Programming patterns and development guidelines for Semantic Sensor Grids (SemSorGrid4Env)

The web of Linked Data holds great potential for the creation of semantic applications that can combine self-describing structured data from many sources including sensor networks. Such applications build upon the success of an earlier generation of 'rapidly developed' applications that utilised RESTful APIs. This deliverable details experience, best practice, and design patterns for developing high-level web-based APIs in support of semantic web applications and mashups for sensor grids. Its main contributions are a proposal for combining Linked Data with RESTful application development summarised through a set of design principles; and the application of these design principles to Semantic Sensor Grids through the development of a High-Level API for Observations. These are supported by implementations of the High-Level API for Observations in software, and example semantic mashups that utilise the API

Specification of high-level application programming interfaces (SemSorGrid4Env)

This document defines an Application Tier for the SemsorGrid4Env project. Within the Application Tier we distinguish between Web Applications - which provide a User Interface atop a more traditional Service Oriented Architecture - and Mashups which are driven by a REST API and a Resource Oriented Architecture. A pragmatic boundary is set to enable initial development of Web Applications and Mashups; as the project progresses an evaluation and comparison of the two paradigms may lead to a reassessment of where each can be applied within the project, with the experience gained providing a basis for general guidelines and best practice. Both Web Applications and Mashups are designed and delivered through an iterative user-centric process; requirements generated by the project case studies are a key element of this approach

From global observations to local information: The Earth Observation Monitor

Earth Observation (EO) data are available around the globe and can be used for a range of applications. To support scientists and local stakeholders in the usage of information from space, barriers, especially in data processing, need to be reduced. To meet this need, the software framework Earth Observation Monitor provides access and analysis tools for global EO vegetation time-series data based on standard-compliant geo-processing services. Data are automatically downloaded from several data providers, processed, and time-series analysis tools for vegetation analyses extract further information. A web portal and a mobile application have been developed to show the usage of interoperable geospatial web services and to simplify the access and analysis of global EO time-series data. All steps from data download to analysis are automated and provided as operational geo-processing services. Open-source software has been used to develop the services and client applications

Probabilistic uncertainty in an interoperable framework

This thesis provides an interoperable language for quantifying uncertainty using probability theory. A general introduction to interoperability and uncertainty is given, with particular emphasis on the geospatial domain. Existing interoperable standards used within the geospatial sciences are reviewed, including Geography Markup Language (GML), Observations and Measurements (O&M) and the Web Processing Service (WPS) specifications. The importance of uncertainty in geospatial data is identified and probability theory is examined as a mechanism for quantifying these uncertainties. The Uncertainty Markup Language (UncertML) is presented as a solution to the lack of an interoperable standard for quantifying uncertainty. UncertML is capable of describing uncertainty using statistics, probability distributions or a series of realisations. The capabilities of UncertML are demonstrated through a series of XML examples. This thesis then provides a series of example use cases where UncertML is integrated with existing standards in a variety of applications. The Sensor Observation Service - a service for querying and retrieving sensor-observed data - is extended to provide a standardised method for quantifying the inherent uncertainties in sensor observations. The INTAMAP project demonstrates how UncertML can be used to aid uncertainty propagation using a WPS by allowing UncertML as input and output data. The flexibility of UncertML is demonstrated with an extension to the GML geometry schemas to allow positional uncertainty to be quantified. Further applications and developments of UncertML are discussed

Evaluation ofWeb Processing Service Frameworks

As geoprocessing on the web has matured in recent years, an increasing number of geoprocessing services and functionality are becoming available in the form of online Web Processing Services (WPS). Consequently, the quality of such geoprocessing services is of importance to ensure that WPS instances fulfill users’ expectations. In this paper, we illustrate, and discuss initial results from a quantitative analysis of the performance of WPS servers. To do so, we used two test scenarios to measure response time, response size, throughput, and failure rate of five WPS servers including 52 Degree North, Deegree, GeoServer, Py- WPS, and Zoo. We also assess each WPS server in terms of qualitative metrics such as software architecture, perceived ease of use, flexibility of deployment, and quality of documentation. A case study addressing accessibility assessment is used to evaluate the relative advantages and disadvantages of each implementation, and point to challenges experienced while working with these WPS servers

