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What is Big Data Technology?
In March 2012, the Obama Administration announced the “Big Data Research and Development
Initiative.” By improving our ability to extract knowledge and insights from large and complex
collections of digital data, the initiative promises to help accelerate the pace of discovery in
science and engineering, strengthen our national security and transform teaching and learning.
To launch the initiative, six Federal departments and agencies announced more than $200 million
in new commitments that, together, promise to greatly improve the tools and techniques needed
to access, organize, and glean discoveries from huge volumes of digital data.
Some companies are already sponsoring Big Data-related competitions and providing funding
for university research. Universities are beginning to create new courses—and entire courses of
study—to prepare the next generation of “data scientists.” Organizations like Data Without
Borders are helping non-profits by providing pro bono data collection, analysis, and
visualization. OSTP would be very interested in supporting the creation of a forum to highlight
new public-private partnerships related to Big Data.
Big Data Across the Federal Government
March 29, 2012
Below are highlights of ongoing Federal government programs that address the challenges of,
and tap the opportunities afforded by, the big data revolution to advance agency missions and
further scientific discovery and innovation.
DEPARTMENT OF DEFENSE (DOD)
Data to Decisions: The Department of Defense (DOD) is “placing a big bet on big data”
investing $250 million annually (with $60 million available for new research projects) across the
Military Departments in a series of programs that will:
Harness and utilize massive data in new ways and bring together sensing, perception and
decision support to make truly autonomous systems that can maneuver and make decisions on
their own.
Improve situational awareness to help warfighters and analysts and provide increased support
to operations. The Department is seeking a 100-fold increase in the ability of analysts to extract
information from texts in any language, and a similar increase in the number of objects,
activities, and events that an analyst can observe.
To accelerate innovation in Big Data that meets these and other requirements, DOD will
announce a series of open prize competitions over the next several months.
DEFENSE ADVANCED RESEARCH PROJECTS AGENCY (DARPA)
The Anomaly Detection at Multiple Scales (ADAMS) program addresses the problem of
anomaly-detection and characterization in massive data sets. In this context, anomalies in data
are intended to cue collection of additional, actionable information in a wide variety of real-
world contexts. The initial ADAMS application domain is insider threat detection, in which
anomalous actions by an individual are detected against a background of routine network
activity.
The Cyber-Insider Threat (CINDER) program seeks to develop novel approaches to detect
activities consistent with cyber espionage in military computer networks. As a means to expose
hidden operations, CINDER will apply various models of adversary missions to "normal"
activity on internal networks. CINDER also aims to increase the accuracy, rate, and speed with
which cyber threats are detected.
The Insight program addresses key shortfalls in current intelligence, surveillance and
reconnaissance systems. Automation and integrated human-machine reasoning enable operators
to analyze greater numbers of potential threats ahead of time-sensitive situations. The Insight
the program aims to develop a resource management system to automatically identify the threat
networks and irregular warfare operations through the analysis of information from imaging and
non-imaging sensors and other sources.
The Machine Reading program seeks to realize artificial intelligence applications by developing
learning systems that process natural text and insert the resulting semantic representation into a
knowledge base rather than relying on expensive and time-consuming current processes for
knowledge representation require expert and associated knowledge engineers to handcraft
information.
The Mind's Eye program seeks to develop a capability for “visual intelligence” in machines.
Whereas the traditional study of machine vision has made progress in recognizing a wide range of
objects and their properties—what might be thought of as the nouns in the description of a
scene—Mind's Eye seeks to add the perceptual and cognitive underpinnings needed for
recognizing and reasoning about the verbs in those scenes. Together, these technologies could
enable a more complete visual narrative.
The Mission-oriented Resilient Clouds program aims to address security challenges inherent in
cloud computing by developing technologies to detect, diagnose and respond to attacks,
effectively building a “community health system” for the cloud. The program also aims to
develop technologies to enable cloud applications and infrastructure to continue functioning
while under attack. The loss of individual hosts and tasks within the cloud ensemble would be
allowable as long as overall mission effectiveness was preserved.
The Programming Computation on Encrypted Data (PROCEED) research effort seeks to
overcome a major challenge for information security in cloud-computing environments by
developing practical methods and associated modern programming languages for computation on
data that remains encrypted the entire time it is in use. By manipulating encrypted data without
first decrypting it, adversaries would have a more difficult time intercepting data.
