Novel Visualization & Display Technologies

Visualizing data is an essential part of any data analysis. The complexity of projects in large organizations requires the decomposition of those projects into simpler tasks managed by smaller, more or less autonomous teams within the larger organization.  In addition, the recent development of sophisticated software tools such as those developed by KBSI has enhanced the effectiveness of decision, design, analysis, and other activities within these teams.  However, the division of large projects in such a fashion creates a new problem: the difficulty of sharing information among the different project teams, their contexts, and the different tools supporting activities performed by those teams.  The utility of supporting tools is a function of the degree to which they (and the agents that use them) can share information across their different contexts in the sort of distributed environments that are a hallmark of complex projects.  However, the data produced by software of this kind is typically maintained in closed architecture databases.  In the overwhelming majority of cases, each software tool has its own private data repository. 

The central problem with this is not necessarily that the data generated by these tools is inaccessible, but that the semantic content of this data (i.e., the information itself) is typically not accessible to other (human or computer) agents in the organization.  Typically, this is because data is not very good at describing itself or representing its meaning in a way that is accessible.

A complex representation (e.g., a data model or a business process model) carries the information in virtue of some established, systematic connection between the components of the representation and the world.  It is this connection that determines the semantic content of the data being represented.  Typically, however, the semantic rules of a representation system for a given application and the semantic intentions of the application designers are not advertised or in any way accessible to other agents in the organization.  This makes it difficult, even impossible, for such agents to determine the semantic content of a database - semantic inaccessibility

How is it possible to access the semantics of enterprise data across different contexts?  How is it possible to fix their semantics objectively in a way that permits accurate interpretation by agents outside the immediate context of this data?  Without this ability, the kind of coordination between enterprise teams necessary for a truly integrated environment is not possible.  The use of novel visualization mechanisms is perceived as a critical technology enabler to address the semantic inaccessibility challenge.

KBSI has excelled over the last two decades in providing quality data visualization.  To briefly name a few, the RampMap® toolkit, was developed for Tinker Air Force Base to provide digital asset visualization and management of repair facilities, ramp sites, and equipment.  KBSI’s Predictive and Preventive Maintenance Expert System (PPMES), is in use at the Corpus Christi Army Depot, to monitor, diagnose, and analyze preventative maintenance action data and to provide on-line monitoring of CCAD mission-critical sensory data.  In an ongoing effort, Hybrid Framework for Information Visualization Enablers (HI-FIVE), KBSI is developing novel, model-driven, ontology-centric, standards-based data visualization generation for information portals.  HI-FIVE leverages the (DoD-standard) IDEF family of methods, web-services, and, finally, a proven data display format called Data Display Markup Language (DDML), also developed by KBSI.

KBSI’s DASHCON™ is a dashboard configuration and scoring model deployment framework that deploys high-payoff decision dashboards for military commanders.  A set of dashboard configuration utilities make it easy for non-programmers to configure dashboards comprised of user-selected scoring models (e.g., provider categorization model). 

KBSI’s Personal Data Prospector (PDP®) is an open architecture, web based application that enables rapid knowledge discovery, experiment management, and knowledge applications in distributed, collaborative environments.  The PDP® technology supports an end-to-end knowledge discovery process including (1) defining the problem, (2) preparing the data (including data assessment, repair, and validation), (3) performing data search / data processing / data mining, (4) integrating the analysis results, and (5) interpreting and presenting the results for decision-making.

 

 

RampMap®

The RampMap® software provides map-based, real-time visibility of maintenance, repair, and overhaul (MRO) assets on site. This kind of visibility is critical to reducing the wasted movement of aircraft, or other MRO subjects, and to improve the collaborative planning, resource allocation, dispatching and statusing of MRO assets and work.

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Software Tool for Efficient Airspace Management (STEAM™)

KBSI is developing a software system that applies robust decision support tools, data mining, and statiscal methods to the intelligent management of special use airspace (SUA).

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Adaptive Toolkit for the Discovery of Threats (ATDT)

KBSI developed a toolkit that integrates intelligent knowledge discovery techniques, advanced data mining technologies, and knowledge-based methods for automated threat detection. ATDT is an agent-based decision support system that mines data (news feeds, web databases, traffic reports, radio intercepts, human intelligence, etc.) to extract meaningful knowledge or "indicators" of emerging threats.