Sensor web geoprocessing on the grid

Recent standardisation initiatives in the fields of grid computing and geospatial sensor middleware provide an exciting opportunity for the composition of large scale geospatial monitoring and prediction systems from existing components. Sensor middleware standards are paving the way for the emerging sensor web which is envisioned to make millions of geospatial sensors and their data publicly accessible by providing discovery, task and query functionality over the internet. In a similar fashion, concurrent development is taking place in the field of grid computing whereby the virtualisation of computational and data storage resources using middleware abstraction provides a framework to share computing resources. Sensor web and grid computing share a common vision of world-wide connectivity and in their current form they are both realised using web services as the underlying technological framework. The integration of sensor web and grid computing middleware using open standards is expected to facilitate interoperability and scalability in near real-time geoprocessing systems. The aim of this thesis is to develop an appropriate conceptual and practical framework in which open standards in grid computing, sensor web and geospatial web services can be combined as a technological basis for the monitoring and prediction of geospatial phenomena in the earth systems domain, to facilitate real-time decision support. The primary topic of interest is how real-time sensor data can be processed on a grid computing architecture. This is addressed by creating a simple typology of real-time geoprocessing operations with respect to grid computing architectures. A geoprocessing system exemplar of each geoprocessing operation in the typology is implemented using contemporary tools and techniques which provides a basis from which to validate the standards frameworks and highlight issues of scalability and interoperability. It was found that it is possible to combine standardised web services from each of these aforementioned domains despite issues of interoperability resulting from differences in web service style and security between specifications. A novel integration method for the continuous processing of a sensor observation stream is suggested in which a perpetual processing job is submitted as a single continuous compute job. Although this method was found to be successful two key challenges remain; a mechanism for consistently scheduling real-time jobs within an acceptable time-frame must be devised and the tradeoff between efficient grid resource utilisation and processing latency must be balanced. The lack of actual implementations of distributed geoprocessing systems built using sensor web and grid computing has hindered the development of standards, tools and frameworks in this area. This work provides a contribution to the small number of existing implementations in this field by identifying potential workflow bottlenecks in such systems and gaps in the existing specifications. Furthermore it sets out a typology of real-time geoprocessing operations that are anticipated to facilitate the development of real-time geoprocessing software.EThOS - Electronic Theses Online ServiceEngineering and Physical Sciences Research Council (EPSRC) : School of Civil Engineering & Geosciences, Newcastle UniversityGBUnited Kingdo

An Information Model For Exchanging Hydrological Rating Tables

Many hydrological data systems provide Internet access to observational and processed data in various forms, from websites to web services. This data is generally described with basic metadata, such as units, names of measured variables, spatial coordinates, and so on. This metadata is largely suitable for further analysis or ingestion into hydrological models. However, when the data has been processed through many – potentially complex – steps, more information is required to give users details of implicit assumptions, inaccuracies, or uncertainties that may have been introduced. A common example of this within hydrology is the use of ratings tables to derive variables such as river discharge. Rating tables are generally developed through field observations using a wide range of methods and are subject to constant revision to adapt to changes in the physical world. Extracting details of rating conversions used in any of the hydrological data repositories found on the Internet is currently either not possible or quite difficult. A contributing factor to this is the lack of standard representations for rating tables and their related concepts. This paper describes work by members of the joint World Meteorology Organisation/Open Geospatial Consortium’s Hydrology Domain Working Group on development of an internationally harmonized information model to describe rating tables, called WaterML2.0 part 2. The paper covers the core aspects of the information model, its implementation within web services, and a visualization client for web-based analysis of rating tables. An international data exchange experiment has been setup to further test the information model in a number of exchange scenarios. The results will be used to refine and progress WaterML2.0 part 2 towards an open standard for data exchange. The standard will lead to increased transparency for data derived using ratings, resulting in improved integration with models and other analytical processes

A semantic sensor web for environmental decision support applications

Sensing devices are increasingly being deployed to monitor the physical world around us. One class of application for which sensor data is pertinent is environmental decision support systems, e.g., flood emergency response. For these applications, the sensor readings need to be put in context by integrating them with other sources of data about the surrounding environment. Traditional systems for predicting and detecting floods rely on methods that need significant human resources. In this paper we describe a semantic sensor web architecture for integrating multiple heterogeneous datasets, including live and historic sensor data, databases, and map layers. The architecture provides mechanisms for discovering datasets, defining integrated views over them, continuously receiving data in real-time, and visualising on screen and interacting with the data. Our approach makes extensive use of web service standards for querying and accessing data, and semantic technologies to discover and integrate datasets. We demonstrate the use of our semantic sensor web architecture in the context of a flood response planning web application that uses data from sensor networks monitoring the sea-state around the coast of England

Geospatial Standards for Web-enabled Environmental Models

Serving geographic information via standardized Web services has been widely accepted as a useful approach. Web-enabled environmental models simulating real-world phenomena are, however, rare. The models predict observations traditionally served by geospatial Web services compliant to well-defined standards. Using standardized Web services could support decoupling of models, comparison of similar models, and the automatic integration into existing geospatial workflows. Modeling experts face several open issues when migrating existing environmental computer models to the Web. The selection of the Web service interface depends on the input parameters required for the successful execution of the computer model. Losing control over the execution of the models, and consequently also the confidence in model results, can be addressed to a certain extent by using translucent and standardized workflow languages. Mechanisms and open problems for the implementation of geospatial Web service compositions are discussed. Two scenarios about oil spills and the exposure to air pollution illustrate the impact of unconfigured model parameters for standard-compliant spatial data clients