Knowledge Base Version Reintegration

Given two versions of a knowledge base (KB), independently modified, we investigated the problem of incorporating changes made to one KB version into the other. We have implemented a system that will perform such a reintegration, autonomously, using predetermined user preferences. This effort has lead to a greater insight into the version reintegration problem and has highlighted those areas where user intervention would be the most beneficial in a semi-autonomous system

A Query Integrator and Manager for the Query Web

We introduce two concepts: the Query Web as a layer of interconnected queries over the document web and the semantic web, and a Query Web Integrator and Manager (QI) that enables the Query Web to evolve. QI permits users to write, save and reuse queries over any web accessible source, including other queries saved in other installations of QI. The saved queries may be in any language (e.g. SPARQL, XQuery); the only condition for interconnection is that the queries return their results in some form of XML. This condition allows queries to chain off each other, and to be written in whatever language is appropriate for the task. We illustrate the potential use of QI for several biomedical use cases, including ontology view generation using a combination of graph-based and logical approaches, value set generation for clinical data management, image annotation using terminology obtained from an ontology web service, ontology-driven brain imaging data integration, small-scale clinical data integration, and wider-scale clinical data integration. Such use cases illustrate the current range of applications of QI and lead us to speculate about the potential evolution from smaller groups of interconnected queries into a larger query network that layers over the document and semantic web. The resulting Query Web could greatly aid researchers and others who now have to manually navigate through multiple information sources in order to answer specific questions

Cluster-Based Optimization of Cellular Materials and Structures for Crashworthiness

The objective of this work is to establish a cluster-based optimization method for the optimal design of cellular materials and structures for crashworthiness, which involves the use of nonlinear, dynamic finite element models. The proposed method uses a cluster-based structural optimization approach consisting of four steps: conceptual design generation, clustering, metamodel-based global optimization, and cellular material design. The conceptual design is generated using structural optimization methods. K-means clustering is applied to the conceptual design to reduce the dimensional of the design space as well as define the internal architectures of the multimaterial structure. With reduced dimension space, global optimization aims to improve the crashworthiness of the structure can be performed efficiently. The cellular material design incorporates two homogenization methods, namely, energy-based homogenization for linear and nonlinear elastic material models and mean-field homogenization for (fully) nonlinear material models. The proposed methodology is demonstrated using three designs for crashworthiness that include linear, geometrically nonlinear, and nonlinear models

Value Sets via Ontology Views

We present a method for defining value sets as queries over ontologies (ontology views), and a mechanism for evaluating such queries. In particular we demonstrate an approach utilizing reusable template queries and parameterized URLs. We illustrate this method using an example from the Ontology of Clinical Research (OCRe)

Querying Non-Materialized Ontology Views

One approach to simplifying ontologies, for inclusion in a more tractable semantic web, is through the use of non-materialized view queries. View queries define how a simplified “view” or “application” ontology is derived from larger more complex ontologies. In this work we look at a language for specifying view queries over OWL/RDFS sources, and we illustrate some initial ideas for how to execute user queries over our view ontology, without materializing it first

Ontology View Query Management

Like views in relational databases, ontology views are expressed as queries, but over source ontologies rather than tables. To enhance the reusability of such views, we are constructing a view Query Manager application. The Query Manager allows queries to be edited, executed, and stored for reuse. View queries are discoverable by searching the Query Manager's metadata catalog. The Query Manager also supports the storage of materialized view results upon which further queries may be issued

An Intuitive Graphical Query Interface for Protégé Knowledge Bases

Emily is a graphical query engine for Protégé knowledge bases that was developed by the Structural Informatics Group (SIG) at the University of Washington. Currently this application is adapted for a specific knowledge model, the Foundational Model of Anatomy (FMA) [1], but it could readily be generalized for use with other Protégé knowledge bases. In developing the Emily query interface, our intent was to provide a tool that was simple and intuitive to use, like the Queries tab provided with Protégé, but with improved information retrieval capabilities. Although some more advanced query mechanisms exist, currently they are too complicated for non-expert end users. The Algernon tab [2], for example, provides extensive Protégé query capabilities but requires users to learn a query scripting language. We sought to develop a query interface that was intuitive enough for end users to operate, with only minor instruction, yet was powerful enough to gather interesting information from a knowledge base that was not easily attained by browsing alone

Conceptual design of equipment to excavate and transport regolith from the lunar maria

NASA hopes to have a manned lunar outpost completed by 2005. In order to establish the base, regolith must be excavated from the lunar surface. Regolith will be used as a source for life-supporting elements and as radiation shielding for the lunar outpost. The design team from the University of Texas at Austin designed excavation and transportation equipment for initial operations of the lunar base. The design team also characterized the elements to be found in the regolith and determined the power required to excavate regolith. The characterization of the soil was based on a literature review of lunar geography. Power requirements for excavation were developed by adapting terrestrial equations for excavation power requirements and adapting them to lunar soil conditions. The design of the excavation and transportation equipment was broken into three functions: loosing, collecting, and transporting. A scarifier was selected to loosen, a bucket was selected to collect, and a load-haul system was selected to transport. The functions are powered by a modular fuel cell powered vehicle that provides power for motion of the equipment

Three Position Papers on Intelligent Design in the Public Schools

These brief working documents are used in my Biology 101 course to encourage students to draw together what they know about science, politics, and the theology of the human will to speak to a current issue. In a team format, they are encouraged to compare these positions and select one which they (as a team) wish to identify with. The preponderance of teams are attracted to the third position. Assumptions made toward the end of this third position are accepted with little critical thought. It has been a fascinating exercise in using a biological issue to address fundamental philosophical problems we all face and don’t admit to very readily