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Adaptive Trajectory Reshaping and Control System (ATRC)

KBSI developed requirements for the design, development and demonstration of algorithms and real time solution techniques for an adaptable and reconfigurable Reusable Launch Vehicle (RLV) command, control, and guidance system.

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Blood Reserve Availability Assessment, Tracking, and Management System (BRAMS™)

KBSI is developing a system that allows users to manually enter data via a Web-based system, and to apply data mining and analytics in detecting blood supply problems, analyzing system behavior, evaluating alternate solutions, and optimizing the blood supply chain.

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Data Display Translation Framework (DDTF)

KBSI is developing an advanced component-based Data Display Markup Language (DDML), an XML-based neutral format also developed by KBSI, as the inter-lingua in translating the data display languages supported by different vendors.

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Hybrid Decision Wizard (HDWizard™)

KBSI developed, built, and validated a hybrid decision support toolkit that utilizes a combination of common sense reasoning, domain knowledge based reasoning, and soft computing techniques to support intelligent decision making. The HDWizard™ technology is an agent-based decision support system that facilitates the automated generation of information from disparate and distributed data to support user-defined decision support goals.

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Hybrid Framework for Information Visualization Enablers (HI-FIVE)

KBSI is designing a novel, model-based, “no-programming required” approach to information visualization. HI-FIVE provides an extendible framework for rapidly developing, configuring, and managing data displays, enabling the understanding of “system of systems” data.  

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Information-Fusion based Indication & Warning Assessment and Recognition System (IIWARS)

KBSI developed a system that, using text mining technologies and information fusion, improves the DoD's terrorist threat assessment capabilities. IIWARS uses advanced text and data mining methods to mine data from multiple, distributed text sources (news feeds, web databases, traffic reports, radio intercepts, human intelligence) and extract multiple features and "indicators" of an emerging or actual threat. These indicators are then fused into a threat model which can be compared to hypothesized threat Course Of Action (COA) templates.

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Knowledge Discovery Wizard (KDWIZARD)

KBSI designed, developed, and validated an adaptive framework for knowledge discovery. This framework provides mechanisms for generating knowledge-discovery applications beginning with end-user specifications of decision objectives and sets of data sources, provides users with a larger and more focused selection of decision alternatives.

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Military Health Data Mining Algorithms Library (M-HDML)

KBSI applied data mining technologies and techniques to the storage and retrieval of patient data, helping doctors to more accurately diagnose their patients.

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On Demand Simulation Support (ODSS)

KBSI designed, built, and deployed a system that provides for the rapid creation and application of simulation modeling for depot management decision support. ODSS uses a hybrid discrete-event/rule based simulation engine for execution within an advanced experiment management environment, providing support for optimizing plans, schedules, situation response, and process designs.

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Toolkit for Agent-based Knowledge Extraction (TAKE™)

KBSI applied a hybrid approach that combines ontology engineering methods with cutting-edge knowledge discovery techniques to extract, analyze, and map ontologies from distributed and disparate knowledge and data sources. The TAKE™ technology enables the rapid and cost effective analysis, redesign, integration and/or reengineering of complex systems.

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Transformation in Maintenance and Repair (XFMR)

KBSI is examining the methods and technologies required to transform Air Logistics Center (ALC) operations to a warrior-centric, highly adaptive, and more efficient sustainment enterprise activities. The XFMR solution concept allows for interactive critical chain resequencing, constraint violation identification, and automated and optimized critical chain plan option generation. 

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XML/IDEF3-based Training

KBSI defined a neutral format for capturing, organizing, and sharing process-related knowledge that is based on the Integrated Definition family of methods and the eXtended Markup Language (XML). Using this standard, KBSI developed an advanced authoring tool-kit for situation-based, process-centric computer-based training systems.

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Raster to Parametric CAD (R2P CAD)

KBSI investigated and demonstrated the conversion of CALS Type I raster mechanical drawings to parametric vector format, and to parametric 3D solid models, improving electronic commerce, competitive reprocurement, and maintenance for related systems.

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