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Pathways Summary Brief 25 Aug2010



Overview to the HSCB Pathways Program

Overview to the HSCB Pathways Program



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  • Pathways is an integrated program developed within the DDR&E sponsored Human Social Culture & Behavior Modeling program (HSCB).Pathways is about building a capability to address DoD needs to conduct Socio-cultural modeling. We will do this by allowing models and data to be brought together and made interoperable with each other and disparate data (hybrid); and therefore useful in conducting theory-driven analyses to meet timely operational decision making requirements. Three key concepts we will address in this brief are: What is a socio-cultural topology? How will we navigate a socio-cultural topology ? and, Why hybrid modeling?Finally, we will discuss technical and program metrics that will tell us when we are successful.
  • The Social-Cultural space can be thought of as multi-dimensional. Mapping all the dimensions requires thinking about a conceptual surface – an n-dimensional map. Further the dimensions can and do overlap, and in some cases are orthogonal to each other. This makes this a very complex problem to ask operational decision makers to get their heads around! Some dimension are that: There are groups of people, that are:Geo-spatially distributed, Move in both space and time, have values (that are relatively stable), attitudes that are complex and dynamic, Competing for resourcesHave trigger issues Are being influenced by a number of other people and factors: Including economics, politics (local, regional, etc.), transportation, corruption, etc. * These Questions developed during Skope “HSCB Day with cross-domain analysts.
  • There are different types of S-C models in this domain – all of which will be necessary to addressing operational S-C needs. It is useful to note that the different kinds of S-C models lend themselves to answering different kinds of questions. “What Is” questions are often best addressed through data-driven models and methods. “What if” questions which involve predictive analyses often are addressed using theory or model driven methods. We posit that every S-C analysis will need to incorporate both approaches.Further, the context of these what if and what is analyses will change as the unit of interest changes from local people and groups to regional and national or even international analyses.
  • Data is clearly going to be critical – and yet it is highly disparate - taking very different forms - comes from all kinds of sources - in lots of different security enclaves. This is very complex. It needs to be brought together and made accessible to Look at the analysis side – it is really hard to do analyses when you are dealling with enormous amounts of data. The left side shows the diversity of data that will have to be dealt with on an on-going basis.
  • This is a conceptual picture of S-C Modeling domain. Data driven models help define the topology and what is known. Hypothesis driven modeling will enable predicting outcomes. Together they allow the identification of S-C Pathways and thus, navigation of the S-C domain space. What is hard in addressing S-C User requirements?In data driven models the critical problem is considering what data to include and conditioning it to send into the models (simulations)In the theory driven approaches we are pushing out beyond the data to explore what you do & don’t know – in effect map out the domain spaceIn order to Navigate the S-C domain, we need to consider both and develop a capability to both discover hills & valleys, centers of gravity as well as plot a course through the space. This will require models to be broken down into theoretically meaningful meta-models that will serve to constrain the problem space, and allow the S-C theorist / modeler to assess the validity of the hybrid models.
  • What makes this hard: High Uncertainty & Dynamics. In 1972, Dr. Horst Rittel coined the phrase “wicked problem” to described the complex interplay of social, political, and cultural dynamics. Also known as interactive, complex and adaptive problems, wicked problems are exactly what “wars amongst the people” are… This is why we need a framework that supports hybrid modeling… The Framework will be an engine for navigating in the S-C domain.Hybrid Modeling means:The joining of 2 (or more) different modeling products (& data) to address an operational need. This means we need to think of the products as having complicated probability distribution models. Therefore, we need to think of COAs as having a distribution function – not a point as we do today. Further hybrid modeling means mashing together models with data that may not have been structured for, or used with a model.Pathways assertion: Addressing the DoD requirements for S-C will require seeding simulations with real world (empirical) data, then using constrained predictions of change using models derived from theories. Individual Models and theories will be implemented as S-C meta models that constrain the topology (problem space) and suggest meaningful assumptions and limitations in developing alternative Courses Of Action (COAs).
