Hagenston, Marty G., Chance, Samuel G.
Approved for public release; distribution is unlimited / Recent military operations have redefined the way modern warfare is waged. In a deliberate effort to achieve and retain information dominance and decision superiority, many innovative technologies have emerged to assist the human war fighter. Unquestionably, these technologies have generated resounding successes on the battlefield, the likes of which have never been seen. With all the success, however, there are still areas for improvement as the potential exists for further reducing already short sensor-to-shooter times. The current World Wide Web (WWW) is largely a human-centric information space where humans exchange and interpret data ( Berners-Lee, 1, 1999). The Semantic Web (SWEB) is not a separate Web, but an extension of the current one in which content is given well-defined meaning, better enabling computers and people to work in cooperation (Berners-Lee et al). The result is the availability of the various backgrounds, experiences, and abilities of the contributing communities through the self-describing content populating the SWEB ( Berners-Lee, 1999). This thesis assesses current SWEB technologies that promise to make disparate data sources machine interpretable for use in the construction of actionable knowledge with the intent of further reducing sensor-to-shooter times. The adoption of the SWEB will quietly be realized and soon machines will prove to be of greater value to war fighting. When machines are able to interpret and process content before human interaction and analysis begins, their value will be further realized. This off-loading, or delegation, will produce faster sensor-to-shooter times and assist in achieving the speed required to achieve victory on any battlefield. / Lieutenant, United States Navy / Major, United States Army
Chance, Samuel G. Hagenston, Marty G.
(has links) (PDF)
Thesis (M.S. in Information Technology Management)--Naval Postgraduate School, September 2003. / Thesis advisor(s): Alexander Bordetsky, Douglas P. Homer. Includes bibliographical references (p. 255-262). Also available online.
Thesis (M.A.)--California State University Channel Islands, 2007. / Submitted in partial fulfillment of the requirements for the degree of Masters Of Science in Computer Science. Title from PDF t.p. (viewed October 22, 2009).
Lino, Natasha Correia Queiroz
Visualisation in intelligent planning systems [Ghallab et al., 2004] is a subject that has not been given much attention by researchers. Among the existing planning systems, some well known planners do not propose a solution for visualisation at all, while others only consider a single approach when this solution sometimes is not appropriate for every situation. Thus, users cannot make the most of planning systems because they do not have appropriate support for interaction with them. This problem is more enhanced when considering mixed-initiative planning systems, where agents that are collaborating in the process have different backgrounds, are playing different roles in the process, have different capabilities and responsibilities, or are using different devices to interact and collaborate in the process. To address this problem, we propose a general framework for visualisation in planning systems that will give support for a more appropriate visualisation mechanism. This framework is divided into two main parts: a knowledge representation aspect and a reasoning mechanism for multi-modality visualisation. The knowledge representation uses the concept of ontology to organise and model complex domain problems. The reasoning mechanism gives support to reasoning about the visualisation problem based on the knowledge bases available for a realistic collaborative planning environment, including agent preferences, device features, planning information, visualisation modalities, etc. The main result of the reasoning mechanism is an appropriate visualisation modality for each specific situation, which provides a better interaction among agents (software and human) in a collaborative planning environment. The main contributions of this approach are: (1) it is a general and extensible framework for the problem of visualisation in planning systems, which enables the modelling of the domain from an information visualisation perspective; (2) it allows a tailored approach for visualisation of information in an AI collaborative planning environment; (3) its models can be used separately in other problems and domains; (4) it is based on real standards that enable easy communication and interoperability with other systems and services; and (5) it has a broad potential for its application on the Semantic Web.
Boulos, Maged Nabih Kamel
No description available.
In recent years there has been a proliferation of scientific resources available through the Internet including, for example, datasets and computational modelling services. Scientists are becoming increasingly dependent upon these resources, which are changing the way they conduct their research activities with increasing emphasis on conducting ‘in silico’ experiments as a way to test hypotheses. Scientific workflow technologies provide researchers with a flexible problem-solving environment by facilitating the creation and execution of experiments from a pool of available services. This thesis investigates the use of workflow tools enhanced with semantics to facilitate the design, execution, analysis and interpretation of workflow experiments and exploratory studies. It is argued that in order to better characterise such experiments we need to go beyond low-level service composition and execution details by capturing higher-level descriptions of the scientific process. Current workflow technologies do not incorporate any representation of such experimental constraints and goals, which is referred to in this thesis as scientist’s intent. This thesis proposes an abstract model of scientific intent based on the concept of an Agent in the Open Provenance Model (OPM) specification. To realise this model a framework based upon a number of Semantic Web technologies has been developed, including the OWL ontology language and the Semantic Web Rule Language (SWRL). Through the use of social simulation case studies the thesis illustrates the benefits of using this framework in terms of workflow monitoring, workflow provenance and annotation of experimental results.
