17 Sep 2019 Susan K. Gregurick is the Division Director for Biophysics, Biomedical Technology, and Computational Biosciences (BBCB) in NIH's National

The FAIR Data Principles (Findable, Accessible, Interoperable, Reusable) were drafted at a Lorentz Center workshop in Leiden in the Netherlands in 2015. The principles have since received worldwide recognition by various organisations including FORCE11 , National Institutes of Health (NIH) and the European Commission as a useful framework for thinking about sharing data in a way that will enable maximum …

Earlier this month NIH’s Dr. Dawei Lin, a data scientist from NIAID, and colleagues published the community-developed TRUST principles to promote the adoption of Transparency, Responsibility, User focused, Sustainability, and Technology. FAIR data are data which meet principles of findability, accessibility, interoperability, and reusability. The acronym and principles were defined in a March 2016 paper in the journal Scientific Data by a consortium of scientists and organizations. The FAIR principles emphasize machine-actionability because humans increasingly rely on computational support to deal with data as a result of the increase in volume, complexity, and creation speed of data.

Fair data principles nih

FAIR: findable, accessible, interoperable, reusable) primarily focus on characteristics of data that will facilitate increased data sharing among entities while ignoring power differentials and historical contexts. Obviously, the main objective of the FAIR Data Principles is the optimal preparation of research data for man and machine. The following checklist may help to comply with the principles of the FAIR Data Publishing Group, which is part of the FORCE 11 community. In this blog post we take a closer look at the requirements and give some examples. 2020-06-30 · NIH’s Sequence Read Archive is the largest, most diverse collection of next generation sequencing data from human, non-human and microbial sources.Hosted by the National Center for Biotechnology Information at the National Library of Medicine (), SRA data is also available on the Google Cloud Platform and Amazon Web Services as part of the NIH Science and Technology Research Infrastructure There are a total of 15 FAIR principles that can be applied to research in all scientific disciplines. The FAIR principles are mainly focused on machine readability, but also target human understanding of research data, in order to enable the reuse of data.

The aim of this special issue is to highlight unique contributions towards the development and assessment of FAIR data, systems, and analysis.

Staff from the National Institutes of Health (NIH) worked with others in HHS to revise and service on panels such as Institutional Review Boards or Data and Safety reference to public prices or other reasonable measures of fair ma

1The NIH BD2K Center of Excellence in Biomedical Computing, University The FAIR Guiding Principles for scientific data management and av P SANCHES · Citerat av 2 — I show that the. worN of producing data does not stop with the worN of the engineers who produce ICTYbased During the research conducted in this thesis, efforts were made to ensure fair principles in collecting Nih Public access: 267. Nyckelord [en].

FAIR-principerna spelar en mycket viktig roll i arbetet för öppen vetenskap. De beskriver några av de mest centrala riktlinjerna för god datahantering och öppen tillgång till forskningsdata. FAIR innebär att forskningsdata ska vara Findable (sökbara), Accessible (tillgängliga), Interoperable (interoperabla) och Reusable (återanvändbara).

At a glance, perhaps it seems like a simple treatment principle but the imILT data stands well compared to published results for locally advanced, unresectable So, it´s fair to say, once again, that precision matters.

Many in the data science community are familiar with the FAIR principles—a set of principles to make data findable, accessible, interoperable, and reusable. Earlier this month NIH’s Dr. Dawei Lin, a data scientist from NIAID, and colleagues published the community-developed TRUST principles to promote the adoption of Transparency, Responsibility, User focused, Sustainability, and Technology.
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INCF promotes the field of neuroinformatics and aims to advance data reuse and standards and best practices that embrace the principles of Open, FAIR, and F1 G. Strategy, principles and processes for allocation of space at SciLifeLab at Re: SciLifeLab has a two-pronged approach to FAIR data, where the Strategic Future View In 2004, the former NIH Director Elias Zerhouni researchers, FAIR principles, higher education, pedagogy, reproducible research Med årvisse åpne data om tilstanden i norsk høyere utdanning The National Institute of Health (NIH) provides free models which are I den mån de förfinar sina algoritmer baserat på nya data den utsätts för, så kallad online learning .

STRIDES – biomedicinska data; NIH Data Sharing Repositories Webb: https://www.dtls.nl/fair-data/personal-health-train/ national access to documents rules is in principle freely available for re-use.”. av C Annerstedt · 2010 · Citerat av 98 — The study consists of two parts: quantitative data collection of grades in PE given The study has shown that the principles of fair and equitable grading in Öppen förläsning: Core Values as Principles for Deeper Learning in Teacher där forskningsdata och metadata ska göras FAIR och maskinläsbara satte EU på Det skedde i slutet av 2016 och de leder det fyraåriga pilotprojektet NIH Data allmän - core.ac.uk - PDF: www.pubmedcentral.nih.gov. ▷.
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It is not enough that the NIH commit to FAIR data principles, the nation’s experts in health and biomedical informatics contend, the NIH must require that grantees also align to such principles as a condition of funding. The NIH released its draft Data Science Strategic Plan in early March, NIH should require that data management plans must describe how the researchers address each of the 15 FAIR Principles.

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NHLBI BioData Catalyst is a cloud-based platform providing tools, applications, and workflows in secure workspaces. By increasing access to NHLBI datasets and innovative data analysis capabilities, BioData Catalyst accelerates efficient biomedical research that drives discovery and scientific advancement, leading to novel diagnostic tools, therapeutics, and prevention strategies for heart

A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly Many in the data science community are familiar with the FAIR principles—a set of principles to make data findable, accessible, interoperable, and reusable. Earlier this month NIH’s Dr. Dawei Lin, a data scientist from NIAID, and colleagues published the community-developed TRUST principles to promote the adoption of Transparency, Responsibility, User focused, Sustainability, and Technology. FAIR data are data which meet principles of findability, accessibility, interoperability, and reusability. The acronym and principles were defined in a March 2016 paper in the journal Scientific Data by a consortium of scientists and organizations. The FAIR principles emphasize machine-actionability because humans increasingly rely on computational support to deal with data as a result of the increase in volume, complexity, and creation speed of data. The abbreviation FAIR/O data FAIR-principerna spelar en mycket viktig roll i arbetet för öppen vetenskap. De beskriver några av de mest centrala riktlinjerna för god datahantering och öppen tillgång till forskningsdata.