Collaborative Intelligence Component

Overview

This project consists of a web-based application designed to demonstrate a collaborative intelligence component. It's an industrial pilot that showcases the functionalities of data visualization and manipulation using HTML, CSS, and JavaScript.

Features

• Display of data in a table format.
• Data loading from a CSV file.
• Dynamic interaction with data (e.g., filtering and status updating).
• Custom CSS styling for a pleasant user interface.
• Use of Google Fonts for typography.
• Interactive chart for data visualization.

Structure

• HTML: The HTML file contains the basic structure of the web page, including headers, a table for displaying data, and a section for charts.
• CSS: The CSS within the <style> tag in the HTML head provides custom styling for the web page, including fonts, colors, and layout designs.
• JavaScript: The script at the end of the body handles data loading, parsing, and dynamic updating of the table and chart.

Usage

1. Viewing the Page: Open the HTML file in a web browser to view the interface.
2. Loading Data: Click on the 'Load CSV' button to upload and display data from a CSV file.
3. Interacting with Data: Use radio buttons to change the score types and interact with the data in the table.
4. Printing Non-OK Rows: Click on 'Print Non-OK Rows to File' to save rows with a non-OK status to a file.

Customization

• Styling: Modify the CSS in the <style> tag to customize the look and feel of the web page.
• Data Handling: Adjust the JavaScript functions to change how data is loaded, parsed, and displayed.

Requirements

• A modern web browser.
• A CSV file for data upload.

Citation

For academic use, please refer to our work:

@incollection{hoch2023multi,
  title={Multi-Stakeholder Perspective on Human-AI Collaboration in Industry 5.0},
  author={Hoch, Thomas and Martinez-Gil, Jorge and Pichler, Mario and Silvina, Agastya and Heinzl, Bernhard and Moser, Bernhard and Eleftheriou, Dimitris and Estrada-Lugo, Hector Diego and Leva, Maria Chiara},
  booktitle={Artificial Intelligence in Manufacturing: Enabling Intelligent, Flexible and Cost-Effective Production Through AI},
  pages={407--421},
  year={2023},
  publisher={Springer Nature Switzerland Cham}
}

Acknowledgement

This work is performed in the context of the AI REDGIO 5.0 “Regions and (E)DIHs alliance for AI-at-the-Edge adoption by European Industry 5.0 Manufacturing SMEs” EU Innovation Action Project under Grant Agreement No 101092069