A human rights approach to an international code of conduct for genomic and clinical data sharing

Fostering data sharing is a scientific and ethical imperative. Health gains can be achieved more comprehensively and quickly by combining large, information-rich datasets from across conventionally siloed disciplines and geographic areas. While collaboration for data sharing is increasingly embraced by policymakers and the international biomedical community, we lack a common ethical and legal framework to connect regulators, funders, consortia, and research projects so as to facilitate genomic and clinical data linkage, global science collaboration, and responsible research conduct. Governance tools can be used to responsibly steer the sharing of data for proper stewardship of research discovery, genomics research resources, and their clinical applications. In this article, we propose that an international code of conduct be designed to enable global genomic and clinical data sharing for biomedical research. To give this proposed code universal application and accountability, however, we propose to position it within a human rights framework. This proposition is not without precedent: international treaties have long recognized that everyone has a right to the benefits of scientific progress and its applications, and a right to the protection of the moral and material interests resulting from scientific productions. It is time to apply these twin rights to internationally collaborative genomic and clinical data sharing.     

To share or not to share: Incentivizing data sharing in life science communities

Most scientists recognize the importance of sharing data online in an open fashion. Nonetheless, many studies have documented the concerns that accompany data sharing activities, including loss of credit or IP, misuse and the time needed to curate interoperable data. To this end, discussions around data sharing often identify incentives that could potentially ameliorate these disincentivising concerns. Nonetheless, current Open Data discussions often rely on evidence‐based studies to identify the disincentives to overcome. This results in highly specific and directed interventions. In contrast, this paper offers a different interpretation of these concerns. To do so, it makes use of the Thomas Theorem which suggests that: “If men define situations as real, they are real in their consequences”. Using empirical evidence from sub‐Saharan African (bio)chemistry laboratories, this paper illustrates how individual perceptions of research environments – whether associated with evidence or not – are highly influential in shaping data sharing practices. It concludes with the suggestion that discussion on incentivising data sharing amongst scientific communities need to take a broader set of concerns into account and offer a more creative approach to ameliorating environmental disincentives.     

Mine, yours, ours? Sharing data on human genetic variation

The achievement of a robust, effective and responsible form of data sharing is currently regarded as a priority for biological and bio-medical research. Empirical evaluations of data sharing may be regarded as an indispensable first step in the identification of critical aspects and the development of strategies aimed at increasing availability of research data for the scientific community as a whole. Research concerning human genetic variation represents a potential forerunner in the establishment of widespread sharing of primary datasets. However, no specific analysis has been conducted to date in order to ascertain whether the sharing of primary datasets is common-practice in this research field. To this aim, we analyzed a total of 543 mitochondrial and Y chromosomal datasets reported in 508 papers indexed in the Pubmed database from 2008 to 2011. A substantial portion of datasets (21.9%) was found to have been withheld, while neither strong editorial policies nor high impact factor proved to be effective in increasing the sharing rate beyond the current figure of 80.5%. Disaggregating datasets for research fields, we could observe a substantially lower sharing in medical than evolutionary and forensic genetics, more evident for whole mtDNA sequences (15.0% vs 99.6%). The low rate of positive responses to e-mail requests sent to corresponding authors of withheld datasets (28.6%) suggests that sharing should be regarded as a prerequisite for final paper acceptance, while making authors deposit their results in open online databases which provide data quality control seems to provide the best-practice standard. Finally, we estimated that 29.8% to 32.9% of total resources are used to generate withheld datasets, implying that an important portion of research funding does not produce shared knowledge. By making the scientific community and the public aware of this important aspect, we may help popularize a more effective culture of data sharing.     

Bioinformatics for glycomics: status, methods, requirements and perspectives

The term 'glycomics' describes the scientific attempt to identify and study all the glycan molecules - the glycome - synthesised by an organism. The aim is to create a cell-by-cell catalogue of glycosyltransferase expression and detected glycan structures. The current status of databases and bioinformatics tools, which are still in their infancy, is reviewed. The structures of glycans as secondary gene products cannot be easily predicted from the DNA sequence. Glycan sequences cannot be described by a simple linear one-letter code as each pair of monosaccharides can be linked in several ways and branched structures can be formed. Few of the bioinformatics algorithms developed for genomics/proteomics can be directly adapted for glycomics. The development of algorithms, which allow a rapid, automatic interpretation of mass spectra to identify glycan structures is currently the most active field of research. The lack of generally accepted ways to normalise glycan structures and exchange glycan formats hampers an efficient cross-linking and the automatic exchange of distributed data. The upcoming glycomics should accept that unrestricted dissemination of scientific data accelerates scientific findings and initiates a number of new initiatives to explore the data.     

