SOLICITATION NOTICE
D -- Collaborative Advanced Analytics & Data Sharing (CAADS) Software - J&A
- Notice Date
- 7/28/2016
- Notice Type
- Presolicitation
- NAICS
- 541511
— Custom Computer Programming Services
- Contracting Office
- Department of Health and Human Services, Centers for Disease Control and Prevention, Procurement and Grants Office (Atlanta), 2920 Brandywine Road, Room 3000, Atlanta, Georgia, 30341-4146
- ZIP Code
- 30341-4146
- Solicitation Number
- 2016-Q-65123
- Archive Date
- 8/13/2016
- Point of Contact
- Nancy Khalil,
- E-Mail Address
-
kuj2@cdc.gov
(kuj2@cdc.gov)
- Small Business Set-Aside
- N/A
- Description
- J&A Date: 0726 Year: 16 Zip: 30341 Centers for Disease Control and Prevention (CDC); 2920 Brandywine Road Atlanta, GA 30341 Contact: Nancy Khalil, Contract Specialist, nmkhalil@cdc.gov FAR, Subpart 5.204-NOTICE OF INTENT TO SOLE SOURCE The Centers for Disease Control and Prevention (CDC), National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP) intends to solicit a single source and award a firm-fixed price contract to Lockheed Martin Services Inc., 700 North Frederick Ave Gaithersburg, MD 20879-3328, in accordance with FAR Part 12. The purpose of this procurement is to acquire Collaborative Advanced Analytics & Data Sharing (CAADS) Software. This software is the only product capable of satisfying agency requirements. The software allows joining of very large datasets, including partial or whole genomes for each pathogen with the associated epidemiological data to infer, characterize, and analyze transmission networks. Furthermore, this is the only software suite that demonstrates compatibility with our HPC environment and stringent network requirements of the CDC. The authentication system is unified such that a user need only supply a single login credential in order to access all of the suite's services, preferably through integration with lightweight directory access protocol (LDAP). The system is capable of encryption of data while in motion and at rest to protect data privacy and ensure mission integrity and the reputation of the agency. The system also allows for scalable and parallelized ingestion of large datasets (ranging from giga- to petabytes in size) that can be ingested from raw sources (unstructured, semi-structured and structured) and existing databases. This ingestion process does not require any programming expertise and be accessible through a point-and-click, web-based interface. During ingestion, the software provides visualizations (such as histograms and statistical summaries) of each column in the data. The software guides the user via machine learning to generate a data cleaning script that can be run in parallel on a compute cluster. Script generation and maintenance should not require programming expertise. That script is sharable in plain text to facilitate the transformation step or process for later use or sharing with other data scientists for reproduction of the transformation (both within and outside the CDC). The software also includes a point-and-click work flow design component that includes the ability to (1) join and transform data via dropdown menus and check boxes (2) statistical summaries (3) predictive analytic and machine learning tools to aid decision making [these include k-means clustering, decision trees, linear dirichlet allocation (LDA), support vector machine modeling, naïve Bayes predictors, principle component analysis (PCA), linear and logistic regression, neural networks, receiver operating curves (ROC), and various other analytic methods] as well as tooltips and online instructions to support users with selecting and applying these tools. The outputs of elements of the work flow contain visualizations of the results obtained during that analytical step that can be exported as images for easy dissemination and sharing. The system provides limited collaborator access to visualize the results of each analytical step without the ability to modify the work flow. The software also includes a network visualization/animation component that renders networks-based on static network data, but also builds, visualizes, and analyzes novel network representations of that data using a method called data discovery link-analysis. The network visualization component is fully customizable with respect to the raw data and aggregate functions applied to the raw data to allow for simple re-characterization of a transmission network to investigate new hypotheses in real-time. Therefore, the suite requires the ability to dynamically model data based on graphical user interface interaction. It also includes an automatic recognition of data types, such as with dates and/or times, to generate time-series visualizations and animations. The network visualization component includes the functionality to save the analytics and visualizations as a template for sharing with other data analysts to re-use without having to repeat the same work flow and analytics. The software also supports the integration of geographical information system (GIS) tools and data into the data visualization component. This integration leverages the extensive investment and experience the agency has in the Environmental Systems Research Institute (ESRI) suite for GIS and geodatabase analyses. The software is also modular such that as better tools for the project are identified they can replace or add to the existing components. Only one responsible source and no other supplies or services will satisfy agency requirements. The associated NAICS Code is 541511. The Classification Code is D318 for IT and Telecom-Integrated Hardware/Software. This is not a solicitation and proposals are not requested. Interested organizations may submit their capabilities/qualifications statement to perform the effort, in writing to Mrs. Nancy Khalil, via email at nmkhalil@cdc.gov with "Solicitation Number 2016-Q-65123" referenced in the subject line, no later than 12:00pm EST on Friday, July 29, 2016. Disclaimer and Important Notes. This notice does not obligate the Government to award a contract or otherwise pay for the information provided in response. The Government reserves the right to use information provided by respondents for any purpose deemed necessary and legally appropriate. Any organization responding to this notice should ensure that its response is complete and sufficiently detailed to allow the Government to determine the organization's qualifications to perform the work. 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. After a review of the responses received, a pre-solicitation synopsis and solicitation may be published in Federal Business Opportunities. However, responses to this notice will not be considered adequate responses to a solicitation. Confidentiality. 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).
- Web Link
-
FBO.gov Permalink
(https://www.fbo.gov/spg/HHS/CDCP/PGOA/2016-Q-65123/listing.html)
- Record
- SN04199468-W 20160730/160728234534-cc2252d52fc235f6ea385879b9405c88 (fbodaily.com)
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