We are a group of data toolsmiths who develop and study the role of visualization techniques as a transparent lens between what is computed from data and what is communicated to the human mind.
As George Bernard Shaw so eloquently said: “The single biggest problem in communication is the illusion that it has taken place.” This is oh-so-evident in today’s age, where, information, if communicated properly, can cure diseases and fuel discoveries, but, if miscommunicated, can lead to an “infodemic” in the worst-case scenario.
To solve this conundrum, at NiiV, we pursue intelligibility as the foundational principle for making information more accessible, meaningful, and actionable to experts (e.g., doctors, climate scientists) and non-experts alike.
We operationalize this principle by visualizing data, big or small, with the ultimate goal of letting human observers see, understand, and trust the information that is often generated by black-box algorithms.
By embracing a human-centered data science approach that ultimately culminates in interactive visual analytic interfaces, we preserve the best of both worlds: the power of computational methods and that of human judgment and reasoning.
Oct ’22: Bhattacharjee presented paper at VizSec
July ’22: Bhattacharjee interned at PNNL for summer and fall '22
Apr ’22: Yuan presented position paper at HCDS@CHI
Oct ’21: 2 papers presented at IEEEVIS: short paper track (Vaidya) and TREX workshop(Dasgupta)
Oct ’21: Dasgupta chairs session on VIS+AI at IEEEVIS
July ’21: Dasgupta receives NJIT Seed grant for research on communicative visualization
May ’21: Yuan interned at Accern for summer '21
Oct ’20: 2 papers and a poster presented at IEEEVIS ‘20
May ’20: Paper at EuroVis presented by Bhattacharjee
May ’20: Dasgupta receives grant from Hearst Corporation for data visualization training
Privacy-Preserving Data Visualization
Adapt visualizations to prevent disclosure of sensitive information by developing information loss metrics that can help address the trade-off between privacy gain and loss of utility due to anonymization.
- Bhattacharjee, Kaustav, Akm Islam, Jaideep Vaidya, and Aritra Dasgupta. "PRIVEE: A Visual Analytic Workflow for Proactive Privacy Risk Inspection of Open Data." arXiv preprint arXiv:2208.06481 (2022).
- Yuan, Jun, Julia Stoyanovich, and Aritra Dasgupta. "Rankers, Rankees, & Rankings: Peeking into the Pandora's Box from a Socio-Technical Perspective." Position paper presented at 2022 CHI Workshop on Interrogating Human-Centered Data Science (2022).
- Vaidya, Sahaj, Jie Cai, Soumyadeep Basu, Azadeh Naderi, Donghee Yvette Wohn, and Aritra Dasgupta. "Conceptualizing Visual Analytic Interventions for Content Moderation." In Proceedings of 2021 IEEE Visualization Conference (VIS), IEEE, 2021.
- Wenskovitch, John, Corey Fallon, Kate Miller, and Aritra Dasgupta. "Beyond Visual Analytics: Human-Machine Teaming for AI-Driven Data Sensemaking."Proc. of IEEE VIS 2021 Workshop on Trust and Expertise in Visual Analytics, 2021.
- Vaidya, Sahaj, and Aritra Dasgupta. "Knowing what to look for: A Fact-Evidence Reasoning Framework for Decoding Communicative Visualization." In 2020 IEEE Visualization Conference (VIS), pp. 231-235. IEEE, 2020.
- Islam, Akm, and Aritra Dasgupta. "UrbanForest: Seeing the data forest despite the trees." In IEEE Visualization Conference (VIS) 2020 Posters, 2020
- Bhattacharjee, Kaustav, Min Chen, and Aritra Dasgupta. "Privacy‐Preserving Data Visualization: Reflections on the State of the Art and Research Opportunities." Computer Graphics Forum 39.3 (2020): 675-92.
- Aritra Dasgupta, Jorge Poco, Bernice Rogowitz, Kyungsik Han, Enrico Bertini, Claudio T Silva “The Effect of Color Scales on Climate Scientists’ Objective and Subjective Performance in Spatial Data Analysis Tasks.” IEEE Transactions on Visualization and Computer Graphics, vol. 26, no. 3, 2020, pp. 1577–91. Crossref, doi:10.1109/tvcg.2018.2876539.