The Data Governance Act and the EU's move towards facilitating data sharing

The implementation of the EU General Data Protection Regulation (GDPR) has had significant impacts on biomedical research, often complicating data sharing among researchers. The recently announced proposal for a new EU Data Governance Act is a promising step towards facilitating data sharing, if it can interplay well with the GDPR.Subject Categories: S&S: Ethics

The EU General Data Protection Regulation (GDPR) has affected biomedical research, often complicating data sharing. The recently announced proposal for a new EU Data Governance Act, is a promising step towards facilitating data sharing.

In an attempt to improve and increase data sharing in the EU and to optimize the re‐use of personal and non‐personal data, the European Commission has recently announced the proposal for a new EU Data Governance Act (https://ec.europa.eu/digital‐single‐market/en/news/proposal‐regulation‐european‐data‐governance‐data‐governance‐act). If approved, it will enable the creation and regulation of “secure spaces” where various types of data, including health data, can be shared and re‐used for both commercial and altruistic purposes, including scientific research. The Data Governance Act, within the framework of a European Strategy for Data, (https://ec.europa.eu/info/sites/info/files/communication‐european‐strategy‐dat‐19feb2020_en.pdf), would address some of the shortcomings and drawbacks of the current regulatory framework which holds back sharing and re‐using data for biomedical research purposes.While the proposed Act would apply to all types of personal and non‐personal data, the increasing demand for sharing health data has most likely been a major rationale for this new legislation of data governance. Notably, sharing health and genetic data for scientific research entails an extra layer of complexity, owing to concerns over data protection and privacy when sharing sensitive personal data. Vice versa, there are also concerns in the scientific community over the negative impact of regulatory restrictions on sharing health data in data‐driven biomedical research. The pressing question here is how far the EU’s proposed legislative and policy framework can offset either concerns?     

A review of biology,fisheries and population structure of Dentex dentex (Sparidae)

The common dentex Dentex dentex (Linnaeus, 1758) is an iconic marine coastal fish in the Mediterranean Sea. It is a demersal sparid fish (0–200 m), that grows to a maximum length of 100 cm and a weight of 13 kg, with a relatively long life span (more than 20 years). As a high trophic level predator, it holds a key position in coastal marine food webs. The common dentex is of great economic importance for both artisanal (small-scale coastal fisheries) and recreational fishing. Despite its economic and ecological importance, scientific data on this species in its natural environment are still very scant. The global commercial catch of common dentex has fluctuated over the last 60 years on an interannual time scale, and has declined significantly since the 1990s. There are few data regarding fishing effort and total catch from recreational fishing for common dentex, but it appears that this species is particularly targeted by this activity. The common dentex is now classified as “vulnerable” in the Red List of Threatened Species in the Mediterranean Sea. This review summarizes the current literature on D. dentex in regard to biology, ecology, parasitology, population structure, commercial and recreational fishing, and management regulations. Future research directions to fill gaps in current knowledge are suggested.     

The use of electronic monitoring within tuna longline fisheries: implications for international data collection,analysis and reporting

Electronic monitoring (EM) consisting of on-board video imagery and on-shore analysis, offers an alternative or supplement to at-sea observer programs in commercial fisheries. In the western and central Pacific Ocean (WCPO), where observer coverage in most tuna longline fisheries has historically been?<?5%, the advent of EM has been perceived as a tool for meeting international data collection and exchange obligations. However, the capability of EM to collect and support interpretation of records into data for all fields currently collected by at-sea observers is still under assessment. We use the Western and Central Pacific Fisheries Commission (WCPFC) as a case-study to evaluate the longline WCPFC regional observer programme minimum standard data fields, their current scientific application, the proportion of member countries exchanging data and the capability of EM technology to collect these fields. We identify that 78% of the longline fields can be collected with current EM technology, with 84% of these used in scientific analyses. For the 16% of fields not routinely used in scientific analyses, the introduction of EM may facilitate a sufficient increase in data availability to support their future use. Alternative tools would be required to collect fields that EM could not record to ensure data continuity and scientific rigour are not compromised. In examining the capability of EM in the context of WCPFC member state requirements under international law, we advocate for a holistic and integrated approach to the use of EM in future research and monitoring programs in both the WCPO and global longline fisheries.     

