NOVEMBER 12-‐15, 2013 Preface The 8th International Conference on Semantic Technologies for Intelligence, Defense, and Security (STIDS 2013) provides a forum for academia, government and industry to share the latest research on semantic technology for defense, intelligence and security applications. Semantic technology is a fundamental enabler to achieve greater flexibility, precision, timeliness and automation of analysis and response to rapidly evolving threats. The STIDS 2013 theme is Semantic Technologies for Big Data. Topics of general interest for STIDS include: • • • • •
Creating an interoperable suite of public-‐domain ontologies relevant to intelligence analysis covering diverse areas Ontologies and reasoning under conditions of uncertainty Semantic technology and ontological issues related to: o Source credibility and evidential pedigree o Use of sensing devices including security, e.g. global infrastructure grid (GIG), images and intelligence collection in general Usability issues relating to semantic technology
Best practices in ontological engineering Ian Emmons and Kathryn Laskey STIDS 2013 Technical Chairs Paulo Costa STIDS 2013 General Chair
STIDS 2013 Committees
STIDS 2013 Program Committee Stephen Allen Carl Andersen Robert Battle
Rommel
Carvalho Werner Ceusters Suzanne Collier
Paulo Costa
Mike Dean Jody Des Roches
Ian Emmons Matt Fisher
Katherine
Goodier Mark Greaves
Richard
Haberlin Brian Haugh John Hebeler Terry Janssen
Greg Joiner Kenneth Kisiel
Mieczylaw
Kokar
Dave Kolas Kathryn Laskey
Nancy Lawler Mike Letsky
William
Mandrick Dan Maxwell Dave Mireles
Ranjeev Mittu Jeffrey Morrison
Leo Obrst Mary Parmelee
Semantic Research, Inc.
Raytheon BBN Technologies
Amazon.com George Mason University
University at Buffalo Raytheon BBN Technologies
George Mason University
Raytheon BBN Technologies Joint Warfare Analysis Center
Raytheon BBN Technologies Progeny Systems Corporation
Xcelerate Solutions Pacific Northwest National Lab
George Mason University Institute for Defense Analyses University of Maryland - BC
SAIC, Inc.
Raytheon BBN Technologies
Office of Naval Research
Northeastern University Raytheon BBN Technologies
George Mason University US Department of Defense
Office of Naval Research
Data Tactics, Inc.
KaDSci, Inc.
Raytheon BBN Technologies US Navy Research Laboratory
Office of Naval Research
MITRE Corporation
MITRE Corporation Joe Rockmore Dorene Ryder Ciara Sibley Barry Smith
Tony Stein Gheorghe Tecuci
Andreas Tolk Brian Ulicny
Andrea Westerinen
Duminda Wijesekera
Opower, Inc.
Raytheon BBN Technologies
Google, Inc.
Cyladian Technology
Consulting
Raytheon BBN Technologies US Navy Research Laboratory NCOR, University at Buffalo Raytheon BBN Technologies
George Mason University Old Dominion University
Vistology, Inc.
SAIC
George Mason University STIDS 2013 Proceedings Page iii
STIDS Steering Committee Paulo Costa
Mike Dean
Ian Emmons Katherine Goodier
Terry Janssen
Kathryn Laskey William Mandrick
Leo Obrst Barry Smith
George Mason University Raytheon BBN Technologies Raytheon BBN Technologies
NIC, Inc.
SAIC George Mason University
Data Tactics
MITRE Corporation
NCOR, University at Buffalo STIDS 2013 Organizing Committee General Chair
Paulo Costa Technical Chairs
Ian Emmons Kathryn Laskey
Publicity Chair
William Mandrick Classified Session Chair
Brian Haugh
Local Team (GMU) Debra Schenaker (Administrative Chair) Priscilla McAndrews
Shou Matsumoto Felipe Bombarda
Karen Tai
STIDS 2012 Platinum Sponsor
owned small business that specializes in Data Management, Data Architecture, Data Engineering, Semantic Data Representations, and Big Data. Since 2005, our engineers have been on the forefront of large, multi-‐domain, data systems supporting Government and commercial organizations. Our engineering staff is over 90% TS/SCI cleared (many with polygraphs) with over 25% having advanced degrees and doctorates. We offer a suite of solutions to help customers handling very large, “Big Data” problem sets. Our team of senior engineers and data scientists excel at the most intractable problems for customers such as AIR FORCE, ARMY, DARPA, DHS, DNI, NSA and many others. From tactical to strategic efforts, our team has led the creation, integration, and implementation of innovative and proven solutions in the world of Data Alignment, Modeling, and Analytics. We are also very active in standards development including the NIST Cloud Computing and Big Data standards along with Semantic Standards (e.g. BFO, SUMO, DOLCE, etc) and actively contribute to the open source communities (e.g. Apache, Source Forge, GIT, etc). Data Tactics is highly invested in fostering and/or leading collaborations with academia and national labs in advanced research & development initiatives that support disruptive technologies. Our team brings a rich history of supporting prototyping, experimental technology integration, mission oriented demonstrations, and specifically cloud development and integration.
