1. Semantic Integration for Government and Private Industry 29 November 2012 Eric Little, PhD Director, Information Management elittle@orbistechnologies.com 321-480-4818

2. Overview of Core Technologies for Scalable Cloud-based Semantics RDF, RDFS, RDFa Ontologies Linked Data Knowledge representation Artificial Intelligence Rules/Inference Semantic Search Hadoop MapReduce Distributed Computing NoSQL Virtualization Dynamic Provisioning Natural Language Processing Entity Extraction Information Extraction Information Retrieval Identity Resolution Semantic Role Labeling Machine Learning Information Extraction CLOUD SEMANTICS Semantic Annotation Ontology Population Scalable Inference Distributed Triple Stores Distributed Indexing Text Mining Information Assurance / Cyber Security Enterprise Architecture Systems Engineering IP Portfolio Mgt TECHNOLOGY SERVICES Orbis Technologies, Inc. Proprietary2

3. Orbis developed cloud applications  Sematic Web-Based Cloud Text Analytics oCollection of analytics designed to process and semantically correlate documents in a Google data processing environment  Ontology Harmonization and Mediation oAnalytics designed to rapidly integrated disparate data sources and mediate data models in a cloud environment  Data Center Analytics oSpecialty analytics designed to show the value of the data being stored in a data center Enterprise based productivity services  Business Process Management oDesigned for heavily regulated environments where the workflow is regulated and managed oPersists the workflow in the IT environment  Business Intelligence oProductivity based applications deigned to transform the cloud data to support mission specific analysis Semantic-based Products & Services 3 Orbis Technologies, Inc. Proprietary

4. 4 Semantic Cloud Turnkey private cloud project infrastructure  Configuration Management  System Infrastructure  Orbis hosted private HW environment  Business Intelligence Application development  Third Party Access  Project Tracking  Business Process Management Fee for service model Designed to migrate into client IT Enterprise once project reaches maturity 4 Sophisticated cost and performance driven program environment allows the client to best mange risk “Best of Breed” company selection enabled by an open architecture Sophisticated cost and performance driven program environment allows the client to best mange risk “Best of Breed” company selection enabled by an open architecture

5. Extended Semantic Services Can Raise Awareness Semantic Web Training  Designed by practitioners for multiple skillsets  Key concepts covered oOntology development, reasoning, technology, etc.  Multiple Attendees oOpen to client participation oHosted by Orbis or held at client location Enterprise Level Advisory Service  Architecture modernization oAssist clients migrating legacy systems to semantic and/or cloud architectures  Insider threat and security assessments  Mobile app migration Orbis Technologies, Inc. Proprietary5

6. Why Semantics and Cloud? Capabilities examples  Fusion/Information correlation - Interconnected data from hundreds of sources creates large graphs (TB - GB files) that need to be analyzed  Information retrieval and search oCloud provides outstanding query response time, document correlation, data integration,.. Standards implementation  Semantic web standards increase data interoperability  Open architecture oAllows for third-party developers Most efficient and effective approach to incorporating domain knowledge derived from subject matter experts  Key to long-term knowledge management and retention Orbis Technologies, Inc. Proprietary6

7. USE CASE EXAMPLES Orbis Technologies, Inc. Proprietary7

8. Government and Industries With Whom We Work US Military (Army, Air Force) Intelligence Agencies Defense Threat Reduction Agency (DTRA) Petrochemicals Pharmaceuticals Medical Device Financial Services Telecommunications Insurance Airlines Orbis Technologies, Inc. Proprietary8

9. Building Semantic Profiles From Raw Petroleum Data Orbis Technologies, Inc. Proprietary9 Key data elements are identified – creating lexicon of important terms Data elements are categorized into appropriate classes – ranges are captured for auto- classification Can be applied to crude stocks, equipment, refineries, products, processes, etc. Advanced logics allow for reasoning over data sets such that new patterns and information can be gained

10. Orbis Federated Semantic Approach for Business Business Centric vs. Data Centric Definitions – Taken Separately Orbis Federated Semantic Approach Orbis Technologies, Inc. Proprietary10 Distinct ontological terms (and corresponding contextual information) can be captured in a single federated ontology stack

11. Regulatory Compliance Orbis Technologies, Inc. Proprietary11 Information Gets Extracted from Various Data Sources and is Semantically Linked Analysis Outcomes & Findings Can be Linked Regulatory Documents and Reports Advanced Enterprise Search (Concepts, Entities, Relationships) and a Document Viewer Backed by Cloud Based NLP Processing Extracted Entities Are Correlated in Each Document and Across Documents

12. Challenges Working at the Enterprise Broaden overall data analysis effort – All data can be utilized Cloud data dashboard (adopt business intelligence view of data) Orbis Technologies, Inc. Proprietary12 Exploit existing databases and data analytics (Originality, Document Correlation, User Assertions, etc.) to create a dashboard that enables an assessment of the weapon system metrics, health, and trend analysis.

13. Challenges Working at the Enterprise-Cont. Semantic systems magnify existing data management problems  RDF provides verbose data description, where a single document could result in tens of thousands of RDF triples oEasy to reach billions of triples for a large relational database  Provenance and pedigree highlight issues with lack of data efficacy oAuthoritative and supplementary data sources are either treated equally or require additional logic to resolve-may impact confidence in the results Distributed processing and elastic infrastructure needed for enterprise scalability  Rich analytics can use more expressive logic  Analytics and data are processed together to minimize network latencies Orbis Technologies, Inc. Proprietary13

14. Summary Semantics requires expansion to other technologies to be applicable across enterprise applications Requires a host of interconnected discriminating products and services  Semantic web-based applications  Productivity driven services  Hosted private program infrastructures  Enabling training and advisory services Cloud and semantic web have a symbiotic relationship  Need each other to scale and demonstrate value Success requires one to define enterprise domains and harvest value associated with enterprise data integration of different kinds for numerous applications Orbis Technologies, Inc. Proprietary14

15. THANK YOU QUESTIONS? 15 Orbis Technologies, Inc. Proprietary