From 213cbcf874724fbe1823286c238f9c543bdacbb6 Mon Sep 17 00:00:00 2001 From: rly Date: Thu, 11 Apr 2024 02:28:28 -0700 Subject: [PATCH] Add readme --- README.md | 18 +++++++++++++++++- 1 file changed, 17 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 7753121..c64a01a 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,19 @@ # HDMF-AI - an HDMF schema and API for AI/ML workflows -![Schema](paper/schema.png) +`HDMF-AI` is a schema and Python API for storing the common results of AI algorithms in a standardized way within the Hierarchical Data Modeling Framework (HDMF). + +`HDMF-AI` is designed to be flexible and extensible, allowing users to store a range of AI and machine learning results and metadata, such as from classification, regression, and clustering. These results are stored in the `ResultsTable` data type, which extends the `DynamicTable` data type within the base HDMF schema. The `ResultsTable` schema represents each data sample as a row and includes columns for storing model outputs and information about the AI/ML workflow, such as which data were used for training, validation, and testing. + +By leveraging existing HDMF tools and standards, `HDMF-AI` provides a scalable and extensible framework for storing AI results in an accessible, standardized way that is compatible with other HDMF-based data formats, such as Neurodata Without Borders [@rubel2022neurodata], a popular data standard for neurophysiology, and HDMF-Seq, a format for storing taxonomic and genomic sequence data. By enabling standardized co-storage of data and AI results, `HDMF-AI` may enhance the reproducibility and explainability of AI for science. + +![UML diagram of the HDMF-AI schema. Data types with orange headers are introduced by HDMF-AI. Data types with blue headers are defined in HDMF. Fields colored in gray are optional.](paper/schema.png) + +## Installation + +```bash +pip install hdmf-ai +``` + +## Usage + +For example usage, see `example_usage.ipynb`.