Data Science Community News
NLM Director Dr. Patricia Flatley Brennan Appointed Interim NIH Associate Director for Data Science
ON JANUARY 6, 2017, the National Institutes of Health announced that National Library of Medicine Director Patricia Flatley Brennan, RN, PhD will assume an additional role as NIH Interim Associate Director for Data Science.
The Associate Director for Data Science (ADDS) and team provide input to the overall NIH vision and actions undertaken by each of the 27 Institutes and Centers in support of biomedical research as a digital enterprise. Among other duties, the office oversees the Big Data to Knowledge (BD2K) initiative, stimulating the best developments in the data science community.
This year will see the transition of trans-NIH data science initiatives to NLM, with the operational oversight of the BD2K initiatives being housed within the Common Funds programs in the Division of Program Coordination, Planning and Strategic Initiatives. This change builds on the recommendations by the NLM Working Group Report to the NIH Director, makes concrete steps towards the vision of NLM’s future proclaimed in the Advisory Committee to the NIH Director’s report—that the National Library of Medicine become the “epicenter of data science for the NIH.”
“I believe the future of health and health care rests on data—genomic data, environmental sensor-generated data, electronic health records data, patient-generated data, research collected data,” Dr. Brennan observed. “The data originating from research projects is becoming as important as the answers those research projects are providing.”
“NLM must play a key role in preserving data generated in the course of research, whether conducted by professional scientists or citizen scientists,” she continued. “We know how to purposefully create collections of information and organize them for viewing and use by the public. We can extend this skill set to the curation of research data. We also have the utilities in place to protect the data by making sure only those individuals with permission to access data can actually do so.”
“NLM is well positioned to add these new functions to its research portfolio,” the NLM Director observed. “In this new year and the years to follow, we welcome these exciting opportunities and challenges.”
Big Data to Knowledge Multi-Council Working Group - January 2017
Notice is hereby given of a meeting of the Big Data to Knowledge (BD2K) Multi-Council Working Group.
Name of Working Group: Big Data to Knowledge Multi-Council Working Group
Date: January 9, 2017 - Canceled
This portion of the meeting is open to the public and is being held by teleconference. This is a listen ONLY meeting. Please submit any questions or comments via email to the contact person listed below.
Join WebEx Meeting
Meeting number: 627 298 875
Meeting password: 1234
Open Session: 11:00am - 12:00pm ET
Discussion will review current Big Data to Knowledge (BD2K) activities and newly proposed BD2K initiatives.
- Roll Call and Introduction
- Update from the Associate Director for Data Science
- BD2K All Hands Meeting and Open Data Science Symposium Recap
Closed Session: 12:30pm - 3:00pm ET
Agenda: Discussion will focus on review of proposed FY17 Funding Plans for BD2K Funding Opportunity Announcements and Administrative Supplements.
Individuals who plan to attend and need special assistance, such as sign language interpretation or other reasonable accommodations, should notify Tonya Scott, email: Tonya.Scott@nih.gov, phone: 301-402-9817.
Federal Register Meeting Announcement:
National Institutes of Health, Office of the Director - Notice of Meeting
Public Voting Determines Three Finalists for the Open Science Prize
Public voting for the Open Science Prize is now closed. Thank you to everyone who voted. The 3 prototypes which scored highest and will therefore be going forward to the next stage of review are:
MyGene2: Accelerating Gene Discovery with Radically Open Data Sharing
Real-Time Evolutionary Tracking for Pathogen Surveillance and Epidemiological Investigation
We will now be collecting expert reviews of these three prototypes. We anticipate announcing the the Grand Prize winner in early March 2017.
For additional information, contact: Elizabeth.Kittrie@nih.gov.
Need Cloud for Your Research? Calling All NIH Extramural Investigators
The NIH Big Data to Knowledge (BD2K) initiative has partnered with the CMS Alliance to Modernize Healthcare (CAMH), operated by MITRE, to launch and test a new funding paradigm that will provide NIH extramural researchers with access to cloud computing and storage capabilities. This funding model, called the Commons Credits Pilot, will provide extramural biomedical investigators with active NIH grants access to cloud-based environments to network, securely store, and share their work in the form of digital objects.
The first cycle for applications is open now through January 16, 2017.
Successful pilot applicants will receive dollar-denominated “credits” to obtain cloud-based computing and storage resources through an online market environment. Currently, the Commons Credits Pilot environment offers a variety of conformant cloud providers, including IBM, Seven bridges, and resellers of Google and Amazon. This list will grow as more vendors become available. Investigators will have the flexibility to select their preferred cloud provider from the list and provide feedback to NIH on their experiences. The Commons Credits Pilot is not a grants program; it has shorter application requirements and review times, ensuring that the credits are dispensed rapidly to keep pace with novel research.
