Accarino, G., Donno, D., Immorlano, F., Elia, D., & Aloisio, G. (2023). An Ensemble Machine Learning Approach for Tropical Cyclone Localization and Tracking From ERA5 Reanalysis Data. Earth and Space Science, 10.

Pondi, B., Appel, M., & Pebesma, E. (2024). OpenEOcubes: an open-source and lightweight R-based RESTful web service for analyzing earth observation data cubes.

S. Fiore, M. Rampazzo, D. Elia, L. Sacco, F. Antonio and P. Nassisi, “A Graph Data Model-based Micro-Provenance Approach for Multi-level Provenance Exploration in End-to-End Climate Workflows,” 2023 IEEE International Conference on Big Data (BigData), Sorrento, Italy, 2023, pp. 3332-3339,

Nica, R., Götz, S. & Moltó, G. CMK: Enhancing Resource Usage Monitoring across Diverse Bioinformatics Workflow Management Systems. J Grid Computing 22, 62 (2024).

Otsu, K., & Maso, J. (2024). Digital Twins for Research and Innovation in Support of the European Green Deal Data Space: A Systematic Review. Remote Sensing, 16(19), 3672

Tangaro, Marco Antonio; Antonacci, Marica; Donvito, Giacinto; Foggetti, Nadina; Mandreoli, Pietro; Colombo, Daniele; Pesole, Graziano; Zambelli, Federico,  Dynamic configuration and data security for bioinformatics cloud services with the Laniakea Dashboard, NAR Genomics and Bioinformatics, 2024, 6, lqae140

G. Padovani, V. Anantharaj, S. Fiore (2025). yProv4ML: Effortless provenance tracking for machine learning systems, SoftwareX, Volume 31, 2025, 102298, ISSN 2352-7110,

L. Sacco, C. Sopranzetti and S. Fiore, “Enabling Provenance Tracking in Workflow Management Systems,” 2024 IEEE International Conference on Big Data (BigData), Washington, DC, USA, 2024, pp. 4402-4409,

G. Padovani, V. Anantharaj, L. Sacco, T. Kurihana, M. Bunino, K. Tsolaki, M. Girone, F. Antonio, C. Sopranzetti, M. Fronza, S. Fiore (2024). “A software ecosystem for multi-level provenance management in large-scale scientific workflows for AI applications,” SC24-W: Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis, Atlanta, GA, USA, 2024, pp. 2024-2031

N. G. Marchioro, Y. Velegrakis, V. Anantharaj, I. Foster, S. Fiore, “Trustworthy Provenance for Big Data Science: a Modular Architecture Leveraging Blockchain in Federated Settings”

Campos, I. , interTwin: Advancing Scientific Digital Twins through AI, Federated Computing and Data under review

A. Altherr, I. Campos, A. Cotellucci, R. Gruber, T. Harris, J. Komijani, F. Margari, M. K. Marinkovic, L. Parato, A. Patella, S. Rosso, N. Tantalo, P. Tavella; Comparing QCD+QED via full simulation versus the RM123 method: U-spin window contribution to…

Asprea, L., Cellini, E., Legger, F., Romano, A., Sarandrea, F., & Vallero, S. (2025). GlitchFlow, a Digital Twin for transient noise in Gravitational Wave Interferometers. EPJ Web of Conferences, 337, 01203.

Ciangottini, D., Spiga, D., Memon, A. S., Manzi, A., Filipcic, A., Troja, A., Fanzago, F., Bianchini, G., Sgaravatto, M., Prica, T., Boccali, T., & Tedeschi, T. (2025). Unlocking the compute continuum: Scaling out from cloud to HPC and HTC resources. EPJ Web of Conferences, 337, 01296