Synergy between science and informatics is required to develop a more robust understanding of the Earth as a system of systems. Interaction of Earth systems is recorded in both geological and biological data, yet the capability to integrate across disciplines is hampered by diverse social and technological approaches to research and communication. Ontology-based informatics provides the ability to share, access, and discover data across disciplines. This ability will lead to data integration and new models that enable evaluation of past, present, and future changes associated with Earth systems. Significant challenges that must be met in order to promote such an understanding encompass social and technical considerations, such as professional credit for data sharing, development of data registration services for ready access to heterogeneous and distributed data, and development of new approaches for evaluating trust and security in a web environment. Integration of data from different scientific disciplines will require development and management of new Earth system ontologies. If done properly, this development will not only enable but engage the next generation workforce.

The primary factors needed to manage disaster events are time-critical geospatial information on the event occurrence and presentation of that information in an easily manageable, collaborative/interactive geospatial decision-support and visualization environment. In this chapter, we describe the development, integration, and use of an unmanned airborne system (UAS), a multispectral sensor with autonomous onboard processing capabilities, a data distribution system, and geospatial processes to deliver real-time information to emergency incident management teams facing wildland fires. The unique integration of the described tools has contributed to an order of magnitude decrease in the delivery time of critical geospatial information to disaster managers. The UAS wildfire imaging campaigns in the western United States in 2007 and 2008 are briefly described in the context of real-world adaptation and utility of the resultant information improvements. These capabilities have far-reaching applications to other time-critical, disaster event management scenarios, and they are being expanded to further utilize various UAS platforms and other airborne sensor system data. This chapter will also describe the resultant integration issues faced and the solutions for ubiquitous adaptation of many of these processes in future UAS missions.

Several types of fundamental ontological relations connect the endurant (continuant) and perdurant (occurrent) entities in every domain. These include: instantiation, parthood, location, and connection relations, and those that are derived from them, such as adjacency, overlap, containment, and coincidence. Some of these types of relations, and their subtypes, are formally defined in the context of the Web Ontology Language (OWL) for a variety of endurant geological examples, mostly from the Nankai Trough in southwest Japan and the San Andreas fault in California. Here, the foundational ontological relations are discussed to show their application in building useful earth science ontologies. These relations, defined as properties in OWL, are given in the context of the Resource Description Framework (RDF) triples and their relationship to relational databases. The role of properties in providing semantics, reasoning, and knowledge structuring and representation is discussed for various ontological relations. The semantics of classes are provided by the metaproperty and restrictions of the properties that use these classes as domain and range. Types of properties are described from different perspectives and for different purposes. Property subclassing, through OWL's subproperty construct, is used to restrict properties. The formal definitions of the foundational taxonomic (isA), partonomic (partOf), location (locatedIn), containment (containedIn, componentOf), and topologic (overlap, adjacentTo) relations, at the class and instance levels, are given in first-order logic for continuant geological entities. Geologic examples for several other basic relations such as derivesFrom, transformationOf, and absorb are also given.

Metadata are an essential tool for use in the management of geoscientific information. Well-managed metadata provide a number of key information management functions, including facilitating data discovery and providing a robust framework for information asset management. The realization of these and other benefits is predicated on the existence of well-maintained metadata. Sadly, metadata are commonly absent, incomplete, inaccurate, inarticulate, or obsolete. Some of the benefits and opportunities that arise from well-managed metadata collections are discussed here. The rapid development of spatial data infrastructures means that maintenance of metadata for geoscience information is becoming increasingly important.

Low levels of geospatial literacy and geoscientific understanding mean that basic geological map data are meaningful to, and can therefore be interpreted by, a remarkably small number of people with specialist knowledge and training. Nevertheless, geological maps continue to underpin the exploration, exploitation, and management of natural resources such as fossil fuels, minerals, and groundwater. Geological maps can, however, be the essential basis for derived, spatial geoscience information with which complex science relating to societally relevant issues such as geohazards can be communicated meaningfully to the layperson. Such derived spatial geoscience information offers opportunities for geological surveys and agencies to demonstrate societal relevance by creating social and economic benefits. Production and delivery of such information from complex geoscientific data should therefore be central to the mission of geological surveys and agencies. This pathway is traced from data to information and knowledge of use in decision making. Societal benefits and impacts are described and quantified using case studies and independent economic impact analysis data.

