SKEMA: Scientific Knowledge Extraction and Model Analysis

This is the main code repository for the SKEMA project. It contains the source code and documentation for the text reading, structural alignment, and model role analysis components of SKEMA.

For details, see our project documentation

Directory structure

This repository contains code written in Python, Rust, and Scala. The directory structure has been chosen to make the components written in all these languages coexist peacefully.

At the top level, we have the following files and directories:

• Dockerfile.skema-py: Dockerfile for the skema python library (includes program analysis, img2mml, and isa components).
• Dockerfile.skema-rs: Dockerfile for the skema-rs service.
• LICENSE.txt: License for the software components in this repository.
• README.md: This README file.
• scripts: Miscellaneous scripts
• pyproject.toml: This file declares and defines the skema Python package.
• skema

The skema directory contains two different types of directories:

• A Rust workspace: skema-rs
• A number of Python subpackages:
  • program_analysis
  • gromet
  • model_assembly
  • text_reading
  • skema_py: Web service for converting code to GroMEt function networks and pyacsets.
  • img2mml: Web service for extracting equations from images.

Of the Python subpackages, the last two (skema_py and img2mml) are currently the most 'outward/user-facing' components. The program_analysis, gromet, and model_assembly directories are comprised primarily of library code that is used by the skema-py service.

The text_reading directory contains three subdirectories:

• mention_linking: Python subpackage for linking mentions in code and text
• text_reading: Scala project for rule-based extraction of mentions of scientific concepts.
• notebooks: Jupyter notebooks for demoing text reading/mention linking functionality.

Python

For instructions on installing our Python library, please see our developer documentation.

Other

The README.md files in the skema/skema-rs and skema/text_reading/text_reading directories provide instructions on how to run the software components that are written in Rust and Scala respectively.

Docker

For information on our releases and published docker images, please see this page

Examples

We maintain several containerized examples demonstrating system capabilities at https://github.com/ml4ai/ASKEM-TA1-DockerVM.