Wolf-Fritz Riekert

Using Semantic, Geographical, and Temporal Relationships to Enhance Search and Retrieval in Digital Catalogs

The amount and quality of information available on the Internet increases steadily. To search for information, users are provided with search engines which often return unsatisfactory search results. Against this background, digital catalog systems are becoming more and more popular. Unlike earlier search engines, they contain information about information (meta-information) available on the Internet or in the holdings of digital libraries but not the information itself. Users can benefit from these systems in two ways depending on what information is modeled in them. Firstly, these systems allow for new types of queries; secondly, the quality of retrieval results is improved. This paper sets out how semantic, geographical, and temporal relationships can be integrated into digital catalog systems and how these relationships can be used to enhance search and retrieval processes in such systems. The presentation covers both concepts and a comprehensive description of a digital catalog system which is already used by environmental agencies.

Extracting area objects from raster image data

An algorithm for extracting the spatial objects contained in raster image data is presented. Input to the algorithm is a Siemens computer-aided design (SICAD)-Hygris raster file representing a classification of the plane. Output of the algorithm is a SICAD geographic information system (GIS) external file containing the topologically complete definitions of all area objects and their constituents, such as arcs and nodes, as implied by the classification. The algorithm is based on a one-pass plane sweep that processes the input raster data in a strictly sequential order. Processing takes place only if certain color changes, also called events, occur. Each event triggers a well-defined sequence of simple actions.<<ETX>>

Environmental Informatics as a New Discipline of Applied Computer Science

For many years, computer-based systems for processing environmental information have been developed in environmental protection and environmental research. A broad range of applications in environmental research and protection is covered by these systems, including monitoring and control, information management, data analysis, as well as planning and decision support. A new discipline, known as Environmental Informatics, is emerging which combines computer science topics such as data base systems, geographic information systems, modeling and simulation, computer graphics, user interface design, knowledge processing, and neural networks, with respect to their application to environmental problems.

The ZOO Metasystem: A Direct-Manipulation Interface to Object-Oriented Knowledge Bases

Transparency and adaptability are important criteria for the usability of computer systems. It is not easy to fulfill these criteria in ill-structured domains by using traditional software concepts. The object-oriented approach, however, allows the construction of metasystems which enable the user to understand and manipulate the underlying conceptual schemata of an application system.ZOO is a metasystem for the application expert. ZOO visualizes the contents of an object-oriented knowledge base in a graphic, spatial representation as a net of icons. ZOO allows its user to inspect, manipulate, create and delete the components of a knowledge base through direct manipulation of graphic objects.

ENVIRONMENTAL MONITORING: MODELS, METHODS, AND SYSTEMS

Environmental monitoring is the continuous, automated observation of changes in the environment. Powerful models, methods, and systems that have been developed for the purpose of environmental monitoring are now leaving the laboratory setting, and some of them are already being applied. When they are applied in countries that have well established environmental authorities and a high population density, these applications are actually additional measures to protect the environment. However, the situation in less developed or less densely populated countries is quite different. For these countries, the new techniques of environmental monitoring can offer totally new opportunities for better environmental protection.

Cooperative Management of Data and Services for Environmental Applications

In recent years, systems for processing environmental information have been evolving from research and development systems to practical applications. Many of these systems already support environmental activities of the public sector. Most of these systems, however, were developed as island solutions. The integration of such heterogeneous systems and the support of cooperation on a regional, national and international scale is a big challenge of today. It requires new methods to access and make use of the services and data offered by the agencies of such a distributed system. Metadata (such as in data and service dictionaries) and codata (such as spatiotemporal references) must be provided in order support the proper usage of these data and services. Systems integration techniques are required in order to overcome the heterogeneity of the existing systems. An approach to fulfill these requirements is shown by examples from recent work at FAW that has been conducted in the context of the Environmental Information System Baden-Wurttemberg.

RESEDA: A knowledge-based advisory system for remote sensing

This article describes the design and implementation of RESEDA (RemoteSensorDataAnalysis), a knowledge-based system for the extraction of environmental information from digital raster images of the earth. The images may have been obtained from airborne or spaceborne sensors. Ancillary data is used to improve the results of the image analysis; in particular, we are using digital map data stored in a geographic information system for this purpose. The main goal of the system is to provide easy access to remote sensing technology for non-expert users, such as decision makers in environmental management.

UIS-management of data and services in the environmental information systems of Baden-Württemberg

In the Environmental Information System (UIS) of Baden-W&uuml;rttemberg, an extensive collection of information and knowledge is accumulated in the form of data, methods, and multimedia documents on a variety of computer platforms. A service-oriented approach based on meta-information and WWW technology has been chosen to bring this treasure of information and knowledge to the workplace of every employee in the environmental administration. The guiding idea was to identify data, functionalities, and multimedia information that can be used in multiple ways and to supply them as self-contained network services. This helps to make the use of the available hardware and software resources more economical and, in addition, allows for a relatively unrestricted and easy access to the information sources offered by the UIS.

Providing Declarative Access to a Processing System for Satellite Image Data

This paper describes the RESEDA Assistant, a knowledge-based access system to a processing system for satellite data. This system provides declarative access to the functions offered by a commercial data analysis system. That is, instead of requiring users to specify how the satellite data should be analyzed, users need only describe what kind of target data they are interested in. Descriptions of the data types and methods offered by the underlying data analysis system are represented in a knowledge base and utilized by the system.

Architecture of a knowledge-based system for remote sensor data analysis

This paper describes the current status of the project RESEDA, which stands for REmote SEnsor Data Analysis. The main objective of RESEDA is the development of a knowledge-based system for the extraction of environmental information from digital raster images of the earth, obtained from airborne or spaceborne sensors. The project is designed to satisfy user demands for standardization and for improvement of image-processing results by means of ancillary data. The project, which is funded by Siemens and by the Federal State of Baden-Württemberg, is conducted by the FAW (the Research Institute for Applied Knowledge Processing) in Ulm, West Germany.