Research and Training Funding

Funding Opportunity Announcements

Browse below for Data Science Funding Opportunity Announcements.

This page last reviewed on August 7, 2019

Feed last updated: January 25 2020 11:49 am
Title FOA Number Organization Release Date Expiration Date Purpose Search Terms
Request for Information (RFI): Second Draft Specification for Conformant Cloud Providers NOT-LM-16-002 NLM Dec 22 2015 N/A Request Information RFI): Second Draft Specification Conformant Cloud Providers Notice Number: NOT-LM-16-002 Key Dates Release Date:   December 22, 2015 Response Date: January 22, 2016 Related Announcements None Issued National Library Medicine NLM) Purpose National Institutes Health NIH) funds basic applied research the biomedical health sciences, generating large amounts new research data every year. the scope scale research data increased, standard mechanisms which data found shared indexes, web portals, journal articles, scientific conferences, direct transmission data via electronic networks, name few) insufficient. Further, federal policies require data generated federal support shared, making broadly accessible, easily computable readily sharable. part its efforts resolve problem, NIH developing Commons1, shared, virtual space sharing data, software, digital learning resources, workflows other products research. Commons help ensure the digital artifacts publicly funded research Findable, Accessible, Interoperable Reusable FAIR). NIH supporting implementation the Commons concept via variety pilot activities within NIH Big Data Knowledge BD2K) program.  Computational infrastructure the Commons initially envisioned employing cloud computing services. ldquo;conformant provider” cloud services the Commons offer array options, such Infrastructure a Service IaaS), Platform a Service PaaS) Software a Service SaaS). conformant provider one meets NIH defined requirements business relationships, interfaces, capacity, networking connectivity, information assurance authentication authorization. Dec 23, 2014, NIH released Sources Sought Notice2, SS-NIHCOMMONS-2015, FedBizOps, requesting information an initial set proposed conformance requirements. Comments received the initial requirements revised.  NIH now requesting comments the revised version the conformance requirements, prior identifying conformant providers.     NIH intends finalize requirements based industry scientific feedback during January 2016, to open process providers cloud compute services become conformant soon practicable after requirements finalized. Although details the conformance certification process not finalized, NIH intends utilize reviewed self-certification process during pilot phase. Information Requested NIH requests input two major areas: 1. NIH wishes obtain feedback potential providers a) ability meet proposed conformance requirements, b) interest acting providers c) any requirement deemed the provider be sufficiently burdensome it prevent potential provider participating. 2. NIH wishes obtain feedback potential users conformant cloud services, is, the research community, to a) whether services described the proposed conformance requirements meet needs, b) additional capabilities required, types capabilities be necessary meet general requirements scientific computing c) barriers researchers experienced using cloud services host data sets. NIH particularly interested responses those already cloud services store data make widely available draft conformance requirements posted at: https://datascience.nih.gov/commons/technical_conformance.pdf. to Submit Response Responses this RFI must submitted electronically conformance_requirements@nih.gov later 30 days after publication this RFI. Responses this RFI voluntary. RFI for planning purposes only should be construed a solicitation as obligation the part the Federal Government, National Institutes Health, individual NIH institutes Centers. NIH does intend make any type award based responses this RFI to pay either preparation information submitted the Government’s of such information. NIH use information submitted response the RFI its discretion. Respondents advised the Government under obligation acknowledge receipt the information provided will provide feedback respondents. information submitted be analyzed may shared internally, incorporated future changes the NIH cloud conformance requirements, appropriate at Government’s discretion. Proprietary, classified, confidential, sensitive information should be included your response. Inquiries Please direct inquiries to: George A. Komatsoulis, Ph.D. National Library Medicine NLM) Telephone:  301-594-7875 Email:  komatsog@mail.nih.gov Vivien Bonazzi, Ph.D. Office the NIH Associate Director Data Science ADDS) Telephone:  301-451-8276 Email:  bonazziv@mail.nih.gov 1https://datascience.nih.gov/commons 2https://www.fbo.gov/index?s=opportunity&mode=form&id=09c44aa4c0877c150e7... data science, big data, computational
Request for Information (RFI): Input on Sustaining Biomedical Data Repositories NOT-ES-15-011 NIEHS Feb 18 2015 N/A Request Information RFI): Input Sustaining Biomedical Data Repositories Notice Number: NOT-ES-15-011 Key Dates Release Date:     February 18, 2015 Response Date:  March 18, 2015 Related Announcements None Issued National Institute Environmental Health Sciences NIEHS) National Cancer Institute NCI) National Human Genome Research Institute NHGRI) National Institute Allergy Infectious Diseases NIAID) National Institute Drug Abuse NIDA) National Institute General Medical Sciences NIGMS) Office Strategic Coordination Common Fund) Purpose Request Information RFI) to solicit comments ideas economic, technical, policy administrative approaches toward enhancing long-term sustainability biomedical data repositories. Background ability harvest wealth information contained biomedical Big Data” the potential advance our understanding human health disease; however, enormity Big Data creates major organizational analytical impediments accelerating pace scientific discovery. biomedical datasets become increasingly large, diverse, complex, tax conventional methods sharing, managing, analyzing data. Furthermore, researchers’ abilities capitalize biomedical Big Data science-based approaches limited poor data accessibility interoperability, lack appropriate tools, insufficient training. response the opportunities challenges presented the dawning era Big Data biomedical research, NIH launched Big Data Knowledge BD2K) initiative a trans-NIH initiative cultivate digital research enterprise within biomedicine, facilitate discovery support new knowledge, to maximize community engagement. Biomedical research an increasingly data intensive enterprise due part the rapid advance many life science technologies. data enterprise created multitude repositories, are growing both scale complexity, the preservation distribution data across scientific community. challenge the scientific community to develop effective means sustaining biomedical data repositories knowledge therein.   growing datasets flat research budgets around world, challenge sustaining repositories straining capacity current funding approaches fulfill need.  is essential develop new, innovative business models.  addition, NIH considering repositories be integrated within larger biomedical digital research enterprise as accelerate our capability find, access, reuse, interoperate information across diverse data types.  