Risk Identification & Quantification in Complex Human-Natural Systems via Convergent Data Intensive Research

Schafer TLJ, Mcgranaghan RM, Sherman MG, Feng MLE, Owolabi OO, Ryan SE, Düker MC, Jauch M, Matteson DS (2021)

Publication Type: Conference contribution

Publication year: 2021

Publisher: Association for Computing Machinery

Pages Range: 4155-4156

Conference Proceedings Title: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Event location: Virtual, Online, SGP

ISBN: 9781450383325

DOI: 10.1145/3447548.3469480

Abstract

Human-natural systems involve complex interdependent processes, but domain specific processes are traditionally studied in non-overlapping research silos. The Predictive Risk Investigation SysteM (PRISM) for multi-layer dynamic interconnection analysis is a group of collaborators across multiple domains who work to discover data driven connections specifically among domain risks. We bring our inter-disciplinary approach to risk assessment to our KDD'21 workshop. Our workshop is a step toward a holistic approach to systemic risk analysis by welcoming speakers in applied and technical research at the forefront of risk and complex systems.

Authors with CRIS profile

Marie-Christine Düker

Involved external institutions

Cornell University US United States (USA) (US) Atmospheric & Space Technology Research Associates (ASTRA), LLC. US United States (USA) (US) University of Massachusetts Amherst (UMass) US United States (USA) (US) Lincoln Park Zoo US United States (USA) (US) Tufts University US United States (USA) (US)

How to cite

APA:

Schafer, T.L.J., Mcgranaghan, R.M., Sherman, M.G., Feng, M.-L.E., Owolabi, O.O., Ryan, S.E.,... Matteson, D.S. (2021). Risk Identification & Quantification in Complex Human-Natural Systems via Convergent Data Intensive Research. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 4155-4156). Virtual, Online, SGP: Association for Computing Machinery.

MLA:

Schafer, Toryn L. J., et al. "Risk Identification & Quantification in Complex Human-Natural Systems via Convergent Data Intensive Research." Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2021, Virtual, Online, SGP Association for Computing Machinery, 2021. 4155-4156.

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