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Open AccessCase Report

A Collaborative Research Exploration of Pollutant Mixtures and Adverse Birth Outcomes by Using Innovative Spatial Data Mining Methods: The DoMiNO Project

1
Department of Pediatrics, University of Alberta, Edmonton, AB T6G 1C9, Canada
2
Department of Computing Science, University of Alberta, Edmonton, AB T6G 2E8, Canada
*
Author to whom correspondence should be addressed.
On behalf of the DoMiNO Project Team, Data Mining and Neonatal Outcomes (DoMiNO), University of Alberta, Edmonton, AB T6G 1C9, Canada.
Challenges 2019, 10(1), 25; https://doi.org/10.3390/challe10010025
Received: 13 December 2018 / Revised: 15 March 2019 / Accepted: 18 March 2019 / Published: 25 March 2019
Environmental health research is gaining interest due to the global concern of environmental factors impacting health. This research is often multifaceted and becomes complex when trying to understand the participation of multiple environmental variables. It requires the combination of innovative research methods, as well as the collaboration of diverse disciplines in the research process. The application of collaborative approaches is often challenging for interdisciplinary teams, and much can be learned from in-depth observation of such processes. We share here a case report describing initial observations and reflections on the collaborative research process of the Data Mining and Neonatal Outcomes (DoMiNO) project (2013–2018), which aimed to explore associations between mixtures of air pollutants and other environmental variables with adverse birth outcomes by using an innovative data mining approach. The project was built on interdisciplinary and user knowledge participation with embedded evaluation framework of its collaborative process. We describe the collaborative process, the benefits and challenges encountered, and provide insights from our experience. We identified that interdisciplinary research requires time and investment in building relationships, continuous learning, and engagement to build bridges between disciplines towards co-production, discovery, and knowledge translation. Learning from interdisciplinary collaborative research experiences can facilitate future research in the challenging field of environmental health. View Full-Text
Keywords: spatial data mining; adverse birth outcomes; interdisciplinary research; integrated knowledge translation; collaboration; environmental health research; exposome spatial data mining; adverse birth outcomes; interdisciplinary research; integrated knowledge translation; collaboration; environmental health research; exposome
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MDPI and ACS Style

Wine, O.; Zaiane, O.R.; Osornio Vargas, A.R. A Collaborative Research Exploration of Pollutant Mixtures and Adverse Birth Outcomes by Using Innovative Spatial Data Mining Methods: The DoMiNO Project. Challenges 2019, 10, 25.

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