address challenges, BD2K seeks information approaches, business models, ideas will inform NIH improving value current mechanisms developing new mechanisms sustain biomedical data repositories a long-term basis; developing strategies, technologies business models accommodate rapidly evolving, interdisciplinary research needs requiring access multiple data types a variety resources. Information Requested stakeholders an interest strategies address sustainability biomedical data repositories invited provide information. you choose, can categorize area expertise including that apply: Biomedical science researcher Bioinformatician Data scientist Standard developer maintainer Research data repository manager Library information scientist Data curator Professional society officer Funder Publisher Administrator president, provost, dean equivalents academic non-profit organizations) Non-profit employee Tool services vendor Biotech company employee Business developer Economist other financial expert Your response also include detailed roles within industry, government, academia the history experiences relevant repositories. NIH seeking information addresses, is limited to, following areas: Financial Models – New business models sustaining digital repositories, including not limited examples cited http://datacommunity.icpsr.umich.edu/sites/default/files/WhitePaper_ICPS... http://www.sr.ithaka.org/research-publications/guide-best-revenue-models....  Innovation – Sustaining data repositories while enabling new innovations finding, accessing, integrating and reusing contents a wide variety stakeholders. Evaluation  - Criteria determine data repositories require sustained funding models no longer need be sustained, including, not limited metrics measuring value given repositories data within those repositories. Best Practices - Current, new, emerging means practices sustain data repositories the long-term. Partnerships - type, form, governance partnerships ensure long-term access essential data repositories including, not limited to, private-sector organizations, non-profit foundations, universities, national international government agencies, combinations thereof. Technical – Technological developments needed sustain data repositories a cost-effective while furthering accessibility usability a broad set stakeholders. Human Capital – Models enhance efficiency the application human capital associated data repositories. Life Cycle – Consideration the evolution value, cost, scale data repositories emerge, reach maturity, either gain lose relevance the long term. Submitting Response responses must submitted BD2K_Sustainability_RFI@niehs.nih.gov March 18, 2015. Please include Notice number NOT-ES-15-011 the subject line. Responders free address any all the categories listed above. submitted information be reviewed NIH staff. Responses this RFI voluntary. Please not include any proprietary, classified, confidential, sensitive information your response. NIH use information submitted response this RFI its discretion will provide comments any responder's submission. collected information be reviewed NIH staff, appear reports, may shared publicly an NIH website. Government reserves right use any non-proprietary technical information summaries the state the science, any resultant solicitation(s). NIH use information gathered this RFI inform development future funding opportunity announcements. RFI for information planning purposes only should be construed a solicitation as obligation the part the Federal Government, National Institutes Health NIH), individual NIH Institutes Centers. NIH does intend make any awards based responses this RFI to otherwise pay preparation any information submitted for Government's of such information. basis claims against U.S. Government shall arise a result a response this request information from Government’s of such information. Inquiries Please direct inquiries to: Allen Dearry, Ph.D. National Institute Environmental Health Sciences NIEHS) Telephone: 919-541-3068 Email: dearry@niehs.nih.gov data science, big data
Request for Information (RFI) soliciting input into the deliberations of the Advisory Committee to the NIH Director (ACD) Working Group on the Nationa NOT-OD-15-067 NIH Feb 13 2015 N/A Request Information RFI) Soliciting Input the Deliberations the Advisory Committee the NIH Director ACD) Working Group the National Library Medicine NLM) Notice Number: NOT-OD-15-067 Key Dates Release Date: February 13, 2015 Related Announcements None Issued National Institutes Health NIH) Purpose Notice a time-sensitive Request Information RFI) soliciting input the deliberations the Advisory Committee the NIH Director ACD) Working Group the National Library Medicine NLM). Background defined statute, NLM established ldquo;assist advancement medical related sciences to aid dissemination exchange scientific other information important the progress medicine to public health.” world’s largest biomedical library, NLM maintains makes available vast multimedia collection published literature, organizational archives manuscripts, still moving images; builds provides electronic information resources used billions times year millions scientists, health professionals, members the public; supports conducts research, development, training biomedical informatics, data information science, health information technology; coordinates 6,100-member National Network Libraries Medicine promotes provides access health information communities across United States. pursuit its mission, NLM achieved successes, such pioneering free Internet access PubMed, access genetic genomic data through GenBank, clinical trial registration results through clinicaltrials.gov, NIH-funded biomedical research part the NIH Public Access Policy, supporting research training programs institutions throughout country. full scope activities the NLM be found http://www.nlm.nih.gov/. Ultimately, creation maintenance these resources help support enable access the results research funded NIH many organizations. NIH committed ensuring the NLM continues leverage technological advances information data science facilitate scientific breakthroughs understanding health disease scientists, health professionals, the public. order help chart course the future the NLM, NIH Director established working group charged 1) reviewing current mission, organization, programmatic priorities the NLM; 2) articulating strategic vision the NLM ensure it remains international leader biomedical health information. addressing charge, working group to assess specifically the NLM should: Continue meet biomedical community’s rapidly evolving scientific technological needs; Lead development adoption information technologies; Facilitate collection, storage, use biomedical  data the biomedical health research communities; Continue lead promoting open access models biomedical data scientific literature; Balance computational methods human-based approaches indexing; Maximize utilization cost-efficiency the NLM’s National Network Libraries Medicine; Maximize usefulness the NLM’s outreach exhibits programs the context future opportunities; Interface effectively the broader expanding NIH efforts data science; Directly contribute addressing major data science challenges facing biomedical research enterprise. part the working group’s deliberations, NIH seeking input stakeholders the general public through RFI. Information Requested Request Information RFI) seeks input regarding strategic vision the NLM ensure it remains international leader biomedical data health