ArticleFrontiers in neuroinformatics2019
Responsible Data Governance of Neuroscience Big Data.
Article in Frontiers in neuroinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Which Framework to Use? A Systematic Review of Ethical Frameworks for the Screening or Evaluation of Health Technology Innovations.Science and engineering ethics · 2022Pooled it
- The ethical and legal landscape of brain data governance.PloS one · 2022Pooled it
- Reconciling global collaboration and data sovereignty in neuroscience.Nature neuroscience · 2026Review
- Construction of a Theoretical Framework for Scientific Data Governance.Scientific data · 2026Article
- Ethical Governance Strategies for the Responsible Innovation of Neurotechnologies: A Scoping Review.Journal of bioethical inquiry · 2025Article
- Real-world evidence to support health technology assessment and payer decision making: is it now or never?International journal of technology assessment in health care · 2025Article
- Reflections about Blockchain in Health Data Sharing: Navigating a Disruptive Technology.International journal of environmental research and public health · 2024Article
- Overview: Research on the Genetic Architecture of the Developing Cerebral Cortex in Norms and Diseases.Methods in molecular biology (Clifton, N.J.) · 2024Article
- The coming decade of digital brain research: A vision for neuroscience at the intersection of technology and computing.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- One hundred years of neurosciences in the arts and humanities, a bibliometric review.Philosophy, ethics, and humanities in medicine : PEHM · 2023Review
- The past, present and future of neuroscience data sharing: a perspective on the state of practices and infrastructure for FAIR.Frontiers in neuroinformatics · 2023Review
- The evolution of Big Data in neuroscience and neurology.Journal of big data · 2023Article
- Time to consider animal data governance: perspectives from neuroscience.Frontiers in neuroinformatics · 2023Article
- Towards an understanding of global brain data governance: ethical positions that underpin global brain data governance discourse.Frontiers in big data · 2023Article
- The role of artificial intelligence in paediatric neuroradiology.Pediatric radiology · 2022Review
- Article
- Artificial intelligence and Big Data in neurology.Arquivos de neuro-psiquiatria · 2022Article
- International data governance for neuroscience.Neuron · 2022Review
- Data Management Schema Design for Effective Nanoparticle Formulation for Neurotherapeutics.AIChE journal. American Institute of Chemical Engineers · 2021Article
- Research and Practice of AI Ethics: A Case Study Approach Juxtaposing Academic Discourse with Organisational Reality.Science and engineering ethics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Current discussions of the ethical aspects of big data are shaped by concerns regarding the social consequences of both the widespread adoption of machine learning and the ways in which biases in data can be replicated and perpetuated. We instead focus here on the ethical issues arising from the use of big data in international neuroscience collaborations. Neuroscience innovation relies upon neuroinformatics, large-scale data collection and analysis enabled by novel and emergent technologies. Each step of this work involves aspects of ethics, ranging from concerns for adherence to informed consent or animal protection principles and issues of data re-use at the stage of data collection, to data protection and privacy during data processing and analysis, and issues of attribution and intellectual property at the data-sharing and publication stages. Significant dilemmas and challenges with far-reaching implications are also inherent, including reconciling the ethical imperative for openness and validation with data protection compliance and considering future innovation trajectories or the potential for misuse of research results. Furthermore, these issues are subject to local interpretations within different ethical cultures applying diverse legal systems emphasising different aspects. Neuroscience big data require a concerted approach to research across boundaries, wherein ethical aspects are integrated within a transparent, dialogical data governance process. We address this by developing the concept of "responsible data governance," applying the principles of Responsible Research and Innovation (RRI) to the challenges presented by the governance of neuroscience big data in the Human Brain Project (HBP).
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.