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2017 | OriginalPaper | Buchkapitel

Goal-Oriented Regulatory Intelligence: How Can Watson Analytics Help?

verfasst von : Okhaide Akhigbe, Susie Heap, Sakib Islam, Daniel Amyot, John Mylopoulos

Erschienen in: Conceptual Modeling

Verlag: Springer International Publishing

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Abstract

Regulations are introduced by governments to ensure the well-being, safety, and other societal needs of citizens and enterprises. Governments also create programs aiming to improve awareness about and compliance with regulations. Goal models have been used in the past to conceptualize regulations and to measure compliance assessments. However, regulators often have difficulties assessing the performance of their regulations and programs. In this paper, we model both regulations and regulatory programs with the Goal-oriented Requirement Language. Using the same conceptualization framework enables asking questions about performance and about the evidence-based impact of programs on regulations. We also investigate how Watson Analytics, a cloud-based data exploration service from IBM, can be used pragmatically to explore and visualize goal satisfaction data to understand compliance issues and program effectiveness. A simplified example inspired from a Canadian mining regulation is used to illustrate the many opportunities of Watson Analytics in that context, and some of its current limitations.

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Vorheriges Kapitel Mining Goal Refinement Patterns: Distilling Know-How from Data

Nächstes Kapitel An Alternative Approach to Metainformation Conceptualisation and Use

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Titel: Goal-Oriented Regulatory Intelligence: How Can Watson Analytics Help?
verfasst von: Okhaide Akhigbe
Susie Heap
Sakib Islam
Daniel Amyot
John Mylopoulos
Verlag: Springer International Publishing
Buch: Conceptual Modeling
Print ISBN: 978-3-319-69903-5

Electronic ISBN: 978-3-319-69904-2

Copyright-Jahr: 2017
DOI: https://doi.org/10.1007/978-3-319-69904-2_7

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