| Acronym | OBEST |
| Visibility | Public |
| Description | The Ontology of Bioethics and Ethics of Science & Technology (OBEST) is an ontology that examines moral and ethical norms, basic ethical principles and their application in biological research, and scientific and technological practices. This constitutes a significant research area within the field of Dialectics of Nature. |
| Status | Production |
| Format | OWL |
| Categories | |
| Groups |
| Abstract |
As an interdisciplinary field, OBEST establishes a value-based framework for scientific and technological decision-making by analyzing the ethical impact of technological activities on humans and human society. It encompasses a comprehensive research system, including foundational theories, applied ethics, and policy and regulations. The research scope includes:
1.Societal Impact of Technological Application: Addressing socio-moral controversies arising from the implementation of technology.
2.Break down ethical barriers to fields and technologies: Explores fundamental frameworks and basic ethical principles of bioethics & science and technology ethics in the big data era, based on clarifying the logical relationship between bioethics and Science & technology ethics.
3.Ethical Frameworks for Science and Technology Policy: Focusing on ethical considerations in policy formulation global and local.
4.Practical ethics for frontier fields: Explore special requirements of basic principles application in bioethics, data ethics, and AI ethics based on the objectives and technological features. Explore ethical review strategies and key points in difference science and technology fields.
5.Standardizes ethical terminology, regulates cutting-edge technological development and corresponding ethical advancements—including ethical standards, research methodologies, and capacity-building, such as gene editing and generative artificial intelligence.
6.Establishing semantic norms for frontier bioethics and research ethics driven by digitalization, big data, and artificial intelligence. Provides a human-machine consensus foundation for interdisciplinary science & technology ethics, addressing challenges such as semantic tracking in large language models' training and generation processes, while facilitating international collaboration.
Initially, we focused on bioethics and data ethics. This is open for supplement and revision, please join us. Email: [email protected]
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| Contact | Jian Guan (关健) ([email protected]) Jiangan Xie (谢江安) ([email protected]) |
| Creation date | November 5, 2025
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| Deprecated |
false
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| Homepage |
https://github.com/OBEST-ontology/OBEST
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| License | 
|
| Modification date | November 6, 2025
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| Natural language |
English
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| Notes |
As an interdisciplinary field, OBEST establishes a value-based framework for scientific and technological decision-making by analyzing the ethical impact of technological activities on humans and human society. It encompasses a comprehensive research system, including foundational theories, applied ethics, and policy and regulations. The research scope includes:
1.Societal Impact of Technological Application: Addressing socio-moral controversies arising from the implementation of technology.
2.Break down ethical barriers to fields and technologies: Explores fundamental frameworks and basic ethical principles of bioethics & science and technology ethics in the big data era, based on clarifying the logical relationship between bioethics and Science & technology ethics.
3.Ethical Frameworks for Science and Technology Policy: Focusing on ethical considerations in policy formulation global and local.
4.Practical ethics for frontier fields: Explore special requirements of basic principles application in bioethics, data ethics, and AI ethics based on the objectives and technological features. Explore ethical review strategies and key points in difference science and technology fields.
5.Standardizes ethical terminology, regulates cutting-edge technological development and corresponding ethical advancements—including ethical standards, research methodologies, and capacity-building, such as gene editing and generative artificial intelligence.
6.Establishing semantic norms for frontier bioethics and research ethics driven by digitalization, big data, and artificial intelligence. Provides a human-machine consensus foundation for interdisciplinary science & technology ethics, addressing challenges such as semantic tracking in large language models' training and generation processes, while facilitating international collaboration.
Initially, we focused on bioethics and data ethics. This is open for supplement and revision, please join us. Email: [email protected]
See more...
|
| Object creation date property | |
| Object modification date property | |
| Subject |
https://data.bioontology.org/categories/Human
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https://data.bioontology.org/categories/Other
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https://data.bioontology.org/categories/Health
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https://data.bioontology.org/categories/Biomedical_Resources
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https://data.bioontology.org/categories/Development
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| Submission date | November 5, 2025
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| Version information |
1.0.1
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| uri |