Roy Ladner

Fuzzy Set Approaches to Spatial Data Mining of Association Rules

This paper presents an approach to the discovery of association rules for fuzzy spa- tial data. Association rules provide information of value in assessing significant correlations that can be found in large databases. Here we are interested in correlations of spatially related data such as soil types, directional or geometric relationships, etc. We have combined and extended techniques developed in both spatial and fuzzy data mining in order to deal with the uncertainty found in typical spatial data.

The 2-3TR-tree, a trajectory-oriented index structure for fully evolving valid-time spatio-temporal datasets

Supporting large volumes of multi-dimensional data is an inherent characteristic of modern database applications, such as Geographical Information Systems (GIS), Computer Aided design (CAD), and Image and Multimedia Databases. Such databases need underlying systems with extended features like query languages, data models, and indexing methods, as compared to traditional databases, mainly because of the complexity of representing and retrieving data. The presented work deals with access methods for databases that accurately model the real world. More precisely, the focus is on index structures that can capture the time varying nature of moving objects, namely spatio-temporal structures. A new taxonomy to classify these structures has been defined according to dataset characteristics and query requirements. Then, a new spatio-temporal access method, the 2-3TR-tree, has been designed to process specific datasets and fulfill specific query requirements that no other existing spatio-temporal index could handle.

Spatial data methods and vague regions: A rough set approach

Uncertainty management has been considered essential for real world applications, and spatial data and geographic information systems in particular require some means for managing uncertainty and vagueness. Rough sets have been shown to be an effective tool for data mining and uncertainty management in databases. The 9-intersection, region connection calculus (RCC) and egg-yolk methods have proven useful for modeling topological relations in spatial data. In this paper, we apply rough set definitions for topological relationships based on the 9-intersection, RCC and egg-yolk models for objects with broad boundaries. We show that rough sets can be used to express and improve on topological relationships and concepts defined with these models.

Enhancing the US Navy's GIDB Portal with Web Services

Using Web services, the authors have been able to increase the amount of data accessible through the Naval Research Laboratorys geospatial information database (GIDB) portal. They created a Web crawler for Web mapping services (WMS) that harvests and adds data to the portal index and a translator that provides access to non-WMS data through the WMS interface. The integrated Web services broker, using traditional Web services standards, provides automated access to meteorological and oceanographic data

Soft computing techniques for web services brokering

To enhance and improve the interoperability of meteorological Web Services, we are currently developing an Integrated Web Services Brokering System (IWB). IWB uses a case-based classifier to automatically discover Web Services. In this paper, we explore the use of rough set techniques for selecting features prior to classification. We demonstrate the effectiveness of this feature technique by comparing it with a leading non-rough set (Information Gain) feature selection technique.

Case-based classification alternatives to ontologies for automated web service discovery and integration

Web Services are becoming the standard technology used to share data for many Navy and other DoD operations. Since Web Services technologies provide for discoverable, self-describing services that conform to common standards, this paradigm holds the promise of an automated capability to obtain and integrate data. However, automated integration of applications to access and retrieve data from heterogeneous sources in a distributed system such as the Internet poses many difficulties. Assimilation of data from Web-based sources means that differences in schema and terminology prevent simple querying and retrieval of data. Thus, machine understanding of the Web Services interface is necessary for automated selection and invocation of the correct service. Service availability is also an issue that needs to be resolved. There have been many advances on ontologies to help resolve these difficulties to support the goal of sharing knowledge for various domains of interest. In this paper we examine the use of case-based classification as an alternative/supplement to using ontologies for resolving several questions related to knowledge sharing. While ontologies encompass a formal definition of a domain of interest, case-based reasoning is a problem solving methodology that retrieves and reuses decisions from stored cases to solve new problems, and case-based classification involves applying this methodology to classification tasks. Our approach generalizes well in sparse data, which characterizes our Web Services application. We present our study as it relates to our work on development of the Advanced MetOc Broker, whose objective is the automated application integration of meteorological and oceanographic (MetOc) Web Services.

Normalization in a rough relational database

The rough relational database model was developed for the management of uncertainty in relational databases. In this paper we discuss rough functional dependencies and the normalization process used with them. Normalization is an important part of the relational database design process and rough normalization provides similar benefits for the rough relational database model.

Design of an Integrated Web Services Brokering System

This article describes an Integrated Web Services Brokering System (IWB) to support the automated discovery and application integration of Web Services. In contrast to more static broker approaches that deal with specific data servers, our approach creates a dynamic knowledge base from Web Service interface specifications. This assists with brokering of requests to multiple data providers even when those providers have not implemented a community standard interface or have implemented different versions of a community standard interface. A specific context we illustrate here is the domain of meteorological and oceanographic (MetOc) Web Services. Our approach includes the use of specific domain ontologies and has evaluated the use of case-based classification in the IWB to support automated Web Services discovery. It was also demonstrated that the mediation approach could be extended to OGC Web Coverage Services.

Web access of meteorological and oceanographic data

Web services are becoming the standard technology used to share data for many navy and other DoD operations. These enable an automated capability to obtain and integrate data for data fusion. However assimilation of data from Web-based sources means that differences in schema and terminology prevent simple querying and retrieval of data. Thus, machine understanding of the Web services interface is necessary for automated selection and invocation of the correct service. In this paper we describe an advanced architecture that can provide access to Web-based meteorological and oceanographic (METOC) data that can be utilized in geospatial data fusion. We also discuss the use of case-based classification as an alternative/supplement to using ontologies for resolving knowledge sharing. While ontologies encompass a formal definition of a domain of interest, case-based reasoning is a problem solving methodology that retrieves and reuses decisions from stored cases to solve new problems, and case-based classification involves applying this methodology to classification task.

New developments in Internet-based delivery of MetOc data to Warfighters

Access and retrieval of meteorological and oceanographic data from heterogeneous sources in a distributed system presents many issues. Effective bandwidth utilization is important for any distributed system. In addition, specific issues need to be addressed in order to assimilate spatio-temporal data from multiple sources. These issues include resolution of differences in datum, map-projection and time coordinate. Reduction in the complexity of data formats is a significant factor for fostering interoperability. Simplification of training is important to promote usage of the distributed system. Here, we describe particular techniques that revolutionize the Internet-based delivery of MetOc data to address the needs of the Warfighter.