International Society for Data Science and Analytics - ISDSA

01/18/2026

The 2026 Annual Meeting of ISDSA on Data Science is scheduled to be held in Beijing, China from July 28 to July 31. Abstract is accepted till Feb 15, 2026. More information can be found at https://meeting.isdsa.org.

06/26/2025

Register here: https://meeting.isdsa.org/

02/17/2025

01/12/2024

2024 Data Science and Psychology Meeting Call for Abstracts (July 21–24, 2024 | Vienna, Austria)

08/24/2023

New issue of the Journal of Behavioral Data Science. All articles are open access. Feel free to share.
Marvin, L., Liu, H., & Depaoli, S. (2023). Using Bayesian Piecewise Growth Curve Models to Handle Complex Nonlinear Trajectories. Journal of Behavioral Data Science, 3(1), 1–33. https://doi.org/10.35566/jbds/v3n1/marvin
Ogasawara, H. (2023). On Some Known Derivations and New Ones for The Wishart Distribution: A Didactic. Journal of Behavioral Data Science, 3(1), 34–58. https://doi.org/10.35566/jbds/v3n1/ogasawara
Wyman, A., & Zhang, Z. (2023). API Face Value: Evaluating the Current Status and Potential of Emotion Detection Software in Emotional Deficit Interventions. Journal of Behavioral Data Science, 3(1), 59–69. https://doi.org/10.35566/jbds/v3n1/wyman
S, V. (2023). Predicting Dyslexia with Machine Learning: A Comprehensive Review of Feature Selection, Algorithms, and Evaluation Metrics. Journal of Behavioral Data Science, 3(1), 70–83. https://doi.org/10.35566/jbds/v3n1/s
McClure, K. (2023). Bayesian IRT in JAGS: A Tutorial. Journal of Behavioral Data Science, 3(1), 84–107. https://doi.org/10.35566/jbds/v3n1/mccure

Using Bayesian Piecewise Growth Curve Models to Handle Complex Nonlinear Trajectories Authors Luca Marvin University of California, Merced Haiyan Liu University of California, Merced Sarah Depaoli University of California, Merced DOI: https://doi.org/10.35566/jbds/v3n1/marvin Keywords: Piecewise Gro...

03/04/2023

Free workshops on data science and quantitative methods. Also please join our meeting in Shanghai. https://meeting.isdsa.org

12/19/2022

The new issue (Volume 2, Number 2) of Journal of Behavioral Data Science is now published. There are seven articles in this issue. Enjoy!

Zhang, T., Tong, X., & Zhou, J. (2022). Disentangling the Influence of Data Contamination in Growth Curve Modeling: A Median Based Bayesian Approach. Journal of Behavioral Data Science, 2(2), 1–22. https://doi.org/10.35566/jbds/v2n2/p1

Liu, H. ., Qu, W., Zhang, Z., & Wu, H. (2022). A New Bayesian Structural Equation Modeling Approach with Priors on the Covariance Matrix Parameter. Journal of Behavioral Data Science, 2(2), 23–46. https://doi.org/10.35566/jbds/v2n2/p2

Du, H., Ke, Z., Jiang, G., & Huang, S. (2022). The Performances of Gelman-Rubin and Geweke’s Convergence Diagnostics of Monte Carlo Markov Chains in Bayesian Analysis. Journal of Behavioral Data Science, 2(2), 47–72. https://doi.org/10.35566/jbds/v2n2/p3

Suzuki, H., & Gonzalez, O. (2022). Relative Predictive Performance of Treatments of Ordinal Outcome Variables across Machine Learning Algorithms and Class Distributions. Journal of Behavioral Data Science, 2(2), 73–98. https://doi.org/10.35566/jbds/v2n2/suzuki

Xu, Z. (2022). Handling Ignorable and Non-ignorable Missing Data through Bayesian Methods in JAGS. Journal of Behavioral Data Science, 2(2), 99–126. https://doi.org/10.35566/jbds/v2n2/xu
Qiu, M. (2022). A Tutorial on Bayesian Latent Class Analysis Using JAGS. Journal of Behavioral Data Science, 2(2), 127–155. https://doi.org/10.35566/jbds/v2n2/qiu
Shao, S. (2022). A Tutorial on Bayesian Analysis of Count Data Using JAGS. Journal of Behavioral Data Science, 2(2), 156–173. https://doi.org/10.35566/jbds/v2n2/shao

Journal of Behavioral Data Science aims to provide a free-of-charge-to-publish and open-access journal to researchers and practitioners in the area of data science and data analytics.

10/31/2022

The Department of Integrative Physiology at CU Boulder invites applications for two tenure-track positions at the rank of assistant professor.

Applications are only accepted electronically (https://jobs.colorado.edu/) at CU Boulder Jobs, posting #42876.

07/27/2022

New issue of Journal of Behavioral Data Science is now available online. Below is a list of articles in this issue.

Borsboom, D., Blanken, T., Dablander, F., van Harreveld, F., Tanis, C., & Van Mieghem, P. (2022). The Lighting of the BECONs: A Behavioral Data Science Approach to Tracking Interventions in COVID-19 Research. Journal of Behavioral Data Science, 2(1), 1–34. https://doi.org/10.35566/jbds/v2n1/p1

Lu, L., & Zhang, Z. (2022). How to Select the Best Fit Model among Bayesian Latent Growth Models for Complex Data. Journal of Behavioral Data Science, 2(1), 35–58. https://doi.org/10.35566/jbds/v2n1/p2

Jacobucci, R., & Li, X. (2022). Does Minority Case Sampling Improve Performance with Imbalanced Outcomes in Psychological Research?. Journal of Behavioral Data Science, 2(1), 59–74. https://doi.org/10.35566/jbds/v2n1/p3

Marcoulides, K., Quan, J., & Wright, E. (2022). The Impact of Sample Size on Exchangeability in the Bayesian Synthesis Approach to Data Fusion. Journal of Behavioral Data Science, 2(1), 75–105. https://doi.org/10.35566/jbds/v2n1/p5

Waggoner, P., & Kennedy, R. (2022). The Role of Personality in Trust in Public Policy Automation. Journal of Behavioral Data Science, 2(1), 106–123. https://doi.org/10.35566/jbds/v2n1/p4/

Sales Rodrigues, K. A. (2022). Book Review: An Introduction to Nonparametric Statistics. Journal of Behavioral Data Science, 2(1), 124–127. https://doi.org/10.35566/jbds/v2n1/p8

The Lighting of the BECONs A Behavioral Data Science Approach to Tracking Interventions in COVID-19 Research Authors Denny Borsboom * University of Amsterdam Tessa Blanken University of Amsterdam Fabian Dablander University of Amsterdam Frenk van Harreveld University of Amsterdam Charlotte C. Tanis....

05/27/2022

See a list of studies that will be presented at ISDSA 2022 on May 31 and June 1.

https://meeting.isdsa.org/index.php/isdsa/2022/schedConf/program

03/24/2022

One week left to submit your abstract to our Data Science Meeting on May 31 and June 1, 2022.

Submit your abstract at https://meeting.isdsa.org