Data Analysis Dashboard

Dashboard that allows human operators monitor and extract knowledge from tabular data through visualization/interpretability, querying, and inference features.

Image 1: The main view of the Data Analysis Dashboard

Asset Description

The Data Analysis Dashboard facilitates the comprehensive monitoring of tabular data (e.g., from sensor arrays) with sophisticated processing and analysis capabilities. Its key benefits include intuitive visualisation, flexible querying, and the ability to infer patterns and detect anomalies, giving human operators critical decision-making support. It uses some classical Data and Knowledge Engineering methods (e.g., Knowledge Graphs) and is implemented based on the Streamlit framework.

Key Features

Data Upload and Preprocessing:

• Upload datasets via file input or URL.
• Manage missing values using various imputation methods.
• Encode categorical variables and coerce numeric data.

Correlation Analysis:

• Compute Pearson and Spearman correlations, as well as Euclidean similarity.
• User-defined thresholds for filtering significant relationships.
• Knowledge Graph Creation:
• Automatically generate RDF graphs representing significant correlations.
• Define relationships using user-specified thresholds.

Inference Rules:

• Input custom IF-THEN rules to add inferred relationships to the RDF graph.

Visualization:

• Visualize correlations using interactive Plotly subplots.
• Display the knowledge graph as a network with customizable aesthetics.

SPARQL Querying:

• Query the RDF graph using SPARQL with a user-friendly interface.

Usage

This software helps users analyse datasets and uncover hidden relationships. Initially the user should perform the following:

• Upload a CSV file containing the data to be analysed
• Configure the data preprocessing aspects (handling missing values and data types)

Afterwards the user can explore their data and underlying relations , extracting knowledge in a flexible way:

• Select pairs of features and see the visualisations of correlation analysis

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Image 2: Statistical analysis

• Build a knowledge graph that represents significant relationships in the data
• Interact directly with the knowledge graph through a SPARQL query interface

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Image 3: Visualisation, querying and inference

Note: The asset is under Ongoing Development

Licence

This project is licensed under the MIT License.

Resources

• A live demo of this component can be found here
• The source code is available at the following GitHub repository
• Created by Software Competence Center Hagenberg - SCCH
• Contact jorge.martinez-gil@scch.at

Acknowledgement

This tool has been mainly developed in the frame of the project TrineFlex from the European Union’s Horizon Europe research and innovation programme under Grant Agreement No 101058174.