Suzette Stoutenburg

Applying Semantic Rules to Achieve Dynamic Service Oriented Architectures

As the complexity and tempo of world events increase, command and control (C2) systems must move to a new paradigm that supports the ability to dynamically modify system behavior in complex, changing environments. Historically, the behavior of Department of Defense (DoD) C2 systems has been embedded in executable code, providing static functionality that is difficult to change. We propose the use of semantic models to represent system behaviors abstracted from procedural code, and we demonstrate that this provides a well-defined foundation for dynamic service oriented architectures. This paper describes an implementation that models a military convoy traveling through an unsecured area under changing conditions. The W3C standard Web Ontology Language (OWL) was used to describe the battlespace domain, and the proposed W3C Semantic Web Rule Language (SWRL) was used to capture recommended operating procedures for convoys in theater. In our experiment, two sets of rules were used: one set models rules of engagement for favorable visibility conditions on the battlefield, and the other models rules of engagement for poor visibility conditions. Ontologies and rule sets were translated into integrated knowledge bases that could be consulted as a service to derive alerts and recommendations for the convoy commander. Messages injected over an enterprise service bus (ESB) provide the changing conditions that affect the battlespace. We then were able to show that a dynamic event, such as an unexpected sandstorm, causes the appropriate set of rules of engagement grounded in the ontologies to be applied to the service to guide the convoy to safety. This paper describes the overall approach and the challenges we encountered. We outline the architectural options for constructing dynamic services and describe the semantic-based approach selected. We conclude with our findings and recommendations, including a set of requirements for a standard rule language needed to support agile services

Ontologies and Rules for Rapid Enterprise Integration and Event Aggregation

Ontologies enable explicit expression of collective concepts and support Machine-to-Machine (M2M) interactions at the semantic level. Ontologies expressed in a standard language, such as the Web Ontology Language (OWL) and exposed on a network offer the potential for unprecedented interoperability solutions since they are semantically rich, computer interpretable and inherently extensible. Rules that operate over ontologies allow for fusion of events in a semantically rich way. In this paper, we describe how we applied ontologies and rules for rapid enterprise integration of heterogeneous data sources and aggregation of events in the battlefield. We found that once a robust foundational domain ontology is established, it is easy and quick to integrate new data sources and therefore rapidly provide new system capabilities. We also found that rules that operate over ontological concepts are useful in agile aggregation of events for enhanced situational awareness.

Dynamic service oriented architectures through semantic technology

The behavior of Department of Defense (DoD) Command and Control (C2) services is typically embedded in executable code, providing static functionality that is difficult to change. As the complexity and tempo of world events increase, C2 systems must move to a new paradigm that supports the ability to dynamically modify service behavior in complex, changing environments. Separation of service behavior from executable code provides the foundation for dynamic system behavior and agile response to real-time events. In this paper we show how semantic rule technology can be applied to express service behavior in data, thus enabling a dynamic service oriented architecture.

Modernizing Centers for Disease Control and Prevention Informatics Using Surveillance Data Platform Shared Services

Public health surveillance is the cornerstone of public health practice. In the United States, the Centers for Disease Control and Prevention (CDC) and states share responsibility for the surveillance enterprise. States have primary responsibility for traditional name-based disease reporting, and they subsequently share anonymized data with CDC. At the same time, CDC maintains many surveillance systems at the federal level. For decades, the number of these single-disease or condition, single-purpose surveillance systems has grown as CDC has needed to expand surveillance data collection to address new public health problems. Currently, CDC has more than 110 surveillance systems. Although these systems provide CDC with the surveillance data needed by the agency, many are experienced as repetitive and burdensome by state and local public health departments, with little or no coordination. This profusion of CDC systems results in duplication of effort, discrepancies among the data elements collected by various programs, and the need to use multiple information technology (IT) systems, which may not be interoperable. Recognizing these problems, multiple CDC surveillance stakeholders (eg, the US Congress, the Council of State and Territorial Epidemiologists, and the Federal Advisory Committee to the CDC Director) have urged CDC to create a more integrated approach to national public health surveillance and an approach that makes greater use of established data standards. In 2014, CDC launched a new surveillance strategy to streamline and improve the surveillance capabilities of the agency and the public health system. This new strategy is guiding the agency’s efforts to eliminate unnecessary redundancies in surveillance data collection and reporting and to increase surveillance IT system interoperability. The goal is to improve the quality, timeliness, and availability of surveillance data in the public health system (Figure 1). Importantly, the new CDC surveillance strategy also aims to reduce the burden of data exchange on state and local health departments. As part of this strategy, in May 2016, CDC launched a new public health informatics initiative that is intended to reduce the use of single-purpose (siloed) systems for surveillance and to develop reusable, shared services that can be plugged into multiple surveillance activities and programs in the agency. Shared services are business, science, and IT functions that are standardized and built once for reuse by multiple parts of an organization. At CDC, shared services will allow the agency to use fewer

Rules and Rule Markup Languages for the Semantic Web

Towards an Event-Driven Architecture: An Infrastructure for Event Processing Position Paper.- Enabling Semantic Web Inferencing with Oracle Technology: Applications in Life Sciences.- A Realistic Architecture for the Semantic Web.- Active Rules in the Semantic Web: Dealing with Language Heterogeneity.- Towards an Abstract Syntax and Direct-Model Theoretic Semantics for RuleML.- A Semantic Web Framework for Interleaving Policy Reasoning and External Service Discovery.- Reactive Rules-Based Dependency Resolution for Monitoring Dynamic Environments.- Towards Discovery of Frequent Patterns in Description Logics with Rules.- Design and Implementation of an ECA Rule Markup Language.- Extending the SweetDeal Approach for e-Procurement Using SweetRules and RuleML.- Using SWRL and OWL to Capture Domain Knowledge for a Situation Awareness Application Applied to a Supply Logistics Scenario.- A Semantic Web Based Architecture for e-Contracts in Defeasible Logic.- Merging and Aligning Ontologies in dl-Programs.- A Visual Environment for Developing Defeasible Rule Bases for the Semantic Web.- Flavours of XChange, a Rule-Based Reactive Language for the (Semantic) Web.- Rule-Based Framework for Automated Negotiation: Initial Implementation.- Uncertainty and RuleML Rulebases: A Preliminary Report.- Nested Rules in Defeasible Logic.- ContractLog: An Approach to Rule Based Monitoring and Execution of Service Level Agreements.- The OO jDREW Reference Implementation of RuleML.