The data‐index: An author‐level metric that values impactful data and incentivizes data sharing

Author‐level metrics are a widely used measure of scientific success. The h‐index and its variants measure publication output (number of publications) and research impact (number of citations). They are often used to influence decisions, such as allocating funding or jobs. Here, we argue that the emphasis on publication output and impact hinders scientific progress in the fields of ecology and evolution because it disincentivizes two fundamental practices: generating impactful (and therefore often long‐term) datasets and sharing data. We describe a new author‐level metric, the data‐index, which values both dataset output (number of datasets) and impact (number of data‐index citations), so promotes generating and sharing data as a result. We discuss how it could be implemented and provide user guidelines. The data‐index is designed to complement other metrics of scientific success, as scientific contributions are diverse and our value system should reflect that both for the benefit of scientific progress and to create a value system that is more equitable, diverse, and inclusive. Future work should focus on promoting other scientific contributions, such as communicating science, informing policy, mentoring other scientists, and providing open‐access code and tools.     

国家级生物大数据中心展望

大数据时代下,科学大数据已经成为科技创新和社会经济发展的新动力。我国是生物数据生产大国,生命大数据是人口健康和国家安全的重要战略资源。面对我国生物数据因存储零散、缺乏系统监管而大量丢失和流失,以及严重依赖国际生物组学大数据中心的局面,亟需从国家层面建设我国自己的生命大数据保存和管理体系。本文以美国NCBI为例介绍了国际生物大数据中心的发展历程及现状,阐明我国建立国家级生物大数据中心的重要性、迫切性、当前历史机遇和发展前景。中国科学院北京基因组研究所生命与健康大数据中心为此做了大量努力,并在数据存储、汇交和转化应用上取得了阶段性成果,以期推进我国生物大数据中心的建设,提高生命科学研究的国际竞争力和影响力。     

Integration of evidence across human and model organism studies: A meeting report

The National Institute on Drug Abuse and Joint Institute for Biological Sciences at the Oak Ridge National Laboratory hosted a meeting attended by a diverse group of scientists with expertise in substance use disorders (SUDs), computational biology, and FAIR (Findability, Accessibility, Interoperability, and Reusability) data sharing. The meeting's objective was to discuss and evaluate better strategies to integrate genetic, epigenetic, and 'omics data across human and model organisms to achieve deeper mechanistic insight into SUDs. Specific topics were to (a) evaluate the current state of substance use genetics and genomics research and fundamental gaps, (b) identify opportunities and challenges of integration and sharing across species and data types, (c) identify current tools and resources for integration of genetic, epigenetic, and phenotypic data, (d) discuss steps and impediment related to data integration, and (e) outline future steps to support more effective collaboration—particularly between animal model research communities and human genetics and clinical research teams. This review summarizes key facets of this catalytic discussion with a focus on new opportunities and gaps in resources and knowledge on SUDs.     

Databases and Web Tools for Cancer Genomics Study

Publicly-accessible resources have promoted the advance of scientific discovery. The era of genomics and big data has brought the need for collaboration and data sharing in order to make effective use of this new knowledge. Here, we describe the web resources for cancer genomics research and rate them on the basis of the diversity of cancer types, sample size, omics data comprehensiveness, and user experience. The resources reviewed include data repository and analysis tools; and we hope such introduction will promote the awareness and facilitate the usage of these resources in the cancer research community.     

