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Problem Formulation in Knowledge Discovery via Data Analytics (KDDA) for Environmental Risk Management.

Yan Li1, Manoj Thomas2, Kweku-Muata Osei-Bryson3

  • 1Center for Information Systems and Technology (CISAT), Claremont Graduate University, 130 E. Ninth St. ACB225, Claremont, CA 91711, USA. yan.li@cgu.edu.

International Journal of Environmental Research and Public Health
|December 17, 2016
PubMed
Summary
This summary is machine-generated.

A new framework formalizes Knowledge Discovery via Data Analytics (KDDA) for environmental risk management (ERM). It uses a DM³ ontology to define objectives and infer analytical goals for better problem formulation in ERM.

Keywords:
Knowledge Discovery via Data Analytics (KDDA)decision supportenvironmental riskontologyproblem formulation

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Area of Science:

  • Environmental science
  • Data science
  • Risk management

Background:

  • Environmental risk management (ERM) increasingly uses data analytics.
  • A formalized process for Knowledge Discovery via Data Analytics (KDDA) is needed.
  • Limited research exists on decision support for ERM objectives and analytical goals.

Purpose of the Study:

  • To address problem formulation in the ERM understanding phase of KDDA.
  • To develop a DM³ ontology for capturing ERM objectives and inferring analytical goals.
  • To create a framework for decision-making in ERM problem formulation.

Main Methods:

  • Developed a DM³ ontology to capture ERM objectives and infer analytical goals.
  • Created a framework to assist decision-making in problem formulation.
  • Applied ontology inferencing to conceptualize Hazardous Air Pollutants (HAPs) exposure shifts.

Main Results:

  • The ontology-based system provides structured guidance for knowledge retrieval.
  • Ontology inferencing can discover analytical goals and techniques.
  • A case study on HAPs exposure demonstrates the approach's utility.

Conclusions:

  • The proposed KDDA process and framework enhance ERM problem formulation.
  • Integrating diverse data sources and appropriate KDDA techniques is crucial.
  • The study highlights challenges and opportunities for KDDA in environmental risk management.