- Dasgupta, Aritra, Hong Wang, Nancy O'brien, and Susannah Burrows. "Separating the Wheat from the Chaff: Comparative Visual Cues for Transparent Diagnostics of Competing Models." IEEE Transactions on Visualization and Computer Graphics 26.1 (2020): 1043-053.
- Dasgupta, Aritra, Robert Kosara, and Min Chen. "Guess Me If You Can: A Visual Uncertainty Model for Transparent Evaluation of Disclosure Risks in Privacy-Preserving Data Visualization." 2019 IEEE Symposium on Visualization for Cyber Security (VizSec) (2019)
- Burrows, Susannah M., Aritra Dasgupta, Sarah Reehl, Lisa Bramer, Po-Lun Ma, Philip J. Rasch, and Yun Qian. "Characterizing the Relative Importance Assigned to Physical Variables by Climate Scientists When Assessing Atmospheric Climate Model Fidelity." Advances in Atmospheric Sciences 35.9 (2018): 1101-113.
- Bridging Computation and Visual Communication of Change using Levels of Abstraction, A Dasgupta, M Pirrung, J Bruce, J Scholtz, K Han, D Arendt, IEEEVIS Workshop on Visual Communication
- Dasgupta, Aritra. "Experts’ Familiarity Versus Optimality of Visualization Design: How Familiarity Affects Perceived and Objective Task Performance." Cognitive Biases in Visualizations (2018): 75-86. Print.
- Cristian Felix, Aritra Dasgupta, and Enrico Bertini. 2018. "The Exploratory Labeling Assistant: Mixed-Initiative Label Curation with Large Document Collections." In Proceedings of the 31st Annual ACM Symposium on User Interface Software and Technology (UIST '18). Association for Computing Machinery, New York, NY, USA, 153–164. DOI:https://doi.org/10.1145/3242587.3242596
- Aritra Dasgupta, Dustin Arendt, Lyndsey Franklin, Pak Chung Wong, Kristin Cook. "Human factors in streaming data analysis: Challenges and opportunities for information visualization." Computer Graphics Forum. Vol. 37. No. 1. 2018.
- Dasgupta, Aritra. "Towards Understanding Familiarity Related Cognitive Biases in Visualization Design and Usage." DECISIVe: Workshop on Dealing with Cognitive Biases in Visualizations. IEEE VIS. 2017.
- Krause, Josua, Aritra Dasgupta, Jordan Swartz, Yindalon Aphinyanaphongs, and Enrico Bertini. "A Workflow for Visual Diagnostics of Binary Classifiers Using Instance-Level Explanations." 2017 IEEE Conference on Visual Analytics Science and Technology (VAST) (2017).
- Tamagnini, Paolo, Josua Krause, Aritra Dasgupta, and Enrico Bertini. "Interpreting Black-Box Classifiers Using Instance-Level Visual Explanations." Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics - HILDA'17 (2017).
- Dasgupta, Aritra, Susannah Burrows, Kyungsik Han, and Philip J. Rasch. "Empirical Analysis of the Subjective Impressions and Objective Measures of Domain Scientists' Visual Analytic Judgments." Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (2017).
- Aritra Dasgupta, Joon-Yong Lee, Ryan Wilson, Robert Lafrance, Nick Cramer, Kristin Cook, Samuel H. Payne "Familiarity vs trust: A comparative study of domain scientists' trust in visual analytics and conventional analysis methods." IEEE transactions on visualization and computer graphics 23.1 (2016): 271-280.
- Josua Krause, Aritra Dasgupta, Jean-Daniel Fekete, Enrico Bertini"Seekaview: An intelligent dimensionality reduction strategy for navigating high-dimensional data spaces." 2016 IEEE 6th Symposium on Large Data Analysis and Visualization (LDAV). IEEE, 2016.
- Kosara, Robert, Aritra Dasgupta, and Enrico Bertini. "Reflecting on the Design Criteria for Explanatory Visualizations." In Workshop on Creation, Curation, Critique and Conditioning of Principles and Guidelines in Visualization (C4PGV). 2016.
- Aritra Dasgupta, Jorge Poco, Enrico Bertini, Claudio Silva "Reducing the analytical bottleneck for domain scientists: Lessons from a climate data visualization case study." Computing in Science & Engineering 18.1 (2016): 92-100.