New strategies for sustainability within the Department of Defense are focused on addressing present and future needs while strengthening community partnerships that improve operational abilities. This “across-the-fence line” strategic thinking requires innovative tools that can engage a broad segment of the community and a variety of military interest groups. These tools must provide a platform for understanding the challenges and realizing the goals of both private- and public-sector interests. They must tangibly represent many different potential futures, their implications, and policies that can help mobilize solutions quickly and easily in a uniform, consistent, and democratic manner. The Strategic Sustainability Assessment (SSA) consists of a series of complementary tools for forecasting and backcasting that provide regional stakeholders a unique perspective on potential sustainable regional policy and investment choices. Forecasting approaches use dynamic spatial modeling techniques to project potential future urban transformations and their implication to the social, environmental, and economic fabric of the region. Backcasting is used to determine critical sets of strategic interventions designed to offset the simulated future impacts. The results of the analysis are managed through the use of a Web-based GeoPortal. This helps to democratize the information by providing it to local stakeholders in a useable and accessible way. The hope is that greater and more direct access to models and the information they generate will help lead to better, more sustainable planning decisions in our military bases and in our communities.

Soil liquefaction takes place during and/or after the occurrence of an earthquake and is a major contributor to urban seismic risk. Geologists use a technique called the cone penetration test (CPT) to determine the properties of soils, including liquefaction levels, which yields large amounts of soil data. The analysis of such massive amounts of data requires high-performance computing resources. In this paper, we present GQO (Grid Query Optimizer), a distributed algorithm that enables the analysis of large CPT data sets efficiently on a grid cyberinfrastructure.

Over the past decade, desktop image analysis and geographic information system (GIS) software have matured into the dominant tool for geoprocessing. Desktop solutions usually incorporate a broad range of geospatial processing functionality together with locally maintained data in order to provide a tightly coupled and largely autonomous environment for carrying out operational geospatial activity. This approach has also been adopted by the research community. Researchers typically bring together at the local level both the necessary analytical tools and the data for the research activity at hand. There is now, however, a move away from such desktop technology. A loosely coupled service-oriented architecture, based on the deployment of Web services developed and maintained by a dispersed community, is now seen as a more powerful and flexible approach. Likewise, with this approach, the data may also be distributed and accessed directly from databases maintained by the collection agencies rather than being duplicated at the site where analysis is being undertaken. This new approach, based on established and emerging standards for geospatial interoperability, has many advantages, which are discussed herein. This chapter describes the challenges associated with the more dispersed and collaborative nature of the operational and research programs that are based on such an architectural approach. The need for and benefits of a persistent interoperability test bed for geosciences research and education are discussed, as is the question of ways in which to facilitate the move of such an architectural approach into routine operational use.

GEONETCast is a global, near–real-time, environmental data dissemination system in support of the Global Earth Observation System of Systems (GEOSS). The goal of the system is to enable enhanced dissemination, application, and exploitation of environmental data and products for the diverse societal benefits defined by the Group on Earth Observations (GEO), including agriculture, energy, health, climate, weather, disaster mitigation, biodiversity, water resources, and ecosystems. The system consists of three regional broadcasts: EUMETCast (operated by the European Organisation for the Exploitation of Meteorological Satellites [EUMETSAT], covering Europe, Africa, and parts of Asia and the Americas), CMACast (operated by the China Meteorological Administration [CMA], covering Asia and parts of the Pacific), and GEONETCast Americas (operated by the U.S. National Oceanic and Atmospheric Administration [NOAA], covering North, Central, and South America and the Caribbean). The GEONETCast system uses the Digital Video Broadcast-Satellite (DVB-S) or Digital Video Broadcasting–Satellite–Second Generation (DVB-S2) standard over commercial communications satellites and low-cost, off-the-shelf technology to widen the access of new user groups to Earth observation information.

Here, we describe the development and implementation of standards for the dissemination of geoscience information. We do this from the perspective of the British Geological Survey, but this perspective is considered typical of many geological survey organizations. When geoscience data dissemination occurred through the use of paper maps, standards were mainly developed by individual organizations. The introduction of digital systems for map production and data storage required the development of corporate data models. The evolution of the Web as a means of searching for data led to the development of metadata standards, first at the national level, but soon after at the international level as well. The requirement for interoperable digital geoscience data has led to the need for an accepted international conceptual data model, and so we describe the development and implementation of GeoSciML, the GeoScience Markup Language (GSML). Agreement on a schema enables delivery of data in a standard form, but semantic harmonization is required for full interoperability. The implementation of Web services using GeoSciML requires the use of Open Geospatial Consortium (OGC) and International Organization for Standardization (ISO) open standards, but difficulties have been encountered through lack of full compliance with these standards on the part of software suppliers. The UK Digital National Framework is a means of achieving interoperability between data from different domains at a national level, and it is a good basis for compliance with the mandatory pan-European INSPIRE (Infrastructure for Spatial Information in Europe) framework. The international standards described here are essential in order to meet society's growing demand for interoperable geoscience information in a wide variety of applications.