DATA TACTICS – WHAT WE DO
REFERENCE ARCHITECTURES • IC ITE DNI Enterprise Strategy • Army Red Disk/NSA Ghost
Machine • DCGS-‐A Standard Cloud (DSC) • Air Force TENCAP TURNKEY BIG DATA IMPLEMENTATIONS • Secure Enterprise Hadoop • Elastic Ingest and Semantic
Markup • Distributed Analytics ADVANCED ANALYTICS • Multiple Algorithm
Development Programs • Information Artifact Ontology
Development • Advanced Machine Learning
(i.e. NLP) integration • Advanced Video and Image
Entity extraction SECURE DATABASE ARCHITECTURES • Secure Entity Database (SED) • Defense Cross-‐Domain Analytic
Capability (DCAC) CYBERSECURITY • Information Assurance • Security Architecture, Design,
and Configuration • Policies, Process Development,
and Validation
STIDS 2012 Keynote Speaker: November 13
Highly Expressive yet Scalable Knowledge for
Intelligence, Defense, and Security
We present recent results on semantic web knowledge representation & reasoning, and knowledge acquisition, that tightly combine highly expressive rules and ontologies specified semi-‐automatically -‐-‐ yet rapidly -‐-‐ by starting from effectively unrestricted English text. The knowledge employs a new logic, Rulelog, that has strong capabilities to express meta knowledge. Rulelog permits higher-‐order logic formulas that are defeasible (i.e., can have exceptions). It is rich enough to serve as a relatively direct target for natural language processing, using Textual Logic, a new method that employs logic-‐based mappings in natural language (NL) text interpretation and text generation.
Rulelog also leverages its meta capabilities to achieve computational tractability via restraint, a new form of bounded rationality. Rulelog, and the Textual Logic that leverages it, constitute a pretty radical step forward in terms of fundamental capabilities in semantic tech, with a number of advantages including in the social scalability of knowledge authoring and reuse. Yet this step is incremental relative to legacy technology, in that the new knowledge representation transforms into the same fundamental logic as used in relational and RDF databases and in commercially predominant business rule systems. It's applicable in several intelligence, defense, and security (IDS) areas including: info access policies (e.g., confidentiality, compliance); info integration, flow and ontology mapping (e.g., in situation awareness); modeling of causal events and risk; intelligence analysis and debate; e-‐learning (e.g., just-‐in-‐time training); contracts (e.g., compliance); question-‐ answering (QA); and NL-‐based human-‐computer interaction (HCI).
We discuss some of the exciting opportunities and challenges.
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Biography: Dr. Benjamin Grosof
Benjamin Grosof is an industry leader in knowledge representation, reasoning, and acquisition. He has pioneered semantic technology and industry standards for rules, the combination of rules with ontologies, the applications of rules in e-‐commerce and policies, and the acquisition of rules and ontologies from natural language (NL). He has had driving roles in RuleML, W3C RIF (Rule Interchange Format), and W3C OWL-‐RL (rule-‐based ontologies). He led the invention of several fundamental technical advances in knowledge representation, including courteous defeasibility, restraint bounded rationality, and the rule-‐based technique, which rapidly became the currently dominant approach to commercial implementation of OWL. He has extensive experience in machine learning, probabilistic reasoning, and user interaction design.