information. particular, comments being sought regarding current value and future need NLM programs, resources, research training efforts, services e.g., databases, software, collections) – collectively referred in RFI hereafter ldquo;NLM elements”. comments include are limited the following topics: Current NLM elements are the most, least, value the research community including biomedical, clinical, behavioral, health services, public health, historical researchers) future capabilities will needed support evolving scientific technological activities needs. Current NLM elements are the most, least, value health professionals e.g., those working health care, emergency response, toxicology, environmental health, public health) future capabilities will needed enable health professionals integrate data knowledge biomedical research effective practice. Current NLM elements are most, least, value patients the public including students, teachers, the media) future capabilities will needed ensure trusted source rapid dissemination health knowledge the public domain. Current NLM elements are most, least, value other libraries, publishers, organizations, companies, individuals use NLM data, software tools, systems developing providing value-added complementary services products future capabilities would facilitate development products services make of NLM resources. NLM be better positioned help address broader growing challenges associated with: Biomedical informatics, ldquo;big data”, data science; Electronic health records; Digital publications; Other emerging challenges/elements warranting special consideration. to Submit Response Responses this RFI must submitted electronically via: http://grants.nih.gov/grants/rfi/rfi.cfm?ID=41. Responses be accepted through March 13, 2015. Responses this RFI voluntary. Please not include any proprietary, classified, confidential, sensitive information your response.  NIH use information submitted response this RFI its discretion will provide comments any responder's submission. The collected information be reviewed NIH staff, appear reports, may shared publicly an NIH website. Government reserves right use any non-proprietary technical information summaries the state the science, any resultant solicitation(s). The NIH use information gathered this RFI inform development future funding opportunity announcements. RFI for information planning purposes only should be construed a solicitation as obligation the part the Federal Government, National Institutes Health NIH), individual NIH Institutes Centers. No basis claims against U.S. Government shall arise a result a response this request information from Government’s of such information. Inquiries Please direct inquiries Lyric Jorgenson, Ph.D. Office the Deputy Director Science, Outreach, Policy Telephone: 301-496-1455 Email: jorgensonla@od.nih.gov data science, big data, computational, informatics
Request for Information (RFI) on the NIH Big Data to Knowledge (BD2K) Initiative Resources for Teaching and Learning Biomedical Big Data Management an NOT-LM-15-001 NLM Nov 04 2014 N/A Request Information RFI) the NIH Big Data Knowledge BD2K) Initiative Resources Teaching Learning Biomedical Big Data Management Data Science Notice Number: NOT-LM-15-001 Key Dates Release Date: November 4, 2014 Response Date: December 31, 2014 Related Announcements None Issued National Library Medicine NLM) Purpose National Institutes Health NIH) recognizes increasing demands placed biomedical researchers share data generate through federally-funded research projects. part its Big Data Knowledge BD2K) Initiative, NIH wishes help broader scientific community update knowledge skills the important areas the science, storage, management sharing biomedical big data. NIH wants identify array timely, high quality courses online learning materials already available data science data management topics biomedical big data. Background ability harvest wealth information contained biomedical big data the potential advance our understanding human health disease; however, enormity big data creates major organizational analytical impediments rapid translational impact. biomedical datasets become increasingly large, diverse, complex, tax conventional methods sharing, managing, analyzing data. Furthermore, researchers’ abilities capitalize biomedical big data science-based approaches limited poor data accessibility interoperability, lack appropriate tools, insufficient training. response the opportunities challenges presented the dawning era quot;Big Data" biomedical research, NIH launched Big Data Knowledge BD2K) initiative a trans-NIH initiative cultivate digital research enterprise within biomedicine, facilitate discovery support new knowledge, to maximize community engagement. BD2K addresses four major aims that, combination, meant enhance utility biomedical big data: 1) facilitate broad of biomedical digital assets making discoverable, accessible, citable; 2) conduct research develop methods, software, tools needed fully analyze biomedical big data; 3) enhance training the development use methods tools necessary biomedical big data science; 4) enable data ecosystem accelerates both basic translational discovery part a digital enterprise. Biomedical big data from sources, massive stand-alone datasets generated large collaborations the small datasets produced individual investigators. value all data be amplified through aggregation integration. BD2K initiative a community-enabled endeavor towards maximizing collective value current future biomedical digital assets better inform protect human health. BD2K part a larger ecosystem driven data policies shared infrastructure. the BD2K initiative, term quot;Biomedical Big Data" inclusive the diverse digital objects may impact basic, translational, clinical, social, behavioral, environmental, informatics research questions. Such data types include imaging, phenotypic, genotypic, molecular, clinical, behavioral, environmental, many types biological biomedical data. may also include data generated other purposes e.g., social media, search histories, economic, geographical, cell phone data). Finally, also encompass metadata, data standards, software tools involved data processing analysis. universities begin implement federal policies requiring to share research data have gathered the support public funds1, scientists, graduate students, librarians other professional administrative staff learning or refreshing they know data science the management biomedical research data. organizations universities already engaged providing courses other instruction staff, faculty student researchers help master new skills needed working biomedical big data. part the BD2K program, shared Biomedical Big Data resource soon become reality, providing public access shared biomedical research data research tools2. Curriculum training materials relating data science data management topics also become part the shared biomedical big data research resource, including those funded NIH through BD2K initiatives. Information Requested this Request Information RFI) Notice, NIH invites interested knowledgeable persons inform NIH existing learning resources covering Biomedical Big Data management data science topics such as, not limited to: Data Management Data capture storage Data mapping integration disparate types Data annotation curation, including metadata Version tracking multi-site data management Pipelines data processing analysis Statistics Modeling including methods data