AMENDMENT 2 for BAA FA8750-18-S-7009
The purpose of this modification is to republish the original announcement pursuant to FAR 35.016(c).
This republishing also includes the following changes:
(a) Part I-updated Contracting Officer point of contact
(b) Section I, added information regarding Fundamental Research and Cloud Computing;
(c) Section III, Eligibility Information has been updated;
(d) Section IV, 4.a., updated the Cost Sharing or Matching language;
(e) Section IV, 4.c., updated the link in the Executive Compensation and First-Tier Subcontract/Subrecipient paragraph;
(f) Section V, updated White Paper/Proposal Review Process and the Simplified Acquisition Threshold in paragraph 3;
(g) Section VI, Proposal Formattting, updated the date for the RI-Specific Proposal Preparation Instructions;
(h) Section VI, updated Administrative and National Policy Requirements language, and added Small Business Participation language;
(i) Section VII, Agency Contacts are updated;
No other changes have been made.
AMENDMENT 3 to BAA FA8750-18-S-7009
The purpose of this modification is to republish the original announcement, incorporating any previous amendments, pursuant to FAR 35.016(c).
This republishing also includes the following changes:
No other changes have been made.
________________________________________
NAICS CODE: 541715
FEDERAL AGENCY NAME: Department of the Air Force, Air Force Materiel Command, AFRL - Rome Research Site, AFRL/Information Directorate, 26 Electronic Parkway, Rome, NY, 13441-4514
BAA ANNOUNCEMENT TYPE: Modification/Amendment
BROAD AGENCY ANNOUNCEMENT (BAA) TITLE: Adaptive Multi Source Exploitation of Documents (AMUSED)
BAA NUMBER: FA8750-18-S-7009
PART I – OVERVIEW INFORMATION
This announcement is for an Open, Two (2) Step BAA which is open and effective until 30 Sep 2022. Only white papers are due at this time. While white papers will be considered if received prior to 3:00 PM on 30 Sep 2022, the following submission dates are suggested to best align with projected funding:
FY18 – The initial white paper submissions for each Focus Area is due as follows:
16 Jan 18 – Focus Area C/Text Analytics for Cyber Domain
12 Mar 18 – Focus Area A/Global Treat Discovery and Identification
16 Apr 18 – Focus Area B/Emerging Threat Analytics
Thereafter suggested submissions dates for all the focus areas are:
FY19 by 30 Mar 2018
FY20 by 29 Mar 2019
FY21 by 27 Mar 2020
FY22 by 26 Mar 2021
Offerors should monitor the Contract Opportuities on the Beta SAM website at https://beta.SAM.gov in the event this announcement is amended.
CONCISE SUMMARY OF FUNDING OPPORTUNITY: The Air Force Research Laboratory, Information Directorate is seeking innovative analytics, analytical tools, algorithm developments, projects, and experiments focused on achieving Adaptive Multi-Source Exploitation of Documents (AMUSED). This BAA is a follow-on to BAA AFRL-RIK-2015-0019 Multi-Source Information Extraction and Network Analysis (MUSIENA).
BAA ESTIMATED FUNDING: Total funding for this BAA is approximately $24.9M. Individual awards will not normally exceed 36 months with dollar amounts normally ranging from $100K to $900K each. There is also the potential to make awards up to any dollar value as long as the value does not exceed the available BAA ceiling amount.
ANTICIPATED INDIVIDUAL AWARDS: Multiple Awards are anticipated
TYPE OF INSTRUMENTS THAT MAY BE AWARDED: Procurement contracts, grants, cooperative agreements or other transactions (OT) depending upon the nature of the work proposed. In the event that an Other Transaction for Prototype agreement is awarded as a result of this competitive BAA, and the prototype project is successfully completed, there is the potential for a prototype project to transition to award of a follow-on production contract or transaction. The Other Transaction for Prototype agreement itself will also contain a similar notice of a potential follow-on production contract or agreement.