An active NIH extramural grant is required for participation in the Commons Credits Pilot. Successful applications will likely complement the current grant(s) to enable novel research that may not have been accomplished or funded through other outlets. NIH expects that requests will not typically exceed $50,000 in dollar-denominated credits.
To date, the NIH Commons Credits Pilot has been shared with researchers at various research institutes and conferences, including the BD2K All-Hands Meeting held November 29-30, 2016. NIH encourages active NIH grant holders to take advantage of this new funding mechanism and we hope that you’ll also share this opportunity with your respective institutes.
Interested researchers should register and apply now at: http://www.commons-credit-portal.org. The Commons Credits Pilot team has created a short instructional video describing the application process within the portal to facilitate participation. To stay connected on the latest news regarding the NIH Commons Credit Pilot:
Please share this very exciting announcement with your extramural reasearch communities. For additional information, email the Commons Credits Pilot Team at: firstname.lastname@example.org.
Public Voting for the Open Science Prize is LIVE!
Public voting for the Open Science Prize is LIVE!
Help shape new directions in biomedical research by VOTING HERE.
Voting will be open December 1, 2016 through January 6, 2017 at 11:59pm PST.
In the spirit of Open Science, we invite you to help decide which of the prototypes competing for the Open Science Prize will be considered for the final grand prize. You will be asked to review 6 prototypes developed by the finalist teams and cast your vote for the most novel and impactful ones. The 3 prototypes receiving the highest number of public votes will advance to a final round of review by a panel of science experts and judges. A single, grand prize winner of $230,000 will be announced in March 2017.
In this competition, the teams were challenged to use open, publicly accessible data to improve human health. Each team produced prototypes that demonstrate how the power of Open Data can be harnessed to address a wide array of human health concerns through crowdsourcing or the development of innovative platforms on which to conduct computational modeling. Each team includes at least one U.S. and one international member with the goal of forging new collaborations with health and technology innovators from across the world, benefiting the global research community and the public in the process.
We invite you to watch the video demonstrations and test drive the prototypes before voting at: https://www.openscienceprize.org/. An archive of the NIH Open Data Science Symposium webcast is available here: http://www.tvworldwide.com/events/bd2k/161129/default.cfm?id=16845&type=flv&test=0&live=0, if you would like to watch the onstage prototype demonstrations or any other presentations from the Big Data to Knowledge (BD2K) All Hands Meeting (November 29-30) or Open Data Science Symposium (December 1).
The winning prototype will be selected by the National Institutes of Health and the Wellcome Trust and publically announced in March 2017. For additional information, email: Elizabeth.Kittrie@nih.gov.
The Open Science Prize is a collaboration between the National Institutes of Health (Bethesda, MD, USA) and the Wellcome Trust (London, UK), with additional funding provided by the Howard Hughes Medical Institute (Chevy Chase, MD, USA). This opportunity is being funded in part by the NIH Big Data to Knowledge (BD2K) Initiative.
We appreciate your help with getting the word out to your stakeholder communities about this worldwide public voting opportunity. Thank you for voting and helping to support the Open Science Prize.
bioCADDIE DataMed Version 1.5 Now Live
The bioCADDIE development team announces the release of DataMed Version 1.5, a Data Discovery Index (DDI) prototype
…with enhancements and important code corrections!
Thanks to user feedback, the DDI prototype has many new usability enhancements and code corrections.
New features introduced:
- Increased coverage to twice the number of biomedical data repositories
- Total number of datasets doubled
- Repositories mapped to DATS 2.1 metadata model
- Sorting on publication date of the dataset
- Visualization of results via timeline
- Usability enhancements based on user feedback and user interviews
User-reported issues resolved:
- Search capabilities expanded to include search by dataset IDs, PMIDs
- Compatibility with Google Chrome fixed
- Generate collections from search results
- Ability to view results in different formats
- Links to related datasets
- and Many More Features...!
DataMed is a work in progress and the bioCADDIE development team welcomes your feedback HERE.
Get involved in the bioCADDIE project and DataMed user studies!
For more details, contact: Anupama.E.Gururaj@uth.tmc.edu or email@example.com.