The Video and Image Retrieval and Analysis Tool (VIRAT) program aim to develop a system
to provide military imagery analysts with the capability to exploit the vast amount of overhead
video content being collected. If successful, VIRAT will enable analysts to establish alerts for
activities and events of interest as they occur. VIRAT also seeks to develop tools that would
enable analysts to rapidly retrieve, with high precision and recall, video content from extremely
large video libraries.
The XDATA program seeks to develop computational techniques and software tools for
analyzing large volumes of semi-structured and unstructured data. Central challenges to be
addressed include scalable algorithms for processing imperfect data in distributed data stores and
effective human-computer interaction tools that are rapidly customizable to facilitate visual
the reasoning for diverse missions. The program envisions open source software toolkits for flexible
software development that enables processing of large volumes of data for use in targeted defense
applications.
DEPARTMENT OF HOMELAND SECURITY (DHS)
The Center of Excellence on Visualization and Data Analytics (CVADA), a collaboration among
researchers at Rutgers University and Purdue University (with three additional partner
universities each) leads research efforts on large, heterogeneous data that First Responders could
use to address issues ranging from manmade or natural disasters to terrorist incidents; law
enforcement to border security concerns; and explosives to cyber threats.
DEPARTMENT OF ENERGY (DOE)
The Office of Advanced Scientific Computing Research (ASCR) provides leadership to the data
management, visualization, and data analytics communities including digital preservation and
community access. Programs within the suite include widely used data management technologies
such as the Kepler scientific workflow system; and Storage Resource Management standard; a
variety of data storage management technologies, such as BeSTman, the Bulk Data Mover and
the Adaptable IO System (ADIOS); FastBit data indexing technology (used by Yahoo!); and two
major scientific visualization tools, ParaView, and VisIt.
The High-Performance Storage System (HPSS) is software that manages petabytes of data on
disks and robotic tape systems. Developed by DoE and IBM with input from universities and
labs around the world, HPSS is used by digital libraries, defense applications and a range of
scientific disciplines including nanotechnology, genomics, chemistry, magnetic resonance
imaging, nuclear physics, computational fluid dynamics, climate science, etc., as well as
Northrop Grumman, NASA, and the Library of Congress.
Mathematics for Analysis of Petascale Data addresses the mathematical challenges of extracting
insights from huge scientific datasets and finding key features and understanding the
relationships between those features. Research areas include machine learning, real-time analysis
of streaming data, stochastic nonlinear data-reduction techniques, and scalable statistical analysis
techniques applicable to a broad range of DOE applications including sensor data from the
the electric grid, cosmology, and climate data.
The Next Generation Networking program supports tools that enable research collaborations to
find, move and use large data: from the Globus Middleware Project in 2001 to the GridFTP data
transfer protocol in 2003, to the Earth Systems Grid (ESG) in 2007. Today, GridFTP servers
move over 1 petabyte of science data per month for the Open Science Grid, ESG, and Biology
communities. Globus middleware has also been leveraged by a collaboration of Texas
universities, software companies, and oil companies to train students in state-of-the-art
petroleum engineering methods and integrated workflows.
March 29, 2012
Below are highlights of ongoing Federal government programs that address the challenges of,
and tap the opportunities afforded by, the big data revolution to advance agency missions and
further scientific discovery and innovation.
DEPARTMENT OF DEFENSE (DOD)
Data to Decisions: The Department of Defense (DOD) is “placing a big bet on big data”
investing $250 million annually (with $60 million available for new research projects) across the
Military Departments in a series of programs that will:
Harness and utilize massive data in new ways and bring together sensing, perception and
decision support to make truly autonomous systems that can maneuver and make decisions on
their own.
Improve situational awareness to help warfighters and analysts and provide increased support
to operations. The Department is seeking a 100-fold increase in the ability of analysts to extract
information from texts in any language, and a similar increase in the number of objects,
activities, and events that an analyst can observe.
To accelerate innovation in Big Data that meets these and other requirements, DOD will
announce a series of open prize competitions over the next several months.