AGENCY CONTACT INFORMATION: All white paper and proposal submissions and any questions of a technical nature shall be directed to the cognizant Technical Point of Contact (TPOC) as specified below (unless otherwise specified in the technical area):
BAA MANAGER:
TPOC: Edward DePalma
Mailing Address: AFRL/RIEA, 525 Brooks Road, Rome NY 13441-4505
Telephone: (315)330-3069
Email: [email protected]
Questions of a contractual/business nature shall be directed to the cognizant contracting officer, as specified below (email requests are preferred):
Amber Buckley
Telephone (315) 330-3605
Email: [email protected]
Emails must reference the solicitation (BAA) number and title of the acquisition.
Communication between Prospective Offerors and Government Representatives: Dialogue between prospective offerors and Government representatives is encouraged. Technical and contracting questions can be resolved in writing or through open discussions. Discussions with any of the points of contact shall not constitute a commitment by the Government to subsequently fund or award any proposed effort. Only Contracting Officers are legally authorized to commit the Government.
Offerors are cautioned that evaluation ratings may be lowered and/or proposal rejected if proposal preparation (Proposal format, content, etc.) and/or submittal instructions are not followed.
PART II – FULL TEXT ANNOUNCEMENT
BROAD AGENCY ANNOUNCEMENT (BAA) TITLE: Adaptive Multi Source Exploitation of Documents (AMUSED)
BAA NUMBER: BAA FA8750-18-S-7009
CATALOG OF FEDERAL DOMESTIC ASSISTANCE (CFDA) Number: 12.800 & 12.910
I. FUNDING OPPORTUNITY DESCRIPTION:
The Information Directorate, Information Fusion Branch, is soliciting white papers under this announcement for unique and innovative technologies to explore and develop Adaptive Multi Source Exploitation of Documents (AMUSED) capabilities including but not limited to, analytics, analytical tools, algorithm developments, projects, and experiments that will provide the Air Force the means to better conduct analytical operations in support of their Intelligence, Surveillance, and Reconnaissance mission including Cyber. This announcement is comprised of three research areas: (1) Global Threat Discovery and Identification (GTD-ID); (2) Emerging Threat Analytics (ETA); and (3) Text Analytics for Cyber Domain (TA4CD), where each has research areas that taken together comprise the focus of AMUSED research and development.
BACKGROUND: Past research in text analysis has led to the automated capabilities that are now in use to extract relevant information from large volumes of textual data. The development of this technology has reduced textual data overload, increased the accuracy of analysis, and decreased the cycle time and manpower requirements needed to assess threats and vulnerabilities. However, this is a situation that has not remained static from either the perspective of the anticipated number of data sources or projected analytical needs. Further development is required to not just keep pace but to move beyond current performance levels, to overcome limitations in moving to new data types and domains, and to achieve new, more sophisticated capabilities.
Fundamentally the analysis of textual content must produce higher levels of comprehension and understanding than presently exists. As textual information has increased in both quantity and complexity the demands for greater analytical capabilities have also grown dramatically. While basic documents still comprise a large portion of textual information, valuable content can now be extracted from a range of other sources including a variety of social media material (chat, email, blogs, etc.), many open source materials and the metadata descriptors that relate back to additional media forms (video, imagery, speech, etc.). The value of textual analysis going forward will now be gauged by the ability to work effectively in and across these and other components of a complex data environment while advancing the capabilities in exploiting traditional sources.
Current network discovery and analysis science has focused on static relationship or event based networks of interest. This occurs primarily on one or two particular data sources. These capabilities are adept at enabling an analyst to effectively analyze network data within a single data source, but the analyst is then left to make mental correlations of observations and conclusions drawn from one data source to other data sources. Furthermore, current input methods do not account for semantic equivalences during the ingestion of the data, making the analyst’s job even more difficult.
One of the greatest technical challenges facing all decision support systems is the heterogeneous aspect of the data that is collected by millions of sensors and the different stovepipe architectures used to store this data. In order to perform useful analytics, a composite picture of the key entities, events, and locations need to be pieced together from the original disparate data sources. The ingesting and integrating of information from disparate data sources remains a difficult and unresolved problem.
