The Cyberinfrastructure Knowledge Network (CKN) is an extensible and portable distributed framework designed to optimize AI at the edge—particularly in dynamic environments where workloads may change suddenly (for example, in response to motion detection). CKN enhances edge–cloud collaboration by using historical data, graph representations, and adaptable deployment of AI models to satisfy changing accuracy‑and‑latency demands on edge devices.
CKN facilitates seamless connectivity between edge devices and the cloud through event streaming, enabling real‑time data capture and processing. By leveraging event‑stream processing, it captures, aggregates, and stores historical system‑performance data in a knowledge graph that models application behaviour and guides model selection and deployment at the edge.
At the heart of the Patra Knowledge Base is the concept of Model Cards. These cards are essentially detailed records that provide essential information about each AI/ML model. This information includes technical details like the model's accuracy and latency, but it goes beyond that to include non-technical aspects such as fairness, explainability, and the model's behavior in various deployment environments. This holistic approach is intended to create a comprehensive understanding of the model's strengths and weaknesses, enabling more informed decisions about its use and deployment
Features
Getting Started
See the full documentation for detailed instructions on creating custom plug‑ins and streaming events to the knowledge graph.
Prerequisites
The Patra Knowledge Base is a system designed to manage and track AI/ML models, with the objective of making them more accountable and trustworthy. It's a key part of the Patra ModelCards framework, which aims to improve transparency and accountability in AI/ML models throughout their entire lifecycle. This includes the model's initial training phase, subsequent deployments, and ongoing usage, whether by the same or different individuals.
The Patra Toolkit is a component of the Patra ModelCards framework designed to simplify the process of creating and documenting AI/ML models. It provides a structured schema that guides users in providing essential information about their models, including details about the model's purpose, development process, and performance. The toolkit also includes features for semi-automating the capture of key information, such as fairness and explainability metrics, through integrated analysis tools. By reducing the manual effort involved in creating model cards, the Patra Toolkit encourages researchers and developers to adopt best practices for documenting their models, ultimately contributing to greater transparency and accountability in AI/ML development.
1. Create a CKN Topic
Set up Environment Variables
Create a Model Card