This chapter describes the need for complex semantic models, i.e., ontologies of real-world categories, referents, and instances, to go beyond the barriers of terminology and data structures. Terms and local data structures are often tolerated in information technology because these are simpler, provide structures that humans can seemingly interpret easily and easily use for their databases and computer programs, and are locally salient. In particular, we focus on both the need for ontologies for data integration of databases, and the need for foundational ontologies to help address the issue of semantic interoperability. In other words, how do you span disparate domain ontologies, which themselves represent the real-world semantics of possibly multiple databases? We look at both sociocultural and geospatial domains and provide rationale for using foundational and domain ontologies for complex applications. We also describe the use of the Common Semantic Model (COSMO) ontology here, which is based on lexical-conceptual primitives originating in natural language, but we also allow room for alternative choices of foundational ontologies. The emphasis throughout this chapter is on database issues and the use of ontologies specifically for semantic data integration and system interoperability.

The first step in the preservation of digital scientific data is gathering enough information “about” a scientific outcome or data collection so that it can be discovered and used a decade later as easily as it is used at the time. Data provenance, or lineage of a collection, can capture the way in which a particular scientific collection was created, when, and by whom. Tools that automate the collection of provenance can reduce the burden on the researcher, and provenance data can be stored in ways that make the data more amenable to long-term preservation. We discuss the various dimensions of data provenance in data-driven geospatial science with the goal of conveying a good grasp of provenance collection, representation, and use. Our research in data cyberinfrastructure utilizes real-time observational data in on-demand weather forecasts, and we discuss this aspect as well.

This paper presents a description of the theoretical foundations of a novel method of geoinformatics, the event bush, and discusses its place and role in a newly formulated framework for information modeling of geoenvironments. The event bush addresses a particular yet very wide type of geoenvironment, that of directed alternative changes, which is likely to occur in many information domains. Modeling these environments, this method has reached the state of conceptual model and may become, with further development, one of the first examples of strict formal theory in the earth sciences. The method is exemplified by application to the complex volcanic environment of Mount Etna, Sicily.

The need to develop a geoscience cyberinfrastructure framework for both the discovery and semantic integration of disciplinary databases in geosciences is abundantly clear as we seek to unravel both the evolutionary history of Earth and address significant societal challenges. Although geoscientists have produced large amounts of data, the ability to find, access, and properly interpret these large data resources has been very limited. The main reason for the difficulties associated with both discovery and integration of heterogeneous and distributed data sets is perhaps related to the adoption of various acronyms, notations, conventions, units, etc., by different research groups. This makes it difficult for other scientists to correctly understand the semantics associated with data, and it makes the interpretation and integration of data simply infeasible. This paper presents the scientific rationale for developing new capabilities for semantic integration of data across geoscience disciplines. In order to enable the sharing and integration of geosciences data on a global scale, ontology-based data registration and discovery are required. Hence, this paper describes the need to develop foundation-level ontologies for efficient, reliable, and accurate data sharing among geoscientists. Ontologically registered data can be modeled through the use of geoscientific tools to answer complex user queries. This paper emphasizes the need to share tools such as Web services that are registered to a service ontology and made accessible to the scientific community at large. Future development would include an ontology of concepts associated with processes, enabling users to conduct both forward and reverse modeling toward a more robust understanding of complex geoscience phenomena. This paper presents two use cases for a semantic infrastructure model registering data and services, including processes for analysis of complex geoscience queries.

This chapter discusses the origins and purpose of Global Map, the current situation of the initiative, and the challenges it faces in the future. A major societal challenge facing the world today involves finding a way to deal more effectively with growing environmental problems. Reliable geographic information at a global scale is an indispensable element in formulating policy responses to global environmental challenges. The main purpose of Global Map is to describe the status of the global environment to aid in decision-making processes. Global Map provides digital maps of the terrestrial surface of Earth at a resolution of 1 km, with consistent and comparable specifications for every country. It is produced in cooperation with the national mapping organization in each country. Global Map was initiated by the government of Japan as a contribution to the action plan of the United Nations Agenda 21 program. There are four vector and four raster layers. Version 1 of Global Map was released in June 2008 and includes coverage of Antarctica. It also includes two global maps with complete high-quality coverage, one on land cover and the other on percentage tree cover. New uses of Global Map include disaster adaptation, mitigation, and management, and educational applications. Although Global Map as a product is important, the cooperative process by which Global Map is produced is equally important. This ongoing cooperation will help to ensure the future of Global Map as it enters a new phase in its development and make a substantial contribution to capacity building in the application of geoinformation to sustainable development.