Information Science Professional's Engagement in Developing Data Documentation Frameworks for Machine Learning

As machine learning continues to expand across domains, the robust data documentation frameworks and practices have become increasingly important to facilitate transparency. While the development of metadata frameworks is a longstanding focus in the field of information science, little is known about how information science professionals contribute to data documentation framework in machine learning contexts. This study explores the current engagement of information science professionals in developing data documentation frameworks for ML models. We conducted a literature search in a systematic way with the assistance of a generative AI tool and analyzed the authors’ professional backgrounds. Preliminary findings indicate that information science professionals play limited leadership roles in developing data documentation, more often contributing to supporting roles.