DEFENSE ADVANCED RESEARCH PROJECTS AGENCY (DARPA)
The Anomaly Detection at Multiple Scales (ADAMS) program addresses the problem of
anomaly-detection and characterization in massive data sets. In this context, anomalies in data
are intended to cue collection of additional, actionable information in a wide variety of real-
world contexts. The initial ADAMS application domain is insider threat detection, in which
anomalous actions by an individual are detected against a background of routine network
activity.
The Cyber-Insider Threat (CINDER) program seeks to develop novel approaches to detect
activities consistent with cyber espionage in military computer networks. As a means to expose
hidden operations, CINDER will apply various models of adversary missions to "normal"
activity on internal networks. CINDER also aims to increase the accuracy, rate, and speed with
which cyber threats are detected.
The Insight program addresses key shortfalls in current intelligence, surveillance and
reconnaissance systems. Automation and integrated human-machine reasoning enable operators
to analyze greater numbers of potential threats ahead of time-sensitive situations. The Insight
the program aims to develop a resource management system to automatically identify the threat
networks and irregular warfare operations through the analysis of information from imaging and
non-imaging sensors and other sources.
The Machine Reading program seeks to realize artificial intelligence applications by developing
learning systems that process natural text and insert the resulting semantic representation into a
knowledge base rather than relying on expensive and time-consuming current processes for
knowledge representation require expert and associated knowledge engineers to handcraft
information.
The Mind's Eye program seeks to develop a capability for “visual intelligence” in machines.
Whereas the traditional study of machine vision has made progress in recognizing a wide range of
objects and their properties—what might be thought of as the nouns in the description of a
scene—Mind's Eye seeks to add the perceptual and cognitive underpinnings needed for
recognizing and reasoning about the verbs in those scenes. Together, these technologies could
enable a more complete visual narrative.
The Mission-oriented Resilient Clouds program aims to address security challenges inherent in
cloud computing by developing technologies to detect, diagnose and respond to attacks,
effectively building a “community health system” for the cloud. The program also aims to
develop technologies to enable cloud applications and infrastructure to continue functioning
while under attack. The loss of individual hosts and tasks within the cloud ensemble would be
allowable as long as overall mission effectiveness was preserved.
The Programming Computation on Encrypted Data (PROCEED) research effort seeks to
overcome a major challenge for information security in cloud-computing environments by
developing practical methods and associated modern programming languages for computation on
data that remains encrypted the entire time it is in use. By manipulating encrypted data without
first decrypting it, adversaries would have a more difficult time intercepting data.
The Video and Image Retrieval and Analysis Tool (VIRAT) program aim to develop a system
to provide military imagery analysts with the capability to exploit the vast amount of overhead
video content being collected. If successful, VIRAT will enable analysts to establish alerts for
activities and events of interest as they occur. VIRAT also seeks to develop tools that would
enable analysts to rapidly retrieve, with high precision and recall, video content from extremely
large video libraries.
The XDATA program seeks to develop computational techniques and software tools for
analyzing large volumes of semi-structured and unstructured data. Central challenges to be
addressed include scalable algorithms for processing imperfect data in distributed data stores and
effective human-computer interaction tools that are rapidly customizable to facilitate visual
the reasoning for diverse missions. The program envisions open source software toolkits for flexible
software development that enables processing of large volumes of data for use in targeted defense
applications.
The Center of Excellence on Visualization and Data Analytics (CVADA), a collaboration among
researchers at Rutgers University and Purdue University (with three additional partner
universities each) leads research efforts on large, heterogeneous data that First Responders could
use to address issues ranging from manmade or natural disasters to terrorist incidents; law
enforcement to border security concerns; and explosives to cyber threats.
DEPARTMENT OF ENERGY (DOE)
The Office of Advanced Scientific Computing Research (ASCR) provides leadership to the data
management, visualization, and data analytics communities including digital preservation and
community access. Programs within the suite include widely used data management technologies
such as the Kepler scientific workflow system; and Storage Resource Management standard; a
variety of data storage management technologies, such as BeSTman, the Bulk Data Mover and
the Adaptable IO System (ADIOS); FastBit data indexing technology (used by Yahoo!); and two
major scientific visualization tools, ParaView, and VisIt.