In the Cyber Domain, multiple analyst groups, with diverse Mission Areas, need rapid, effective means to identify Essential Element of Interest (EEIs), in support of both Cyber Operations and Defensive Cyber Analysis. EEIs are pieces of information that answer questions deemed critical to mission accomplishment (see formal definition in Joint Publication 2-0, Joint Intelligence, dated 22 Oct 2013).
OBJECTIVES: The three research areas within this AMUSED BAA are (1) Global Threat Discovery and Identification (GTD-ID), (2) Emerging Threat Analytics (ETA) and (3) Text Analytics for Cyber Domain (TA4CD) with each containing the key technical Focus Areas for development. Submissions/White Papers should clearly identify the AMUSED research area or specify the individual Focus Area being addressed.
A. Global Threat Discovery and Identification (GTD-ID): The GTD-ID research area must deliver advanced text exploitation to provide deeper understanding of the information that can be pulled from multi-source unstructured text. The individual focus areas of this research area are User Driven Domain Customization, Complex Event Extraction and Text Exploitation Platform for Multi-Source Analysis (MSA). These technologies are key enablers that will more widely deliver affordable, easy to use, accurate text exploitation technology to AF users and each may be the emphasis of a white paper submission under GTD-ID.
Focus Area A1 - User Driven Domain Customization
As text exploitation tools gain acceptance in the DOD and Intelligence communities, they are exposed to a wider variety of domains of interest. Even within the Air Force, different user groups are interested in different types of documents, on different topics, with different entities, relations and events of interest. In order to achieve maximum results for each individual user, GTD-ID products must support customization for their specific use-case. This will enable ready transition and adoption of this technology through the development of effective user-driven domain customization allowing subject matter experts (SME) to tailor GTD-ID capabilities to their environment rather than require specialized technical expertise to perform this customization. An analyst should not be required to understand the underlying technology; they should be able to concentrate on what they do best, which is the task of analyzing data. This focus area will develop robust techniques allowing domain experts to quickly, affordably and effectively customize text extraction capabilities to work on their new text types and domains.
While AFRL/RI has sponsored prior R&D in domain porting which has made progress towards this goal, there is still considerable work to be done to reach the higher level of domain customization performance that will leverage advanced learning techniques to provide a user-driven capability.
Focus Area A2 - Complex Event Extraction
Complex event extraction means moving beyond individual events that do not provide a sufficient level of situational awareness and toward a broader and more comprehensive understanding of collective events and their importance. Achieving success in complex event extraction should include extracting/associating event arguments with events, extracting relations between events (e.g., before, prerequisite-of, causal); within-document event co-reference; cross-document event co-reference; and developing algorithms that are capable of understanding how events fit together in a logical way. To truly understand what is going on there must be this understanding of how the individual events fit together conceptually and into some higher-level logical structure (e.g., based on causality, temporal ordering, etc.). Research into event structures, event scenarios, event schemas, and event scripts would be of particular benefit in addressing this need. As the amount of event information to be assessed accumulates, there will be a need to measure the confidence level in the understanding of the larger event (scenario) in total. The overall intent of this research thrust is to provide the technological foundation to enable more powerful event-centric analysis (from information from text).
Focus Area A3 - Text Exploitation Platform for Multi-Source Analysis (TE Platform for MSA)
The TE Platform for MSA will achieve a comprehensive, robust, flexible, scalable, web-based text exploitation framework for multi-source text analysis. The framework will support “end-to-end” functionality, including (but not limited to) data preparation and ingestion, including document zoning to enable separate processing of structured (header, footer, tables, lists, etc.) and unstructured portions of text; textual data analysis and visualization; multi-source analysis; search/filtering of document collections; Information Extraction (IE) and content management. Additionally there are key design requirements which include scalability, flexibility and robustness that will promote application for new/different use-cases along with adaptability and vendor-independence which will promote openness of the solution. Adhering to best practices and standards that help the framework attain these design requirements is encouraged, such as the Apache Unstructured Information Management Architecture (UIMA). The end result will be a strong and viable technology platform for rapidly transitioning new/maturing text exploitation capabilities to our users in support of Multi-Source Analysis.
