Theodor Foerster

The Geoprocessing Web

As Web services technology has matured in recent years, an increasing amount of geospatial resources and processing functions are available in the form of online Web services. Consequently, effective and efficient data processing methods for geospatial information extraction and knowledge discovery over the Web are a major challenge for research and industry. The Geoprocessing Web, which consists of light-weight protocols, crowd-sourcing capability, and the capability to process real-time geospatial data sources provided by sensors, enables distributed, interoperable and collaborative processing of geospatial data for information and knowledge discovery. This paper provides a comprehensive overview about the state-of-the-art architecture and technologies, and the most recent developments in the Geoprocessing Web.

Integrating OGC Web Processing Services into Geospatial Mass-Market Applications

Enabling the integration of information provided by OGC Web Processing Services into geospatial mass-market applications is promising, as it increases the availability of information for most ordinary users. This information will be most likely based on the latest available data (e.g. collected by sensors) and can thereby support the user in time-constrained decisions. This paper presents an approach to actually configure and integrate such processes into geospatial mass-market applications. The applicability of the approach is demonstrated by a risk management scenario. The software presented has been developed within the Geoprocessing Community of the 52°North initiative and is available through an Open Source license.

Sensor bus: an intermediary layer for linking geosensors and the sensor web

In recent years, the standards of OGCs Sensor Web Enablement (SWE) initiative have been applied in a multitude of projects to encapsulate heterogeneous geosensors for web-based discovery, tasking and access. Currently, SWE services and the different types of geosensors are integrated manually due to a conceptual gap between these two layers. Pair-wise adapters are created to connect an implementation of a particular SWE service with a particular type of geosensor. This approach is contrary to the aim of reaching interoperability and leads to an extensive integration effort in large scale systems with various types of geosensors and various SWE service implementations. To overcome this gap between geosensor networks and the Sensor Web, this work presents an intermediary layer for integrating these two distinct layers seamlessly. This intermediary layer is called the Sensor Bus as it is based on the message bus architecture pattern. It reduces the effort of connecting a sensor with the SWE services, since only the adaption to the Sensor Bus has to be created. The communication infrastructure which acts as the basis for the Sensor Bus is exchangeable. In this work, the Sensor Bus is based on Twitter. The involved SWE services as well as connected geosensors are represented as user profiles of the Twitter platform.

Spatio-temporal aggregation of European air quality observations in the Sensor Web

An increasing amount of observations from different applications such as long-term environmental monitoring or disaster management is published in the Web using Sensor Web technologies. The standardization of these technologies eases the integration of heterogeneous observations into several applications. However, as observations differ in spatio-temporal coverage and resolution, aggregation of observations in space and time is needed. We present an approach for spatio-temporal aggregation in the Sensor Web using the Geoprocessing Web. In particular, we define a tailored observation model for different aggregation levels, a process model for aggregation processes and a Spatio-Temporal Aggregation Service. The presented approach is demonstrated by a case study of delivering aggregated air quality observations on-demand in the Sensor Web.

Publishing sensor observations into Geospatial Information Infrastructures: A use case in fire danger assessment

To improve environmental monitoring, the availability of large coverage, interoperable spatio-temporal data is crucial for its integration into environmental models, for example, to compute fire danger models. In order to produce up-to-date and accurate results, these models require data with high temporal and spatial resolution. Thus, it is promising to consider the increasing number of in-situ sensors providing observations of our environment in real-time. Today, interoperable access to such spatio-temporal data is achieved by Geospatial Information Infrastructures (GIIs). From a technical point of view, GIIs provide these data through standards-based Web service interfaces. While those Web service interfaces already enable the interoperable discovery and retrieval of sensor observations, the functionality to publish sensor observations is still an arduous task. Hence, in this paper, we present an approach to improve the registration of sensors and the publication of their observations via standards-based Web service interfaces. We evaluate our approach by extending a standards-based GII and by applying the developed approach as a proof of concept to integrate in-situ weather observations into the European Forest Fire Information System for assessing fire danger in Spain.

Interaction patterns for bridging the gap between sensor networks and the Sensor Web

The Sensor Web Enablement (SWE) initiative of the Open Geospatial Consortium (OGC) defines standards for Web Service interfaces and data encodings usable as building blocks to implement a Sensor Web for geospatial applications. These standards encapsulate heterogeneous sensors installed in existing sensor networks for web-based discovery, scheduling and access. SWE has been applied in a multitude of projects in the recent years, showing its suitability in real world scenarios. However, there is still a fundamental challenge to be tackled. While SWE enables interoperability and is well-designed towards the upper application layer, the interaction between the Sensor Web and the underlying sensor network layer is not yet sufficiently described. This work identifies five fundamental interaction patterns between the Sensor Web and sensor networks by introducing an intermediary layer, prototypically implemented using Twitter. The patterns bridge the gap between the two distinct layers and are essential for enabling future sensor plug & play within the Sensor Web.

