Data Management Plan for the LZP FLPP Project Optical Neural Networks Leveraging Synthetic Dimension (DIMENSION) (Nr. lzp-2024/1-0612)
Year: 2025
Type: article
Abstract: This DMP serves as a comprehensive guide for managing the data generated during the DIMENSION project. This project focuses on fundamental research of synthetic dimension physics. The DMP outlines how we will handle, store, share, and preserve the data collected, ensuring it supports the project's objectives and is accessible for future research and development. The DIMENSION project will generate and collect a variety of data crucial for advancing optical neural networks (ONNs) technology. Specifically, the datasets will include data sets used for training, validating, and testing ONNs. The data will also be stored in various formats, e.g., CSV. Data will be collected using sophisticated signal processing tools and optical measurement equipment. All data will be initially stored in raw format to ensure no initial data loss and then processed for analysis. In line with our commitment to advancing knowledge in the field of optical communications, the processed data will be made available to the research community. A dedicated data manager will oversee the implementation of this DMP, assisted by the project team. Responsibilities for data collection, processing, analysis, and sharing will be clearly defined within the project team to ensure adherence to the plan.
Author: Oskars Ozoliņš
Institution: Riga Technical University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6968517761
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