Related papers: Collaborative Data Behaviors in Digital Humanities…
Collaborative robots are increasingly deployed alongside humans in factories, hospitals, schools, and other domains to enhance teamwork and efficiency. Systems that seamlessly integrate humans and robots into cohesive teams for coordinated…
Recent advances in visual analytics have enabled us to learn from user interactions and uncover analytic goals. These innovations set the foundation for actively guiding users during data exploration. Providing such guidance will become…
Scientific datasets play a crucial role in contemporary data-driven research, as they allow for the progress of science by facilitating the discovery of new patterns and phenomena. This mounting demand for empirical research raises…
The outcome of the explorative data analysis (EDA) phase is vital for successful data analysis. EDA is more effective when the user interacts with the system used to carry out the exploration. In the recently proposed paradigm of iterative…
Data sharing partnerships are increasingly an imperative for research institutions and, at the same time, a challenge for established models of data governance and ethical research oversight. We analyse four cases of data partnership…
Human-machine interaction has been around for several decades now, with new applications emerging every day. One of the major goals that remain to be achieved is designing an interaction similar to how a human interacts with another human.…
In this study, we conducted semi-structured interviews with 21 IIR researchers to investigate their data reuse practices. This study aims to expand upon current findings by exploring IIR researchers' information-obtaining behaviors…
We characterize 16 challenges faced by those investigating and developing remote and synchronous collaborative experiences around visualization. Our work reflects the perspectives and prior research efforts of an international group of 29…
Artificial Intelligence is being employed by humans to collaboratively solve complicated tasks for search and rescue, manufacturing, etc. Efficient teamwork can be achieved by understanding user preferences and recommending different…
Team chemistry is the holy grail of understanding collaborative human behavior, yet its quantitative understanding remains inconclusive. To reveal the presence and mechanisms of team chemistry in scientific collaboration, we reconstruct the…
Collaborations are pervasive in current science. Collaborations have been studied and encouraged in many disciplines. However, little is known how a team really functions from the detailed division of labor within. In this research, we…
Human-AI collaborative tools attract attentions from the data storytelling community to lower the expertise barrier and streamline the workflow. The recent advance in large-scale generative AI techniques, e.g., large language models (LLMs)…
Despite rapid progress in autonomous web agents, human involvement remains essential for shaping preferences and correcting agent behavior as tasks unfold. However, current agentic systems lack a principled understanding of when and why…
We focus on collaborative activities that engage computer graphics designers and social scientists in systems design processes. Our conceptual symmetrical account of technology design and theory development is elaborated as a mode of mutual…
Purpose: The purpose of this paper is to contribute to the debate as to whether collaboration in coworking spaces contributes to firm innovativeness and impacts the business models of organizations in a positive manner. Methodology: This…
Joint activity describes when more than one agent (human or machine) contributes to the completion of a task or activity. Designing for joint activity focuses on explicitly supporting the interdependencies between agents necessary for…
Large-scale interacting human activities underlie all social and economic phenomena, but quantitative understanding of regular patterns and mechanism is very challenging and still rare. Self-organized online collaborative activities with…
As belief around the potential of computational social science grows, fuelled by recent advances in machine learning, data scientists are ostensibly becoming the new experts in education. Scholars engaged in critical studies of education…
Collaborative tagging describes the process by which many users add metadata in the form of keywords to shared content. Recently, collaborative tagging has grown in popularity on the web, on sites that allow users to tag bookmarks,…
In a world where technology is increasingly embedded in our everyday experiences, systems that sense and respond to human emotions are elevating digital interaction. At the intersection of artificial intelligence and human-computer…