Securboration to develop Cross-Organizational Semantic Services (CROSS) for the Joint Planning and Development Office (JPDO)
Securboration, working with the JPDO and AFRL, has been funded to extend the Ontology Generation and Evolution Processor (OGEP)research and development effort into an operational CROSS capability. CROSS will expedite the automatic processing of both formal planning, programming, and acquisition information sources (for example, enterprise architecture (EA), requirements, research and development (R&D) roadmaps, etc…) and informal artifacts (textual documents, reports, statistics, …) to help identify and synchronize interagency activities. This effort will help drive interagency synchronization to more efficiently deliver NextGen capabilities as the DoD seeks “order of magnitude” NextGen cost reductions for the Department of Defense (DoD), Federal Aviation Administration (FAA), and partners.
Securboration, Inc. delivered the latest version of their Requirements Analysis Portlet (RAP) to the United States Transportation Command (USTRANSCOM) Common Production Environment (CPE). RAP addresses the organization’s need to map a requirement to joint capability areas, capability gaps, and organizational activities based on unstructured text in a needs statement. RAP uses Securboration’s Semantic Grounding Mechanism (SGM) to provide a common understanding of a system’s capabilities and data requirements that is based on semantics instead of rigid syntax. It provides accurate mapping suggestions in a timely fashion, freeing the operator from time consuming manual mapping processes.
Securboration has been awarded a contract to develop the Collaborative Event Processing Environment (CEPE) for USTRANSCOM. CEPE will wrap current Fusion Center Knowledge Management (KM) capabilities in a graphical user interface (GUI) allowing direct Subject Matter Expert (SME) editing of ontologies and topics, predictive assessment of the meta-tagging and routing impact of these edits, and configuration management of Fusion Center knowledge representation resources. CEPE will be a browser-based tool compatible with the Fusion Center’s existing network and content management footprint, and will capture user feedback and expertise, learning preferences and domain knowledge over time. Rather than attempt to turn SMEs into ontologists, CEPE will bring many repeatable, automatable knowledge representation processes under the SMEs’ control, using wizarding and learning over time to usefully match feedback patterns to new knowledge and improved meta-tagger and message routing behavior.
Securboration Awarded Contract to Automatically Mark Intelligence Data With Appropriate Classification
Securboration has been awarded a contract from the U.S. Air Force to automate classification and releaseability marking of intelligence data by using metadata tagging to speed sharing of information between multiple, independent security domains. The goal of this effort is to provide almost real-time exchange, dissemination, search, access, display and association of disparate information across multiple communities of interest. Inconsistent population of sensor data fields are currently hampering the sharing of data and slows analysis by requiring the analyst to manually search multiple sources for significant data. Securboration will apply semantic modeling to provide a solution that not only explains the rationale for marking to the user but also can be easily tailored by the analyst as needed.
Securboration has been awarded an Air Force contract to research link analysis of knowledge extracted from social media communications. The social media involved will include blogs, Twitter-like messages, social networking posts, and bulletin board threads. Securboration’s experience with semantic technologies will be leveraged to assist the military’s need to visualize knowledge extracted from social media communications with the same fidelity provided by using traditional sources.
Securboration has been selected by the Air Force Research Laboratory (AFRL) to define, develop and demonstrate innovative approaches to accurately present and represent globally-distributed blue force readiness and capability in a timely manner. Securboration will develop the Blue-force Awareness Capability and Understanding System (BACUS). This system will collect blue force information from multiple sources, perform semantic reasoning over this gathered information with respect to current mission strategies, generate a representation of the blue force state in standardized interoperable formats, and publish the representation to systems that support Integrated Battle Planning Capability. These capabilities in BACUS will enable it to help improve the blue force situational awareness in the battle planning community.
Securboration Awarded Contract for Automated Multi-Processor Conversion Capability for Legacy Software
Securboration has been awarded a contract by the Office of the Secretary of Defense (OSD) to develop techniques for automatically parallelizing existing sequential code. Processor speeds have plateaued and manufacturers have turned to multi-processor architectures to increase computing power. The cost of purchasing new multi-processor hardware is small in comparison to the cost of rewriting sequential legacy software to take advantage of the multi-processor environment. Securboration is creating the Tri-tier Architectural Modeling Environment (TAME) to provide an automated way to convert legacy sequential software into multi-threaded software that is fully capable of exploiting multiple processors. TAME will involve profiling, parallelizing, optimizing, and verifying of the software without changing the source code. This novel approach aims to allow existing legacy code to be improved in regard to performance while not requiring any of the source code to be rewritten and retested therefore providing significant cost savings and minimize risk.
Securboration has been awarded a contract by the Office of the Secretary of Defense (OSD) for researching and defining operating system mechanisms to efficiently partition, communicate, and execute programs on many-core systems. Manufacturers have increased the number of computing cores instead of increasing clock speed. This contract continues previous work which aimed to focus on allowing efficient operation of many programs which can be easily maintainable, adapatable, and usable by administrators with minimal training as number of processors, memory, and available communications bandwidth change.
Securboration has been selected by the Air Force Research Laboratory (AFRL) to explore, systematically study and develop technology that enables computers to proactively support analyst activity. The goal is to provide a bidirectional human and information technology partnership where the computer learns, adapts and informs analysts based on their typical practices, situational context, and available data content. The system under development, referred to as the Adaptive Data Immersion Environment or ADIEN, combines machine learning, text analytics, and semantic search to learn and evolve user preferences based on individual usage patterns. Additionally, as new data products become available they will be automatically identified and seamlessly added into analyst’s workspace. These capabilities in ADIEN will enable it to act as personalized, proactive assistant that can automatically tailor the workspace to the analyst’s needs while also automatically identifying and processing information potentially relevant to their missions.
Securboration has been awarded a contract by the United States Army to develop analytical tools that improve the theoretical relevance, meaning, reliability and validity of data extracted from social media sources. The social ties between users can have varying strengths and this effort seeks to identify more meaningful ties that create a strong online community from the noise surrounding them. Securboration intends to create a Social media Understanding and Reasoning Framework (SURF) that will use structured and unstructured social media information to identify significant social topologies, motifs, embedded online communities and individual characteristics. This effort will seek to combine well-grounded social theory with mathematical theory, graph theory and computational theory to create analytical tools for mining of social media.