Data science is a relatively new and growing discipline. And at this point, the boundaries of what data science encompasses are still being defined.
To help further this process of defining data science, dozens of leading data scientists recently gathered in Park City, Utah for the 2018 Data Science Leadership Summit.
The goal for the summit was to create an academic community for data science that takes collective responsibility for advancing research, education, practice, outreach, and public engagement. School of Computational Science and Engineering Professor and Co-Executive Director of the Institute for Data Engineering and Science Srinivas Aluru served as chair of this historic summit.
“Most universities don’t have data science departments. Essentially, we want to identify who is leading data science activities on these campuses. In some cases, it’s an institute, in some cases it’s a person leading an educational program, and in some cases, it could be a department chair,” said Aluru.
“We are looking for people who are influencing data science research and education and bringing them together for a collaborative conversation.”
The two-day summit, held Oct. 12-13, included session topics ranging from data science organizational structures, undergraduate data science education to data ethics and privacy as well as academic data science career paths. Two keynote presentations by leading data scientists Vipin Kumar, of the University of Minnesota, who recently presented a CSE distinguished lecture, and Blaise Aguera y Arcas of Google AI were also highlights of the event.
The summit marks the second recent gathering of academic leaders who influence data science research and education on their campuses.
International data science event
A similar meeting targeted to data science institute and center leaders worldwide took place in August. The day-long invitation-only applied data science panel was orchestrated by the Alan Turing Institute and The Data Science Institute of the Imperial College London. Aluru represented Georgia Tech at the event, which was held in conjunction with the twenty-fourth international conference on Knowledge Discovery and Data Mining (KDD 2018).
During the event, attendees explored challenges to understanding and defining standards and definitions for analytics roles, skill sets, and career paths in the data science industry.
“Some of the goals of the day were to learn best practices from other institutes and programs, figure out how to move forward together as a community, and understand the funding models across different countries and universities. We also made progress on issues such as how should we educate? What research we should focus on? And, how best can education programs, industry partnerships, and research work together for the overall benefit of the field,” said Aluru.
As part of the conversation and educational aspect of the panel, each attendee presented a poster detailing how their data science institute was run, how they were funded, and what the different roles and responsibilities were for their respective institutions.
“As the new field of data science expands, the need to identify and define both its use and direction becomes paramount to this seemingly large and omnipresent field,” said Moderator Usama Fayyad in the panel description.