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<p class="MsoNormal"><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif"">Request for Information (RFI): Input on Development of Analysis Methods and Software for Big Data
<o:p></o:p></span></font></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif"">Notice Number: NOT-HG-13-014<o:p></o:p></span></font></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif"">Key Dates<br>
Release Date: August 8, 2013<br>
<b><span style="font-weight:bold">Response Due Date:</span></b> September 6, 2013
<o:p></o:p></span></font></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif"">Issued by<br>
National Human Genome Research Institute (<a href="http://www.nhgrii.nih.gov"><font color="blue"><span style="color:blue">NHGRI</span></font></a>)<o:p></o:p></span></font></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif"">Purpose<o:p></o:p></span></font></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif"">This Request for Information (RFI) is to solicit comments and ideas for
the development of analysis methods and software tools, as part of the overall Big Data to Knowledge (BD2K) Initiative. Specifically, this RFI solicits input on needs for software and analysis methods related to data compression/reduction, data visualization,
data provenance, and data wrangling. <o:p></o:p></span></font></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif"">Background<o:p></o:p></span></font></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif"">Biomedical research is becoming more data-intensive as researchers are
generating and using increasingly large, complex, and diverse datasets. This era of 'Big Data' in biomedical research taxes the ability of many researchers to release, locate, analyze, and interact with these data and associated software due to the lack of
tools, accessibility, and training. In response to these new challenges in biomedical research, and in response to the recommendations of the Data and Informatics Working Group (DIWG) of the Advisory Committee to the NIH Director (<a href="http://acd.od.nih.gov/diwg.htm"><font color="blue"><span style="color:blue">http://acd.od.nih.gov/diwg.htm</span></font></a>),
NIH has launched the trans-NIH Big Data to Knowledge (BD2K) Initiative (<a href="http://www.bd2k.nih.gov"><font color="blue"><span style="color:blue">www.bd2k.nih.gov</span></font></a>).
<o:p></o:p></span></font></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif"">The long-term goal of the NIH BD2K Initiative is to support advances in
data science, other quantitative sciences, policy, and training that are needed for the effective use of Big Data in biomedical research. (The term "biomedical" is used here in the broadest sense to include biological, biomedical, behavioral, social, environmental,
and clinical studies that relate to understanding health and disease). The term 'Big Data' refers to datasets that are increasingly larger, more complex, and which exceed the abilities of currently used approaches to manage and analyze. "Big Data" is also
meant to capture the opportunities and address the challenges facing all biomedical researchers in accessing, managing, analyzing and integrating large datasets of diverse data types. Such data types may include imaging, phenotypic, molecular (including –omics),
clinical, environmental, behavioral, and many other types of biological and biomedical data. "Big Data" also includes data generated for other purposes (e.g. social media, search histories, cell phone data) when they are repurposed and applied to address
health research questions. Biomedical Big Data primarily emanate from three sources: (1) a small number of groups that produce very large amounts of data, usually as part of projects specifically funded to produce important resources for use by the research
community at large, or large collections of electronic health records; (2) individual investigators who produce large datasets for their own project, but which might be broadly useful to the research community at-large; (3) an even greater number of investigators
who each produce small datasets whose value can be amplified by aggregating or integrating them with other data.