integration) Inference including large p, small N problems) Prediction including Machine Learning) Quantification uncertainty Big Data Computer Science Algorithms, algorithmic complexity Optimization Distributed storage processing Visualization Programming languages NIH interested collections aggregations) the topics listed above well resources focused individual topics. needed instructional resources training data management data science already available. Please identify resources materials interest characteristics such as, not limited to: Graduate-level short courses, tutorials workshops online, in-person hybrid) are open all; Graduate-level online tutorials modules; Massive Open Online Courses MOOCs; Curriculum plans resources including sample datasets data management plans used data management training; Evaluation approaches online data science data management courses. NIH interested collections aggregations) the above well individual topics. Materials self-guided learning must available online for download standard digital formats. each class learning resource, please provide information will help NIH identify locate resources, such as: name the course resource; URL the online resource a site describes offers resource; sponsor the resource, such organization instructor. Additional information, also welcome, including comments the course resource. to Submit Response responses must submitted electronically December 31, 2014, the form an email NLMEPINFO_BD2K@mail.nih.gov , using subject data management'. Responses this RFI Notice voluntary. submitted information be reviewed the NIH staff later available the public. Submitted information not considered confidential. not attach PPT files other curriculum materials themselves your response. Responses welcome associations professional organizations well individual stakeholders. request for information planning purposes should be construed a solicitation as obligation the Federal Government NIH. awards be based responses this Request Information. information submitted be analyzed may used reports presentations. Those respond advised NIH under obligation acknowledge receipt your comments, provide comments your submission. proprietary, classified, confidential and/or sensitive information should included your response. NIH the government reserve right use any non-proprietary technical information any future solicitation(s). Inquiries Please direct inquiries to: Valerie Florance, Ph.D. National Library Medicine Telephone: 301-496-4621 Email: NLMEPINFO_BD2K@mail.nih.gov http://grants.nih.gov/grants/guide/notice-files/NOT-OD-14-111.html http://bd2k.nih.gov/faqs.html data science, big data, informatics, data integration, machine learning, data standards, statistics
Request for Information (RFI) on Science Drivers Requiring Capable Exascale High Performance Computing NOT-GM-15-122 NIGMS Sep 15 2015 N/A Request Information RFI) Science Drivers Requiring Capable Exascale High Performance Computing Notice Number: NOT-GM-15-122 Key Dates Release Date:   September 15, 2015 Related Announcements NOT-GM-15-123 Issued National Institute General Medical Sciences NIGMS) Purpose is multi-agency request information identify scientific research topics applications need High Performance Computing HPC) capabilities extend 100 times beyond today’s performance scientific applications. Currently, computational modeling, simulation, well data assimilation data analytics used an increasing number researchers answer complex multispatial, multiphysics scientific questions more realism. the scientific discovery horizon expands as advances high performance computing become central scientific workflows, sustained petascale application performance be insufficient meet needs. addition, HPC expanding traditional numerically oriented computation also include large-scale analytics e.g., Bayesian approaches model refinement, large-scale image analysis, machine learning, decision support, quantifying uncertainty multimodal multi spatial analyses). Architectures technologies used modeling simulation currently differ those used data integration analytics, are increasingly converging. extreme computing ecosystem must therefore accommodate broad spectrum growing data science activities. Background White House Executive Order, July 29, 2015, establishes National Strategic Computing Initiative NSCI) a whole-of-government effort designed create cohesive, multi-agency strategic vision Federal investment strategy, executed collaboration industry academia, maximize benefits HPC the United States. Department Energy DOE), National Science Foundation NSF), the Department Defense DOD) the lead agencies this effort support significantly advanced HPC ecosystem within next decade.   of objectives the initiative to deliver capable Exascale” computing capability delivers 100 times today's application performance. is request information NSF, DOE, NIH community input identifying scientific research would benefit a greatly enhanced new generation HPC far beyond can done using current technologies architectures. information be used assist agencies construct roadmap, build exascale-capable ecosystem required support scientific research, inform research, engineering development process. is likely a range advanced capabilities need be developed respond the varied computing needs across science disciplines. seek responses applications subfields life e.g., biological, social, health biomedical) sciences, mathematical physical sciences, geosciences, energy science, engineering research.  seek only traditional areas numerical intensity such simulations nuclear physics, biomolecular physics, weather climate modeling, materials science, also any areas rely deriving fundamental understanding large scale analytics would require 100-fold increase over today’s application performance. Information Requested respect your field expertise traditional non-traditional research areas applications HPC, agencies request input/feedback. comments include are limited the following areas concern: specific scientific research challenges would need projected 100-fold increase application performance over is possible today.  potential impact the research the scientific community, national economy, society.   specific limitations/barriers existing HPC systems must overcome perform studies this area.  comment also include level performance current architectures, the projected increase performance is needed future architectures. Any related research areas foresee would benefit this level augmented computational capability. Identification any barriers addition computational capability impact proposed research also considered. Important computational technical parameters the problem you expect to in 10 years 2025).  addition any specialized unique computational capabilities are required and/or need be scaled for addressing scientific problem, e.g., the areas computing architectures, systems software hardware, software applications, algorithm development, communications, networking. Alternative models deployment resource accessibility arising of exascale computing. Improvements scientific workflow well particular requirements may needed specific domains. Capabilities needed the end-to-end system, including data requirements such data analytics visualization tools, shared data capabilities, data services includes databases, portals data transfer tools/nodes. Foundational issues need be addressed such training, workforce development collaborative environments. areas relevance the Agencies consider. Submitting Response responses must submitted NIGMS_exascale@nigms.nih.gov October 16, 2015. comments must submitted via E-mail text as attached electronic document.  