  • Five technology development Requirements:Data organization via meta-taggingModel characterization to aid discovery and integrationArchitecture for joining collections of models, create COA modelsThe definition of a S-C State Domain Controller based on S-C theory and constrains modeling knowledge requirements & actively tests underlying assumptions.Discovery of key factors within modelsVisualization that links data, models, results- There is a body of data from the real world, viewed here as state variables.  Some of these variables are explicitly collectible; while others are derived from the collected information.  Among the collectible data, there are some that could be influenced, e.g., to effect a preferred course of action.  The first key technology is to organize all this data (sea of data) to be accessible as the data and applications evolve. - There is the concept of Socio-Cultural terrain (s). The terrain is n-dimensional (reflecting not just geography, & time, but attitudes, environmental factors, outside influences that might warp the terrain space). Extreme (game changing) states could be shown as peaks & valleys, or shifts to alternate S-C terrain maps; for instance droughts/floods, feast / famine would change the shape of the map). This serves the Navigation metaphor by allowing one to indicate "where one is".  There are many types of maps.  One technology challenge is how to transform the state data to a coordinate position on the map(s).  In the schematic, one takes X0 and Y0 and locates one's initial position as S0. - Once one has (is on) a socio-cultural terrain, the concept of Course of Action models enters the picture.  The architecture technologies make it easy to produce such COA models.  See Path1 and Path2 in the schematic.  The architecture also makes it possible to discover the actionable factors within the models. - Finally, the visualization technologies allow the analyst to examine the possible paths (here, shown as Path1 and Path2) and then examine what input variables and settings would cause each path to be realized. 
  • Might be useful to think of the Meta-Theory as a Business or Process model for S-C Analysis.Different processes might be appropriate for different S-C domains, e.g.How to do S-C modeling that marginalizes insurgents within a populationHow to do S-C modeling that facilitates stabilizations at the local levelHow to empower local governments during humanitarian crisis.How to detect external influences to economic & political stability.Performers:Pick a context you are enthusiastic about (or two)Need first cut by Aug QPR Meetings. Evaluate during Phase 2 (if not sooner). Nice if you talk to each other….. The expectations is that one of our system metrics is interoperability… Provide graphics as storyboards to support outreach. Video?? Tell us when they will be implemented for evaluation.Provide alternate models considered & rationale.Gov’t may seek to apply S-C meta-theories as point of convergence among architectures. End of Phase 2 – Formal evaluations of Meta-Theories as implemented within architectures.
  • We believe that hybrid modeling for the S-C domain will need to be tied to a meta-model that is both meaningful and observable to the S-C theorists. It will instantiate a meta-theory for the creation of hybrid S-C models. It must be meaningful to the users of the hybrid-models, and as such, will have visualization components coupled to the meta-model within the Pathways visualization framework. The meta-model shown here is representative of the kind of model we may need. It was developed under the IARPA A-SpaceX program and describes the common elements of the analytic process. The analytic process is inherently structured, so this model seems to be very robust across a number of domains. This model is similar to those taught to analysts with the IC. There are two conceptual loops embedded within the model: Foraging (Looking for and organizing raw information); and Sense Making (Organizing information to address a problem or topic). a key feature is that the transition between stages are detectable as explicit behaviors. Adding structure is tantamount to adding information. The analyst ultimately composes a story to be shared with other people, and should be able to provide supporting evidence and explain the interpretation that led there. When elements at an upper stage do not make sense, or require new information to supplement, the analyst iterates back down through the stages.The process is highly iterative … but generally linear (one must go through all the steps to some degree for a given analysis to deliver a complete analysis and be able to explain it). How should we implement the meta-model? Need to address:How would you show a meta-model is correct?How will you address what is required for care and feeding of the models / meta-models? (How will you know if the meta-model you are using is appropriate and current?) Social theory should suggest the meta-model. We should look for ontologies that suggest the S-C variables and decompose them to show inter-dependencies – in effect reveal a meta-theory for the S-C theories & models we expect to deal with. We may want to think about levels of meta-models….What would you propose as a “mechanical” construct for addressing this issue?Linearize the state space so as to constrain hybrid models & complexities. See also optimal filtering… Use to limit the state space.We cannot be using the models in an open-loop modeling process…. Might want to implement this function in terms of a “Model Predictive Controller”. Take in observations to verify that the topology model is appropriate, and it will be valid to use a meta model.Limit the hybrid modeling to 6-8 terms – these should be derived from the meta-model.Do we have constant measurements that can feed the controller? What are they?Note: The goal of a Model Predictive Controller is to facilitate goal constrained optimization. It should:Show possible actionsLet the modeler Identify the best actionsSuggest the Schedule for actionsTell us when the model is wrong; suggest how the model could be fixed. Tell us when we are operating outside identified constraints.
