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

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...

Full description

Saved in:
Bibliographic Details
Main Authors: Samar, Sahil, Chen, Mia, Karpinski, Jack, Ray, Michael, Sarin, Archita, Garcia, Christian, Lange, Matthew, Stubbs, Joe, Thomas, Mary
Format: Journal Article
Language:English
Published: 16-04-2023
Subjects:
Computer Science - Artificial Intelligence
Computer Science - Cryptography and Security
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
DOI:10.48550/arxiv.2304.11086