetabyte data sets have underscored the limitations of our analytics capabilities supported by relational database management systems. This essay argues that an ontology‐based approach to data analytics provides a practical framework to address the semantic challenges presented by B ig D ata sets. No ontological framework can address the operational and management requirements introduced by the availability of B ig D ata sets, however. There are also a number of IT architectural factors that must be considered in implementing such a framework.