Data Videos for Information Communication
Data Videos (or DVs) are brief animated videos that present a narrative stemming from data. Under this theme, our goal is to explore methods for creating and studying the impact of Data Videos for effectively communicating information. We aim to explore means to construct visual narratives that can inspire end-users to take action through data-driven insights. Our projects have identified major narrative categories and key visualizations employed in highly popular online Data Videos, ways in which DVs can induce behaviour change, and developed tools such as DataClips to help novices rapidly construct DVs. We are exploring the value of automated DV and Micro-Data Video (MDV) generation that further incorporate elements from common persuasive technology frameworks. Our vision includes the rapid and easy creation of such data presentation strategies for many groups of end-users.
Research Goals
Video Insights
Exploration of Data Videos
We decomposed Data Videos to understand their narrative constructs and constituting components. Our projects have identified major narrative categories and key visualizations employed in highly popular online Data Videos. We further explored how expert designers design Data videos (Amini et al., 2015).
Implementation of Persusive Strategies
We investigate how we can enhance data videos so that they can induce behaviour change. We found that incorporating persuasive elements into DVs enhances their persuasive potential (Choe et al., 2019). Our studies also highlighted the potential benefits of integrating emotions in data storytelling (Sakamoto et al., 2022). Additionally, we emphasized the importance of considering personality differences and incorporating actionable solutions in data videos (Sallam et al., 2022).
 (Choe et al., 2019) |
 (Sakamoto et al., 2022) |
 (Sallam et al., 2022) |
| Persuasive Data Videos: Investigating Persuasive Self-Tracking Feedback with Augmented Data Videos |
Persuasive Data Storytelling with a Data Video during Covid-19 Infodemic |
Towards Design Guidelines for Effective Health-Related Data Videos |
Creation of Data Videos
We created DataClips, an authoring tool aimed at lowering the barriers to crafting data videos (Amini et al., 2016). We tested DataClips and demonstrated that non-experts are able to learn and use the tool with a short training period to produce high quality clips. Our future work aims at utilizing the advancement in Large Language Models (LLM) along with the knowledge we generated in our previous studies, to fully automate the creation of Data Videos.
Related Publications
Exploring the Design of Social Robot User Interfaces for Presenting Data-Driven Stories
Anuradha Herath, Samar Sallam, Yumiko Sakamoto, Randy Gomez, and Pourang Irani. (2023, December). Exploring the Design of Social Robot User Interfaces for Presenting Data-Driven Stories. In Proceedings of the 22nd International Conference on Mobile and Ubiquitous Multimedia (MUM '23). (pp. 321-339). Association for Computing Machinery.
Presenting Data with Social Robots: An Exploration into Conveying Data Videos using an Artificial Physical Narrator
Anuradha Herath, Samar Sallam, Tanvi Vuradi, Yumiko Sakamoto, Randy Gomez and Pourang Irani. (2023, December). Presenting Data with Social Robots: An Exploration into Conveying Data Videos using an Artificial Physical Narrator (HAI '23). (pp. 476-478). Association for Computing Machinery.
Persuasive Data Storytelling with a Data Video during Covid-19 Infodemic: Affective Pathway to Influence the Users’ Perception about Contact Tracing Apps in less than 6 Minutes
Sakamoto Y, Sallam S, Leboe-McGowan J, Salo A, Irani P. Persuasive data storytelling with a data video during Covid-19 infodemic: Affective pathway to influence the users’ perception about contact tracing apps in less than 6 minutes. Proceedings of the 2022 Pacific Vis. 2022.
Towards Design Guidelines for Effective Health-Related Data Videos: An Empirical Investigation of Affect, Personality, and Video Content
Sallam S, Sakamoto Y, Leboe-McGowan J, Latulipe C, Irani P. Towards Design Guidelines for Effective Health-Related Data Videos: An Empirical Investigation of Affect, Personality, and Video Content. Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems.
Persuasive Data Videos: Investigating Persuasive Self-Tracking Feedback with Augmented Data Videos
Choe, E. K., Sakamoto, Y., Fatmi, Y., Lee, B., Hurter, C., Haghshenas, A., & Irani, P. (2019). Persuasive data videos: Investigating persuasive self-tracking feedback with augmented data videos. In AMIA Annual Symposium Proceedings (Vol. 2019, p. 295). American Medical Informatics Association.
Hooked on data videos: assessing the effect of animation and pictographs on viewer engagement
Amini, F., Riche, N. H., Lee, B., Leboe-McGowan, J., & Irani, P. (2018, May). Hooked on data videos: assessing the effect of animation and pictographs on viewer engagement. In Proceedings of the 2018 International Conference on Advanced Visual Interfaces (pp. 1-9).
Evaluating Data-Driven Stories and Storytelling Tools
Amini, F., Brehmer, M., Bolduan, G., Elmer, C., & Wiederkehr, B. (2018). Evaluating data-driven stories and storytelling tools. In Data-driven storytelling (pp. 249-286). AK Peters/CRC Press
Authoring Data-Driven Videos with DataClips
Amini, F., Riche, N. H., Lee, B., Monroy-Hernandez, A., & Irani, P. (2016). Authoring data-driven videos with dataclips. IEEE transactions on visualization and computer graphics, 23(1), 501-510.
Understanding Data Videos: Looking at Narrative Visualization through the Cinematography Lens
Amini, F., Henry Riche, N., Lee, B., Hurter, C., & Irani, P. (2015, April). Understanding data videos: Looking at narrative visualization through the cinematography lens. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (pp. 1459-1468).
Team Members
Pourang P. Irani
Professor Principal's Research Chair in Ubiquitous Analytics
University of British Columbia (Okanagan campus)
Room No: 304
Charles E. Fipke Centre for Innovative Research
3247 University Way
Kelowna, BC V1V 1V7
Email: pourang.irani@ubc.ca
I am a Professor in the Department of Computer Science at the University of British Columbia (Okanagan campus) and Principal's Research Chair in Ubiquitous Analytics. My research lies broadly in the areas of Human-Computer Interaction and Information Visualization. More specifically, our team is concentrating on designing and studying novel interactive systems for sensemaking "anywhere" and "anytime". For advancing this work we rely on mixed reality (MR) and wearable technologies for developing novel prototypes of visual interfaces and devices. I am also the Principal Investigator on an NSERC CREATE grant on Visual and Automated Disease Analytics. The aim of the VADA program is to train the next generation data scientists with a focus on health data analytics.
