A Collaborative Research Exploration of Pollutant Mixtures and Adverse Birth Outcomes by Using Innovative Spatial Data Mining Methods: The DoMiNO Project
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 re...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-03-01
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| Series: | Challenges |
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| Online Access: | https://www.mdpi.com/2078-1547/10/1/25 |
| _version_ | 1824006170527924224 |
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| author | Osnat Wine Osmar R. Zaiane Alvaro R. Osornio Vargas |
| author_facet | Osnat Wine Osmar R. Zaiane Alvaro R. Osornio Vargas |
| author_sort | Osnat Wine |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-18T20:23:09Z |
| format | Article |
| id | doaj.art-a324b505a4b04ca381d94fd673406f34 |
| institution | Directory Open Access Journal |
| issn | 2078-1547 |
| language | English |
| last_indexed | 2024-12-18T20:23:09Z |
| publishDate | 2019-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Challenges |
| spelling | doaj.art-a324b505a4b04ca381d94fd673406f342022-12-21T20:54:17ZengMDPI AGChallenges2078-15472019-03-011012510.3390/challe10010025challe10010025A Collaborative Research Exploration of Pollutant Mixtures and Adverse Birth Outcomes by Using Innovative Spatial Data Mining Methods: The DoMiNO ProjectOsnat Wine0Osmar R. Zaiane1Alvaro R. Osornio Vargas2Department of Pediatrics, University of Alberta, Edmonton, AB T6G 1C9, CanadaDepartment of Computing Science, University of Alberta, Edmonton, AB T6G 2E8, CanadaDepartment of Pediatrics, University of Alberta, Edmonton, AB T6G 1C9, CanadaEnvironmental 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.https://www.mdpi.com/2078-1547/10/1/25spatial data miningadverse birth outcomesinterdisciplinary researchintegrated knowledge translationcollaborationenvironmental health researchexposome |
| spellingShingle | Osnat Wine Osmar R. Zaiane Alvaro R. Osornio Vargas A Collaborative Research Exploration of Pollutant Mixtures and Adverse Birth Outcomes by Using Innovative Spatial Data Mining Methods: The DoMiNO Project Challenges spatial data mining adverse birth outcomes interdisciplinary research integrated knowledge translation collaboration environmental health research exposome |
| title | A Collaborative Research Exploration of Pollutant Mixtures and Adverse Birth Outcomes by Using Innovative Spatial Data Mining Methods: The DoMiNO Project |
| title_full | A Collaborative Research Exploration of Pollutant Mixtures and Adverse Birth Outcomes by Using Innovative Spatial Data Mining Methods: The DoMiNO Project |
| title_fullStr | A Collaborative Research Exploration of Pollutant Mixtures and Adverse Birth Outcomes by Using Innovative Spatial Data Mining Methods: The DoMiNO Project |
| title_full_unstemmed | A Collaborative Research Exploration of Pollutant Mixtures and Adverse Birth Outcomes by Using Innovative Spatial Data Mining Methods: The DoMiNO Project |
| title_short | A Collaborative Research Exploration of Pollutant Mixtures and Adverse Birth Outcomes by Using Innovative Spatial Data Mining Methods: The DoMiNO Project |
| title_sort | collaborative research exploration of pollutant mixtures and adverse birth outcomes by using innovative spatial data mining methods the domino project |
| topic | spatial data mining adverse birth outcomes interdisciplinary research integrated knowledge translation collaboration environmental health research exposome |
| url | https://www.mdpi.com/2078-1547/10/1/25 |
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