  • These are not definitive nor exhaustive. They are an initial attempt to characterize the performance characteristics we believe would demonstrate a suitable S-C meta-theory that would facilitate S-C Hybrid modeling.
  • This schematic provides a functional view of how Pathways contributes to the analysis process. It starts with an overall policy or treatment question, e.g., a commander is wanting to improve the economy in a province via business initiatives. The four steps are as follows:A large corpus of data is assembled and a variety of relationships are determined. These can be correlations, or in some cases may represent causal relationships. These relationships are the basis for the next step, finding models appropriate to the analysis questions.In this step, the analyst develops several topics or lines of inquiry to answer the overarching question. These could be, for this discussion, different business sectors in which the commander might recommend investments. Pathways would assemble hybrid models that allow projections of courses of action.The third step simulates several potential outcomes for different settings of decision variables.The last step compares these projections with respect to real world data. The actual evidence may not yield strong support for any of the projected paths. The Evidence Calculus would measure the degree of support, and would suggest where additional data would be most beneficial in improving this measure. In more complex scenarios, this assessment of evidence coupled with a larger set of projections can also help suggest what next questions should be addressed.Metrics for Pathways development include:How many data categories are incorporated in Step 1 and how many relationships are discernedHow many analysis topics are generated (with some computer support) and how well-matched are the projections to real data (measured in scientifically valid experiments)How useful are the projections when measured by the evidence calculus. I.e., can the degree of support of the modeled projections, as measured by the evidence calculus, be improved upon with guided and feasible additional data collection.
  • How are we going to implement this… Bottom up & top-down strategy. We will Work with real users. Across the top are candidate exemplars… Users will work through a common interface that guides them through the critical capabilities and limitations of component models and with limitations of specific data. The “knob and dials” and strategies for using them are composed as the mash-up is composed. We will develop hybrid model implementations that work within this new framework that create specific decision support solutions the analysts can deliver to their commanders. We will be able to integrate from a technology base of emergent model and tool development efforts (e.g. from ONR).
  • Approach to bringing it together – Technology Integration Events (TIEs). Throught the TIES we will know that we are meeting the objectives.
  • How will we know we are successful?Pathways will: (Way ahead from MG Flynn Fixing Intel Document, Jan, 2010)Enable automatic collection and processing of huge amounts of social and cultural information to answer questions about:Local economics and wealth / property ownership.Power brokers and how they may be influenced.Metrics and predictors of effectiveness for development projects and level of cooperation of local populace.Communication conduits with people in a position to provide current, relevant informationEnable analysts to identify what they know and don’t know in utilizing a model, as well as what assumptions they have made.Provide decision makers with knowledge, analysis and information needed to wage a successful counter-insurgency.Provide a conceptual map to leverage popular support and marginalize the insurgency itself.

Pathways Summary Brief   25 Aug2010 Pathways Summary Brief 25 Aug2010 Presentation Transcript

  • HSCB Pathways Program25August 2010
  • HSCB & The Need for Frameworks
    HSCB Phase 1: Shotgun of projects. All about models… “Seeds in the field & Let’s see what grows” – Showcased at “Focus 2010”
    HSCB Phase 2: Need to rationalize & create foci for rapid protyping into operational capabilities by FY12
    • Define a common “framework” to ensure that models and data will come together as needed
    • Must be supportable & transitionable within DoD PORs
    • Address urgent operational needs in a repeatable manner
    • Form basis for “composable” modeling
    • Serve as catalyst for next generation S-C modeling
    • 6.3 / 6.4 Foci given anticipated HSCB Funding profile
    CTTSO releases HSCB BAA 09-Q-4590 in May 2009
    CTTSO HSCB BAA 09-Q-4590
    Goal: Build and demonstrate end-to-end HSCB functional capabilities:
    Enable an analyst to translate an operational requirement to into a analytic strategy given available data & models
    Execute best available models against best available data (individually & as hybrid / composites) to perform analyses
    Visualize and share results, source data & models in a consistent manner amenable to supporting command / tactical decision-making related to understand stability and threats in regions and develop appropriate course of action
    Semi-automatically manage data, condition and load it into appropriate models
    Provide a basis for an analyst to find and link together models with data to develop a usable product that supports operational decision making (i.e. enable Hybrid-Modeling).