Handling the semantics of sensor observables within SWE discovery solutions

When searching for sensor data, sensor instances, or Sensor Web Enablement (SWE) services the description of the observed phenomenon plays an important role. Obviously, every user searching for sensor data needs to specify in which kind of sensor data he is interested. In current SWE applications, the information about the observed phenomenon is provided as a unique link encoded as a Uniform Resource Name (URN). However, relying on those URNs to perform string based search for sensor observables has serious drawbacks when it comes to realizing advanced sensor discovery tools as the meaning of the observables is ignored. This work presents an approach that makes use of semantic annotations of SWE resources. The presented solution relies on a dictionary for sensor observables, the Sensor Observable Registry (SOR). This dictionary comprises URNs identifying observables, definitions of these observables in natural language, and pointers to formal phenomenon definitions contained in ontologies. This makes it possible to rely on existing reasoning mechanisms for determining equivalent or related observables (e.g., specializations or generalizations) to the one specified by a user. Finally, an approach is presented, how the SOR can be used for enhancing the sensor discovery process by linking it to sensor catalogues and registries.

Live Geoinformation with Standardized Geoprocessing Services

To realize live geoinformation, which is about providing information as soon as it is available, new approaches for instant geoprocessing and efficient resource utilization are required. Currently, such geoprocessing on the web is handled sequentially instead. This article describes a new approach by processing geodata streams and thereby enabling a continuous processing for improved resource utilization rates. In particular, this work applies HTTP Live Streaming for example of standardized geoprocessing services. The approach is evaluated for processing a large volume datasets of OpenStreetMap data. The presented implementation is based on Free and Open Source software.

Discovering the Sensor Web through Mobile Applications

Sensor data is crucial for mobile applications to support the user in the field. Several mobile applications are available for accessing such sensor data. However, a comprehensive approach for discovering such sensor data in the Sensor Web according to the user’s context (i.e. the location) has not been proposed yet. This article describes an approach for discovering data and services in the Sensor Web through mobile applications. The approach is demonstrated by an air quality scenario and is implemented based on Free and Open Source Software.

Editorial: Towards a Geoprocessing Web

As Web services technology has matured in recent years, an increasing amount of geospatial content and processing capabilities are available online as Web services. These Web Services enable interoperable, distributed, and collaborative geoprocessing to significantly enhance the abilities of users to collect, analyze and derive geospatial data, information, and knowledge over the network. A Web-based distributed geospatial computing and large networks of collaborating applications is emerging as the next step in the evolution of geoprocessing. The Geoprocessing Web is changing the way in which geoscience applications and systems are designed, developed and used. In this special issue, we collect a number of research and application papers to present the current research on theoretic frameworks and practical implementations in the Geoprocessing Web, and identify related challenges and open issues. What are the distinguishing characteristics of the Geoprocessing Web? What are the achievements and challenges of the Geoprocessing Web with respect to data, service, workflows and semantics? The paper by Zhao et al., tackles these questions, and provides a comprehensive overview about the state-of-the-art architecture and technologies, and the most recent developments in the Geoprocessing Web. Interoperability is achieved by using standards. The Open Geospatial Consortium (OGC) has developed the Web Processing Service (WPS) specification that defines common service interfaces and message encodings for standard Web-based geoprocessing. The paper by Lopez-Pellicer et al., discusses the use of search engines and focused crawlers for checking the availability of the OGC WPS, and provides quantitative data about the scalability of the Geoprocessing Web. The interoperable OGC WPS can be used as the mediation allowing one to seamlessly execute a geoprocessing job on different computing platforms ranging from a standalone GIS server up to computer clusters and large Grid infrastructures. The paper by Giuliani et al., proposes an extension of OGC WPS for mediating different geospatial and Grid software packages. The service-oriented workflow is essential for complex geospatial applications and knowledge discovery over the Web. Service composition concerns with how to discover, coordinate, and integrate a set of component services. The paper by Li et al., proposes a QoS-aware game theory approach to geoprocessing service composition for concurrent tasks. In his paper, a noncooperative game-based mathematical model, which is related to the competitive relationships between tasks, is used to build a best response function to maintain the workflow optimization. As opposed to the commonly used process-centric composition model, the paper by Jesus et al., presents how to use a newly