Data Analytics using Ontologies of Management Theories: Towards Implementing "From Theory to Practice"

被引：0

作者：

Kim, Henry M. ^{[1
]}

Cheung, Jackie Ho Nam ^{[2
]}

Laskowski, Marek ^{[1
]}

Gel, Iryna ^{[3
]}

机构：

[1] York Univ, Toronto, ON, Canada

[2] Kingsdale Shareholder Serv, Toronto, ON, Canada

[3] Canadian Tire, Toronto, ON, Canada

来源：

PROCEEDINGS OF 2016 IEEE 17TH INTERNATIONAL CONFERENCE ON INFORMATION REUSE AND INTEGRATION (IEEE IRI) | 2016年

关键词：

Ontologies; Data Analytics; Accounting; Enterprise Modeling; First-Order Logic; PRINCIPLES;

D O I：

10.1109/IRI.2016.62

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

We explore how computational ontologies can be impactful vis-a-vis the developing discipline of "data science." We posit an approach wherein management theories are represented as formal axioms, and then applied to draw inferences about data that reside in corporate databases. That is, management theories would be implemented as rules within a data analytics engine. We demonstrate a case study development of such an ontology by formally representing an accounting theory in First-Order Logic. Though quite preliminary, the idea that an information technology, namely ontologies, can potentially actualize the academic cliche, "From Theory to Practice," and be applicable to the burgeoning domain of data analytics is novel and exciting.

引用

页码：417 / 422

页数：6

共 34 条

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