- Aritra Dasgupta, Jorge Poco, Yaxing Wei, Robert Cook, Enrico Bertini, Claudio Silva "Bridging theory with practice: An exploratory study of visualization use and design for climate model comparison." IEEE transactions on visualization and computer graphics 21.9 (2015): 996-1014.
- Dasgupta, Aritra, Robert Kosara, and Luke Gosink. "VIMTEX: A Visualization Interface for Multivariate, Time‐Varying, Geological Data Exploration." Computer Graphics Forum. Vol. 34. No. 3. 2015.
- Jorge Poco, Aritra Dasgupta, Yaxing Wei, William Hargrove, Christopher R Schwalm, Deborah N Huntzinger, Robert Cook, Enrico Bertini, Claudio T Silva "Visual reconciliation of alternative similarity spaces in climate modeling." IEEE transactions on visualization and computer graphics 20.12 (2014): 1923-1932.
- Aritra Dasgupta, Eamonn Maguire, Abdul-Rahman Alfie, Min Chen "Opportunities and challenges for privacy-preserving visualization of electronic health record data." Proc. of IEEE VIS 2014 Workshop on Visualization of Electronic Health Records. Vol. 13. 2014.
- Jorge Poco, Aritra Dasgupta, Yaxing Wei, William Hargrove, Christopher Schwalm, Robert Cook, Enrico Bertini, Claudio Silva "SimilarityExplorer: A Visual Inter‐Comparison Tool for Multifaceted Climate Data." Computer Graphics Forum. Vol. 33. No. 3. 2014.
- DN Huntzinger, CR Schwalm, AM Michalak, RB Cook, AR Jacobson, KM Schaefer, A Dasgupta, J Poco"Global net land carbon sink: results from the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP)." AGUFM 2013 (2013): B13M-05.
- Y Wei, RB Cook, F Du, A Dasgupta, J Poco, DN Huntzinger, CR Schwalm, E Boldrini, M Santoro, J Pearlman, F Pearlman, S Nativi, S Khalsa "Integrate Data into Scientific Workflows for Terrestrial Biosphere Model Evaluation through Brokers." AGUFM 2013 (2013): IN53E-06.
- Dasgupta, Aritra, Min Chen, and Robert Kosara. "Measuring privacy and utility in privacy‐preserving visualization." Computer Graphics Forum. Vol. 32. No. 8. 2013.
- Brian Duffy, Aritra Dasgupta, Robert Kosara, S Walton, Min Chen "Measuring Visual Complexity of Cluster-Based Visualizations." arXiv preprint arXiv:1302.5824 (2013).
- Dasgupta, Aritra, Robert Kosara, and Luke Gosink. "Meta parallel coordinates for visualizing features in large, high-dimensional, time-varying data." IEEE Symposium on Large Data Analysis and Visualization (LDAV). IEEE, 2012.
- Dasgupta, Aritra, and Robert Kosara. "The importance of tracing data through the visualization pipeline." Proceedings of the 2012 BELIV Workshop: Beyond Time and Errors-Novel Evaluation Methods for Visualization. 2012.
- Dasgupta, Aritra, Min Chen, and Robert Kosara. "Conceptualizing visual uncertainty in parallel coordinates." Computer Graphics Forum. Vol. 31. No. 3pt2. Oxford, UK: Blackwell Publishing Ltd, 2012.
- Dasgupta, Aritra. The visual uncertainty paradigm for controlling screen-space information in visualization. Diss. The University of North Carolina at Charlotte, 2012.
- Dasgupta, Aritra, and Robert Kosara. "Adaptive privacy-preserving visualization using parallel coordinates." IEEE transactions on visualization and computer graphics 17.12 (2011): 2241-2248.
- Dasgupta, Aritra, and Robert Kosara. "Privacy-preserving data visualization using parallel coordinates." Visualization and Data Analysis 2011. Vol. 7868. International Society for Optics and Photonics, 2011.
- Dasgupta, Aritra, and Robert Kosara. "Pargnostics: Screen-space metrics for parallel coordinates." IEEE Transactions on Visualization and Computer Graphics 16.6 (2010): 1017-1026.
- Dasgupta, Aritra, and Robert Kosara. "The Need for Information Loss Metrics in Visualization." Workshop on The Role of Theory in Information Visualization. 2010.
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