The High-Performance Storage System (HPSS) is software that manages petabytes of data on
disks and robotic tape systems. Developed by DoE and IBM with input from universities and
labs around the world, HPSS is used by digital libraries, defense applications and a range of
scientific disciplines including nanotechnology, genomics, chemistry, magnetic resonance
imaging, nuclear physics, computational fluid dynamics, climate science, etc., as well as
Northrop Grumman, NASA, and the Library of Congress.
Mathematics for Analysis of Petascale Data addresses the mathematical challenges of extracting
insights from huge scientific datasets and finding key features and understanding the
relationships between those features. Research areas include machine learning, real-time analysis
of streaming data, stochastic nonlinear data-reduction techniques, and scalable statistical analysis
techniques applicable to a broad range of DOE applications including sensor data from the
the electric grid, cosmology, and climate data.
The Next Generation Networking program supports tools that enable research collaborations to
find, move and use large data: from the Globus Middleware Project in 2001 to the GridFTP data
transfer protocol in 2003, to the Earth Systems Grid (ESG) in 2007. Today, GridFTP servers
move over 1 petabyte of science data per month for the Open Science Grid, ESG, and Biology
communities. Globus middleware has also been leveraged by a collaboration of Texas
universities, software companies, and oil companies to train students in state-of-the-art
petroleum engineering methods and integrated workflows.
BES Scientific User Facilities have supported a number of efforts aimed at assisting users with
data management and analysis of big data, which can be as big as terabytes (10 12 bytes) of data
per day from a single experiment. For example, the Accelerating Data Acquisition, Reduction
and Analysis (ADARA) project addresses the data workflow needs of the Spallation Neutron
Source (SNS) data system to provide real-time analysis for experimental control; and the
Coherent X-ray Imaging Data Bank has been created to maximize data availability and more
efficient use of synchrotron light sources.
The Data and Communications in Basic Energy Sciences workshop in October 2011 sponsored
by BES and ASCR identified needs in experimental data that could impact the progress of
scientific discovery.
The Biological and Environmental Research Program (BER), Atmospheric Radiation
Measurement (ARM) Climate Research Facility is a multi-platform scientific user facility that
provides the international research community infrastructure for obtaining precise observations
of key atmospheric phenomena needed for the advancement of the atmospheric process
understanding and climate models. ARM data are available and used as a resource for over 100
journal articles per year. Challenges associated with collecting and presenting the high temporal
resolution and spectral information from hundreds of instruments are being addressed to meet
user needs.
The Systems Biology Knowledgebase (Kbase) is a community-driven software framework
enabling data-driven predictions of microbial, plant and biological community function in an
environmental context. Kbase was developed with an open design to improve algorithmically
development and deployment efficiency, and for access to and integration of experimental data
from heterogeneous sources. Kbase is not a typical database but a means to interpret missing
information to become a predictive tool for experimental design.
The Office of Fusion Energy Sciences (FES)
The Scientific Discovery through Advanced Computing (SciDAC) partnership between FES and
the office of Advanced Scientific Computing Research (ASCR) addresses big data challenges
associated with computational and experimental research in fusion energy science. The data
management technologies developed by the ASCR – FES partnerships include high performance
input/output systems, advanced scientific workflow and provenance frameworks, and
visualization techniques addressing the unique fusion needs, which have attracted the attention of
European integrated modeling efforts and ITER, international nuclear fusion research and
engineering project.
The Office of High Energy Physics (HEP)
The Computational High Energy Physics Program supports research for the analysis of large,
complex experimental data sets as well as large volumes of simulated data—an undertaking that
typically requires a global effort by hundreds of scientists. Collaborative big data management
ventures include PanDA (Production and Distributed Analysis) Workload Management System
and XRootD, a high performance, fault-tolerant software for fast, scalable access to data
repositories of many kinds.
The Office of Nuclear Physics (NP)
The US Nuclear Data Program (USNDP) is a multisite effort involving seven national labs and
two universities that maintain and provides access to extensive, dedicated databases spanning
several areas of nuclear physics, which compile and cross-check all relevant experimental results
on important properties of nuclei.
The Office of Scientific and Technical Information (OSTI)
OSTI, the only U.S. federal agency member of DataCite (a global consortium of leading
scientific and technical information organizations) play a key role in shaping the policies and
technical implementations of the practice of data citation, which enables efficient reuse and
verification of data so that the impact of data may be tracked, and a scholarly structure that
recognizes and rewards data producers may be established.