  • Road to Pathways
  • HSCB Pathways ProgramDefining a Navigation Frameworkfor Socio-Cultural Topology
    28 July 2010
  • MG Flynn, USA, J2 ISAF; “Fixing Intel” - Jan 2010
    “Our operators must find better ways to answer fundamental questions about the environment in which we operate and the people we are trying to protect and persuade.”
  • HSCB Environment:Socio-Cultural (S-C) Topology questions are diverse
    Model Driven Methods
    “What if new economic initiatives are implemented in the southern provinces?
    “What if acceptable stability for the country is not achieved in the next 6 months?
    “What if local and district groups were empowered to define the rule of law and justice?”
    What if Questions
    Data Driven Methods
    “What is the local population’s attitude toward the insurgents? Is the population ready to marginalize the insurgency movement, especially in the south.
    “What is the village’s sentiment toward US? Has it changed since the 2 new schools were built?”
    “What are the key factors that drive popular support for the insurgency verses that for the government?”
    What is
    Individuals and
    Small groups
    Regional Populations
    General Population,
    Government Institutions.
  • S-C Data Challenges
    Diverse and Dynamic Data
    Variety of Models
    Structured tables
    Descriptive, Statistical
    Geo-spatial data
    Unstructured text from reports
    Chat rooms
    Pathways Modeling Engine
    Today’s Limits: Few extant methods and standards for joining information, analyses, and forecasts of this breadth, volume, and variability. Real World Data
    Impact if Pathways is successful: Enhanced mission performance through easier data organization and access, and by making analyses, and forecasts easier to assemble and use
  • Pathways Objective Capability:
    Socio-Cultural Navigation
    What if this occurred; or action was taken?
    Hypothesis Driven Methods
    Models for humanitarian response
    Models for forward base
    Models for Division HQ to determining tipping points
    Modeling Challenges:
    Develop Models for the Mapping S-C topology
    Develop Models for Navigating the topology
    Develop Models for forecasting plausible futures
    What is the Status?
    Data Driven Methods
    Socio-Cultural Data
  • Develop a new hybrid modeling engine for navigating the Socio-Cultural Topology.
    Pathways Technical Objective
    Address the full spectrum of diverse, military, S-C needs as they emerge
    • Enable the tailored and rapid assembly of models with best available data
    • Enable the discovery and adaption of data to meet emergent operational needs.
    • Enable better understanding the operational S-C environments.
    • Support exploring fundamental “what if” and “what is” questions.
    • Provide a common user interface to enable access to hybrid models & data - with interactive visualizations that support S-C situation awareness and commanders’ option assessment.
  • 4. Discovery of actionable factors within the models that influence any given outputs
    3. Build Architecture for joining heterogeneous collections of models; with quick addition of new models, to create COA models
    5. Visualization of threads that link data, models, and analysis to increase model/decision transparency
    2. Model characterization to aid discovery and integration into different applications, i.e., use State Data to generate S-C maps (typically data-driven models in this step)
    Key Technology
    1. Enable data organization via meta-tagging
    Socio-Culture Topology & Requirements
    Socio-Culture Topology: (n-Dimensional State Space)
    • Geospatial & Temporal
    • Entities, e.g.
    • People (individuals)
    • Groups
    • Institutions
    • Events
    • Economics & Security
    • Resources (& movement)
    • Attitudes, Values & Influences, and trends
    State Data
    Data not
    subject to
    Data that
    can be
    Each map may have its own topology, coordinate/attribute scheme.
  • Modeling Conceptual Challenge
    “How do we know we are getting the right answers - not just getting the wrong answers faster?”
    Better question: How do we make sure we are getting useful results from hybrid models?
    Develop Process Theories for how Hybrid Models will be used.
    Different models may be applicable to different analysts at different echelons & with different problems.
    Expose model & data at the appropriate levels to be meaningful to S-C Theorists & Analysts
    “Essentially, all models are wrong – but some are useful.”,
    (George E. P. Box)
  • Meta-Theory for S-C Analysis
    Manage the S-C Modeler / Analyst Dialog as a repeatable Process.
    Demonstrate that we can get better answers through Hybrid Modeling.
