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Overview

ExeKGLib is a Python library that simplifies the construction and execution of Machine Learning (ML) pipelines represented by Executable Knowledge Graphs (ExeKGs). It features a coding interface and a CLI, and allows the user to:

🌟 Features

  1. 🔨 Construct data analytics pipelines that take tabular files (e.g. CSV) as input and process the data using a variety of available tasks and methods.
  2. 💾 Save the constructed pipelines as ExeKGs in RDF Turtle format.
  3. ▶️ Execute the generated ExeKGs.

🌟 Key Benefits of ExeKGLib

  1. 🚀 No-code ML Pipeline Creation: With ExeKGLib, the user can specify the pipeline's structure and the operations to be performed using a simple JSON file (see Creating an ML pipeline), which is then automatically converted to an ExeKG. This ExeKG can be executed to perform the specified operations on the input data (see Executing an ML pipeline).
  2. 📦 Batch Pipeline Creation and Edit: ExeKGLib allows users to create and edit pipelines in a batch fashion through its simple coding interface (see Creating an ML pipeline and Editing an ML pipeline). This enables automatic creation of multiple pipelines as ExeKGs, which can then be queried and analyzed.
  3. 🔗 Linked Open Data Integration: ExeKGLib is a tool that leverages linked open data (LOD) in several significant ways:
    • 📚 Pipeline Creation Guidance: It helps guide the user through the pipeline creation process. This is achieved by using a predefined hierarchy of tasks, along with their compatible inputs, outputs, methods, and method parameters (see available tasks and methods).
    • 🧠 Enhancing User Understanding: It enhances the user's understanding of Data Science and the pipeline's functionality. This is achieved by linking the generated pipelines to Knowledge Graph (KG) schemata that encapsulate various Data Science concepts (see KG schemata).
    • ✅ Validation of ExeKGs: It validates the generated ExeKGs to ensure their executability.
    • 🔄 Automatic Conversion and Execution: It automatically converts the ExeKGs to Python code and executes them.

Under the hood, ExeKGLib uses well-known Python libraries for data processing and visualization and performing predictions such as pandas, matplotlib, and scikit-learn.

ExeKGLib is described in the following paper published as part of ESWC 2023:
Klironomos A., Zhou B., Tan Z., Zheng Z., Gad-Elrab M., Paulheim H., Kharlamov E. ExeKGLib: Knowledge Graphs-Empowered Machine Learning Analytics