Protection of Intellectual Property Rights for Data

DOI

10.2991/978-2-38476-475-4_136How to use a DOI?

Keywords

Data Protection; Intellectual Property; Copyright; Trade secrets

Abstract

In the era of big data, data has become a core production factor, but its immateriality, easy to copy and other characteristics make it difficult for the traditional property system to effectively protect it, and there are problems such as fragmented protection paths and complex disputes over ownership in judicial practice. This paper focuses on the intellectual property system and explores its applicability in data protection. It is found that copyright can provide legal support and scenario-based protection for data by protecting the collection of original data and the form of expression of derived data, but it is necessary to solve the problem of ambiguous standards of originality by clarifying the standards through legislation, expanding the scope of compilation works, and establishing a registration system, etc.; the trade secret path applies to the undisclosed core data, and it is necessary to optimise the confidentiality measures and standards, and to balance the security of data and the trade secret path applies to undisclosed core data and requires optimisation of confidentiality measures and standards, balancing data security and circulation.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yanying Chen
PY  - 2025
DA  - 2025/11/11
TI  - Protection of Intellectual Property Rights for Data
BT  - Proceedings of the 2025 10th International Conference on Modern Management, Education and Social Sciences (MMET 2025)
PB  - Atlantis Press
SP  - 1243
EP  - 1253
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-475-4_136
DO  - 10.2991/978-2-38476-475-4_136
ID  - Chen2025
ER  -