生物多样性数据共享和发表: 进展和建议

生物多样性研究、保护实践、自然资源管理及科学决策等越来越依赖于大量数据的共享和整合。虽然关于数据共享的呼吁和实践越来越多, 但很多科学家仍然主动或被动地拒绝共享数据。关于数据共享, 现实中存在一些认知和技术上的障碍, 比如科学家不愿意共享数据, 担心同行竞争, 认为缺少足够的回报, 不熟悉相关数据保存机构, 缺少简便的数据提交工具, 没有足够时间和经费等。解决这些问题及改善共享文化的关键在于使共享者获得适当的回报(比如数据引用)。基于同行评审的数据发表被认为不但能够为生产、管理和共享数据的科学家提供一种激励机制, 并且能够有效地促进数据再利用。因而, 数据发表作为数据共享的方式之一, 近来引起了较多关注, 在生物多样性领域出现了专门发表数据论文的期刊。在采取数据论文的模式上, 数据保存机构和科技期刊采用联合数据政策在促进数据共享方面可能更具可行性。本文总结了数据共享和发表方面的进展, 讨论了数据论文能在何种程度上促进数据共享, 以及数据共享和数据发表的关系等问题, 提出如下建议: (1)个体科学家应努力践行数据共享; (2)使用DOI号解决数据所有权和数据引用的问题; (3)科技期刊和数据保存机构联合采用更加合理和严格的数据保存政策; (4)资助机构和研究单位应当在数据共享中起到更重要的作用。     

Unpublished genomic data–how to share?

The field of genomics is often cited as the branch of biology that has led the way in data sharing. In most cases, sequencing data are made publicly available immediately after generation and often before the data generators have completed their analyses. Although the pros of such openness cannot be denied, problems can arise when unpublished genomic data are shared. In this editorial we touch on these issues and discuss the roles and responsibilities of the data generators, data users and journal editors.     

基于文献计量的生态系统观测研究网络长期观测数据应用研究

基于CNKI数据库,采用文献计量和知识图谱的方法,通过对应用生态系统观测研究网络长期定位观测数据的文献进行分析,探讨长期观测数据的应用领域、具体用途、用户特点及不同生态站数据的应用状况与研究主题,以期为提高生态系统观测研究网络长期观测数据的共享服务能力、充分发挥长期观测数据的价值提供参考。分析结果表明:生态系统观测研究网络长期观测数据受到越来越多学者的关注,其应用学科领域以林业、农业基础科学为主,同时不断扩展到其他学科中,呈多元化态势;数据主要在生态系统服务研究、模型模拟、人工林研究、水污染研究、生物多样性研究、小麦玉米研究、土壤水分研究等方面发挥作用;数据的主要用户群体为高等院校和科研院所,不同机构应用长期观测数据开展的研究各有侧重;各生态站的长期观测数据能够为揭示其所代表生态区和生态系统类型的生态系统结构与功能、能量流动与养分循环的变化规律,分析主要生态环境问题的现状、动态变化及驱动机制等方面提供重要支撑。最后,对生态系统观测研究网络长期观测数据应用的相关方面提出几点建议:(1)健全数据引用机制,制定相应的科学数据引用和著录标准;(2)发挥生态网络长期观测数据优势,开展专题数据产品的生产,充分开发生态网络长期观测数据的潜在价值;(3)加大和稳定生态站的经费投入,提高生态站的观测能力和水平,同时还要完善、优化生态站布局。     

When Data Sharing Gets Close to 100%: What Human Paleogenetics Can Teach the Open Science Movement

This study analyzes data sharing regarding mitochondrial, Y chromosomal and autosomal polymorphisms in a total of 162 papers on ancient human DNA published between 1988 and 2013. The estimated sharing rate was not far from totality (97.6% ± 2.1%) and substantially higher than observed in other fields of genetic research (evolutionary, medical and forensic genetics). Both a questionnaire-based survey and the examination of Journals’ editorial policies suggest that this high sharing rate cannot be simply explained by the need to comply with stakeholders requests. Most data were made available through body text, but the use of primary databases increased in coincidence with the introduction of complete mitochondrial and next-generation sequencing methods. Our study highlights three important aspects. First, our results imply that researchers’ awareness of the importance of openness and transparency for scientific progress may complement stakeholders’ policies in achieving very high sharing rates. Second, widespread data sharing does not necessarily coincide with a prevalent use of practices which maximize data findability, accessibility, useability and preservation. A detailed look at the different ways in which data are released can be very useful to detect failures to adopt the best sharing modalities and understand how to correct them. Third and finally, the case of human paleogenetics tells us that a widespread awareness of the importance of Open Science may be important to build reliable scientific practices even in the presence of complex experimental challenges.     

