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R3 Data Workshop Summary Now Available

R3 Data Workshop Summary Now Available

On May 7-8, 2019, researchers from the Departments of Mechanical Engineering and Civil and Environmental Engineering at the University of Maryland, College Park came together to participate in a two-day immersive workshop focused on identifying strategic integrated research priorities and challenges related to harnessing data science for risk, reliability, and resilience (R3) assessment.

Workshop participants worked together to:

  • Expand and strengthen the UMD network of researchers working the the area of R3 data analytics:
Participants gained a deeper understanding of the professional skillsets and research motivations of UMD colleagues with a diverse range of expertise and at varying career development stages. This exposure generated specific ideas for near-term action and planted the seeds for future exploration of mutual curiosities and collaborative proposal opportunities.
  • Develop an understanding of different lexicons used in data science in R3:
Through a baselining language exercise, participants shared their working definitions of important terms applied in R3 activities. The exercise highlighted important semantic differences between disciplines and applications, illuminated the importance of clarity in speech, and generated awareness of the need to ask clarifying questions about shared language. With the appreciation that it can be more challenging to recognize nuanced use of similar terminology in closely associated fields than in diverse ones, participants moved forward with an appreciation for the need to strip away assumptions and ensure mutual understanding of definitions.
  • Identify a path forward for tangible workshop output:
Consensus was conversationally established at the close of the event that meaningful material was generated and synthesized during the workshop and that novel ideas for cross-pollination of ideas related to R3 data emerged. As a result, participants proposed that development a perspectives/commentary paper is appropriate to document synthesized co-created knowledge and outline key steps for enabling integration of data science in R3 applications.
  • Plant seeds for future joint research:
Through the ideas generated during the two-day shared, structured brainstorming activities, two concepts rose prominently to the top of the list for future research opportunities. In particualr, there was a share interest in seeking center-level opportunities for developing a core around the intelligent collection and intentional utilization of multi-dimensional, multi-scale data resources that exist within various parts of the university to support improved decision-making in R3 applications. Significant interest was also expressed regarding the need to establish and utilize a common research topic to serve as a boundary object and linkage point for working across multiple scales and areas of expertise. Transportation rose to the top as an immediate favorite thread to weave together the various strengths and research interests of workshop participants.

Workshop organizers have begun the coordination of follow-on activities and will archive the material generated during the workshop in UMD's DRUM repository.

 

June 13, 2019


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