Sharing biological data: why, when, and how.
Ontology highlight
ABSTRACT:
SUBMITTER: Wilson SL
PROVIDER: S-EPMC10390076 | biostudies-literature | 2021 Apr
REPOSITORIES: biostudies-literature
Publications
Sharing biological data: why, when, and how.
Wilson Samantha L SL Way Gregory P GP Bittremieux Wout W Armache Jean-Paul JP Haendel Melissa A MA Hoffman Michael M MM
FEBS letters 20210401 7
Similar Datasets
Project description:Rapid release of prepublication data has served the field of genomics well. Attendees at a workshop in Toronto recommend extending the practice to other biological data sets.
| S-EPMC3073843 | biostudies-literature
Project description:BackgroundMandates abound to share publicly-funded research data for reuse, while data platforms continue to emerge to facilitate such reuse. Birth cohorts (BC) involve longitudinal designs, significant sample sizes and rich and deep datasets. Data sharing benefits include more analyses, greater research complexity, increased opportunities for collaboration, amplification of public contributions, and reduced respondent burdens. Sharing BC data involves significant challenges including consent, privacy, access policies, communication, and vulnerability of the child. Research on these issues is available for biological data, but these findings may not extend to BC data. We lack consensus on how best to approach these challenges in consent, privacy, communication and autonomy when sharing BC data. We require more stakeholder engagement to understand perspectives and generate consensus.MethodsParents participating in longitudinal birth cohorts completed a web-based survey investigating consent preferences for sharing their, and their child's, non-biological research data. Results from a previous qualitative inquiry informed survey development, and cognitive interviewing methods (n = 9) were used to improve the question quality and comprehension. Recruitment was via personalized email, with email and phone reminders during the 14-day window for survey completion.ResultsThree hundred and forty-six of 569 parents completed the survey in September 2014 (60.8%). Participants preferred consent processes for data sharing in future independent research that were less-active (i.e. no consent or opt-out). Parents' consent preferences are associated with their communication preferences. Twenty percent (20.2%) of parents generally agreed that their child should provide consent to continue participating in research at age 12, while 25.6% felt decision-making on sharing non-biological research data should begin at age 18.ConclusionsThese finding reflect the parenting population's preference for less project-specific permission when research data is non-biological and de-identified and when governance practices are highly detailed and rigourous. Parents recognize that children should become involved in consent for secondary data use, but there is variability regarding when and how involvement occurs. These findings emphasize governance processes and participant notification rather than project-specific consent for secondary use of de-identified, non-biological data. Ultimately, parents prefer general consent processes for sharing de-identified, non-biological research data with ultimate involvement of the child.
| S-EPMC6233367 | biostudies-literature
Project description:Escher is a web application for visualizing data on biological pathways. Three key features make Escher a uniquely effective tool for pathway visualization. First, users can rapidly design new pathway maps. Escher provides pathway suggestions based on user data and genome-scale models, so users can draw pathways in a semi-automated way. Second, users can visualize data related to genes or proteins on the associated reactions and pathways, using rules that define which enzymes catalyze each reaction. Thus, users can identify trends in common genomic data types (e.g. RNA-Seq, proteomics, ChIP)--in conjunction with metabolite- and reaction-oriented data types (e.g. metabolomics, fluxomics). Third, Escher harnesses the strengths of web technologies (SVG, D3, developer tools) so that visualizations can be rapidly adapted, extended, shared, and embedded. This paper provides examples of each of these features and explains how the development approach used for Escher can be used to guide the development of future visualization tools.
| S-EPMC4552468 | biostudies-literature
Project description:In recent years, more and more health data are being generated. These data come not only from professional health systems, but also from wearable devices. All these 'big data' put together can be utilized to optimize treatments for each unique patient ('precision medicine'). For this to be possible, it is necessary that hospitals, academia and industry work together to bridge the 'valley of death' of translational medicine. However, hospitals and academia often are reluctant to share their data with other parties, even though the patient is actually the owner of his/her own health data. Academic hospitals usually invest a lot of time in setting up clinical trials and collecting data, and want to be the first ones to publish papers on this data. There are some publicly available datasets, but these are usually only shared after study (and publication) completion, which means a severe delay of months or even years before others can analyse the data. One solution is to incentivize the hospitals to share their data with (other) academic institutes and the industry. Here, we show an analysis of the current literature around data sharing, and we discuss five aspects of data sharing in the medical domain: publisher requirements, data ownership, growing support for data sharing, data sharing initiatives and how the use of federated data might be a solution. We also discuss some potential future developments around data sharing, such as medical crowdsourcing and data generalists.
| S-EPMC7246891 | biostudies-literature
Project description:This study conducts a bibliometric analysis of 252 scientific publications from 2001 to 2023, exploring the evolution and emerging trends in agricultural data spaces. Analyzing articles from the Web of Science and Scopus databases, we address six research questions: the current and interconnected key topics in agricultural data spaces (RQ1), the evolution of research themes over time (RQ2), emerging trends in the field (RQ3), the identification of leading researchers (RQ4), and the primary funding sources for this research area (RQ5), the relationship among research data and small farmers (RQ6). Our findings reveal a shift from traditional to innovative research themes, such as the increasing focus on the Internet of Things (IoT), Blockchain, and Digital Storage. This indicates a trend toward modernizing agricultural practices through technology. We found that the rise of these topics is not correlated with the results shown by Google Scholar for these same terms but is correlated with the economic impact of such areas. Prominent authors and significant funding sources, including the European Union, the United States Department of Agriculture, and Chinese research programs, have been identified, proving the global interest and investment in the digitalization of agriculture. We continue our analysis by identifying some barriers that prevent small farmers from using or sharing research data, among them cultural contexts, lack of trust in providers, and ignorance of terms and conditions. This study offers valuable insights for researchers, policymakers, and practitioners, focusing on the evolution of the dynamic landscape of agricultural data spaces and potential future innovations in fields like data analytics and Artificial Intelligence, Internet of Things, Blockchain, digital divide and digital farming platforms. Our findings emphasize the necessity for targeted policy interventions and support mechanisms to bridge the gap and enable small and medium farmers to benefit from advancements in agricultural data spaces and digitization.
| S-EPMC11745808 | biostudies-literature
Project description:Making data broadly accessible is essential to creating a medical information commons (MIC). Transparency about data-sharing practices can cultivate trust among prospective and existing MIC participants. We present an analysis of 34 initiatives sharing DNA-derived data based on public information. We describe data-sharing practices captured, including practices related to consent, privacy and security, data access, oversight, and participant engagement. Our results reveal that data-sharing initiatives have some distance to go in achieving transparency.
| S-EPMC6730666 | biostudies-literature
Project description: Not available
| S-EPMC5718357 | biostudies-literature
Project description: Not available
| S-EPMC5811187 | biostudies-literature
Project description:Research transparency, reproducibility, and data sharing uphold core principles of science at a time when the integrity of scientific research is being questioned. This article discusses how research data in psychology can be made accessible for reproducibility and reanalysis by describing practical ways to overcome barriers to data sharing. We examine key issues surrounding the sharing of data such as who owns research data, how to protect the confidentiality of the research participant, how to give appropriate credit to the data creator, how to deal with metadata and codebooks, how to address provenance, and other specifics such as versioning and file formats. The protection of research subjects is a fundamental obligation, and we explain frameworks and procedures designed to protect against the harms that may result from disclosure of confidential information. We also advocate greater recognition for data creators and the authors of program code used in the management and analysis of data. We argue that research data and program code are important scientific contributions that should be cited in the same way as publications. (PsycINFO Database Record
| S-EPMC5967383 | biostudies-literature