8.9. REPAIR Scholarly Talk by Aleksi Aaltonen

You are warmly invited to the next session of the REPAIR Scholarly Talk series, featuring Associate Professor Aleksi Aaltonen from the Stevens Institute of Technology. He will deliver a talk titled Data Studies in Management: What Is It? What Should Or Could It Be?. Join us on September 8 at 13:00 at the University of Helsinki’s Main Building (U4062, Unioninkatu 34)

Link for online participants: https://video.helsinki.fi/unitube/live-stream.html?room=l56 Please note that remote participants cannot comment or participate in the discussion.

Data Studies in Management: What Is It? What Should Or Could It Be?

Data have always been a central element in large-scale business and organizing and their importance as a medium of knowing and acting in organizations has grown vastly over the last two decades. Yet, what are (or is) data? Scholars from different backgrounds have come to increasingly question any simple or straightforward conceptions of data, which is paralleled by numerous challenges that companies are facing in managing, using, and sharing their data assets.

In this talk, Aaltonen explores the emerging field of data studies in management that is driven by these and related questions and challenges about data. Aaltonen will use numerous examples from my own research and from the recently published edited volume Research Handbook on Digital Data (Edward Elgar) to make the case for data as an object of research.

About Aleksi Aaltonen

Aleksi Aaltonen is an Associate Professor of Information Systems at the School of Business, Stevens Institute of Technology, where he studies data, organizing, and AI. His publications have appeared in leading academic journals such as Management Science, Information Systems Research, and MIS Quarterly. Aleksi serves as a member of the Research Advisory Council at Numeris, a Deputy Editor-in-Chief at the Journal of Information Technology, and he also maintains the Data Studies Bibliography that is a resource for management scholars studying data.