B. Emerging Threat Analytics (ETA): ETA will address key challenges in multi-source fusion and social media exploitation empowering the analyst with high performance, high accuracy and easily adaptable tools for threat assessment, explanation, and anticipation surrounding individuals of interest, groups and events. This research area will support the design and implementation of state-of-the-art technologies to achieve data alignment for large-scale, disparate data sources and create analytical models for estimating “tactical” phenomena in society at large based on phenomena that occur in social media. The individual focus areas of this research area are Multi-Source Data Fusion and Social Media Analytics.
Focus Area B1 - Multi-Source Data Fusion
The objective of ETA is to employ a flexible and adaptive framework through which layered multi-modal network analysis (LMMNA) can be achieved, to provide the analyst the ability to understand and interrogate the inter and intra source relationships that have and continue to evolve spatially and temporally within and across the spectrum of intelligence data. The framework will incorporate technologies that amalgamate and align disparate data layers (sources and domains); apply entity resolutions to associate and cluster like-entities within and across layers to derive a single graph; and provide access to batch and real-time graph analytic algorithms and heuristics to derive and maintain graph measures, graph matching and graph querying, leveraged to identify valuable semantic and structural elements, and discover new patterns of interest. Simply put, the framework will ultimately facilitate the alignment, association, and analysis of disparate layers of intelligence data to yield a cohesive and comprehensive picture of the evolving cross layer situational awareness. Adhering to best practices and standards that help the framework attain these design requirements is encouraged, such as the Apache TinkerPop Open Source Graph Computing Framework.
When analyzing multi-source information, several issues can arise that inhibit the ability to produce an effectual analysis. Errors in the processing pipeline, data entry, and reporting as well as redundant information and deliberate attempts at misinformation will persist throughout the data. Identifying these knowledge conflicts is an important yet unresolved task. Current methods rely on linguistic cues with little regard to semantics. These constructs measure various features of the text, including parts of speech, tense, and voice. However, it turns out that these measures and constructs are not significant predictors of deceptive behavior and explain only a fraction of the variance. This necessitates a new approach that not only understands the syntactic features of text, but also the semantic features.
Focus Area B2 - Social Media Analytics
Analytical capabilities that can be applied to social media communications have been limited in scope, scale and reach. Identifying mission relevant information from billions of posts generated by millions of users is currently a labor-intensive and subjective process. Central concerns in the analysis of social media data are in the vast amount of data that is constantly being produced and the actual analytics that need to be performed. ETA must develop an improved method for noise reduction and analysis in order to extensively and effectively search the massive social media datasets.
While noise reduction can be used to refine the search space, analysts will still be confronted with content that requires an automated capability that will be able to readily investigate individuals, uncover relationships, and follow connections to reveal networks of people and organizations. Analysts need to understand who the protagonists are, what they have done, and what they are planning. Automated analysis methods are needed that will help analysts rapidly decipher unfolding events and even attempt to predict future events. Where current social media analytics have been focused on analyzing the explicit relationships additional research under ETA is needed to uncover the implicit relationships within social media that are not directly evident. Areas of interest for this research of Social Media content and structure would develop the automated methods to identify embedded motivations and attitudes, expose non-explicit relationships between individuals and groups along with their dynamics in how they interact.
C. Text Analytics for Cyber Domain (TA4CD): This research area will develop adaptive technology enabling multiple analyst groups to more effectively find and exploit Essential Elements of Information (EEIs) relevant to their Mission Area with particular emphasis on the Cyber Domain. As previously stated, EEIs are pieces of information that answer questions deemed critical to mission accomplishment (see formal definition in Joint Publication 2-0, Joint Intelligence, dated 22 Oct 2013). The individual focus areas of this research area are Enhanced Search for EEI Information, Adaptive Multi-Source Processing and Cyber Entity Co-Reference.
Focus Area C1 - Enhanced Search for EEI Information
The goal of this Focus Area is to research and develop technology that significantly improves analysts’ ability to find information relevant to their EEIs. Areas of interest include, but are not limited to, Web-Scale Multi-Lingual Document Search and EEI Modeling and Search.
