Andrew Crapo

Data Provenance architecture to support Information Assurance in a Multi-Level Secure Environment

We describe a framework for capturing Data Provenance information to support Information Assurance attributes like Availability, Authentication, Confidentiality, Integrity and Non-Repudiation. Our approach is applicable to Multi-Level Secure systems where it is not always possible to directly provide data source and data transformation information. We achieve this by combining the subjective and objective trust in data as a “Figure of Merit” value that can cross security boundaries.

TOWARD A UNIFIED ENGLISH-LIKE REPRESENTATION OF SEMANTIC MODELS, DATA, AND GRAPH PATTERNS FOR SUBJECT MATTER EXPERTS

The Semantic Application Design Language (SADL) combines advances in standardized declarative modeling languages based on formal logic with advances in domain-specific language (DSL) development environments to create a controlled-English language that translates directly into the Web Ontology Language (OWL), the SPARQL graph query language, and a compatible if/then rule language. Models in the SADL language can be authored, tested, and maintained in an Eclipse-based integrated development environment (IDE). This environment offers semantic highlighting, statement completion, expression templates, hyperlinking of concepts to their definition, model validation, automatic error correction, and other advanced authoring features to enhance the ease and productivity of the modeling environment. In addition, the SADL language offers the ability to build in validation tests and test suites that can be used for regression testing. Through common Eclipse functionality, the models can be easily placed under source code control, versioned, and managed throughout the life of the model. Differences between versions can be compared side-by-side. Finally, the SADL-IDE offers an explanation capability that is useful in understanding what was inferred by the reasoner/rule engine and why those conclusions were reached. Perhaps more importantly, explanation is available of why an expected inference failed to occur. The objective of the language and the IDE is to enable domain experts to play a more active and productive role in capturing their knowledge and making it available as computable artifacts useful for automation where appropriate and for decision support systems in applications that benefit from a collaborative human-computer approach. SADL is built entirely on open source code and most of SADL is itself released to open source. This paper explores the concepts behind the language and provides details and examples of the authoring and model lifecycle support facilities.

Manufacturability Analysis and Design Feedback System Developed Using Semantic Framework

Early manufacturability feedback is critical for reducing product cost and lead-time. This paper describes a new architecture and platform for authoring and applying manufacturability rules for design. The key step is to define a domain-specific ontology by creating a higher-level semantic language that describes design and manufacturing concepts relevant to specific manufacturing processes. This language has two primary uses; express design in the context of manufacturing and relate manufacturing constraints on design as declarative rules. OWL and Jena (a reasoning engine) are used in the background to reason about specific designs and provide manufacturability feedback in a client-server model. The use of Semantic Web technology makes it easier to augment manufacturability feedback with a query system for the designer that utilizes the same rule knowledge base to answer what-if scenarios. This is implemented using SPARQL and using the CAD design context and so enhances the user experience. This novel approach makes it easier for the domain experts to write or verify rules and the designers to validate concepts before changing the CAD model. This helps in maintaining the independence between the CAD platform and core enterprise knowledge. A pilot study in the sheet metal domain is implemented to demonstrate the steps necessary for complete early manufacturability analysis software and highlights the benefits of this approach.Copyright

Towards autonomic systems for lifecycle support of complex equipment

GE has been a leader in remote monitoring and diagnostics of complex systems, such as medical imaging equipment and aircraft engines, for a number of years. The data gathered and the analytical capabilities developed have naturally lead toward service contracts to maintain individual machines and fleets of machines while lowering the cost of ownership for our customers. As information technology extends the reach of diagnostic, prognostic, and decision support systems, opportunities to optimize support of specific organizational objectives is enhanced. Such a decision support system is envisioned and is inspired by the human autonomic nervous system.

Using semantics to process legal document updates

In most information retrieval systems, updates to indexed documents are handled by either adding the new document to the index and incrementing a version field, or by completely replacing the old version by the new version. These approaches work well when the entire document text is updated, but are insufficient to appropriately handle partial updates in amendments that explicitly state what changes are made to legal contracts. We propose here an approach that parses contract amendments to understand how the amendment is altering the original contract and determine the new effective legal contract. This approach uses semantic modeling and rules to indicate the effective contract to information retrieval systems.

Semantics: Revolutionary Breakthrough or Just Another Way of Doing Things?

It sometimes feels like an uphill battle to explain why an organization should embrace semantic technology rather than continue to rely on relational databases and application programming in object-oriented languages. In this chapter, we review the formal foundations of various representations, and evaluate them against five criteria: understandability of the models, availability of information for retrieval, ability to infer new information which is provably correct, interoperability, and the ability of the data to speak to minds and machines alike with a shared semantics.

An expert fault manager using an object meta-model

This paper describes the design and implementation of an expert fault management (EFM) system, based on an object-oriented meta-model, which can isolate causes of performance problems in a distributed environment. Error diagnosis can integrate application, system, and network related causes and identify the root cause, as well as affected applications. Diagnosis can be proactive or reactive. The implementation is based on the GEN-X expert system, and intelligent agents written in PERL. It is self-configuring, and has demonstrated its ability to detect problems earlier and more accurately than humans.

Requirements Capture and Analysis in ASSERT(TM)

Capturing high-level requirements in a human readable but formal representation suitable for analysis is an important goal for GE. To that end we have augmented an existing controlled-English modeling language with a new controlled-English requirements capture language to create the Requirements Capture frontend of the ASSERT(TM) tool suite. Requirements captured in ASSERT can be analyzed for a number of possible shortcomings, both individually and collectively. Once a set of requirements has reached a satisfactory level of completeness, consistency, etc., it can then be further used to generate test cases and test procedures. This paper will focus on the requirements capture and analysis functions of ASSERT and will illustrate its capabilities with a sample problem previously used as a challenge problem for requirements specification.

A Natural Language Processing and Semantic-Based System for Contract Analysis

The Contract Search Tool is a semantic search platform that enables effective analysis of complex, long-term contractual service agreement for machines such as gas turbines. The approach we developed can effectively identify paragraphs of text for specific legal concepts. Then the key content can be decomposed and organized by the semantics model that captures key elements of the concepts and links to specific paragraphs. This is achieved by performing semantic text analysis to capture implicitly-stated provisions and the definitions of provisions, and relevant information is returned in an organized manner. The tool can be applied to increase productivity of legal review, share legal knowledge with service managers, and reduce legal risk in contract review process.

Addressing uncertainty and conflicts in cross-domain data provenance

Data Provenance is multi-dimensional metadata that can be used to determine Information Assurance attributes like Confidentiality, Authenticity, Integrity, and Non-Repudiation. Traditionally, these Information Assurance attributes have been specified probabilistically as a belief value (or corresponding disbelief value). In this paper, we introduce a framework based on Subjective Logic that directly incorporates uncertainty by representing values as a triple of <belief, disbelief, uncertainty>. This framework allows us to work with uncertainty as well as conflicting pieces of information that may arise from multiple views of an object. We also develop a formal semantic model for specifying and reasoning over Information Assurance properties in a workflow. This model uses a controlled English representation which facilitates the dialogue with domain experts to capture and vet domain knowledge. Since Data Provenance information can grow substantially as the amount of information kept for each object increases and/or as the complexity of a workflow increases, we show how this information can be summarized. This summarization can also generate a trust value in the data so that it can cross security boundaries with user-controllable covert channel implications. Finally, we discuss a range of visualizations ranging from attention-directing high-level visualization to finer-level contextual visualization.