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:

@Inbook{Hoch2024,
	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",
	editor="Soldatos, John",
	title="Multi-Stakeholder Perspective on Human-AI Collaboration in Industry 5.0",
	bookTitle="Artificial Intelligence in Manufacturing: Enabling Intelligent, Flexible and Cost-Effective Production Through AI",
	year="2024",
	publisher="Springer Nature Switzerland",
	address="Cham",
	pages="407--421",
	isbn="978-3-031-46452-2",
	doi="10.1007/978-3-031-46452-2_23",
	url="https://doi.org/10.1007/978-3-031-46452-2_23"
}

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