Editing Total Information Awareness (section)

===Components===

====Genoa====
{{Main|Project Genoa}}
Unlike the other program components, Genoa predated TIA and provided a basis for it.<ref>{{cite book| title = Balancing Privacy & Security: The Privacy Implications of Government Data Mining Programs: Congressional Hearing| publisher = DIANE Publishing| pages = 126| url = https://books.google.com/books?id=5IR9z1pcQqoC| isbn = 9781422320259}}</ref> Genoa's primary function was [[intelligence analysis]] to assist human analysts.<ref name= verton/> It was designed to support both top-down and bottom-up approaches; a policymaker could hypothesize an attack and use Genoa to look for supporting evidence of it or compile pieces of intelligence into a diagram and suggest possible outcomes. Human analysts could then modify the diagram to test various cases.<ref name= harris/>

Genoa was independently commissioned in 1996 and completed in 2002 as scheduled.

====Genoa II====
{{Main|Project Genoa II}}
While Genoa primarily focused on intelligence analysis, Genoa II aimed to provide means by which computers, software agents, policymakers, and field operatives could collaborate.<ref name= verton>{{cite magazine| author = Dan Verton | title = Genoa II: Man and Machine Thinking as One| url = https://books.google.com/books?id=N1zRvHre4noC| magazine = [[Computerworld]]| publisher = IDG Enterprise| date = 1 September 2003| access-date= 3 June 2016}}</ref>

====Genisys====
[[File:Genysis.gif|thumb|Graphic describing the goals of the Genysis project]]
Genisys aimed to develop technologies that would enable "ultra-large, all-source information repositories".<ref name="iaosite-genisys">{{cite web|url=http://infowar.net/tia/www.darpa.mil/iao/Genisys.htm|title=Genisys|work=Information Awareness Office (official website)|access-date=2009-03-15|url-status=dead|archive-url=https://web.archive.org/web/20090216080922/http://infowar.net/tia/www.darpa.mil/iao/Genisys.htm|archive-date=2009-02-16}}</ref> Vast amounts of information were to be collected and analyzed, and the available [[database]] technology at the time was insufficient for storing and organizing such enormous quantities of data. So they developed techniques for virtual data aggregation to support effective analysis across heterogeneous databases, as well as unstructured public data sources, such as the [[World Wide Web]]. "Effective analysis across heterogenous databases" means the ability to take things from databases which are designed to store different types of data—such as a database containing criminal records, a phone call database and a foreign intelligence database. The Web is considered an "unstructured public data source" because it is publicly accessible and contains many different types of data—blogs, emails, records of visits to websites, etc.—all of which need to be analyzed and stored efficiently.<ref name="iaosite-genisys"/>

Another goal was to develop "a large, distributed system architecture for managing the huge volume of raw data input, analysis results, and feedback, that will result in a simpler, more flexible data store that performs well and allows us to retain important data indefinitely".<ref name="iaosite-genisys"/>

====Scalable social network analysis====
Scalable social network analysis (SSNA) aimed to develop techniques based on [[social network analysis]] to model the key characteristics of terrorist groups and discriminate them from other societal groups.<ref name="ethier">{{cite web|url=http://spyapps.net/current-research-in-social-network-theory/ |title=Current Research in Social Network Theory |last=Ethier |first=Jason |work=Northeastern University College of Computer and Information Science |access-date=2009-03-15 |url-status=dead |archive-url=https://web.archive.org/web/20150226213456/http://spyapps.net/current-research-in-social-network-theory/ |archive-date=February 26, 2015 }}</ref>

====Evidence extraction and link discovery====
[[File:EELD.gif|thumb|right|Graphic displaying a simulated application of the evidence extraction and link discovery (EELD) project]]

Evidence extraction and link discovery (EELD) developed technologies and tools for automated discovery, extraction and linking of sparse evidence contained in large amounts of classified and unclassified data sources (such as phone call records from the [[NSA call database]], internet histories, or bank records).<ref name="iaosite-eeld">{{cite web|url=http://infowar.net/tia/www.darpa.mil/iao/EELD.htm|title=Evidence Extraction and Link Discovery|work=Information Awareness Office (official website -- mirror)|access-date=2009-03-15|url-status=dead|archive-url=https://web.archive.org/web/20090215094707/http://infowar.net/tia/www.darpa.mil/iao/EELD.htm|archive-date=2009-02-15}}</ref>

EELD was designed to design systems with the ability to extract data from multiple sources (e.g., text messages, social networking sites, financial records, and web pages). It was to develop the ability to detect patterns comprising multiple types of links between data items or communications (e.g., financial transactions, communications, travel, etc.).<ref name="iaosite-eeld"/> It is designed to link items relating potential "terrorist" groups and scenarios, and to learn patterns of different groups or scenarios to identify new organizations and emerging threats.<ref name="iaosite-eeld"/>

