2022 M. Lee Allison Award for Geoinformatics

Presented to Yolanda Gil

Yolanda Gil

Yolanda Gil
Information Sciences Institute, University of Southern California

 
 

Citation by Doug Walker

With great pleasure and awe, I write this citation for Yolanda Gil for the GSA 2022 M. Lee Allison Award for Geoinformatics. Yolanda proceeded from her Ph.D. in computer science from Carnegie-Melon to impacting the role of computer science in many fields. Her influence on the geosciences is hard to overstate. She is richly deserving of the award through her demonstration of the highest and broadest achievement in Geoinformatics aimed at the Geosciences and, in fact, all of the sciences. Her research, publications, and record of service and honors highlight the fields of artificial intelligence, intelligent systems, and understanding the nature of scientific knowledge.

Gil was a leader in EarthCube, a genuinely interdisciplinary program at the National Science Foundation that just ended this year. Her funding and published research connected with this touched on scientific workflows, preservation of provenance of data artifacts, and both artificial intelligence and knowledge capture methods. At the same time, Gil was active in the fields of biology, semantics, and geospatial analysis. Professor Gil leads the Intelligent Systems for Geoscience Resource Coordination Network NSF with Suzanne Pierce of UT Austin. While you may not have directly interacted with this group, your work has been impacted. It will be progressively influenced as data analysis changes with the advanced computer approaches developed and championed by Professor Gil.

Gil’s honors are many. She is a Fellow of the American Association for the Advancement of Science, a Fellow of the Institute of Electrical and Electronics Engineers, the first recipient of the EarthCube Legacy Award, and a Fellow of the Association for Computing Machinery. She is also a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) and served as its 24th President.

 

Response by Yolanda Gil

I am very thankful to The Geological Society of America for this award, and proud to receive this recognition on behalf of many computer science researchers like myself who diligently work to advance geosciences.

The EarthCube program of the National Science Foundation was designed to expose computing challenges in geosciences and engage interdisciplinary researchers in this area. It was at one of the first EarthCube meetings that I met Lee Allison and witnessed his inspiring leadership and service to the community. I am humbled to receive an award that bears his name.

As an artificial intelligence (AI) researcher, I have been intrigued by representing knowledge and reasoning with it to automate scientific data analysis. Together with Erin Robinson, Chris Mattman, and over two dozen early career researchers, we developed a vision for the Geoscience Papers of the Future. This vision captured principles of reproducible research, open science, digital scholarship. Cédric David, Ibrahim Demir, Bakinam Essawy, Robinson Fulweiler, Jonathan Goodall, Leif Karlstrom, Huikyo Lee, Heath Mills, Ji-Hyun Oh, Suzanne Pierce, Allen Pope, Mimi Tzeng, Sandra Villamizar, Xuan Yu, and many others were committed to improving the computational methods across all geosciences. We synthesized best practices and recommendations to describe and publish data analysis methods in papers, and taught tutorials at universities, research institutions, government agencies, and conferences (including the annual GSA conference). We had significant interest from scientists, and found enthusiastic allies in data curators, infrastructure developers, publishers and funders alike. For geoscientists, this meant an empowering change from ambiguous and incomplete research reports to having more reproducible archival publications. For me it meant that AI research could move the focus from today’s hard to process papers to automatically read well-structured papers so AI could autonomously do research in some not far away future.

I have been very lucky to learn about geosciences from really deep thinkers who were so generous to share with me their passion for understanding our planet. Matty Mookerjee, Marjorie Chan, and Basil Tikoff organized a field trip to Yosemite where we discovered the many opportunities for AI in structural geology, sedimentology, and geomorphology. Kenneth Rubin and Danie Kinkade shared the nuances of capturing metadata for ocean observations. Doug Walker and Kerstin Lehnert made great strides in metadata annotations for physical samples and other field data collection which we adopted. Asti Bhatt and Aaron Ridley helped me appreciate the data sharing and modeling challenges in geospace. Scott Peckham and Chris Duffy collaborated with us to automate the configuration of their hydrology models and their use with climate and agriculture models in data-poor regions of Africa. Suzanne Pierce and Mary Hill shared their vision for participatory modeling for water resources and natural disasters. Julien Emile-Geay and Deborah Khider worked relentlessly with us to develop community ontologies for integrating data in paleoclimate.

Together we have articulated a long-term vision for AI in geosciences, with challenges that are both enticing and rewarding. I am very excited about this research agenda and growing our interdisciplinary community in the years to come.