Microsoft documents preferred.   Please try limit response two pages total. RFI for planning purposes only should be construed a solicitation applications an obligation the part the government. government not pay the preparation any information submitted for government’s of information. agencies use information submitted response this RFI their discretion will provide comments any responder's submission. Responses the RFI be reflected future funding opportunity announcements. information provided be analyzed, appear reports, may shared publicly agency websites. Respondents advised the government under obligation acknowledge receipt the information provide feedback respondents respect any information submitted. proprietary, classified, confidential, sensitive information should included your response. government reserves right use any non-proprietary technical information any resultant solicitation(s), policies procedures. Inquiries Please direct inquiries to: Susan Gregurick, Ph.D. National Institute General Medical Sciences NIGMS) National Institutes Health Telephone: 301-451-6446 Email: susan.gregurick@nigms.nih.gov William L. Miller, Ph.D. Division Advanced Cyberinfrastructure Directorate Computer Information Science Engineering National Science Foundation Telephone: 703-292-7886 Email: WLMiller@nsf.gov Barbara Helland Advanced Scientific Computing Research ASCR) Department Energy Telephone: 301-903-9958 Email: barbara.helland@science.doe.gov data science, computational, data integration, machine learning
Request for Information (RFI) on Next Directions for the National Library of Medicines Unified Medical Language System NOT-LM-20-001 NLM Oct 23 2019 N/A Request Information RFI) Next Directions the National Library Medicine’s Unified Medical Language System® Notice Number: NOT-LM-20-001 Key Dates Release Date: October 23, 2019 Related Announcements None Issued National Library Medicine NLM) Purpose Background Created 1986, National Library Medicine’s NLM) Unified Medical Language System® UMLS) integrates distributes key terminology, classification coding standards, associated resources promote creation effective interoperable biomedical information systems services, including electronic health records. is set files software brings together health biomedical vocabularies standards enable interoperability between computer systems. the past 30 years, researchers, health care providers, industry/vendors, others utilized terminological resources the UMLS various applications natural language processing, text processing, search retrieval, data extraction, other applications. recent advancements improvements e.g., artificial intelligence, AI) computer processing, NLM reviewing computational infrastructure the UMLS consider to improve efficiency utility, to support modern cases. Through RFI, NLM seeks stakeholder input how improve UMLS. Additionally, NLM conduct least public informational webinar presents proposed ideas improving UMLS. input received these efforts be considered NLM the development future versions the UMLS. Information Requested support the NLM Strategic Plan, 2017-2027, and NIH Strategic Plan Data Science, goal this effort to the UMLS leaner, stronger, more useful. such, NLM requesting public comment the considerations listed the bullets follow. Response this Notice voluntary, respondents free address any all the topics listed other topics listed: Considerations focusing UMLS Metathesaurus primarily concept synonyms, inter-concept relationships mappings between concepts, including: Attributes could removed Vocabularies may removed Ways customizing presentation specific cases Customization processes e.g., sub setting through MetamorphoSys) could removed Whether UMLS should retain capability reconstruct native versions the source terminologies its contained vocabularies they be obtained those sources directly Considerations enhancing UMLS Metathesaurus content, including: Vocabularies might added, especially those would improve alignment the work other NIH Institutes Centers other stakeholders Structure the content would facilitate in health data science analytics Better support access retired codes facilitate longitudinal data analysis Considerations enhancing UMLS Metathesaurus distribution, including: Integration the UMLS Fast Healthcare Interoperability Resources® (FHIR) vocabulary services Enhancing application programming interface API) support mapping Consideration the of cloud computing such independent developers/users implement own processing technology against cloud version UMLS Consideration the of machine learning/AI support enhance UMLS Metathesaurus creation process Considerations modifying/simplifying UMLS license supporting open science Any topic may relevant NLM consider modernizing UMLS Submitting Response Comments should submitted electronically the following webpage: https://nlmenterprise.co1.qualtrics.com/jfe/form/SV_4IbbUV1D7x0e0K1 by January 11, 2020. Notice for planning purposes only should be construed a policy, solicitation applications, as obligation the part the Government provide support any ideas identified response it. Please note the Government not pay the preparation any information submitted for use that information. Please not include any proprietary, classified, confidential, sensitive information your response. Government reserves right use any non-proprietary technical information summaries the state the science, any resultant solicitation(s). NIH use information gathered this Notice inform development future funding opportunity announcements policy development. Inquiries Please direct inquiries to: Liz Amos Office the Director, National Library Medicine Telephone: 301-287-4291 Email: liz.amos@nih.gov
Request for Comments: Proposal to Update Data Management of Genomic Summary Results Under the NIH Genomic Data Sharing Policy NOT-OD-17-110 NIH Sep 20 2017 N/A Request Comments: Proposal Update Data Management Genomic Summary Results Under NIH Genomic Data Sharing Policy Notice Number: NOT-OD-17-110 Key Dates Release Date: September 20, 2017 Response Date: October 20, 2017 Related Announcements NOT-OD-18-104 NOT-OD-07-088 NOT-OD-12-136 NOT-OD-14-124 NOT-OD-17-044 NOT-OD-19-023 NOT-OD-19-011--> Issued National Institutes Health NIH) Purpose National Institutes Health NIH) seeking public comments regarding proposed update the access procedures genomic summary results under Genomic Data Sharing GDS) Policy.1 Genomic summary results, also known aggregate genomic data’2 genomic summary statistics’ 3, results primary analyses genomic research convey information relevant understanding genomic associations traits diseases across datasets rather data specific any individual research participant. goal this proposed data management update to provide access genomic summary results through methods proportional the risks benefits posed this type information. Background Overview NIH’s mission to seek fundamental knowledge the nature behavior living systems the application that knowledge enhance health, lengthen life, reduce illness disability.4 Broad responsible sharing genomic summary results generated through analysis NIH-supported research promotes maximum public benefit the federal research investment providing information crucial the interpretation application genomic data research