    Challenge: Start with needs based on what an analyst does today: Define a process theory that will be meaningful to S-C Hybrid Modeling
    Show what can & needs to be done
    Provide a System Diagram & narrative addressing Process
    Map out and expose an S-C Topology
    Develop Courses of Action given the S-C Topology
    Identify Strengths & Weaknesses
    Describe your plan to address weaknesses
    Define Metrics for assessment
    Propose program assessment protocols & metrics
  • Reevaluate
    Search for Support
    Tell Story
    Search for Evidence
    Foraging Loop
    Build Case
    Search for Relations
    Evidence File
    Search for Information
    Sense Making Loop
    Read & Extract
    External Data Sources
    Search & Filter
    Courtesy of PARC (2007)
    A Meta-Model for the Analytic Process
  • Notional Meta-Theory ObjectivesTell us where you think we will end up*
    Tells us what model decomposition is appropriate & meaningful to end users.
    Tells us about data
    What sort of data is needed & help maps what data is available
    Tells the form(s) of data should be to answer need
    Suggests an “evidence calculus”;
    What we need to know from the models
    What we do / don’t know
    Necessary assumptions
    Hypotheses that need to be explored
    ID schemas to tell the story
    ID the Inputs/Outputs of the model to address the operational questions
    *Subject to change without notice
  • Policy/Treatment Question
    Topic 1
    Topic 2
    Topic 3
  • Pathways Way-Ahead
    Brigade & Above
    Strategic Influence for
    Sudan, Congo &
    Horn of Africa
    Battalion & BelowStability Operations for Provincial ReconstructionTeam in Afghanistan
    Tools and Techniquesfor Non-obvious relationships
    1. Select Exemplars that Span Diverse Applications
    Interactive Visualization tools
    2. Identify Hybrid Models that should Address the Exemplars
    Model- and Data-Driven
    3. Develop New Modeling Integration Framework joining Data- and Model-driven uses
    New Generation Modeling System
    4. Integration of point solutions when & where appropriate
    Technology Base for Model andInformation System Development
  • Pathways’ Key Milestones
    Testing, Transition
    Aids to Automate, Guide Analysis
    Dynamic Model, Data Selection
    Establish Static System
    TIE #2
    Technology Integration Experiments (TIE)
    Milestone 1
    Milestone 3
    Milestone 2
    Milestone 4
  • Pathways Program Overview
  • 20
    Hybrid Modeling Engine
    Supporting “mash-up” with data & tailoring on demand
    One-off solutions with hard-wired models & data
    Static views with no visibility into inner workings
    Interactive Visualization
    End-to-End System
    Model Components
    User Composeable - Scaleable Framework
    Custom, brittle, implementations
    Pathways: Evidence of Success
    Combine Empirical and Theory Driven Approaches
    Arbitrary technical approaches guiding tool development
    Hybrid Modeling for Navigating the Socio-Cultural Topology
  • HSCB Pathways ProgramDefining a Navigation Frameworkfor Socio-Cultural Topology
    Combating Terrorism Technical Support Office, (CTTSO)
    Human Social, Culture & Behavior Modeling Program (HSCB)
  • Backup
  • Initial Insights, Concerns & Caveats
    Insights & Concerns:
    Pathways needs to define Challenge Problems (by program phase).
    Clear, Compelling, Operationally Relevant
    Framed in a suitable context
    S-C Theory derived meta-models
    Strategically chosen Mission Areas
    Assessment & Metrics – Evolving as we go … we need input ASAP!
    Programmatic – What progress are you making & is it consistent with the plan?
    Technical – Does it do anything? Does it do what it needs to do?
    Operational – Does it do anything useful & of interest to our customers? Why should we care?
    Transition – Will it go / is it going … anywhere?
  • Initial Insights, Concerns & Caveats
    Insights & Concerns:
    Need to develop “stories” for inside (HSCB) & outside consumption (Scientific Modeling /End-users)(Know you audience!!)
    Vision: Complementary... To HSCB, to each other, to related sponsored efforts
    Mission, Goals & Objectives (by program phase)
    Technology Integration Events (TIEs) & Formal Assessments
    HSCB Outreach Events… as directed.
    Need media & stories ASAP to support “emergent” HSCB outreach events.
  • 25
    Tell a “Story”
    BLUF: You need a story...
    You need to tell us what you are going to do...
    It needs to have an elevator speech ...
    Every story will be different (know your audience!)…
    We need supporting media (stand alone): Posters, 3-Minute Video, etc.
