是时候考虑动物数据治理了:从神经科学的角度来看。

IF 2.5 4区 医学 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Frontiers in Neuroinformatics Pub Date : 2023-08-29 eCollection Date: 2023-01-01 DOI:10.3389/fninf.2023.1233121
Damian Eke, George Ogoh, William Knight, Bernd Stahl
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引用次数: 0

摘要

引言:科学研究主要依赖于动物和人类有机体产生的多模式、多维大数据以及技术数据。然而,与国家、区域和国际层面日益监管的人类数据不同,能够管理非人类动物数据共享和重复使用的监管框架尚未建立。尽管许多国家和地区形成动物数据生成的法律和伦理原则各不相同,但生成的数据是在没有任何治理机制的情况下跨境共享的。本文从神经科学的角度,从概念和经验上表明,有必要对动物数据进行伦理治理。关于在科学研究中使用动物,数据治理机制需要考虑多种伦理观点。方法:采用半结构化访谈法进行数据收集。总共对12名参与者(10名男性和2名女性)进行了13次访谈。访谈被转录并存储在NviVo 12中,在那里进行主题分析。结果:参与者一致认为,由于法规的差异、伦理原则、价值观和信仰的差异以及数据质量问题等因素,现在是考虑动物数据治理的时候了。他们还就治理的可能方法提供了见解。讨论:因此,我们得出结论,数据治理需要一种程序性方法:这种方法不规定特定的道德立场,但允许快速理解道德问题,并就不同立场的差异进行辩论,以促进跨文化和国际合作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Time to consider animal data governance: perspectives from neuroscience.

Introduction: Scientific research relies mainly on multimodal, multidimensional big data generated from both animal and human organisms as well as technical data. However, unlike human data that is increasingly regulated at national, regional and international levels, regulatory frameworks that can govern the sharing and reuse of non-human animal data are yet to be established. Whereas the legal and ethical principles that shape animal data generation in many countries and regions differ, the generated data are shared beyond boundaries without any governance mechanism. This paper, through perspectives from neuroscience, shows conceptually and empirically that there is a need for animal data governance that is informed by ethical concerns. There is a plurality of ethical views on the use of animals in scientific research that data governance mechanisms need to consider.

Methods: Semi-structured interviews were used for data collection. Overall, 13 interviews with 12 participants (10 males and 2 females) were conducted. The interviews were transcribed and stored in NviVo 12 where they were thematically analyzed.

Results: The participants shared the view that it is time to consider animal data governance due to factors such as differences in regulations, differences in ethical principles, values and beliefs and data quality concerns. They also provided insights on possible approaches to governance.

Discussion: We therefore conclude that a procedural approach to data governance is needed: an approach that does not prescribe a particular ethical position but allows for a quick understanding of ethical concerns and debate about how different positions differ to facilitate cross-cultural and international collaboration.

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来源期刊
Frontiers in Neuroinformatics
Frontiers in Neuroinformatics MATHEMATICAL & COMPUTATIONAL BIOLOGY-NEUROSCIENCES
CiteScore
4.80
自引率
5.70%
发文量
132
审稿时长
14 weeks
期刊介绍: Frontiers in Neuroinformatics publishes rigorously peer-reviewed research on the development and implementation of numerical/computational models and analytical tools used to share, integrate and analyze experimental data and advance theories of the nervous system functions. Specialty Chief Editors Jan G. Bjaalie at the University of Oslo and Sean L. Hill at the École Polytechnique Fédérale de Lausanne are supported by an outstanding Editorial Board of international experts. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics and the public worldwide. Neuroscience is being propelled into the information age as the volume of information explodes, demanding organization and synthesis. Novel synthesis approaches are opening up a new dimension for the exploration of the components of brain elements and systems and the vast number of variables that underlie their functions. Neural data is highly heterogeneous with complex inter-relations across multiple levels, driving the need for innovative organizing and synthesizing approaches from genes to cognition, and covering a range of species and disease states. Frontiers in Neuroinformatics therefore welcomes submissions on existing neuroscience databases, development of data and knowledge bases for all levels of neuroscience, applications and technologies that can facilitate data sharing (interoperability, formats, terminologies, and ontologies), and novel tools for data acquisition, analyses, visualization, and dissemination of nervous system data. Our journal welcomes submissions on new tools (software and hardware) that support brain modeling, and the merging of neuroscience databases with brain models used for simulation and visualization.
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