Citation by Anirudh Prabhu
We are thrilled to honor Prof. Xiaogang (Marshall) Ma as the recipient of the 2024 M. Lee Allison Award for Geoinformatics. Prof. Ma is an exemplary geoinformatics scientist who has been at the forefront of data-driven research in the geosciences, semantic technologies and cyberinfrastructure development.
As the PI of the NSF funded projects like OpenMindat (through Earthcube) and Tickbase, among many others, Prof. Ma has led multiple geo and bioscience communities in making their data FAIR. He holds leadership roles in key scientific communities like AGU, GSA, ESIP, and EGU, and serves as an editor for leading journals, including Data Science Journal and Computers & Geosciences. Marshall's vision for geoinformatics and his methods have gained international recognition, evidenced by awards like the IAMG Vistelius Research Award, SciTS Meritorious Contribution Award, ISCU-WDS Data Stewardship Award, and nearly $10 million in grant funding.
Prof. Ma has made a global impact on geoinformatics by democratizing access to geoscience data, building user-friendly cyberinfrastructure, and developing data science solutions for Earth science. His work reduces barriers to research by simplifying data analysis without requiring coding skills.
Response by Xiaogang (Marshall) Ma
It is such a big honor to receive the 2024 M. Lee Allison Award for Geoinformatics from the GSA Geoinformatics and Data Science Division. My first impression of GSA and its geoinformatics activities was back to 2008 when I was a PhD student reading several GSA Special Papers at the library of ITC, Enschede, Netherlands. My first GSA meeting attendance was in 2016, Boulder, CO, and soon I became intensively involved with the activities of the Geoinformatics and Data Science Division, which has lasted till nowadays. I still have the fresh memory of a few conversations with my late postdoctoral mentor, Prof. Peter Fox, on the “-” between “geo” and “informatics” when geoinformatics is written as “geo-informatics”. To my understanding, as geoinformaticians our role is exactly that hyphen in the between. Does that mean that a geoinformatician should be knowledgeable in both geoscience and computer science? Conventionally, those two disciplines have quite different foci. To bind them together, unique research is needed, and we probably can define geoinformatics as a field that develops methods and technologies towards the efficient application of computer science in geoscience for knowledge discovery.
I was lucky to have the opportunity to work with so many enthusiasts of geoinformatics in programs such as OneGeology, the Deep Carbon Observatory, the Global Change Information System, the Deep-time Digital Earth, and most recently, Mindat. My current geoinformatics and data science work focuses on three themes. (1) Data interoperability in the cyberinfrastructure. This involves knowledge representation and ontology/vocabulary building that aims to enhance the utility of online data services. For example, we have applied both geoscience standards such as Dana classification of minerals and computer community standards such as the Open Graph Protocol to the Mindat open data service. (2) Provenance, reproducible workflow and open science. Among many disciplines, including geoscience, there is a crucial need for transparent scientific workflows and credible scientific findings. In my group we have been working on the application of the Common Workflow Language and the W3C Provenance ontology to support explainable AI in workflow platforms. (3) Exploratory data analytics and visualization in a data science life cycle. Data exploration is a useful way to tackle the big data deluge by quickly analyzing the patterns of data retrieved from the open world. For example, in our group we are currently using Large Language Models to develop a friendly user interface that can quickly process requests of data retrieval and analysis written in natural language.
In the recent few years, I have witnessed the thriving of open data and data science related topics within the geoscience community. It is evident that many new innovations and creative applications are yet to happen. I probably can even make a proposition that soon in the future every geoscientist should know some data science methods. Thanks to the nominator and the GSA Geoinformatics and Data Science Division for the M. Lee Allison Award, and I would like to share this honor with all my collaborators and students.