IEEE 2016 International Conference on Data Science and Advanced Analytics (DSAA 2016)
IEEE 2016 International Conference on Data Science and Advanced Analytics (DSAA 2016)
October 17-19, 2016 - Montreal, Canada
Special Session on Health Data Science (HDS)
Aims and Scope:
The health sector has been recently experiencing an increasing accessibility and availability of public and private data from various sources. This wide range of data sources are the result of: 1) the continuing investment in the digitization of health records, 2) the availability of an increasing number of health-related mobile and web-enabled applications, and 3) the use of social media for community-focused health research. This data presents a unique and cost-effective opportunity for knowledge discovery and has the potential to accelerate research while enabling the translation of the research findings to direct benefits to the community. This session brings together scientists, engineers, and researchers from academia and industry in order to discuss:
- The development of algorithms, tools, and techniques that can enhance our understanding of health data
- The use of large data sets to conduct health-focused studies
- The use of social networks to influence community behavior
Contributions that clearly demonstrate the benefits of large scale studies and systems as opposed to traditional studies and systems are highly solicited.
Deadline has been extended to June 12, 2016. For more information, click here.
Exponential Medicine 4-Day Program in San Diego
Exponential Medicine (October 8-11, 2016) is a unique and intensive cross-disciplinary 4-day program that brings together world-class faculty, innovators and organizations from across the biomedical and technology spectrum (from mobile health & 3D printing, to A.I., robotics, synthetic biology, and beyond) to explore and leverage the convergence of fast moving technologies in the reinvention and future of health and medicine. The program will focus on how computing through robotics, big data, and artificial intelligence will cause a disruptive change in medicine.
For more information, visit https://exponential.singularityu.org/medicine/
This program is sponsored by Singularity University. In computing, singularity “is a hypothetical event in which artificial general intelligence would be capable of recursive self-improvement and is the point beyond which events may become unpredictable or even unfathomable to human intelligence.”
Extracting Insights from Healthcare Data with Deep Learning
The Office of the Associate Director for Data Science (ADDS) announces a training opportunity in Deep Learning. This day-long, in-depth workshop is the second session of a two-part series. Part 1 (September 8), is an hour-long overview of deep learning followed by a half hour for questions. Part 2 (September 22), is a day-long, in-depth workshop. Attending or watching the overview first is highly recommended. Registration is required for the September 22 workshop, but not for the September 8 lecture.
Title: Extracting Insights from Healthcare Data with Deep Learning
Date: September 22, 9:00am - 5:00pm ET
Location: Building 31, 6C Room 10, NIH Bethesda campus
This event is a hands-on workshop and will not be videocast.
Open to NIH only; registration required.
Register for this course: https://datascience.nih.gov/deeplearningreg
Information on all upcoming courses: https://datascience.nih.gov/community/workforce/upcoming
Abstract: Recent years have seen a dramatic increase in the amount of healthcare-related data being collected. Now we need powerful analysis tools to extract insights and understanding from these mountains of data. A new approach called Deep Learning - based on neural networks inspired by the brain - is proving to be very effective in a wide range of research, diagnostic, and clinical applications. Join us to learn how advanced deep learning techniques are being applied to these rich data sets to help solve problems in diagnosis of diabetic retinopathy, calculating ventricular ejection fraction, and predicting survival in a Pediatric ICU. We will cover a variety of frameworks, tools, and languages including: DIGITS, Caffe, MXNet, Keras, MATLAB, R, Python, and more. The hands-on exercises will help you get started with applying deep learning to your own work.
For additional information, contact Sonynka Ngosso, 301-402-9816.
Computational Biology: Past, Present, and Future PLOS Symposium
Time: 9:30am - 4:00pm ET
Place: Porter Neuroscience Research Center, Bldg 35A, Rm 620, on the NIH Bethesda campus.
For those unable to attend, the event will be webcast here: https://videocast.nih.gov/summary.asp?live=19639&bhcp=1
Agenda: The Symposium will be chaired by PLOS Editors-in-Chief Ruth Nussinov and Jason Papin and the Journal’s Founding Editor-in-Chief, Dr. Phil Bourne, Associate Director for Data Science, NIH. Keynote addresses will include: David J. Lipman, NCBI; Jennifer Lippincott-Schwartz, Eunice Kennedy Shriver National Institute of Child Health and Human Development; and Bert Vogelstein, Johns Hopkins School of Medicine. The agenda also includes two discussion panels served by PLOS Computational Biology editors from a range of fields. The morning panel will discuss the “Biggest Challenges and Greatest Opportunities in Computational Biology over the Next 10 Years”. The afternoon panel will discuss “How Computational Biology Will Affect Human Health”. The Symposium is open to all NIH/HHS staff and the wider community. Closing remarks will be given by Dr. Michael Gottesman, Deputy Director of Intramural Research, NIH. Please share this invitation with your scientific communities. For additional information, contact: firstname.lastname@example.org.
Read the blog post about the Symposium in PLOS Biologue.