In the ever-growing world of Knowledge Graphs (KGs), understanding the structure and relationships within large datasets can be a daunting task. This is where ABSTAT, developed by UNIMIB as part of the enRichMyData toolbox, steps in to simplify the process.
What is ABSTAT?
ABSTAT is an advanced pattern-based profiling tool designed to help both humans and machines efficiently navigate and explore Knowledge Graphs. By providing schema-level summaries and key statistics, ABSTAT enables users to extract valuable insights and improve data-driven decision-making.
How Does ABSTAT Work?
ABSTAT operates through two key components:
✅ Backend Profiling:
- Extracts and lists schema-level connections within a Knowledge Graph.
- Computes statistics such as the number of occurrences of a particular relationship (e.g., linking dbo:Company to dbo:foundingYear in DBpedia).
- Creates concise summaries of the data structure, making it easier to interpret large datasets.
✅ Frontend Explorative Search:
- Allows users to explore relationships between different entities in a graph.
- Supports query formulation by providing insights into existing connections.
- Helps detect data quality issues and guides feature selection for machine learning models.
Why is ABSTAT Useful?
ABSTAT is particularly beneficial for:
Data Scientists & Analysts– Easily explore and filter KG properties.
Researchers– Understand relationships within large datasets.
Developers & AI Engineers – Enhance machine learning models by selecting the most relevant features.
Tool Openness & Accessibility
ABSTAT is open-source, allowing users to: 🔹 Download, host, and run the tool independently. 🔹 Access an online version with pre-loaded profiles to explore its capabilities.
Discover the Future of Knowledge Graph Exploration
Whether working with large-scale enterprise data, conducting semantic analysis, or improving query formulation, ABSTAT empowers you to make the most of your Knowledge Graphs.
Try ABSTAT today and take your data exploration to the next level!