DEPARTMENT OF VETERANS AFFAIRS (VA)
Consortium for Healthcare Informatics Research (CHIR) develops Natural Language Processing
(NLP) tools in order to unlock vast amounts of information that are currently stored in VA as
text data.
Protecting Warfighters using Algorithms for Text Processing to Capture Health Events
(ProWatch): Efforts in the VA are underway to produce transparent, reproducible and reusable
software for surveillance of various safety-related events. ProWatch is a research-based
the surveillance program that relies on newly developed informatics resources to detect, track, and
measure health conditions associated with military deployment.
Aviva is the VA’s next-generation employment human resources system that will separate the
database from the business applications and from the browser-based user interface. Analytical
tools are already being built upon this foundation for research and ultimately the support of decisions
at the patient encounter.
Observational Medical Outcomes Project is designed to compare the validity, feasibility and
performance of various safety surveillance analytic methods.
Corporate Data Warehouse (CDW) is the VA program to organize and manage data from various
sources with delivery to the point of care for a complete view of the disease and treatment for
individuals and populations.
Health Data Repository is standardizing terminology and data format among health care
providers and notably between the VA and DOD, allowing the CDW to integrate data.
Genomic Information System for Integrated Science (GenISIS) is a program to enhance health
care for Veterans through personalized medicine. The GenISIS consortium serves as the contact
for clinical studies with access to the electronic health records and genetic data in order that
clinical trials, genomic trials, and outcome studies can be conducted across the VA.
Million Veteran Program is recruiting voluntary contribution of blood samples from veterans for
genotyping and genetic sequencing. These genetic samples support the GenISIS consortium and
will be attributed to the “phenotype” in the individual veteran’s health record for understanding
the genetic to disease states.
VA Informatics and Computing Infrastructure provides analytical workspace and tools for the
analysis of large datasets now available in the VA, promoting collaborative research from
anywhere on the VA network.
HEALTH AND HUMAN SERVICES (HHS)
Center for Disease Control & Prevention (CDC)BioSense 2.0 is the first system to take into account the feasibility of regional and national.
coordination for public health situation awareness through an interoperable network of systems,
built on existing state and local capabilities. BioSense 2.0 removes many of the costs associated
with monolithic physical architecture, while still making the distributed aspects of the system
transparent to end-users, as well as making data accessible for appropriate analyses and
reporting.
Networked phylogenomics for bacteria and outbreak ID. CDC’s Special Bacteriology Reference
Laboratory (SBRL) identifies and classifies unknown bacterial pathogens for effective, rapid
outbreak detection. Phylogenomics, the comparative phylogenetic analysis of the entire genome
The DNA sequence will bring the concept of sequence-based identification to an entirely new level
in the very near future with profound implications on public health. The development of an SBRL
genomic pipeline for new species identification will allow for multiple analyses on a new or
rapidly emerging pathogen to be performed in hours, rather than days or weeks.
Center for Medicare & Medicaid Services (CMS)
A data warehouse based on Hadoop is being developed to support analytic and reporting
requirements from Medicare and Medicaid programs. A major goal is to develop a supportable,
sustainable, and scalable design that accommodates accumulated data at the Warehouse level.
Also challenging is developing a solution that complements existing technologies.
The use of XML database technologies are being evaluated to support the transactional-
the intensive environment of the Insurance Exchanges, specifically to support the eligibility and
enrollment processes. XML databases potentially can accommodate Big Tables scale data, but
optimized for transactional performance.
Using administrative claims data (Medicare) to improve decision-making: CMS has a current set
of pilot projects with the Oak Ridge National laboratories that involve the evaluation of data
visualization tools, platform technologies, user interface options, and high performance
computing technologies--aimed at using administrative claims data (Medicare) to create usefully
information products to guide and support improved decision-making in various CMS high
priority programs.
FOOD AND DRUG ADMINISTRATION (FDA)
A Virtual Laboratory Environment (VLE) will combine existing resources and capabilities to
enable a virtual laboratory data network, advanced analytical and statistical tools and
capabilities, crowdsourcing of analytics to predict and promote public health, document management support, tele-presence capability to enable worldwide collaboration, and basically
make any location a virtual laboratory with advanced capabilities in a matter of hours.
