FOA Title: 
Request for Information (RFI) on the NIH Big Data to Knowledge (BD2K) Initiative Resources for Teaching and Learning Biomedical Big Data Management and Data Science
Grant Type: 
Primary IC: 
Release Date: 
Nov 04 2014
Expiration Date: 
AC Source: 
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 , 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: