Conference Agenda (All times are shown in Greenwich Mean Time (GMT) unless otherwise noted)
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Conceptualizing Data Behavior: Bridging Data-Centric and User-Centric Approaches
Time:
Monday, 30/Oct/2023:
11:00am - 12:30pm
Location:Bouzy, 1st Floor, Novotel
Presentations
ID: 267 / [Single Presentation of ID 267]: 1 Panels 90 minutes Confirmation 1: I/we acknowledge that all session authors/presenters have read and agreed to the ASIS&T Annual Meeting Policies Topics: Data Science; Analytics; and Visualization (data science; data analytics; data mining; decision analytics; social analytics; information visualization; images; sound) Keywords: Data behavior, data practice, data needs, research data, open data, data curation and stewardship
Conceptualizing Data Behavior: Bridging Data-Centric and User-Centric Approaches
1Peking University, People's Republic of China; 2University of Vienna, Austria; 3Indiana University Indianapolis, USA; 4University of Washington, USA
With the development of technologies in big data and AI, data has become more and more central to users for various tasks in different contexts. Yet the concept of data behavior, an emerging concept that captures the actions and interactions of individuals with data in various contexts and situations is not explicitly defined and framed. Data behavior focuses on the observable actions and reactions of users when they encounter, discover, seek, use, or create data for individual or collaborative tasks, while data practice encompasses the entire spectrum of how people work with data, from creating and managing to sharing and reusing data, as well as the intentional and strategic decisions and actions involved in these processes. This panel proposes a conversation and discussion about the concepts of data practice and data behavior by drawing on literature in data practice, data curation, and information behavior. This panel aims to discuss, compare, and bridge data-centric and user-centric approaches to conceptualizing data behavior. It will also present some examples of data behavior research in different domains and scenarios. The panel will highlight the challenges and opportunities of data behavior research for information science and practice.
