Open-Know-Where map of facilities and machinery - Data Management Repository

The Open-Know-Where map of facilities and machinery is a map of facilities developed by the Internet of Production Alliance IOPA.

This repository contains Jupyter notebooks designed for the collection and analysis of machinery and facilities data. The notebooks cover a range of topics, including data acquisition processes, machinery cataloging, and map visualization. These resources aim to provide comprehensive insights into the status and usability of machinery and facilities enabling distributed manufacturing.

Installation Instructions

To run the Jupyter notebooks locally, follow these simple steps:

Prerequisites

• Python: Ensure you have Python installed on your machine. You can download it from python.org.
• Jupyter Notebooks: Install Jupyter Notebooks using the following command in your terminal or command prompt:

pip install notebook

Cloning the Repository

Clone the Repository: Open your terminal or command prompt and navigate to the desired directory. Then, clone the repository using:

git clone https://github.com/iop-alliance/okw_data_management.git

Navigate to the Repository:

Move into the repository directory:

cd okw_data_management

Running Jupyter Notebooks

Launch Jupyter: Start the Jupyter Notebook server by running the following command:

jupyter notebook

Access Notebooks: Once the server is running, open your web browser and go to http://localhost:8888. You will see the Jupyter file browser.

Select a Notebook: Navigate to the "notebooks" directory and open the desired notebook (e.g., data_count.ipynb).

Run the Notebook:

Run the notebook cells one by one to execute the code.

Additional Notes

Make sure to read any specific instructions or dependencies mentioned within individual notebooks.

Repository Structure

notebooks/: Contains Jupyter notebooks for machinery and facilities data collection. data/: Placeholder for sample or generated data used in the notebooks. docs/: Store documents associated with the notebooks.

Feel free to explore, experiment, and contribute to enhance the capabilities of machinery and facilities data collection!

Licensing

• License: CCBY4.0 Creative Commons 2024
• Author: Antonio de Jesus Anaya Hernandez, DevOps Engineer.
• Author: The Internet of Production Alliance