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Integrating Diverse Data for Environmental Resilience Research

Explore lessons learned in data integration for environmental research, emphasizing the importance of access, framing questions, innovative methodologies, and collaborative efforts. Learn how integration of varied data sources can enhance understanding of complex ecological systems and societal challenges.

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Integrating Diverse Data for Environmental Resilience Research

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  1. The Integration Core: Lessons Learned LilianNa’iaAlessa, Ph.D., P.Reg.Biol.

  2. New Integrat(ed) Team Members Claire Kione Abigail Liisa

  3. Modes of Inquiry

  4. Types of Integration Tress et al. 2005

  5. A Few of the Core Products • Social Ecological (SES) Hotspots Mapping: social, economic, and biological data. • Agent-Based Modeling to Forecast the Environmental Resilience of Arctic Landscapes (FERAL): social, biological, physical data. • Arctic Water Resources Vulnerability Index (AWRVI): social, biological, physical, engineering data.

  6. Integration • Initially, solicited data. • Eventually, retrieved data from publicly available sources. Lesson Learned: Importance of access to data.

  7. Integration • Based inquiry on questions that were independent of classical scientific tradition (i.e., not necessarily hypothesis driven). • Questions embedded in complicated and emergent phenomena requiring attention by society (e.g., water management). Lesson learned: Importance of framing the question(s).

  8. Integration • Utilized and developed cutting edge methodologies to engage data across scales and contexts. • Borrowed from various disciplinary traditions to develop approaches. Lessons learned: Need for innovative and appropriate methods.

  9. Integration • Often marginalized by disciplines. • Difficult and frustrating but immensely rewarding. • Only successful through collaboration. Lesson learned: Training is important but attitude is everything.

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