Web-Scale Multi-Lingual Document Search: Analysts need to be able to perform fast, effective web-scale search (100M documents+) of multi-lingual data sources, to find documents containing information potentially relevant to their EEIs. Achieving state-of-the-art performance in terms of the relevancy and completeness of results is key. The technology must be portable to new languages and genres, for both high and low-resource languages, preferably by a user vs technology expert.
EEI Modeling & Search: There is a need for innovative technology to effectively search large volumes of potentially relevant documents for information pertinent to answering an EEI. EEIs can range from very specific queries, to very high level questions, such as “How stable is Country X?” Developing search technology that can provide answers to such high-level questions is a challenge, because it really requires answering a number of sub-questions whose answers all contribute to answering the EEI. So, for example, in order to answer the EEI “How stable is Country X?”, one might need to answer a number of sub-questions whose answers all contribute to addressing the EEI, such as “How stable is the current Government in Country X?”, “Are banks open for normal business in Country X?”, “Is food readily available in Country X?”, and “Have the number of violent crimes increased in Country X?” In other words, answering high-level EEIs requires the ability to perform “meta-searches” to define/manage/refine the sub-questions (sub-queries) that must be answered to determine the answer to the high-level EEI. Technology is needed to model EEIs and their sub-queries as sets of Structured Natural Language Queries; manage and refine the EEI query model over time; use the query models to search for relevant information, as well as expand/refine search results based on feedback from the user. The technology must achieve high relevancy of search results, and provide a means to improve system results over timebased on user feedback. Alternate approaches will be considered. Technical approaches must also be user-adaptable to different Mission Areas. The primary language of interest is English; being adaptable to other languages is a plus but not a requirement.
Focus Area C2 - Adaptive Multi-Source Processing
Adaptive Multi-Source Processing will research and develop user-adaptive text exploitation technology that will make it possible to customize text exploitation capabilities to support multiple groups of analysts with different mission areas, different document types, and different information requirements. Areas of interest include, but are not limited to, User-Driven Domain Customization (described above under the GTD-ID Focus Area); TE Platform for MSA (described above under the GTD-ID Focus Area); Adaptive Text Zoning; and Document Structure Analysis.
Adaptive Text Zoning. Currently, text zoning is a manual process that requires a technology expert to analyze new and diverse document types, determine their structure, and then manually create text zoning rules to identify and process the various structured and unstructured portions of the document. The intent of this area is to research and develop an automated capability for Text Zoning that can be adapted to new document types/structures with either no intervention, or very minimal intervention by a user who is not a technology expert.
Document Structure Analysis. Very large documents may consist of multiple coherent discourse units that are more effectively processed as individual sub-documents by a text exploitation platform. The goal of this area is to research discourse parsing, or alternative methods for document structure analysis, in order to identify coherent discourse units within large documents for text processing.
Focus Area C3 - Cyber Entity Co-Reference
Cyber Entity Co-Reference will provide the analyst with capabilities to automate the consolidation of Entities extracted from text that are relevant to the Cyber Domain, both within a document and across multiple documents. This includes, but is not limited to, Equipment Entity Co-Reference.
Equipment Entity Co-Reference (within-document and cross-document). Within and cross-document entity co-reference capabilities already exist for named entities like People and Organizations, enabling automated consolidation, analysis and visualization of this information. Analysts in the Cyber Domain need a comparable capability: within and cross-document Equipment Entity Co-Reference algorithms that will enable automated consolidation of equipment information extracted from text, both within and across many documents. However, the way in which Equipment Entities are discussed in text introduce a number of unique challenges that would make equipment entity co-reference more of challenge than the co-reference for named entities like People, Organizations and Geo-Political Entities. For example, Equipment Entities are typically referred to by a class name (e.g., “the XYZ Router) vs by a uniquely identifiable name (e.g., “the XYZ router with serial #123”), which increases ambiguity. Research in this area will result in a proof-of-concept for within and cross-document Equipment Entity Co-Reference, enabling consolidation of equipment information within and across documents.
