Responsible Data Governance of Neuroscience Big Data

Open access article.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)

Routes for breaching and protecting genetic privacy

We are entering the era of ubiquitous genetic information for research, clinical care, and personal curiosity. Sharing these datasets is vital for rapid progress in understanding the genetic basis of human diseases. However, one growing concern is the ability to protect the genetic privacy of the data originators. Here, we technically map threats to genetic privacy and discuss potential mitigation strategies for privacy-preserving dissemination of genetic data.Comment: Draft for comment

Health technology assessment in Switzerland : a descriptive analysis of “coverage with evidence development” decisions from 1996 to 2013

OBJECTIVES: To identify factors associated with the decisions of the Federal Department of Home Affairs concerning coverage with evidence development (CED) for contested novel medical technologies in Switzerland. DESIGN: Quantitative, retrospective, descriptive analysis of publicly available material and prospective, structured, qualitative interviews with key stakeholders. SETTING: All 152 controversial medical services decided on by the Federal Commission on Health Insurance Benefits within the framework of the new federal law on health insurance in Switzerland from 1997 to 2013, with focus on 33 technologies assigned initially to CED and 33 to evidence development without coverage. MAIN OUTCOME MEASURES: Factors associated with numbers and type of contested services assigned to CED per year, the duration and final outcome of the evaluations and perceptions of key stakeholders. RESULTS: The rate of CED decisions (82 total; median 1.5/year; range 0–9/year), the time to final decision (4.5 years median; 0.75 to +11 years) and the probability of a final ‘yes’ varied over time. In logistic regression models, the change of office of the commission provided the best explanation for the observed outcomes. Good intentions but absence of scientific criteria for decisions were reported as major comments by the stakeholders. CONCLUSIONS: The introduction of CED enabled access to some promising technologies early in their life cycle, and might have triggered establishment of registries and research. Impact on patients’ outcome and costs remain unknown. The primary association of institutional changes with measured end points illustrates the need for evaluation of the current health technology assessment (HTA) system

Rare diseases: matching wheelchair users with rare metabolic, neuromuscular or neurological disorders to electric powered indoor/outdoor wheelchairs (EPIOCs)

Purpose: To describe the clinical features of electric powered indoor/outdoor wheelchair (EPIOC) users with rare diseases (RD) impacting on EPIOC provision and seating. Method: Retrospective review by a consultant in rehabilitation medicine of electronic and case note records of EPIOC recipients with RDs attending a specialist wheelchair service between June 2007 and September 2008. Data were systematically extracted, entered into a database and analysed under three themes; demographic, diagnostic/clinical (including comorbidity and associated clinical features (ACFs) of the illness/disability) and wheelchair factors. Results: Fifty-four (27 male) EPIOC users, mean age 37.3 (SD 18.6, range 11–70) with RDs were identified and reviewed a mean of 64 (range 0–131) months after receiving their wheelchair. Diagnoses included 27 types of RDs including Friedreich’s ataxia, motor neurone disease, osteogenesis imperfecta, arthrogryposis, cerebellar syndromes and others. Nineteen users had between them 36 comorbidities and 30 users had 44 ACFs likely to influence the prescription. Tilt-in-space was provided to 34 (63%) users and specialised seating to 17 (31%). Four users had between them complex control or interfacing issues. Conclusions: The complex and diverse clinical problems of those with RDs present unique challenges to the multiprofessional wheelchair team to maintain successful independent mobility and community living

A Simple Standard for Sharing Ontological Mappings (SSSOM).

Despite progress in the development of standards for describing and exchanging scientific information, the lack of easy-to-use standards for mapping between different representations of the same or similar objects in different databases poses a major impediment to data integration and interoperability. Mappings often lack the metadata needed to be correctly interpreted and applied. For example, are two terms equivalent or merely related? Are they narrow or broad matches? Or are they associated in some other way? Such relationships between the mapped terms are often not documented, which leads to incorrect assumptions and makes them hard to use in scenarios that require a high degree of precision (such as diagnostics or risk prediction). Furthermore, the lack of descriptions of how mappings were done makes it hard to combine and reconcile mappings, particularly curated and automated ones. We have developed the Simple Standard for Sharing Ontological Mappings (SSSOM) which addresses these problems by: (i) Introducing a machine-readable and extensible vocabulary to describe metadata that makes imprecision, inaccuracy and incompleteness in mappings explicit. (ii) Defining an easy-to-use simple table-based format that can be integrated into existing data science pipelines without the need to parse or query ontologies, and that integrates seamlessly with Linked Data principles. (iii) Implementing open and community-driven collaborative workflows that are designed to evolve the standard continuously to address changing requirements and mapping practices. (iv) Providing reference tools and software libraries for working with the standard. In this paper, we present the SSSOM standard, describe several use cases in detail and survey some of the existing work on standardizing the exchange of mappings, with the goal of making mappings Findable, Accessible, Interoperable and Reusable (FAIR). The SSSOM specification can be found at http://w3id.org/sssom/spec. Database URL: http://w3id.org/sssom/spec

SeqCode: a nomenclatural code for prokaryotes described from sequence data

Most prokaryotes are not available as pure cultures and therefore ineligible for naming under the rules and recommendations of the International Code of Nomenclature of Prokaryotes (ICNP). Here we summarize the development of the SeqCode, a code of nomenclature under which genome sequences serve as nomenclatural types. This code enables valid publication of names of prokaryotes based upon isolate genome, metagenome-assembled genome or single-amplified genome sequences. Otherwise, it is similar to the ICNP with regard to the formation of names and rules of priority. It operates through the SeqCode Registry (https://seqco.de/), a registration portal through which names and nomenclatural types are registered, validated and linked to metadata. We describe the two paths currently available within SeqCode to register and validate names, including Candidatus names, and provide examples for both. Recommendations on minimal standards for DNA sequences are provided. Thus, the SeqCode provides a reproducible and objective framework for the nomenclature of all prokaryotes regardless of cultivability and facilitates communication across microbiological disciplines.Funding was provided by the US National Science Foundation (DEB 1841658, DEB 1557042 and EAR 1516680) to B.H., A.-L.R. and A.M.; the US National Institute of General Medical Sciences (GM103440) from the National Institutes of Health to B.H.; the Spanish Ministry of Science, Innovation and Universities (PGC2018-096956-B-C41 and PID2021-126114NB-C42) to R.R.; the Australian Research Council (FL150100038) to P.H.; the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, SFB 1439/1 2021—426547801) and European Regional Development Funds (FEDER) to A.P.; and the International Society for Microbial Ecology (ISME) to all authors