Dear Colleagues,
Volume 20, Number 4 of the
Journal of Data Science (
https://jds-online.org) is a special issue on large-scale spatial data science, co-edited by
• Sameh Abdulah, Extreme Computing Research Center, King Abdullah University of Science and Technology
• Stefano Castruccio, Department of Applied and Computational Mathematics and Statisics, University of Notre Dame
• Marc Genton, Computer, Electrical and Mathematical Science and Engineering Division, King Abdullah University of Science and Technology
• Ying Sun, Computer, Electrical and Mathematical Science and Engineering Division, King Abdullah University of Science and Technology
Kudos to the editors, authors, and reviewers!
All the articles are published under the CC-BY license (
https://creativecommons.org/licenses/by/4.0/) for the widest dissemination. Funded by the School of Statistics and the Center for Applied Statistics, Renmin University of China, there are no Article Processing Charges. The journal features a fast review process and a reproducibility check.
Established in 2003, the Journal of Data Science aims to advance and promote data science methods, computing, and applications in all scientific fields where knowledge and insights are to be extracted from data. We welcome submissions to all the sections including 1) Philosophy of Data Science; 2) Statistical Data Science; 3) Computing in Data Science; 4) Data Science in Action; 5) Data Science Review; 6) Education in Data Science.
Best regards,
Jun Yan
Editor, Journal of Data Science
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Journal of Data Science
Volume 20, Issue 4 (2022): Special Issue: Large-Scale Spatial Data Science, October 2022
Editorial: Large-Scale Spatial Data Science
Sameh Abdulah, Stefano Castruccio, Marc G. Genton, Ying Sun
https://doi.org/10.6339/22-JDS204EDIPub. online: 11 Nov 2022 Type: Editorial Open access
pp. 437–438
The Second Competition on Spatial Statistics for Large Datasets
Sameh Abdulah, Faten Alamri, Pratik Nag, Ying Sun, Hatem Ltaief, David E. Keyes, Marc Genton
Pub. online: 8 Nov 2022 Type: Statistical Data Science Open access
pp. 439–460
High-Dimensional Nonlinear Spatio-Temporal Filtering by Compressing Hierarchical Sparse Cholesky Factors
Anirban Chakraborty, Matthias Katzfuss
https://doi.org/10.6339/22-JDS1071Pub. online: 3 Oct 2022 Type: Statistical Data Science Open access
pp. 461–474
Vecchia Approximations and Optimization for Multivariate Matérn Models
Youssef Fahmy, Joseph Guinness
https://doi.org/10.6339/22-JDS1074Pub. online: 14 Oct 2022 Type: Computing In Data Science Open access
pp. 475–492
On the Use of Deep Neural Networks for Large-Scale Spatial Prediction
Skyler D. Gray, Matthew J. Heaton, Dan S. Bolintineanu, Aaron Olson
https://doi.org/10.6339/22-JDS1070Pub. online: 3 Oct 2022 Type: Data Science In Action Open access
pp. 493–511
Geostatistics for Large Datasets on Riemannian Manifolds: A Matrix-Free Approach
Mike Pereira, Nicolas Desassis, Denis Allard
https://doi.org/10.6339/22-JDS1075Pub. online: 3 Nov 2022 Type: Statistical Data Science Open access
pp. 512–532
Scalable Predictions for Spatial Probit Linear Mixed Models Using Nearest Neighbor Gaussian Processes
Arkajyoti Saha, Abhirup Datta, Sudipto Banerjee
https://doi.org/10.6339/22-JDS1073Pub. online: 3 Nov 2022 Type: Statistical Data Science Open access
pp. 533–544
Multiresolution Broad Area Search: Monitoring Spatial Characteristics of Gapless Remote Sensing Data
Laura J. Wendelberger, Josh M. Gray, Alyson G. Wilson, Rasmus Houborg, Brian J. Reich
pp. 545–565
Supervised Spatial Regionalization using the Karhunen-Loève Expansion and Minimum Spanning Trees
Ranadeep Daw, Christopher K. Wikle
https://doi.org/10.6339/22-JDS1077Pub. online: 9 Nov 2022 Type: Statistical Data Science Open access
pp. 566–584