IMPORTANT NOTES REGARDING:
FUNDAMENTAL RESEARCH. It is DoD policy that the publication of products of fundamental research will remain unrestricted to the maximum extent possible. National Security Decision Directive (NSDD) 189 defines fundamental research as follows:
‘Fundamental research’ means basic and applied research in science and engineering, the results of which ordinarily are published and shared broadly within the scientific community, as distinguished from proprietary research and from industrial development, design, production, and product utilization, the results of which ordinarily are restricted for proprietary or national security reasons.
As of the date of publication of this BAA, the Government cannot identify whether work proposed under this BAA may be considered fundamental research and may award both fundamental and non-fundamental research. Proposers should indicate in their proposal whether they believe the scope of the research included in their proposal is fundamental or not. While proposers should clearly explain the intended results of their research, the Government shall have sole discretion to select award instrument type and to negotiate all instrument terms and conditions with selectees. Appropriate clauses will be included in resultant awards for non-fundamental research to prescribe publication requirements and other restrictions, as appropriate.
For certain research projects, it may be possible that although the research being performed by the awardee is restricted research, a sub-awardee may be conducting fundamental research. In those cases, it is the awardee’s responsibility to explain in their proposal why its sub-awardee’s effort is fundamental research.
CLOUD COMPUTING. In accordance with DFARS Clause 252.239-7010, if the development proposed requires storage of Government, or Government-related data on the cloud, offerors need to ensure that the cloud service provider proposed has been granted Provisional Authorization by the Defense Information Systems Agency (DISA) at the level appropriate to the requirement.
II. AWARD INFORMATION:
1. FUNDING: Total funding for this BAA is approximately $24.9M. The anticipated funding to be obligated under this BAA is broken out by fiscal year as follows:
FY18 - $2.70M
FY19 - $5.05M
FY20 - $5.25M
FY21 - $5.75M
FY22 - $6.15M
The breakout of funding by fiscal year is a projection. The total awards values in any given year will vary.
Email Unclassified electronic submission to the TPOC identified in Section VII. Encrypt or password-protect all proprietary information prior to sending. Offerors are responsible to confirm receipt with the TPOC. AFRL is not responsible for undelivered documents. If electronic submission is used, only one copy of the documentation is required.
In addition to the electronic submission, please also mail a response. Any mailed responses, unclassified/classified, to this announcement must be sent U.S. Postal Service, registered mail or similar service and addressed to AFRL/RIEA, 525 Brooks Road, Rome NY 13441-4505, and reference BAA FA8750-18-S-7009.
Questions can be directed to the TPOC listed in Section VII.
4. OTHER SUBMISSION REQUIREMENTS/CONSIDERATIONS:
a. COST SHARING OR MATCHING: Cost sharing is not a requirement. Cost sharing may be proposed and will be considered on a case-by-case basis. Cost share will not be a factor in selection for award.
b. SYSTEM FOR AWARD MANAGEMENT (SAM). Offerors must be registered in the SAM database to receive a contract award, and remain registered during performance and through final payment of any contract or agreement. Processing time for registration in SAM, which normally takes forty-eight hours, should be taken into consideration when registering. Offerors who are not already registered should consider applying for registration before submitting a proposal. The provision at FAR 52.204-7, System for Award Management (Oct 2016) applies.
c. EXECUTIVE COMPENSATION AND FIRST-TIER SUBCONTRACT/ SUBRECIPIENT AWARDS: Any contract award resulting from this announcement may contain the clause at FAR 52.204-10 - Reporting Executive Compensation and First-Tier Subcontract Awards (Oct 2016). Any grant or agreement award resulting from this announcement may contain the award term set forth in 2 CFR, Appendix A to Part 25 which can be viewed at: https://www.govinfo.gov/app/details/CFR-2012-title2-vol1/CFR-2012-title2-vol1-part25-appA.
d. ALLOWABLE CHARGES: The cost of preparing white papers/proposals in response to this announcement is not considered an allowable direct charge to any resulting contract or any other contract, but may be an allowable expense to the normal bid and proposal indirect cost specified in FAR 31.205-18. Incurring pre-award costs for ASSISTANCE INSTRUMENTS ONLY are regulated by the DoD Grant and Agreements Regulations (DODGARS).