Li, Li, llI@it.swin.edu.au
Ontologies are widely used as data representations for knowledge bases and marking up data on the emerging Semantic Web. Hence, techniques for managing ontol- ogy come to the centre of any practical and general solution of knowledge-based systems. Challenges arise when we look a step further in order to achieve flexibility and scalability of the ontology management. Previous works in ontology management, primarily for ontology mapping, ontology integration and ontology evolution, have exploited only one form or another of ontology management in restrictive settings. However, a distributed and heterogeneous environment makes it necessary for re- searchers in this field to consider ontology interoperability in order to achieve the vision of the Semantic Web. Several challenges arise when we set our goal to achieve ontology interoperability on the Web. The first one is to decide which soft- ware engineering paradigm to employ. The issue of such a paradigm is the core of ontology management when dynamic property is involved. It should make it easy to model complex systems and significantly improve current practice in software engineering. Moreover, it allows the extension of the range of applications that can feasibly be tackled. The second challenge is to exploit frameworks based on the pro- posed paradigm. Such a framework should make possible flexibility, interactivity, reusability and reliability for systems which are built on it. The third challenge is to investigate suitable mechanisms to cope with ontology mapping, integration and evolution based on the framework. It is known that predefined rules or hypotheses may not apply given that the environment hosting an ontology is changing over time. Fortunately, agents are being advocated as a next generation model for en- gineering complex and distributed systems. Also some researchers in this field have given a qualitative analysis to provide a justification for precisely why the agent-based approach is well suited to engineer complex software systems. From a multi-agent perspective, agent technology fits well in developing applications in uncontrolled and distributed environments which require substantial support for change. Agents in multi-agent systems (MAS) are autonomous and can engage in interactions which are essential for any ongoing agents� actions. A MAS approach is thus regarded as an intuitive and suitable way of modelling dynamic systems. Following the above discussion, an agent-based framework for managing ontology in a dynamic environment is developed. The framework has several key characteris- tics such as flexibility and extensibility that differentiate this research from others. Three important issues of the ontology management are also investigated. It is be- lieved that inter-ontology processes like ontology mapping with logical semantics are foundations of ontology-based applications. Hence, firstly, ontology mapping is discussed. Several types of semantic relations are proposed. Following these, the mapping mechanisms are developed. Secondly, based on the previous mapping results, ontology integration is developed to provide abstract views for participating organisations in the presence of a variety of ontologies. Thirdly, as an ontology is subject to evolution in its life cycle, there must be some kind of mechanisms to reflect their changes in corresponding interrelated ontologies. Ontology refinement is investigated to take ontology evolution into consideration. Process algebra is employed to catch and model information exchanges between ontologies. Agent negotiation strategy is applied to guide corresponding ontologies to react properly. A prototype is built to demonstrate the above design and functionalities. It is applied to ontologies dealing with the subject of beer (type). This prototype con- sists of four major types of agents, ranging from user agent, interface agent, ontology agent, and functionary agent. Evaluations such as query, consistency checking are conducted on the prototype. This shows that the framework is not only flexible but also completely workable. All agents derived from the framework exhibit their behaviours appropriately as expected.
Semantic Geospatial Search and Ranking in the Context of the Geographical Information System TerraFlyAlkhawaja, Mortadha Ali 01 January 2010 (has links)
Modern Web based GIS systems have responded significantly to semantic Web technology as it offers opportunities to overcome interoperability and integration problems. There are abundant needs especially for the systems intending to provide more than just a map with basic geographical information. More sophisticated systems can offer more than navigation services and can integrate with several data sources, thereby providing a richer, wider and highly usable information service to be used in business, governmental and different life domains. Search is an essential part of any GIS system because of the huge amount of data representing different meanings that are stored in one or distributed data sources. A model is presented which focuses on searching for geospatial information to answer query semantics rather than query syntax. This model used the most recent and approved standards among the semantic Web communities, and was applied on TerraFly a GIS system. Since ranking is a critical factor in measuring the quality of any search engine, a ranking algorithm is also proposed and evaluated.
Yee, Ka-chi., 余家智.
published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy
Sequeda, Juan Federico
04 September 2015
An early vision in Computer Science was to create intelligent systems ca- pable of reasoning on large amounts of data. Independent results in the areas of Description Logic and Relational Databases have advanced us towards this vision. Description Logic research has advanced the understanding of the tradeoff between the computational complexity of reasoning and the expressiveness of logic languages, and now underpins the Semantic Web. The Semantic Web comprises a graph data model (RDF), an ontology language for knowledge representation and reasoning (OWL) and a graph query language (SPARQL). Database research has advanced the theory and practice of management of data, embodying features such as views and recursion which are capable of representing reasoning. Despite the independent advances, the interface between Relational Databases and Semantic Web is poorly understood. This dissertation revisits this vision with respect to current technology and addresses the following question: How and to what extent can Relational Databases be integrated with the Semantic Web? The thesis is that much of the existing Relational Database infrastructure can be reused to support the Semantic Web. Two problems are studied. Can a Relational Database be automatically virtualized as a Semantic Web data source? This paradigm comprises a single Relational Database. The first contribution is an automatic direct mapping from a Relational Database schema and data to RDF and OWL. The second contribution is a method capable of evalu- ating SPARQL queries against the Relational Database, per the direct mapping, by exploiting two existing relational query optimizations. These contributions are embodied in a system called Ultrawrap. Empirical analysis consistently yield that SPARQL query execution performance on Ultrawrap is comparable to that of SQL queries written directly for the relational representation of the data. Such results have not been previously achieved. Can a Relational Database be mapped to existing Semantic Web ontologies and act as a reasoner? This paradigm comprises an OWL ontology including inheritance and transitivity, a Relational Database and mappings between the two. A third contribution is a method for Relational Databases to support inheritance and transitivity by compiling the ontology as mappings, implementing the mappings as SQL views, using SQL recursion and optimizing by materializing a subset of views. This contribution is implemented in an extension of Ultrawrap. Empirical analysis reveals that Relational Databases are able to effectively act as reasoners. / text
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