Mary Thomas | Searcharxiv

arXiv2025

2024 NSF CSSI-Cybertraining-SCIPE PI Meeting August 12 to 13, 2024, Charlotte, NC

The second annual NSF, OAC CSSI, CyberTraining and related programs PI meeting was held August 12 to 13 in Charlotte, NC, with participation from PIs or representatives of all major awards. Keynotes, panels, breakouts, and poster sessions allowed PIs to engage with each other, NSF staff, and invited experts. The 286 attendees represented 292 awards across CSSI, CyberTraining, OAC Core, CIP, SCIPE CDSE, and related programs, and presented over 250 posters. This report documents the meetings structure, findings, and recommendations, offering a snapshot of current community perspectives on cyberinfrastructure. A key takeaway is a vibrant, engaged community advancing science through CI. AI-driven research modalities complement established HPC and data centric tools. Workforce development efforts align well with the CSSI community.

cs.ET↗

arXiv2023

Development of Authenticated Clients and Applications for ICICLE CI Services -- Final Report for the REHS Program, June-August, 2022

The Artificial Intelligence (AI) institute for Intelligent Cyberinfrastructure with Computational Learning in the Environment (ICICLE) is funded by the NSF to build the next generation of Cyberinfrastructure to render AI more accessible to everyone and drive its further democratization in the larger society. We describe our efforts to develop Jupyter Notebooks and Python command line clients that would access these ICICLE resources and services using ICICLE authentication mechanisms. To connect our clients, we used Tapis, which is a framework that supports computational research to enable scientists to access, utilize, and manage multi-institution resources and services. We used Neo4j to organize data into a knowledge graph (KG). We then hosted the KG on a Tapis Pod, which offers persistent data storage with a template made specifically for Neo4j KGs. In order to demonstrate the capabilities of our software, we developed several clients: Jupyter notebooks authentication, Neural Networks (NN) notebook, and command line applications that provide a convenient frontend to the Tapis API. In addition, we developed a data processing notebook that can manipulate KGs on the Tapis servers, including creations of a KG, data upload and modification. In this report we present the software architecture, design and approach, the successfulness of our client software, and future work.

cs.CR↗