e. GOVERNMENT APPROVED ACCOUNTING SYSTEM: An offeror must have a government approved accounting system prior to award of a cost-reimbursement contract per limitations set forth in FAR 16.301-3(a) to ensure the system is adequate for determining costs applicable to the contract. The acceptability of an accounting system is determined based upon an audit performed by the Defense Contract Audit Agency (DCAA). IMPORTANT: If you do not have a DCAA approved accounting system access the following link for instructions: https://beta.sam.gov/opp/e628c811fafe041accdddf55fb8539bf/view?keywords=AFRL-BAA-Guide&sort=-relevance&index=&is_active=true&page=1
f. HUMAN USE: All research involving human subjects, to include the use of human biological specimens and human data, selected for funding must comply with Federal regulations for human subject protection. Further, research involving human subjects that is conducted or supported by the DoD must comply with 32 CFR 219, “Protection of Human Subjects” found at: http://www.access.gpo.gov/nara/cfr/waisidx_07/32cfr219_07.html, and DoD Directive 3216.02, “Protection of Human Subjects and Adherence to Ethical Standards in DoD-Supported Research” found at: http://www.dtic.mil/whs/directives/corres/pdf/321602p.pdf.
* Selectable proposals will be designated as funded or unfunded. Letters will be sent to the unfunded offerors. These proposals may be funded at a later date without reevaluation, if funding becomes available.
3. FEDERAL AWARDEE PERFORMANCE AND INTEGRITY INFORMATION SYSTEM (FAPIIS) PUBLIC ACCESS: The Government is required to review and consider any information about the applicant that is in the FAPIIS before making any award in excess of the simplified acquisition threshold (currently $250,000) over the period of performance. An applicant may review and comment on any information about itself that a federal awarding agency previously entered. The Government will consider any comments by the applicant, in addition to other information in FAPIIS in making a judgment about the applicant's integrity, business ethics, and record of performance under federal awards when completing the review of risk posed by applicants as described in 2 CFR § 200.205 Federal Awarding Agency Review of Risk Posed by Applicants and per FAR 9.104-6.
VI. STEP TWO INFORMATION – REQUEST FOR PROPOSAL & AWARD:
1. PROPOSAL FORMATING: When developing proposals, reference the AFRL "Broad Agency Announcement (BAA): Guide for Industry," Mar 2015, and RI-Specific Proposal Preparation Instructions, Jul 2019, which may be accessed at: https://beta.sam.gov/opp/e628c811fafe041accdddf55fb8539bf/view?keywords=AFRL-BAA-GUIDE&sort=-relevance&index=&is_active=true&page=1 . Always reference the newest versions of these documents.
2. AWARD NOTICES: Those white papers found to be consistent with the research areas of interest and expected results within the broad topic areas as described in the Funding Opportunity section of this BAA and of interest to the Government may be invited to submit a technical and cost proposal. Notification by email or letter will be sent by the TPOC. Such invitation does not assure that the submitting organization will be awarded a contract. Those white papers not selected to submit a proposal will be notified in the same manner. Prospective offerors are advised that only Contracting Officers are legally authorized to commit the Government. All offerors submitting proposals will receive notification of their evaluation results within 45 days of submission. Offerors should email the TPOC and the Contracting Officer listed in Section VII, for status of their proposal after 45 days, if no such correspondence has been received.
3. DEBRIEFINGS: If a debriefing is requested in accordance with the time guidelines set out in FAR 15.505 and 15.506, a debriefing will be provided, but the debriefing content may vary to be consistent with the procedures that govern BAAs (FAR 35.016). Debriefings will not be provided for white papers.
4. ADMINISTRATIVE AND NATIONAL POLICY REQUIREMENTS:
5. DATA RIGHTS:
AMENDMENT 4 to BAA FA8750-18-S-7009
The purpose of this amendment is to update the Technical Point of Contact (TPOC).
No other changes have been made.
PLEASE SEE THE ATTACHMENT FOR AMENDMENT 5 to BAA FA8750-18-S-7009
PLEASE SEE THE ATTACHMENT FOR AMENDMENT 6 to BAA FA8750-18-S-7009