“Exploring how Data Scientists Review Scholarly Literature” was accepted to CHIIR 2023
Authors: Sheshera Mysore, Mahmood Jasim, Haoru Song, Sarah Akbar, Andre Kenneth Chase Randall and Narges Mahyar
You can find the paper here.
“From Invisible to Visible: Impacts of Metadata in Communicative Data Visualization” was accepted to TVCG 2022
“From Invisible to Visible: Impacts of Metadata in Communicative Data Visualization” was accepted to TVCG 2022
Authors: Alyxander Burns, Christiana Lee, Thai On, Cindy Xiong, Evan Peck, Narges Mahyar
You can find the paper here.
Collaborative Visual Data Analysis Around Large Interactive Surfaces
Collaborative Visual Data Analysis Around Large Interactive Surfaces
Led by: Narges Mahyar & Ali Sarvghad
Note-taking in co-located collaborative visual analytics: Analysis of an observational study A Closer Look at Note Taking in the Co-located Collaborative Visual Analytics Process Roles of notes in co-located collaborative visualization
To gain a deeper understanding of collaborative visual data analysis around large interactive surfaces, we designed and carried out an observational user study. Co-located teams worked on collaborative visual analytics tasks using large interactive wall and tabletop displays. Our findings reinforced the importance of record keeping as an integral activity during collaborative data analysis. In addition, we characterized notes according to their content, scope, and usage, and described how they would fit into the process of collaborative data analysis. We also suggested design guidelines for note-taking functionality for co-located collaborative visual analytics tools.
CoSpaces
CoSpaces
Led by: Narges Mahyar & Ali Sarvghad CoSpaces: Workspaces to Support Co-located Collaborative Visual Analytics Observations of Record-Keeping in Co-located Collaborative Analysis
Project Video
CoSpaces is a prototype that is designed for collaborative data analysis on a large interactive tabletop display. It enables multiple users to simultaneously work together and create statistical charts. Some main features include the ability to record and keep track of the work by automatically saving charts, and also an embedded note-taking mechanism. Tabs are used as channels for providing awareness of collaborators’ work status. Each tab provides a portal for viewing work in progress in another workspace without any interruption. Using tabs, an analyst can view a collaborator’s current work, review work history, and study findings.
CLIP
CLIP (Collaborative Intelligence Pad)
Led by: Narges Mahyar Supporting Communication and Coordination in Collaborative Sensemaking Project Video
CLIP is a prototype tool designed and implemented to facilitate collaborative sense-making. The focus of this project is to assist intelligence analysts to record, schematize, and share their findings and hypotheses. Utilizing peer-to-peer communication, all working instances of CLIP broadcast the latest work of an analyst to the rest of the group. Different privacy levels provide controlled sharing. CLIP supports providing awareness of common work by visually indicating common entities.