NATIONAL ARCHIVES & RECORDS ADMINISTRATION (NARA)
The Cyberinfrastructure for a Billion Electronic Records (CI-BER) is a joint agency-sponsored
testbed notable for its application of a multi-agency sponsored cyberinfrastructure and the
National Archives' diverse 87+ million file collection of digital records and information now
active at the Renaissance Computing Institute. This testbed will evaluate technologies and
approaches to support sustainable access to ultra-large data collections.
NATIONAL AERONAUTICS & SPACE ADMINISTRATION (NASA)
NASA’s Advanced Information Systems Technology (AIST) awards seek to reduce the risk and
cost of evolving NASA information systems to support future Earth observation missions and to
transform observations into Earth information as envisioned by NASA’s Climate Centric
Architecture. Some AIST programs seek to mature Big Data capabilities to reduce the risk, cost,
size and development time of Earth Science Division space-based and ground-based information
systems and increase the accessibility and utility of science data.
NASA's Earth Science Data and Information System (ESDIS) project, active for over 15 years
has worked to process, archive, and distribute Earth science satellite data and data from airborne
and field campaigns. With attention to user satisfaction, it strives to ensure that scientists and the
the public have access to data to enable the study of Earth from space to advance Earth system
science to meet the challenges of climate and environmental change.
The Global Earth Observation System of Systems (GEOSS) is a collaborative, international
effort to share and integrate Earth observation data. NASA has joined forces with the U.S.
Environmental Protection Agency (EPA), National Oceanic and Atmospheric Administration
(NOAA), other agencies and nations to integrate satellite and ground-based monitoring and
modeling systems to evaluate environmental conditions and predict outcomes of events such as
forest fires, population growth, and other developments that are natural and man-made. In the
near-term, with academia, researchers will integrate a complex variety of air quality information
to better understand and address the impact of air quality on the environment and human health.
A Space Act Agreement, entered into by NASA and Cray, Inc., allows for collaboration on one
or more projects centered on the development and application of low-latency, “big data”
systems. In particular, the project is testing the utility of hybrid computers systems using a highly
integrated non-SQL database as a means for data delivery to accelerate the execution of
modeling and analysis software.NASA’s Planetary Data System (PDS) is an archive of data products from NASA planetary
missions, which has become a basic resource for scientists around the world. All PDS-produced
products are peer-reviewed, well-documented, and easily accessible via a system of online
catalogs that are organized by planetary disciplines.
The Multimission Archive at the Space Telescope Science Institute (MAST), a component of
NASA’s distributed Space Science Data Services supports and provide to the astronomical
community a variety of astronomical data archives, with the primary focus on scientifically
related data sets in the optical, ultraviolet, and near-infrared parts of the spectrum. MAST
archives and supports several tools to provide access to a variety of spectral and image data. The
Earth System Grid Federation is a public archive expected to support the research underlying the
International Panel on Climate Change’s Fifth Assessment Report to be completed in 2014 (as it
did for the Fourth Assessment Report). NASA is contributing both observational data and model
output to the Federation through collaboration with the DOE.
National Cancer Institute (NCI)
The Cancer Imaging Archive (TCIA) is an image data-sharing service that facilitates open
science in the field of medical imaging. TCIA aims to improve the use of imaging in today's
cancer research and practice by increasing the efficiency and reproducibility of imaging cancer
detection and diagnosis, leveraging imaging to provide an objective assessment of therapeutic
the response, and ultimately enabling the development of imaging resources that will lead to
improved clinical decision support.
The Cancer Genome Atlas (TCGA) project is a comprehensive and coordinated effort to
accelerate understanding of the molecular basis of cancer through the application of genome
analysis technologies, including large-scale genome sequencing. With the fast development of large
scale genomic technology, the TCGA project will accumulate several petabytes of raw data by
2014.
National Heart Lung and Blood Institute (NHLBI)
The Cardiovascular Research Grid (CVRG) and the Integrating Data for Analysis,
Anonymization and Sharing (iDASH) are two informatics resources supported by NHLBI which
provide secure data storage, integration, and analysis resources that enable collaboration while
minimizing the burden on users. The CVRG provides resources for cardiovascular research
community to share data and analysis tools. iDASH leads development in privacy-preserving
technology and is fostering an integrated data sharing and analysis environment. National Institute of Biomedical Imaging and Bioengineering (NIBIB).