Dr. Grosof has experience applying core technology for knowledge, reasoning, and related HCI in a wide variety of application areas, including: trust/privacy/security, contracts, compliance, legal, and services engineering; financial/ insurance services, risk management,and regulations; defense and national intelligence; biomedical research; and data/ decision analytics. From fall 2007 to early 2013, he led a large research program in Artificial Intelligence (AI) and rule-‐based semantic technologies at Vulcan Inc. for Paul G. Allen; this centered around the SILK system for highly expressive, yet scalable, rules. Previously he was an IT professor at MIT Sloan (2000-‐2007) and a senior software scientist at IBM Research (1988-‐2000). He is president of the expert consulting firm Benjamin Grosof & Associates founded while he was at MIT, and co-‐founder of the recent start-‐up Coherent Knowledge Systems.
His background includes 4 major industry software releases, 2 years in software startups, a Stanford PhD (Computer Science), a Harvard BA (Applied Mathematics), 2 patents, and over 50 refereed publications.
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STIDS 2013 Keynote Speaker: November 14
Exploring the role of Context
in Applied Decision Making
Decision makers in operational environments are often surprised by emerging events and have little time to give deep consideration to alternative courses of action before being forced to make a decision. Decision support has evolved over the last 20 years but even today, decision support tools do not dynamically adapt to a decision maker’s context. This often results in less than optimal decision making. Recent advances in the fields of cognitive science, the mathematics of decision science, human behavioral modeling, team decision making, knowledge creation and transfer, mental model processes, semantic techniques and human factors present new opportunities to create decision support that is context sensitive, and potentially, proactive. To accomplish this, a systematic exploration of the role of context needs to be studied in decision support systems that enable operational decision making.
STIDS 2013 Proceedings Page viii
Decision making is challenging for a number of reasons. Finding and integrating decision-‐relevant information is hard. Context is often absent, implicit, sparsely or poorly represented in task environments requiring its laborious and error-‐prone internal reconstruction by decision makers. The modern pace of operations often means that warfighters find themselves engaging in tasks in ways, and in combinations, for which they hadn’t planned, and for which they may not be prepared. This forces decision makers to multi-‐task amongst many competing and often conflicting mission objectives concurrently.
Next generation decision support will not just “get the decision maker in the ball park” but will be proactive in trying to “keep the decision maker in the ball park” throughout the process despite the high levels of uncertainty and highly dynamic environments. At the center of this new research initiative is the idea that we can develop technologies that are contextually aware of a decision makers’ missions and tasks. It is asserted that algorithms can be developed that effectively anticipate the decision and information needs of decision makers, in many kinds of task environments. Algorithms would then enable the timely presentation of information. Enabling machines to dynamically model and share context with the human decision makers will be key to enabling Proactive Decision Support (PDS). Such decision support will enable the recognition of changes in the environment and the implications for shifting priorities for decisions that could address operational complexity and make enable decision makers to make more optimal decisions, faster.
Biography: Dr. Jeffrey Morrison
Dr. Jeffrey G. Morrison joined ONR’s Human & Bioengineered Systems Department (341) as a Program Officer in January 2011 where he leads the Command Decision Making (CDM) program. The program is conducting Basic & Applied cognitive science research for application to individual & group decision making. The current operational focus is on multi-‐echelon Command & Control. The science focus is on developing Proactive Decision Support tools (PDS) that are aware of mission and tasks context as well as the facilitating the development of a science of Context-‐Driven Decision Making (CDDM).
Prior to coming to ONR, Dr. Morrison was an Engineering Psychologist / Cognitive Scientist with the Space and Naval Warfare Systems Center – Pacific (SSC Pacific) for 17 years. He was most recently embedded as a Navy Scientist with the Combating Terrorism Technical Support Office (CTTSO) where he served as Chief Scientist to the ASD RDT&E sponsored Human Social Culture and Behavior Modeling Program (HSCB). During 2007-‐ 2008, Dr. Morrison was detailed to the Director of National Intelligence where he served as an IARPA Program Manager studying the analytic process and the potential application of virtual world technologies to enable it. Dr. Morrison was a senior scientist supporting several DARPA projects, including the development of user-‐composable automation for Maritime Domain Awareness (FastC2AP), Predictive Analysis for Naval Deployment Activity (PANDA), and the Augmented Cognition program. He also was principle investigator for numerous ONR sponsored projects, including: Knowledge Web (K-‐Web), and Tactical Decision Making Under Stress (TADMUS).
Dr Morrison has been the recipient of numerous professional awards including: The 2005 Jerome H Ely Award for Article of the Year in the Journal of Human Factors; the 2004 ONR Arthur E. Bisson Prize for Naval Technology Achievement; and the American Psychological Association -‐ Division 21, George E. Briggs Award for Original Research.