clinical practice. Genomic summary results an analytic output derived a study’s primary genomic data are currently defined the agency include calculated summary statistics, such genotype counts frequencies, allele counts frequencies, effect size estimates standard errors, likelihoods, p-values. Genomic summary results facilitate interpretation genomic variants may may not) contribute a disease disorder interest. Public sharing genomic summary results large-scale genomic research become crucial advancing scientific clinical discovery.5 However, studies available through NIH-designated data repository6, access this information currently only available through controlled access below an explanation controlled access’). Based input the research community over past few years below), NIH proposing allow broader access genomic summary results most studies subject the NIH GDS Policy. Institutions submitting genomic data NIH-designated data repositories be expected notify NIH any studies which are particular sensitivities i.e., studies including potentially stigmatizing traits, with identifiable isolated study populations). Access genomic summary results such datasets remain under controlled access. NIH committed safeguarding interests study participants maintaining public trust biomedical research. Therefore, NIH seeking public feedback this proposed data management update. History Access Genomic Summary Results 2007, NIH issued policy sharing data generated through NIH-supported genome wide association studies GWAS),7 launched Database Genotypes Phenotypes dbGaP).8 2014, GWAS Policy subsumed under NIH GDS Policy, applies all large-scale genomic data generated NIH-funded research. Under both policies, dbGaP other NIH-designated data repositories provided data through two-tiered system: 1) unrestricted access, includes descriptions available data, research protocols instruments used collect it, summary-level information the data; 2) controlled access, provides individual-level genomic phenotypic data appropriate research purposes under terms are consistent the informed consent under those data collected. Under NIH GWAS Policy, genomic summary results originally included among summary-level information available through unrestricted access. However, 2008 paper Homer et al. demonstrated statistical method the potential resolve individual’s inclusion a member a research group e.g., within disease group) using genomic summary results.9 Notably, method, well others have followed using genomic information types,10,11 requires independent access a known individual’s whole genome data order predict statistical matches’ information within genomic summary results. NIH responded this development moving genomic summary results controlled access portions NIH-designated data repositories. agency also stated intent further assess risks benefits associated unrestricted access this type information light the new methodology.12 basis the 2008 data management change that matching a known individual a disease case’) group within research study might reveal unknown health phenotype information obvious the independently acquired whole genome data.13   Although NIH maintains genomic summary results dbGaP under controlled-access model, research community since developed several highly utilized valuable public data resources share genomic summary results.14 addition, type information continues be publicly available an element published studies the scientific literature. Despite broad availability genomic summary results, NIH not aware any reported examples date individuals being matched participation a research study beyond research analyses designed demonstrate hypothetical possibility such unintended use.15    NIH Discussions Related Genomic Summary Results Access 2012, NIH held Workshop entitled Establishing Central Resource Data Genome Sequencing Projects”16 consider wide scope issues related aggregating genomic data. During discussions, workshop participants noted value genomic summary results scientific clinical discovery, recommended they publicly available—when appropriate. Also 2012, enable access genomic summary results General Research Use17 studies through single data access request, compilation genomic summary results appropriate studies made available through dbGaP.18,19 addition more efficient access this type information, creation the compilation study’ also it possible reduce unnecessary access individual-level genomic data since, that time, only to obtain access genomic summary results under GDS Policy in conjunction the full data set. 2016, NHGRI convened Workshop entitled Sharing Aggregate Genomic Data” explicitly re-consider risks benefits associated access and of genomic summary results.20  Workshop participants highlighted minimal risk associated public access genomic summary results supported open access model most studies.21  Participants note alternate access models should considered sensitive studies where may heightened concerns.   solicit broad input the risks benefits different access models genomic summary results, NIH included topic the February 2017 Request Information RFI) Processes dbGaP Data Submission, Access, Management.”22 Public comments received suggest support broader access genomic summary results, especially under scenarios include additional risk mitigation strategies genomic summary results sensitive studies.23 Proposed Update Genomic Summary Results Access maximize public benefit genomic information generated through NIH-supported research a manner consistent current scientific ethical considerations,24,25,26,27 NIH promote broad sharing genomic summary results most research studies data held an NIH-designated data repository through new rapid access” tier. Rapid access enable access appropriate genomic summary results after interested users affirm agreement a statement regarding responsible of information below). proposed update the GDS Policy’s data management practices support NIH’s goals promote scientific advances protect research participants’ privacy interests reducing need users request controlled access individual-level genomic data, unless is necessary address specific research questions. addition, proposed data management change establishes access model genomic summary results is proportional the distinct risks associated access this type information relative the risks associated access individual-level genomic data.28 Genomic summary results be available include those provided a study’s investigator, any, well summary statistics computed the relevant NIH-designated data repository across non-sensitive studies data included that repository below). Genomic summary results provided include systematically computed statistics such as, not limited to:  genotype counts frequencies; allele counts frequencies; effect size estimates standard errors; likelihoods; p-values. values be defined calculated using scientifically relevant subsets research participants included within study populations e.g., disease, trait-based, control populations). Information methods computing any summary statistics provided an NIH-designated data repository be available through repository’s website.      