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Archimedes/Athena RC, the newly established Unit on AI, Data Science and Algorithms, is proud to host a talk by the world famous scientist Dr. Michael L. Brodie on “A data science reference framework”. The hybrid event will take place on March 18, 2022, at 10:00 – 12:00 (EET).   

 

Human reasoning based on philosophy, mathematics, and science produced three discovery paradigms: empiricism, scientific method & theory, and computation / simulation, each facilitating the greatest achievements of their age and much of human knowledge. Data science is emerging as the fourth discovery paradigm based on inscrutable reasoning yet successfully addressing problems beyond human conception in scope, scale, and complexity. As its unfathomed discovery power emerges, so to do its risks. We must understand data science to benefit from its power while managing its risks. As data science is evolving from 25+ disciplines and thousands of applications there is no coherent, unified definition and vocabulary required for research, development, practice, and teaching in this inherently multidisciplinary field.

The Data Science Research Framework provides means for defining data science as a discovery paradigm and data science disciplines by applying the paradigm to specific phenomena, e.g., drug discovery, image recognition, economic policy. Originally proposed as a common basis for collaboration across, and structure for, 400 data scientists in 20 disciplines in Europe’s earliest and largest Data Science Research Institute (DSRI), it is being developed for the entire data science community and especially the DSRIs now found in most universities. It is intended as an online journal developed by and for the entire data science community.

 

This interactive talk on data science as a discipline presents motivations, purpose, and content for means to address issues that arise in DSRI’s such as Archimedes.
 

Register here to attend the event via Zoom.
 

 

Dr. Michael L. Brodie has 50 years experience in research and industrial practice in data science, databases, distributed systems, integration, AI, and multidisciplinary problem solving. He is a Visiting Scholar in the DASlab, School of Engineering and Applied Sciences, Harvard University. During 2013-2019 he was a Research Scientist in the Data Systems Group at MIT, and chaired the Scientific Advisory Committee of Insight, Ireland, one of Europe’s first and largest Data Science Research Institutes. He has a Ph.D. in databases, AI, and programming languages from the University of Toronto and a Doctor of Science (honoris causa) from the National University of Ireland.