The Development and Launch of an Interoperable and Curated Nanomaterial Registry, led by the
NIBIB institute seeks to establish a nanomaterial registry, whose primary function is to provide
consistent and curated information on the biological and environmental interactions of well-
characterized nanomaterials, as well as links to associated publications, modeling tools,
computational results and manufacturing guidance. The registry facilitates building standards
and consistent information on manufacturing and characterizing nanomaterials, as well as their
biological interactions.
The Internet-Based Network for Patient-Controlled Medical Image Sharing contract addresses
the feasibility of an image sharing model to test how hospitals, imaging centers, and physician
practices can implement cross-enterprise document sharing to transmit images and image reports.
As a Research Resource for Complex Physiologic Signals, PhysioNet offers free web access to
large collections of recorded physiologic signals (PhysioBank) and related open-source software
(PhysioToolkit). Each month, about 45,000 visitors worldwide use PhysioNet, retrieving about 4
terabytes of data.
The Neuroimaging Informatics Tools and Resource Clearinghouse (NITRC) is an NIH blueprint
project to promote the dissemination, sharing, adoption, and evolution of neuroimaging
informatics tools and neuroimaging data by providing access, information and forums for
interaction for the research community. Over 450 software tools and data sets are registered on
NITRC; the site has had over 30.1 million hits since its launch in 2007.
The Extensible Neuroimaging Archive Toolkit (XNAT) is an open-source imaging informatics
the platform, developed by the Neuroinformatics Research Group at Washington University, and
widely used by research institutions around the world. XNAT facilitates common management,
productivity and quality assurance tasks for imaging and associated data.
The Computational Anatomy and Multidimensional Modeling Resource The Los Angeles
Laboratory of Neuro Imaging (LONI) houses Databases that contain imaging data from several
modalities, mostly various forms of MR and PET, genetics, behavior, demographics and other
data. The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a good example of a project
that collects data from acquisition sites around the U.S., makes data anonymous, quarantines it
until quality control is done (often immediately) and then makes it available for download to
users around the world in a variety of formats.
The Computer-Assisted Functional Neurosurgery Database develops methods and techniques to
assist in the placement and programming of Deep Brain Stimulators (DBSs) used for the
treatment of Parkinson’s disease and other movement disorders. A central database has been
developed at Vanderbilt University (VU), which is collaborating with Ohio State and WakeForest universities to acquire data from multiple sites. Since the clinical workflow and the
stereotactic frames at different hospitals can vary, the surgical planning software has been
updated and successfully tested.
NIH Biomedical Information Science and Technology Initiative (BISTI) Consortium for over a
the decade has joined the institutes and centers at NIH to promote the nation’s research in
Biomedical Informatics and Computational Biology (BICB), promoted a number of programs
announcements and funded more than a billion dollars in research. In addition, the collaboration
has promoted activities within NIH such as the adoption of modern data and software sharing
practices so that the fruits of research are properly disseminated to the research community.
NIH Blueprint
The Neuroscience Information Framework (NIF) is a dynamic inventory of Web-based
neuroscience resources: data, materials, and tools accessible via any computer connected to the
Internet. An initiative of the NIH Blueprint for Neuroscience Research, NIF advances
neuroscience research by enabling discovery and access to public research data and tools
worldwide through an open-source, networked environment.
The NIH Human Connectome Project is an ambitious effort to map the neural pathways that
underlie human brain function and to share data about the structural and functional connectivity
of the human brain. The project will lead to major advances in our understanding of what makes
us uniquely human and will set the stage for future studies of abnormal brain circuits in many
neurological and psychiatric disorders.
NIH Common Fund
The National Centers for Biomedical Computing (NCBC) are intended to be part of the national
infrastructure in Biomedical Informatics and Computational Biology. The eight centers create
innovative software programs and other tools that enable the biomedical community to integrate,
analyze, model, simulate and share data on human health and disease.
Patient-Reported Outcomes Measurement Information System (PROMIS) is a system of highly
reliable, valid, flexible, precise, and responsive assessment tools that measure patient-reported
health status. A core resource is the Assessment Center which provides tools and a database to
help researchers collect, store, and analyze data related to patient health status.