    We will do what we can to help…
    • Each project needs to tell a story that makes it clear where you are going, why it is important, how it is relevant to HSCB / Pathways, and why it will make a difference
    • Heilmeier Catechism: (George H. Heilmeier, DARPA TD 1975-77)
    • What are we trying to do?
    • How does this get done at present? Who does it? What are the limitations of the present approaches?
    • What is new about your approach? Why do we think you can be successful at this time?
    • If you succeed, what differences do you think it will make?
    • How long do you think it will take? What are your mid-term and final exams?
    • How much will it cost?
  • Notional Pathways Story Template
    Commander Smith needs to know X in order to do Y – turns to his staff…
    An analyst has n hours to help the commander. He breaks the information need into these questions: A, B, C.
    He uses (Pathways Framework) as a decision support system to find best available information that will answer the questions.
    Discovers models that might help answer the questions
    Looks for and discovers contextually relevant data that could feed the models.
    Assesses the applicability of data to the models & conditions the data as needed.
    Develops (or verifies) an understanding the S-C topology. (Note: May link together models to create the needed S-C Topology.)
    Starts Hybrid Modeling; linking models & data together to create Courses Of Action (COAs) within the topology (s). Documents Assumptions & Limitations.
    Evaluates COAs & Develops recommendations
    Packages Recommendations to give to Commander.
    Command staff looks at recommendations and have visibility into supporting models / analyses.
    Commander makes decisions, wins the war, and everyone lives happily ever after!
  • Development Context Options
    Pathways Kick-Off Guidance
    NEXUS Proposal
    PRISM Proposal
  • Preliminary Recommendations
    SSTR – Somalia - Hospital opening in Mogadishu
    Leverage LM pathfinder project (availability of initial models, data)
    Scenario defined by LM SME (Alex Moore) – value / correctness verified w/ active duty members of reserves
    IO - Mexico – Influence campaign / Military campaign analysis
    Leverage LM Opinion Propagation Models, structured equation models
    Leverage relevant Columbian analyses / models – agent based models related to drug interdiction operations
    Stability Analysis - Congo – Potential partition / stability analyses
    Potential leverage of statistical models and open source models
    Leverage of LM – ORNL Shared vision program – Congo interest
    Considered high interest to AFRICOM
    IO - Disappearance of Leaders – Single Bullet
    Multiple theories could be implemented as models
    Significant literature on authoritarian governments
    Instances of models could be applied to multiple situations
  • HSCB Analysis Users
  • HSCB Planning Users
  • Challenge 1 – COIN Operations in Afghanistan
    Dynamic social political environment; violent disruptions and coercive influences
    Inefficient or Corrupt Governance Practices; Urban-Rural divide
    Regional geo-political influences
    Widely distributed rural societies; embedded threats
    Social-Cultural Analysis Challenges in Quasi-Stable Environments
    Three ISAF LOOs
    Data: Availability of adequate social-cultural and economic data.
    Decision Support: Availability of decision support tools in combination with data to:
    Enable analysts to understand social-cultural dynamics
    Enable planners to develop lines of effort and COA’s within the S-C context
    Enable policy-makers to make effective decisions and create measurable social, security, economic opportunities in Afghanistan.
  • Challenge 2- Strategic Influence Planning in HOA
    Phase 0 (Shaping) Challenges
    Counter growing influence of China
    Preventing spill-over of instability across borders
    Deny safe havens
    Data: Sparse social-cultural and economic data to support sources of influence and behavior to sources
    Decision Support: Availability of decision support tools in combination with data to:
    Enable analysts to understand diverse interests, perspectives, perceptions, and influences
    Enable planners to develop lines of effort and COA’s within the S-C context
    Enable policy-makers to make effective decisions and create measurable effects of Strategic Communications, diplomatic , security, and economic COA’s.
    Horn of Africa
    AFRICOM challenge problems; phase 0 shaping
    Tribal power struggles; environmental degradation; resource competition
    Marginal infrastructure; limited media sources
    Competing foreign influences
  • Project Quad Charts
  • NEXUS Pathways
    OBJECTIVE: Exploit a broad range of extant and evolving heterogeneous Socio-Cultural Modeling and Simulation services to foster improved 1) Situation Understanding and Exploitation; (2) Cultural Drivers and Theories; 3) Course of Action Assessment and (4) Decision Support Options
    MILITARY RELEVANCE: Forecast and Assess the impact and consequences of potential actions on beliefs of hostile, friendly, and neutral actors for specific areas and contexts of interest.
