Stefan Wiemann

Spatial data fusion in Spatial Data Infrastructures using Linked Data

ABSTRACT The synthesis of spatial data from the various sources available on the Web is a major challenge for current applications based on Web-based information retrieval and spatial decision-making. This article addresses spatial data fusion, with particular emphasis on its application in Spatial Data Infrastructures (SDIs). Possibilities for the integration of SDI and Semantic Web developments in the context of spatial data fusion are reviewed with a focus on the harmonized description and usage of feature relations. Specifically, potential applications of Linked Data principles are discussed in detail. On this basis, a classification and a decomposition of fusion processes in a service-oriented environment are proposed. A prototype implementation demonstrates the feasibility and usability of the approach using Open Geospatial Consortium (OGC) and Semantic Web standards.

Design and prototype of an interoperable online air quality information system

This paper focuses on the design and development of a Spatial Data Infrastructure (SDI)-compliant online system for air quality information retrieval, including support for real-time monitoring. This system assesses exposure to ambient air to mitigate potential health risks, which is crucial for susceptible individuals, health practitioners and decision makers. Particular attention is paid to the development of an interoperable, applicable and transferrable approach to the application of robust and flexible air quality modeling as required for early warning systems on the Web. Moreover, the design provides different access levels to system components for both non-expert and scientific users and supports extension with external standard compliant services. The developed Web-client Time2Maps enables the user to view, analyze and download requested air quality information and serves as a portal to the designed online system.

Ad-hoc combination and analysis of heterogeneous and distributed spatial data for environmental monitoring – design and prototype of a web-based solution

ABSTRACT With regard to a multi-dimensional and multi-facetted implementation of the vision of a Digital Earth, capabilities to combine and analyze heterogeneous spatial data sources on the web are becoming increasingly important. In this article, an online system is conceptualized and implemented to facilitate spatial data analysis and decision making specifically for environmental applications. It supports a dynamic search and binding of suitable geoprocessing functionality with respect to the given input data and target description. Geoprocessing patterns are used to create an application-oriented abstraction layer on top of generic geoprocessing services available on the web. As an application scenario the determination and quality assessment for water body structures is taken. For this use case authoritative data, remote sensing imagery and citizen science data gets combined to gain a comprehensive picture of the various spatial, temporal and thematic aspects influencing the quality of inland waters. The prototypical implementation makes use of open standards to facilitate the integration with existing spatial data infrastructures.

Spatial Data Relations as a Means to Enrich Species Observations from Crowdsourcing

The general fascination of nature has always been a major driver for studies on living animal and plant species. A large number of professionals and especially volunteers are organized in related initiatives and projects from the local to the global level, leading to the vast amount of species observations nowadays available on the Web. This article seeks to enhance this knowledge base by the determination, management and analysis of feature entity relations among the observations. Those relationships are considered important for comprehensive biological monitoring and, in general, facilitate the integrated use of existing data sources on the Web. Particular emphasis is put on crowdsourcing, which increasingly receives attention and support by citizen science initiatives. The Linked Data paradigm, representing the core of the Semantic Web, is applied to describe, handle and exploit relations in a standardized and thus interoperable manner. Methodologies to determine and validate relationships are developed and implemented. The implementation combines the analysis of spatio-temporal behavioral patterns of species with a crowdsourcing approach for the validation of determined relations. The vagueness of results is addressed by assessing the probability of a relation.