MODIFICATION
A -- Novel Intelligence from Massive Data (NIMD) R&D Program
- Notice Date
- 4/11/2002
- Notice Type
- Modification
- Contracting Office
- Other Defense Agencies, National Imagery and Mapping Agency, Washington Contracting Center (ACW), Attn: ACW Mail Stop D-6 4600 Sangamore Road, Bethesda, MD, 20816-5003
- ZIP Code
- 20816-5003
- Solicitation Number
- NMA401-02-BAA-0004
- Response Due
- 6/11/2002
- Archive Date
- 10/3/2002
- Point of Contact
- Steven J., Contract Officer, Phone 9999, Fax 9999,
- E-Mail Address
-
ACWEB1@nima.mil
- Description
- The National Imagery and Mapping Agency (NIMA), 4600 Sangamore Road, Bethesda, MD 20816, is soliciting proposals for the Novel Intelligence from Massive Data (NIMD) program via Broad Agency Announcement (BAA) NMA401-02-BAA-0004. The BAA will be posted in its entirety on the following website: www.nima.mil/poc/contracts/baa.html. This BAA was originally released as a draft. It has now been released in its final version. Notification of any subsequent revisions will only be provided on the website listed above. The information below has not changed from the first announcement. It is anticipated that multiple awards will be issued as a result of the BAA. The program length is a minimum of 40 months and possesses a significant budget across the program's anticipated period of performance. Questions can be directed via only e-mail to ACWEB1@nima.mil. Questions should be submitted after review of the BAA and not from only reading this FEDBIZOPPS announcement. The initial proposal submittal date is 11 Jun 2002 and the BAA closing date is 3 October 2002. Please see the BAA for the detailed and definitive information regarding proposal submission date requirements. The following is a brief description of the program. The Novel Intelligence from Massive Data (NIMD) program is aimed at focusing analytic attention on the most critical information found within massive data - information that indicates the potential for strategic surprise. In this context, Novel Intelligence is defined as actionable information not previously known to the analyst or policy makers. It gives the analyst new insight into a previously unappreciated or misunderstood threat. The BAA is interested in research in 5 areas: (1) Modeling analysts and analytic processes; (2) Recognizing, representing, and using prior and tacit knowledge; (3) Generating, representing and tracking multiple scenarios, hypotheses, and/or strategies; (4) Massive data structuring/organization, normalization, ingest, and analysis; and (5) Methods for human information interaction. Novel intelligence is likely to result from recognizing the assumptions, biases, and hypotheses that drive an analysis and systematically helping analysts challenge or extend them. Ultimately, the most powerful analytic environment will be one in which information about analysts is not only induced from their activities, but in which they also have an active hand in explicitly constructing and manipulating representations or models of the analytic targets that contain and make explicit their knowledge, interests, hypotheses and biases, and other traits of their analytic state. NIMD encourages research in two directions simultaneously: developing techniques and tools that assist analysts both in dealing with massive data and in interactively making explicit, modifying and updating their current analytic state, including their hypotheses, knowledge, interests, and biases; and developing techniques and tools that infer the state of analysts and the analytic process from analysts' activities as recorded through an instrumented environment. Key abilities of NIMD-enabled systems are to identify structures within massive data, to generate novel and plausible explanations for those structures, and then to communicate these findings to analysts in ways that support further investigation. Having developed the structures and explanations, a NIMD-enabled system will help analysts evaluate them and track their plausibility as events unfold - gathering and tracking evidence related to multiple chains of reasoning, making it easy to recognize and simultaneously evaluate multiple alternatives objectively. In particular, the system will alert analysts when a less-attended candidate becomes more deserving of attention.
- Place of Performance
- Address: N/A
- Record
- SN00057470-W 20020413/020411213616 (fbodaily.com)
- Source
-
FedBizOpps.gov Link to This Notice
(may not be valid after Archive Date)
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