    Enable commanders and command staff to readily collect, model, forecast, and monitor pertinent situation, trends, and activities.
    Support a broad range of critical military mission areas including Stability, Security, Transition and Reconstruction (SSTR), Influence Operations (IO), Stability Analysis, Humanitarian Assistance and Disaster Relief (HA/DR), etc.
    Integrated Socio-Cultural Model and Data Exploitation for Multiple Missions & Granularity
    TECHNICAL APPROACH:Unlock and link the power of heterogeneous models, simulations, tools, and data through a services oriented architecture (SOA) focused on:
    • Providing innovative modeling and data analytic capabilities including composing hybrid models, semantic and theoretically grounded model interoperability, mixed-method forecast triangulation, etc.
    • Implementing translation and brokering services to support data-dependent modeling/simulation needs from a virtual distributed heterogeneous pool of data sources.
    • Demonstrating framework flexibility by handling high-volume input of raw structured and unstructured data sources to feed a range of mission-specific prototypes.
    Schedule: 60 Months
    FY 10
    FY 11
    FY 12
    FY 15
    FY 14
    FY 13
    Concept Development and Requirements
    System Design
    System Prototype Development and Evaluation
    Capability Develop. & utility assessment
    Capability Enhance, Eval & Transition
    PERFORMERS: Lockheed Martin, Lustick Consulting, SAE Inc. , The Penn State University, The RendonGroup
  • Task
    FY 10
    FY 11
    FY 12
    FY 15
    FY 14
    FY 13
    Concept Development and Requirements
    System Design
    System Prototype Development and Evaluation
    Capability Develop. & utility assessment
    Capability Enhance, Eval & Transition
    OBJECTIVES: Develop and implement an hybrid modeling system to be both scalable & robust, and can be transitioned to operational use.
    PRISM features: provide for unbiased, objective, valid science-based tools to enable DOD Stability Operations, Analysis, Intelligence, and Experimentation.
    MILITARY RELEVANCE / OPERATIONAL IMPACT: Improve intelligence modeling and analysis using integrated analysis tools supported by critical automated information management and coding processes. Provide tools to extract and monitor metrics such that the effects of given actions can be understood by the command staff.
    TECHNICAL APPROACH: Develop and Implement a Computational Model-Based Analysis Capability:
    • Modeling: Build and compose custom computational models of the environment
    • Data Management: Construct a data management system capability to support model building and sharing
    • Interactive Viewing: Explore causal chains and indirect consequences of actions.
    PRISM Team
  • Task
    FY 11
    FY 13
    FY 10
    FY 12
    Requirements Definition and Analysis
    System Design of Framework Architecture
    Develop SOA compliant Prototype & System Eval.
    System Demonstration, Deployment & Transition
    HSCB Modeling Visualization Framework
    Aperture Services andVizlet Components
    • Design, develop and implement “Aperture” an open source interactive visualization framework and API.
    • Implement using web services / protocols.
    • Demonstrate model developer and analyst plug-and-play, component-based, “mashup” approach to modeling.
    • Deliver “Aperture” as non-proprietary, components in a Services Oriented Architecture (SOA).
    • Support interaction for a wide range of operation user scenarios.
    • Provide modelers and operators key visualization capability including time-line views, geo-spatial views, social network graphs, etc.
    Tier 1: Basic Integration
    1 Authentication and Authorization
    2 Persistence
    3 Container and Vizlet Services
    Tier 2: Enhanced Integration
    4 Selection Model
    5 Pasteboard
    6 Command Stack and Activity Logging
    7 Data Mapping, Filtering and Highlighting
    Tier 3: Resource Services
    8 Layout Managers
    9GeoAssociation, Place Disambiguation, Geolocation and Map Services
    10 Iconography Service
    • Design and implement easy-to-use, innovative and interoperable visualization foundation “vizlets”.
    • Provide interactive visualization as reference implementation for integration and extension by PRISM and NEXUS modeling teams.
    • Provide Aperture as a Web 2.0, SOA framework, APIs and documentation under an open source license.
    • Collaborate with Topic One Teams and expert panels.
    • Deliver tested documented releases of Aperture framework every six months.
    PRISM & NEXUS Architecture