National Institute of General Medical SciencesThe Models of Infectious Disease Agent Study (MIDAS) is an effort to develop computationally.
and analytical approaches for integrating infectious disease information rapidly and providing
modeling results to policymakers at the local, state, national, and global levels. While data need
to be collected and integrated globally, because public health policies are implemented locally,
the information must also be fine-grained, with needs for data access, management, analysis and
archiving.
The structural genomics initiative advances the discovery, analysis, and dissemination of three-
dimensional structures of protein, RNA and other biological macromolecules representing the
the entire range of structural diversity found in nature to facilitate fundamental understanding and
applications in biology, agriculture, and medicine. Worldwide efforts include the NIH funded
Protein Structure Initiative, Structural Genomics Centers for Infectious Diseases, Structural
Genomics Consortium in Stockholm and the RIKEN Systems and Structural Biology Center in
Japan. These efforts coordinate their sequence target selection through a central database,
TargetDB, hosted at the Structural Biology Knowledgebase.
The WorldWide Protein Data Bank (wwPDB), a repository for the collection, archiving and free
distribution of high quality macromolecular structural data to the scientific community on a
timely basis represents the preeminent source of experimentally determined macromolecular
structure information for research and teaching in biology, biological chemistry, and medicine.
The U.S. component of the project (RCSB PDB) is jointly funded by five Institutes of NIH,
DOE/BER and NSF, as well as participants in the UK and Japan. The single databank now
contains experimental structures and related annotation for 80,000 macromolecular structures.
The Web site receives 211,000 unique visitors per month from 140 different countries. Around 1
a terabyte of data is transferred each month from the website.
The Biomedical Informatics Research Network (BIRN), a national initiative to advance
biomedical research through data sharing and collaboration provides a user-driven, software-
based framework for research teams to share significant quantities of data – rapidly, securely and
privately – across geographic distance and/or incompatible computing systems, serving diverse
research communities.
National Library of Medicine
Informatics for Integrating Biology and the Bedside (i2b2), seeks the creation of tools and
approaches that facilitate integration and exchange of the informational by-products of
healthcare and biomedical research. Software tools for integrating, mining and representing data
that were developed by i2b2 are used at more than 50 organizations worldwide through an open
source sharing under open source governance. Office of Behavioral and Social Sciences (OBSSR)
The National Archive of Computerized Data on Aging (NACDA) program advances research on
aging by helping researchers to profit from the under-exploited potential of a broad range of
datasets. NACD preserves and makes available the largest library of electronic data on aging in
the United States.
Data Sharing for Demographic Research (DSDR) provides data archiving, preservation,
dissemination and other data infrastructure services. DSDR works toward a unified legal,
technical and substantive framework in which to share research data in the population sciences.
A Joint NIH - NSF Program
The Collaborative Research in Computational Neuroscience (CRCNS) is a joint NIH-NSF
program to support collaborative research projects between computational scientists and
neuroscientists that will advance the understanding of nervous system structure and function,
mechanisms underlying nervous system disorders and computational strategies used by the
nervous system. In recent years, the German Federal Ministry of Education and Research has
also joined the program and supported research in Germany.
NATIONAL SCIENCE FOUNDATION (NSF)
Core Techniques and Technologies for Advancing Big Data Science & Engineering (BIGDATA)
is a new joint solicitation between NSF and NIH that aims to advance the core scientific and
technological means of managing, analyzing, visualizing and extracting useful information from
large, diverse, distributed, and heterogeneous data sets. Specifically, it will support the
development and evaluation of technologies and tools for data collection and management, data
analytics, and/or e-science collaborations, which will enable breakthrough discoveries and
innovation in science, engineering, and medicine - laying the foundations for the U.S.
competitiveness for many decades to come.
Cyberinfrastructure Framework for 21st Century Science and Engineering (CIF21) develops,
consolidates, coordinates, and leverages a set of advanced cyberinfrastructure programs and
efforts across NSF to create meaningful cyberinfrastructure, as well as develop a level of
integration and interoperability of data and tools to support science and education.
CIF21 Track for IGERT. NSF has shared with its community plans to establish a new CIF21
track as part of its Integrative Graduate Education and Research Traineeship (IGERT) program.
This track aims to educate and support a new generation of researchers able to address...
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