is possible privacy risks related broad access genomic summary results be heightened study populations isolated geographic regions with rare traits. is also possible certain study populations be vulnerable group harm due potential stigma related traits being studied other participant protection concerns. addition, studies include data potentially stigmatizing traits, outcomes any privacy breach conceivably cause greater harm research participants is likely under most circumstances. address types sensitivities, institutions submitting datasets NIH-designated data repositories indicate the data sharing plan the Institutional Certification29 genomic summary results such studies should provided only through controlled access.   the purposes this proposed data management update, examples potentially stigmatizing traits expected include, not limited to: illicit drug substance abuse; HIV/AIDS diagnosis; sexual attitudes, preferences, practices. Increased privacy risk heightened risk group harm anticipated stem study populations draw from, are limited to: rare disease communities; studies small sample sizes; isolated identifiable study populations, such indigenous populations underrepresented ethnic groups. Informational Resources support awareness the ethical responsibilities associated responsible of genomic information including genomic summary results), NIH develop informational resources be publicly available through relevant NIH-designated data repositories. Before genomic summary results made accessible through new rapid access’ tier, users affirm they reviewed informational resources provided below). Affirming Responsible of Genomic Summary Results promote responsible of genomic summary results available through rapid access mechanism, users affirm agreement advance science health through use the information. affirmation be achieved via click-through agreement’ users confirm intent use genomic summary results provided responsibly indicating they: 1. Reviewed informational resources available NIH-designated data repositories describing appropriate uses genomic data, including genomic summary results; 2. not attempt re-identify contact any individual group within study population, generate information could allow participants’ identities be readily ascertained; and, 3. promote scientific research health through any of genomic summary results. Informed Consent Consistent the expectations under NIH GDS Policy, NIH expects consent forms the informed consent process human genomic studies clearly articulate access plans data information generated through study, including genomic summary results. NIH expects consent processes other information available potential research participants be transparent participation an NIH-supported study infers acknowledgement investigators aggregate analyze data generated through study. NIH expects consent processes other information explain such analyses other summaries study information including genomic summary results) be shared the scientific literature through public scientific resources, such data sharing resources provide broad unrestricted access the information. Effective Date NIH expects proposed data management update access genomic summary results be effective upon final publication the update.  Proposed Implementation Plans After effective date this data management update, NIH-funded investigators performing research falls under scope the GDS Policy be expected indicate, their Genomic Data Sharing Plan, a study should designated sensitive the purposes access genomic summary results. determination should confirmed the Institutional Certification provided the NIH. datasets submitted to, for data already accessible through, NIH-designated data repositories prior the effective date this data management update, submitting institutions have six months indicate genomic summary results any study submitted one their investigators should maintained controlled access due concerns sensitivity study information. will possible request additional time complete assessment a particular dataset. such cases, genomic summary results that dataset remain controlled access until final determination received the funding Institute Center. a submitting institution confirms appropriateness broader access genomic summary results a particular study prior the end the six-month period, information be available through rapid access tier immediately Request Comments NIH seeking public feedback regarding proposed data management update accessing genomic summary results NIH-funded studies.  NIH encourages comments all stakeholders, is especially interested hearing members the general public, research participants, and/or broader patient community.  NIH seeking overall, general comments any aspect the proposed access model.  NIH also seeking feedback the following specific issues: 1. Risks benefits providing broad access genomic summary results most studies NIH-designated data repositories utilizing proposed rapid access mechanism associated click-through agreement. Risks benefits relate participant protection issues and/or scientific opportunity. 2. Risks benefits maintaining genomic summary results studies designated the submitting institution include sensitive information controlled access. Risks benefits relate participant protection issues and/or scientific opportunity. 3. Appropriateness the proposal institutions submitting study data under NIH GDS Policy indicate datasets should designated sensitive. 4. General comments any topic relevant unrestricted, rapid, controlled-access genomic summary results NIH-funded studies. NIH intends hold least public webinar the proposed data management update the GDS Policy, may also utilize opportunities answer questions receive feedback stakeholders they identified.  Submitting Response Comments the topic areas interest should submitted electronically the following webpage: https://osp.od.nih.gov/gsr-rfi/ mailed to: Office Science Policy OSP), National Institutes Health, 6705 Rockledge Drive, Suite 750, Bethesda, MD 20892, by fax to: 301-496-9839 October 20], 2017. Comments received, including any personal information, be posted without change after close the comment period the NIH GDS website https://osp.od.nih.gov/scientific-sharing/genomic-data-sharing/). Please not include any proprietary, classified, confidential, sensitive information your response. Please note the United States Government not pay the preparation any information submitted for use that information. NIH looks forward your input hope you share RFI document your colleagues. Updates this document, any, be noted. Government reserves right use any non-proprietary technical information summaries the state the science, any resultant solicitation(s). NIH use information gathered this RFI inform development modification data sharing databases, websites, policies practices, processes procedures, supporting documentation e.g., guidance, FAQs). References NIH Genomic Data Sharing Policy.  https://grants.nih.gov/grants/guide/notice-files/NOT-OD-14-124.html. 2 Aggregate data defined the NIH GDS Policy summary statistics compiled multiple sources individual-level data. 3 Summary statistics been defined calculated summary statistics, including genotype counts, allele frequencies, effect size estimates standard errors, p-values calculated a study sample. https://www.genome.gov/pages/policyethics/genomicdata/aggdatareport.pdf. 4 NIH Mission Goals. https://www.nih.gov/about-nih/what-we-do/mission-goals. 5 Lek, Monkol, et al. Analysis protein-coding genetic variation 60,706 humans." Nature 536, 285–291 18 August 2016). doi:10.1038/nature19057. 6 NIH-designated data repository any data repository maintained supported NIH either directly through collaboration. 7 Policy Sharing Data Obtained NIH Supported Conducted Genome-Wide Association Studies GWAS).  