The development of net-centric approaches for intelligence and national security applications has become a major concern in many areas such as defense, intelligence and national and international law enforcement agencies. In this volume we consider the web architectures and recent developments that make n- centric approaches for intelligence and national security possible. These include developments in information integration and recent advances in web services including the concept of the semantic web. Discovery, analysis and management of web-available data pose a number of interesting challenges for research in w- based management systems. Intelligent agents and data mining are some of the techniques that can be employed. A number of specific systems that are net-centric based in various areas of military applications, intelligence and law enforcement are presented that utilize one or more of such techniques The opening chapter overviews the concepts related to ontologies which now form much of the basis of the possibility of sharing of information in the Semantic Web. In the next chapter an overview of Web Services and examples of the use of Web Services for net-centric operations as applied to meteorological and oceanographic (MetOc) data is presented and issues related to the Navy's use of MetOc Web Services are discussed. The third chapter focuses on metadata as conceived to support the concepts of a service-oriented architecture and, in particular, as it relates to the DoD Net-Centric Data Strategy and the NCES core services.
The capabilities of modern technology are rapidly increasing, spurred on to a large extent by the tremendous advances in communications and computing. Automated vehicles and global wireless connections are some examples of these advances. In order to take advantage of such enhanced capabilities, our need to model and manipulate our knowledge of the geophysical world, using compatible representations, is also rapidly increasing. In response to this one fundamental issue of great concern in modern geographical research is how to most effectively capture the physical world around us in systems like geographical information systems (GIS). Making this task even more challenging is the fact that uncertainty plays a pervasive role in the representation, analysis and use of geospatial information. The types of uncertainty that appear in geospatial information systems are not the just simple randomness of observation, as in weather data, but are manifested in many other forms including imprecision, incompleteness and granularization. Describing the uncertainty of the boundaries of deserts and mountains clearly require different tools than those provided by probability theory. The multiplicity of modalities of uncertainty appearing in GIS requires a variety of formalisms to model these uncertainties. In light of this it is natural that fuzzy set theory has become a topic of intensive interest in many areas of geographical research and applications This volume, Fuzzy Modeling with Spatial Information for Geographic Problems, provides many stimulating examples of advances in geographical research based on approaches using fuzzy sets and related technologies.