====Wargaming the asymmetric environment====
Wargaming the asymmetric environment (WAE) focused on developing automated technology that could identify predictive indicators of terrorist activity or impending attacks by examining individual and group behavior in broad environmental context and the motivation of specific terrorists.<ref>{{cite web| url = http://infowar.net/tia/www.darpa.mil/iao/WAE.htm| title = Wargaming the Asymmetric Environment (WAE)| website = www.darpa.mil/iao| publisher = [[Information Awareness Office]]| access-date = 16 June 2016| url-status = dead| archive-url = https://web.archive.org/web/20120528103612/http://infowar.net/tia/www.darpa.mil/iao/WAE.htm| archive-date = 28 May 2012}}</ref>

====Translingual information detection, extraction and summarization====
Translingual information detection, extraction and summarization (TIDES) developed advanced language processing technology to enable English speakers to find and interpret critical information in multiple languages without requiring knowledge of those languages.<ref name="iaosite-tides">{{cite web|url=http://infowar.net/tia/www.darpa.mil/iao/TIDES.htm|title=TIDES|work=Information Awareness Office (official website -- mirror)|access-date=2009-03-15|url-status=dead|archive-url=https://web.archive.org/web/20090215094744/http://infowar.net/tia/www.darpa.mil/iao/TIDES.htm|archive-date=2009-02-15}}</ref>

Outside groups (such as universities, corporations, etc.) were invited to participate in the annual [[information retrieval]], topic detection and tracking, automatic content extraction, and [[machine translation]] evaluations run by [[NIST]].<ref name="iaosite-tides"/> [[Cornell University]], [[Columbia University]], and the [[University of California, Berkeley]] were given grants to work on TIDES.<ref name= bigbrother/>

====Communicator====
[[File:Total Information Awareness -- Communicator diagram.gif|thumb|right|300px|Diagram describing capabilities of the "communicator" project]]

Communicator was to develop "dialogue interaction" technology to enable warfighters to talk to computers, such that information would be accessible on the battlefield or in command centers without a keyboard-based interface. Communicator was to be wireless, mobile, and to function in a networked environment.<ref name="iaosite-communicator">{{cite web|url=http://infowar.net/tia/www.darpa.mil/iao/Communicator.htm|title=Communicator|work=Information Awareness Office (official website)|access-date=2009-03-15|url-status=dead|archive-url=https://web.archive.org/web/20090215094648/http://infowar.net/tia/www.darpa.mil/iao/Communicator.htm|archive-date=2009-02-15}}</ref>

The dialogue interaction software was to interpret dialogue's context to improve performance, and to automatically adapt to new topics so conversation could be natural and efficient. Communicator emphasized task knowledge to compensate for natural language effects and noisy environments. Unlike automated translation of [[natural language processing|natural language]] speech, which is much more complex due to an essentially unlimited vocabulary and grammar, Communicator takes on task-specific issues so that there are constrained vocabularies (the system only needs to be able to understand language related to war). Research was also started on foreign-language computer interaction for use in coalition operations.<ref name="iaosite-communicator"/>

Live exercises were conducted involving small unit logistics operations with the [[United States Marines]] to test the technology in extreme environments.<ref name="iaosite-communicator"/>

====Human identification at a distance====
[[File:Human-id-at-a-distance.gif|thumb|right|300px|Diagram describing capabilities of the "human identification at a distance" project<ref name="iaosite-humanid"/>]]

The human identification at a distance (HumanID) project developed automated [[biometric]] identification technologies to detect, recognize and identify humans at great distances for "force protection", crime prevention, and "homeland security/defense" purposes.<ref name="iaosite-humanid">{{cite web|url=http://infowar.net/tia/www.darpa.mil/iao/HID.htm |title=Human Identification at a distance |work=Information Awareness Office (official website -- mirror) |access-date=2009-03-15 |url-status=dead |archive-url=https://web.archive.org/web/20090215094729/http://infowar.net/tia/www.darpa.mil/iao/HID.htm |archive-date=February 15, 2009 }}</ref>

The goals of HumanID were to:<ref name="iaosite-humanid"/>

* Develop algorithms to find and acquire subjects out to 150 meters (500&nbsp;ft) in range.
* Fuse face and [[gait]] recognition into a 24/7 human identification system.
* Develop and demonstrate a human identification system that operates out to 150 meters (500&nbsp;ft) using visible imagery.
* Develop a low-power millimeter wave radar system for wide field of view detection and narrow field of view gait classification.
* Characterize gait performance from video for human identification at a distance.
* Develop a multi-spectral infrared and visible [[facial recognition system|face recognition]] system.

