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Social and Behavioral Sciences Commons™
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Full-Text Articles in Social and Behavioral Sciences
Digital Scholarship And Data Science Intersect In Libraries: A Needs Assessment Report, Halie Kerns
Digital Scholarship And Data Science Intersect In Libraries: A Needs Assessment Report, Halie Kerns
Library Created Resources
The following report summarized the results of a needs assessment completed in the fall of 2023 at Binghamton University by the Libraries’ Digital Scholarship team. The aim was to understand how data science-focused programming, as part of the digital scholarship’s offerings, would be utilized on campus. The report evaluates existing literature, summarizes findings from twenty-eight interviews done across campus, and lays out an action plan for the Digital Scholarship team’s future planning.
Sports Data Science Job Requirements, Cam E. Morse
Sports Data Science Job Requirements, Cam E. Morse
Student Publications
Data science is an extremely fast growing field in which job opportunities are opening in every industry related to data science. Within the data science field is the sports data science industry which has it's own requirements and specificities that may not be present in other industries. In this paper, research is done using multiple job posting websites such as LinkedIn, Indeed, Sportstek jobs, and TeamworkOnline to explore the job descriptions of many different sports data science jobs. These job descriptions are then examined using Python coding to find the frequencies of specific data science skills in the various job …
Regulating Machine Learning: The Challenge Of Heterogeneity, Cary Coglianese
Regulating Machine Learning: The Challenge Of Heterogeneity, Cary Coglianese
All Faculty Scholarship
Machine learning, or artificial intelligence, refers to a vast array of different algorithms that are being put to highly varied uses, including in transportation, medicine, social media, marketing, and many other settings. Not only do machine-learning algorithms vary widely across their types and uses, but they are evolving constantly. Even the same algorithm can perform quite differently over time as it is fed new data. Due to the staggering heterogeneity of these algorithms, multiple regulatory agencies will be needed to regulate the use of machine learning, each within their own discrete area of specialization. Even these specialized expert agencies, though, …