<o:p></o:p></span></font></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif"">One of the DIWG recommendations was to support the development, implementation,
evaluation, maintenance and dissemination of informatics methods and applications. NIH supports a wide range of bioinformatics and computational science through efforts such as the Biomedical Science and Technology Initiative funding opportunities and through
programs supported by individual NIH institutes and centers. NIH is now considering supporting the development of analytical methods and software tools and will focus initially on four targeted areas to begin to address critical current and emerging needs
of the research community for using, managing, and analyzing more complex and larger data sets: data compression/reduction, visualization, provenance, and wrangling.<o:p></o:p></span></font></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif"">An NIH BD2K Working Group charged with exploring the development of informatics
methods and tools seeks input from the biomedical research communities on the four targeted areas listed above to ensure that research resources generated will have the highest impact and value to the research community. NIH has determined that guidance is
needed from broad scientific community in the following areas: <o:p></o:p></span></font></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><b><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif";font-weight:bold">Data Compression/Reduction</span></font></b><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif""><br>
While data compression is important in BD2K since it helps reduce resource usage, most compression techniques involve trade-offs among various factors, including the degree of compression, the amount of distortion induced and the computational resources required
to compress and decompress the data.<br>
Data reduction aims to more dramatically reduce the data volume, and in the meantime reduce the complexity/dimensionality of data for easier analysis. It usually involves processing and/or reorganization of data to minimize redundancy, eliminate noise, and
preserve signal and data integrity. <o:p></o:p></span></font></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><b><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif";font-weight:bold">Data Visualization</span></font></b><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif""><br>
Data visualization permits researchers to communicate information through graphical and interactive means and enables them to explore and gain insight/knowledge from the data. The challenge in the Big Data era is on interpreting complex, high-throughput data,
especially in the context of other relevant, but often orthogonal, data. <br>
<br>
<b><span style="font-weight:bold">Data Provenance</span></b><br>
Provenance of digital scientific data is useful for determining attribution, identifying relationships between objects, tracking back differences in similar results, guaranteeing the reliability of the data, and to allow researchers to determine whether a particular
dataset can be used in their research (by providing lineage information about the data).
<o:p></o:p></span></font></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><b><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif";font-weight:bold">Data Wrangling</span></font></b><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif""><br>
Data wrangling is a term that is applied to the conversion, formatting, and mapping of data that enables researchers to more easily submit data to a database, expose data to the internet, and allows data to be more easily accessible and shareable. Researchers
who generate datasets that, in aggregate, become "Big Data" often find it difficult to submit data, even when standards are well-established. Specialized informatics skills are often needed, for example, to format data, apply metadata, fill gaps, use ontologies,
capture provenance, annotate features, and apply other functions to reformat, manipulate, transform, or process data.
<o:p></o:p></span></font></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif"">Information Requested<o:p></o:p></span></font></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif"">To maximize the impact of these valuable research resources and tools
(informatics methods and tools) and facilitate its use by scientists with a broad range of expertise, we seek input from scientific and informatics research and user communities in identifying and prioritizing needs and gaps in the four focus areas outlined
above. <o:p></o:p></span></font></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif"">Submitting a Response<o:p></o:p></span></font></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif"">All responses must be submitted via email to
<a href="mailto:BD2KSoftware@mail.nih.gov"><font color="blue"><span style="color:blue">BD2KSoftware@mail.nih.gov</span></font></a> by Friday, September 6, 2013. Please include the Notice number in the subject line. Response to this RFI is voluntary. Responders
are free to address any or all of the categories listed above. The submitted information will be reviewed by the NIH staff.
<o:p></o:p></span></font></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif"">This request is for information and planning purposes only and should
not be construed as a solicitation or as an obligation on the part of the Federal Government. The NIH does not intend to make any awards based on responses to this RFI or to otherwise pay for the preparation of any information submitted or for the Government's
use of such information. <o:p></o:p></span></font></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif"">The NIH will use the information submitted in response to this RFI at
its discretion and will not provide comments to any responder's submission. However, responses to the RFI may be reflected in future funding opportunity announcements. The information provided will be analyzed and may appear in reports. Respondents are advised
that the Government is under no obligation to acknowledge receipt of the information received or provide feedback to respondents with respect to any information submitted. No proprietary, classified, confidential, or sensitive information should be included
in your response. The Government reserves the right to use any non-proprietary technical information in any resultant solicitation(s).<o:p></o:p></span></font></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif"">Inquiries<o:p></o:p></span></font></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><font size="3" face="Times New Roman"><span style="font-size:12.0pt;font-family:"Times New Roman","serif"">Please direct all inquiries to:
<br>
<br>
Jennifer Couch, Ph.D<br>
National Cancer Institute<br>
Telephone: 240-276-6210<br>
Email: <a href="mailto:Jennifer_Couch@nih.gov"><font color="blue"><span style="color:blue">Jennifer_Couch@nih.gov</span></font></a><br>
Website: <a href="http://bd2k.nih.gov/#sthash.i3bBBRHF.dpbs"><font color="blue"><span style="color:blue">http://bd2k.nih.gov/#sthash.i3bBBRHF.dpbs</span></font></a><o:p></o:p></span></font></p>
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