https://grants.nih.gov/grants/guide/notice-files/NOT-OD-07-088.html. 8 NIH Launches dbGaP, Database Genome Wide Association Studies. https://www.nih.gov/news-events/news-releases/nih-launches-dbgap-databas.... 9 Homer N, Szelinger S, Redman M, et al. Resolving Individuals Contributing Trace Amounts DNA Highly Complex Mixtures Using High-Density SNP Genotyping Microarrays. Visscher PM, ed. PLoS Genetics. 2008;4(8):e1000167. doi:10.1371/journal.pgen.1000167. 10 Schadt, Eric E., Sangsoon Woo, Ke Hao. Bayesian method predict individual SNP genotypes gene expression data." Nature genetics 44.5 2012): 603-608. 11 Im, Hae Kyung, et al. sharing quantitative trait GWAS results an era multiple-omics data the limits genomic privacy." The American Journal Human Genetics 90.4 2012): 591-598. 12 https://osp.od.nih.gov/wp-content/uploads/Data_Sharing_Policy_Modificati.... 13 Zerhouni, E.A. Nabel, E.G. Protecting aggregate genomic data. Science. 2008 October 3; 322(5898): 44. Published online 2008 September 4. doi: 10.1126/science.1165490. 14 Genome Aggregation Database gnomAD); Exome Variant Server; Exome Aggregation Consortium ExAC); Type 2 Diabetes Knowledge Portal T2DKP); Michigan Imputation Server; AmbryShare; ClinVar, BRAVO Browse Variants Online, TOPMed’s WGS variant server). 15 Wendler DS, Rid A. Genetic Research Biospecimens Poses Minimal Risk. Trends genetics?: TIG. 2015;31(1):11-15. doi:10.1016/j.tig.2014.10.003. 16Workshop Establishing Central Resource Data Genome Sequencing Projects. 2012. National Institutes Health. https://www.genome.gov/27552142/workshop-on-establishing-a-central-resou.... 17NIH describes data available general research GRU) data no limitations restrictions beyond limitations outlined the Data Certification Agreement. See: https://osp.od.nih.gov/wp-content/uploads/NIH_PTC_in_Developing_DUL_Stat... see: https://osp.od.nih.gov/wp-content/uploads/standard_data_use_limitations.pdf.  18 Notice New Process Requesting dbGaP Access Aggregate Genomic Data General Research Purposes. https://grants.nih.gov/grants/guide/notice-files/NOT-OD-12-136.html. 19 https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs.... 20 NHGRI Workshop Sharing Aggregate Genomic Data. https://www.genome.gov/27566089/workshop-on-sharing-aggregate-genomic-da...   21 Workshop Report Sharing Aggregate Genomic Data. https://www.genome.gov/pages/policyethics/genomicdata/aggdatareport.pdf. 22 Request Information Processes dbGaP Data Submission, Access, Management. https://grants.nih.gov/grants/guide/notice-files/NOT-od-17-044.html. 23 https://osp.od.nih.gov/wp-content/uploads/dbGaP_Public_Comments_Data_Sub.... 24Erlich Y, Narayanan A. Routes breaching protecting genetic privacy. Nature reviews Genetics. 2014;15(6):409-421. doi:10.1038/nrg3723. 25Wendler DS, Rid A. Genetic Research Biospecimens Poses Minimal Risk. Trends Genetics?: TIG. 2015;31(1):11-15. doi:10.1016/j.tig.2014.10.003. 26 Sanderson, Saskia C., et al. Public Attitudes toward Consent Data Sharing Biobank Research: Large Multi-site Experimental Survey the US." The American Journal Human Genetics 100.3 2017): 414-427. 27 Gutmann, A. W., et al. Privacy progress whole genome sequencing." Presidential Committee the Study Bioethical 2012 2012). 28 Craig, D. W., Goor, R., Wang, Z., Paschall, J., Ostell, J., Feolo, M., & Manolio, T. A. Privacy Summary Level Data’; Assessing Managing Risk Sharing Aggregate Genetic Variant Data. Nature Reviews Genetics. 2011;12(10):730-736. doi:10.1038/nrg3067. 29 https://osp.od.nih.gov/scientific-sharing/institutional-certifications/ Inquiries Please direct inquiries to: NIH Office Science Policy Telephone: 301-496-9838 Email: SciencePolicy@od.nih.gov   data science, statistics
Rare Disease Cohorts in Heart, Lung, Blood and Sleep Disorders (UG3/UH3 Clinical Trial Not Allowed) RFA-HL-20-014 NHLBI Apr 04 2019 Jun 18 2020 The purpose of this FOA is to fund research centers that will establish longitudinal cohorts in rare HLBS diseases to investigate unaddressed research questions using epidemiologic study designs and methods that are appropriate for conditions affecting fewer than 200,000 persons in the US. These observational cohort studies should be designed to provide an evidence base for future interventional studies, including clinical trials; for developing better diagnostics than those that are currently available; for answering early translational questions; or for broader implementation of guidelines for managing these diseases. This program will provide opportunities to advance rare disease research using genetics and deep phenotyping to characterize the disease and to identify disease sub-types; to use data science methods that integrate clinical and patient-reported outcomes (PROs) with laboratory, imaging, environmental and -omics data to understand the natural history of disease; to generate data that differentiate patients with the same morphological phenotype but different genetic mutations and severity of outcomes; to elucidate genotype-phenotype interactions and multisystem phenotyping to develop reliable and valid predictive tools to determine who will respond to which treatments and when to intervene; and to encourage innovative methods such as telemedicine to include participants with rare diseases located in remote locations. This initiative will allow applicants to study related rare diseases, disorders, conditions or syndromes together based on pathogenesis, affected biochemical, cellular or physiological features or organ system involvement. Studying related rare diseases within the same cohort could help understand the nuances, and knowledge gained from one disease and could accelerate the advances in related diseases. For example, investigators may propose to study hemoglobin disorders rather than only sickle cell anemia or thalassemia. data science
Radiobiology of High Linear Energy Transfer (High LET) Exposure in Cancer Treatment (R01, Clinical Trial Not Allowed) RFA-CA-20-032 NCI Jan 10 2020 Mar 20 2020 The purpose of this Funding Opportunity Announcement (FOA) is to support multidisciplinary research projects that examine the relative biological effectiveness (RBE) of high linear energy transfer (high LET) radiation on cell and tissue targets. The overall goal of the research is to establish a firm scientific basis for RBE models of high LET radiation and determine potential benefits in cancer treatment. A meritorious application is expected to be well-balanced in terms of interdisciplinary science that spans approaches in both radiation biology and radiation physics research. Priorities for this FOA are on 1) Applications with potential to enhance the understanding of mechanisms related to high LET effects in both cancer and normal tissues; and 2) Characterization of high LET effects that have potential to inform treatment strategies for cancers resistant to conventional radiation or other combined modality treatments.
Pilot Services Research Grants Not Involving Clinical Trials (R34 Clinical Trial Not Allowed) PAR-19-189 NIMH Feb 21 2019 Jan 08 2022 The purpose of this funding announcement is to encourage pilot research that is not an immediate precursor to testing a service intervention but is consistent with NIMH priorities for services research. While NIMH now requires use of an experimental therapeutics model for all intervention studies, there is recognition that some mission-relevant areas of services research do not involve clinical trials.

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