Hippocrates revisited? Old ideals and new realities

Individual genomics has arrived, personal decisions to make use of it are a new reality. What are the implications for the patient-physician relationship? In this article we address three factors that call the traditional concept of confidentiality into question. First, the illusion of absolute data safety, as shown by medical informatics. Second, data sharing as a standard practice in genomics research. Comprehensive data sets are widely accessible. Third, genotyping has become a service that is directly available to consumers. The availability and accessibility of personal health data strongly suggest that the roles in the clinical encounter need to be remodeled. The old ideal of physicians as keepers of confidential information is outstripped by the reality of individuals who decide themselves about the way of using their data.     

Toward Reproducible Computational Research: An Empirical Analysis of Data and Code Policy Adoption by Journals

Journal policy on research data and code availability is an important part of the ongoing shift toward publishing reproducible computational science. This article extends the literature by studying journal data sharing policies by year (for both 2011 and 2012) for a referent set of 170 journals. We make a further contribution by evaluating code sharing policies, supplemental materials policies, and open access status for these 170 journals for each of 2011 and 2012. We build a predictive model of open data and code policy adoption as a function of impact factor and publisher and find higher impact journals more likely to have open data and code policies and scientific societies more likely to have open data and code policies than commercial publishers. We also find open data policies tend to lead open code policies, and we find no relationship between open data and code policies and either supplemental material policies or open access journal status. Of the journals in this study, 38% had a data policy, 22% had a code policy, and 66% had a supplemental materials policy as of June 2012. This reflects a striking one year increase of 16% in the number of data policies, a 30% increase in code policies, and a 7% increase in the number of supplemental materials policies. We introduce a new dataset to the community that categorizes data and code sharing, supplemental materials, and open access policies in 2011 and 2012 for these 170 journals.     

Atlantic salmon (Salmo salar L.) genetics in the 21st century: taking leaps forward in aquaculture and biological understanding

Atlantic salmon (Salmo salar L.) is among the most iconic and economically important fish species and was the first member of Salmonidae to have a high‐quality reference genome assembly published. Advances in genomics have become increasingly central to the genetic improvement of farmed Atlantic salmon as well as conservation of wild salmon stocks. The salmon genome has also been pivotal in shaping our understanding of the evolutionary and functional consequences arising from an ancestral whole‐genome duplication event characterising all Salmonidae members. Here, we provide a review of the current status of Atlantic salmon genetics and genomics, focussed on progress made from genome‐wide research aimed at improving aquaculture production and enhancing understanding of salmonid ecology, physiology and evolution. We present our views on the future direction of salmon genomics, including the role of emerging technologies (e.g. genome editing) in elucidating genetic features that underpin functional variation in traits of commercial and evolutionary importance.     

GOing from functional genomics to biological significance

The chicken genome is sequenced and this, together with microarray and other functional genomics technologies, makes post-genomic research possible in the chicken. At this time, however, such research is hindered by a lack of genomic structural and functional annotations. Bio-ontologies have been developed for different annotation requirements, as well as to facilitate data sharing and computational analysis, but these are not yet optimally utilized in the chicken. Here we discuss genomic annotation and bio-ontologies. We focus specifically on the Gene Ontology (GO), chicken GO annotations and how these can facilitate functional genomics in the chicken. The GO is the most developed and widely used bio-ontology. It is the de facto standard for functional annotation. Despite its critical importance in analyzing microarray and other functional genomics data, relatively few chicken gene products have any GO annotation. When these are available, the average quality of chicken gene products annotations (defined using evidence code weight and annotation depth) is much less than in mouse. Moreover, tools allowing chicken researchers to easily and rapidly use the GO are either lacking or hard to use. To address all of these problems we developed ChickGO and AgBase. Chicken GO annotations are provided by complementary work at MSU-AgBase and EBI-GOA. The GO tools pipeline at AgBase uses GO to derive functional and biological significance from microarray and other functional genomics data. Not only will improved genomic annotation and tools to use these annotations benefit the chicken research community but they will also facilitate research in other avian species and comparative genomics.