A number of universities assisted in designing HumanID. The [[Georgia Institute of Technology]]'s [[Georgia Institute of Technology College of Computing|College of Computing]] focused on [[gait recognition]]. Gait recognition was a key component of HumanID, because it could be employed on low-resolution video feeds and therefore help identify subjects at a distance.<ref name= biometrics>{{cite book| last1 = Bolle| first1 = Ruud M. | last2 = Connell| first2 = Jonathan | last3 = Pankanti| first3 = Sharath| last4 = Ratha| first4 = Nalini K.| last5 = Senior| first5 = Andrew W.| title = Guide to Biometrics| publisher = Springer Science & Business Media| edition = illustrated| date = 29 June 2013| pages = 239| url = https://books.google.com/books?id=DLLbBwAAQBAJ| isbn = 9781475740363}}</ref> They planned to develop a system that recovered static body and stride parameters of subjects as they walked, while also looking into the ability of time-normalized joint angle trajectories in the walking plane as a way of recognizing gait. The university also worked on finding and tracking faces by expressions and speech.<ref name= gtech>{{cite web| url = http://www.cc.gatech.edu/cpl/projects/hid/| title = Human Identification at a Distance| date = 2003| website = www.cc.gatech.edu| publisher = [[Georgia Institute of Technology College of Computing]]| access-date = 16 June 2016}}</ref>

[[Carnegie Mellon University]]'s Robotics Institute (part of the [[Carnegie Mellon School of Computer Science|School of Computer Science]]) worked on dynamic face recognition. The research focused primarily on the extraction of body biometric features from video and identifying subjects from those features. To conduct its studies, the university created databases of synchronized multi-camera video sequences of body motion, human faces under a wide range of imaging conditions, AU coded expression videos, and hyperspectal and polarimetric images of faces.<ref name=cmu>{{cite web| url = http://www.ri.cmu.edu/research_lab_group_detail.html?lab_id=56&menu_id=263| title = Human Identification at a Distance (HumanID)| website = Carnegie Mellon University: The Robotics Institute| publisher = [[Carnegie Mellon University]]| access-date = 16 June 2016| archive-url = https://web.archive.org/web/20160809063631/http://www.ri.cmu.edu/research_lab_group_detail.html?lab_id=56&menu_id=263| archive-date = 9 August 2016| url-status = dead| df = dmy-all}}</ref> The video sequences of body motion data consisted of six separate viewpoints of 25 subjects walking on a treadmill. Four separate 11-second gaits were tested for each: slow walk, fast walk, inclined, and carrying a ball.<ref name= biometrics/>

The [[University of Maryland]]'s Institute for Advanced Computer Studies' research focused on recognizing people at a distance by gait and face. Also to be used were [[infrared]] and five-degree-of-freedom cameras.<ref>{{cite web| url = http://www.umiacs.umd.edu/labs/pirl/hid/overview.html| title = Human Identification at a Distance: Overview| date = 17 April 2001| website = University of Maryland Institute for Advanced Computer Studies| publisher = [[University of Maryland]]| access-date = 16 June 2016}}</ref> Tests included filming 38 male and 6 female subjects of different ethnicities and physical features walking along a T-shaped path from various angles.<ref>{{cite book| editor = Bahram Javidi| title = Optical and Digital Techniques for Information Security| publisher = Springer Science & Business Media| series = Advanced Sciences and Technologies for Security Applications| volume = 1| edition = illustrated| date = 28 June 2005| pages = 283| url = https://books.google.com/books?id=amZSD-UJUVMC| isbn = 9780387206165}}</ref>

The [[University of Southampton]]'s Department of Electronics and Computer Science was developing an "automatic gait recognition" system and was in charge of compiling a database to test it.<ref>{{cite web| url = http://www.gait.ecs.soton.ac.uk/| title = Automatic Gait Recognition for Human ID at a Distance| last = Nixon| first = M.S.| date = 7 August 2003| website = www.ecs.soton.ac.uk| publisher = [[University of Southampton]]| access-date = 16 June 2016| archive-url = https://web.archive.org/web/20160805154831/http://www.gait.ecs.soton.ac.uk/| archive-date = 2016-08-05| url-status = dead}}</ref> The [[University of Texas at Dallas]] was compiling a database to test facial systems. The data included a set of nine static pictures taken from different viewpoints, a video of each subject looking around a room, a video of the subject speaking, and one or more videos of the subject showing facial expressions.<ref>{{cite web| url = http://www.utdallas.edu/~otoole/HID/hum_id_main.html| title = Human Identification Project| last = O'Toole| first = Alice| website = www.utdallas.edu| publisher = [[University of Texas at Dallas]]| access-date =16 June 2016}}</ref> [[Colorado State University]] developed multiple systems for identification via facial recognition.<ref>{{cite web| url = http://www.cs.colostate.edu/evalfacerec/index10.php| title =  Evaluation of Face Recognition Algorithms| website = www.cs.colostate.edu| publisher = [[Colorado State University]]| access-date = 16 June 2016}}</ref> [[Columbia University]] participated in implementing HumanID in poor weather.<ref name= cmu/>

====Bio-surveillance====
[[File:Bio-Surveillance.gif|thumb|right|Graphic describing the goals of the bio-surveillance project]]

The bio-surveillance project was designed to predict and respond to [[bioterrorism]] by monitoring non-traditional data sources such as animal sentinels, behavioral indicators, and pre-diagnostic medical data. It would leverage existing disease models, identify abnormal health early indicators, and mine existing databases to determine the most valuable early indicators for abnormal health conditions.<ref name= BIO/>