A mediation approach in Geospatial Web services gridification

The Geospatial data has been used extensively in many scientific areas but a lot of issues arise for sharing and processing such large amount of data. The geospatial data is exposed most of the time using geospatial Web services, standardized by the Open Geospatial Consortium (OGC). In this paper we discuss solutions and approaches, based on the integration of OGC Web services into the Grid environment, for solving those problems in the context of enviroGRIDS project. The interoperability between the OGC and Grid technologies is promising in solving important challenges in Earth Observation (EO) environment and is discussed at different levels in the project architecture: data level, execution/processing level and portal level.

Currently, increasingly large number of Geospatial Web Services are being built in Spatial Data Infrastructures (SDIs). Although services make it easy for users to access desired information, the quality of Geospatial Web Services will greatly affect the willingness of users in access of these services. Therefore, in order to improve the use of service-oriented architecture for distributed geospatial data sharing, proper measurement of the Geospatial Web Service quality is highly valuable. In this paper, we propose to evaluate Geospatial Web Service quality from Geospatial Web Service activities and Geospatial Service usage. The Geospatial Web Service activities contain four layers: Geospatial Web Service commitment, Geospatial Web Service description, Geospatial Web Service process, and Geospatial Web Service outcome layers. To measure Geospatial Web Service quality score, we consider both objective measurement and subjective measurement. Objective measurement is generated from the comparison of actual service performance with application requirements. Subjective measurement determines users' attitudes towards the consumption of services. In conclusion, this study brings new perspective in evaluating Geospatial Web Services in SDIs. It provides a solution to calculate the Geospatial Web Service quality score from both objective and subjective measurement.

Geospatial web services within a scientific workflow: Predicting marine mammal habitats in a dynamic environment

Spatial Data Infrastructures often maintain directories of public geospatial Web Services built from Web services listed in their registries. However, registry data may be stale and incomplete because their maintenance depends on service owners. A solution is to back the registry with an active directory, or index, that lists Web services found by a Web crawler focused on geospatial Web services. The problem of the identification of the geospatial nature of a Web service appears when such crawler finds a service described in the Web Services Description Language (WSDL). This paper presents two components required to build an active directory: a crawler focused on Open Geospatial Consortium and WSDL-based Web services, and an unsupervised classifier of geospatial Web services described in WSDL.

The use of standards in the geospatial domain, such as those defined by the Open Geospatial Consortium (OGC), for exchanging data has brought a great deal of interoperability upon which systems can be built in a reliable way. Unfortunately, these standards are becoming increasingly complex, making their implementation an arduous task. The use of appropriate software metrics can be very useful to quantify different properties of the standards that ultimately may suggest different solutions to deal with problems related to their complexity. In this regard, we present in this article an attempt to measure the complexity of the schemas associated with the OGC implementation specifications. We use a comprehensive set of metrics to provide a multidimensional view of this complexity. These metrics can be used to evaluate the impact of design decisions, study the evolution of schemas, and so on. We also present and evaluate different solutions that could be applied to overcome some of the problems associated with the complexity of the schemas.

Along with the unprecedented data-collecting capability, the higher algorithm accuracy and real-time application requirements, redundant spatial computing model had been implemented. Traditionally these spatial computing models are stored in different application centers. To avoid waste of resource, Grid workflow provides a powerful tool for sharing both remote sensing data and processing middleware. In order to enhance the interoperability of the heterogeneous quantitative remote sensing retrieval model in the Grid workflow environment, we propose a web service based Grid workflow framework to improve this situation. According to the Open Geospatial Consortium (OGC) and web service standards, we implement a prototype of this framework. Through the experiment, we can find that web service can work well with Grid workflow and provide a management ability of remote sensing model. Also this approach can separate the application logic and process logic, providing the interoperability ability both in application and process layers.

Motivations. In the last decade many projects related to grids have been carried out in Europe at both national and international levels with an important economic contribution by the European Commission.The grid middleware developed within these projects has been deployed into the European grid infrastructure (EGI) made by more than 350 sites all over Europe. The Italian Grid Infrastructure (IGI) is part of EGI and is one of the most important and widest national grid infrastructures in Europe since it provides about 33000 CPU cores, 17 PB of disk space and 9 PB of tape capacity spread over more than 50 sites. Although the grid infrastructure has been initially built according to the needs of a few scientific communities (high energy physics, earth observation and Bioinformatics among the others), it has been gradually evolving in order to provide grid services to a wider and wider user base. Several scientific communities are observing that as the instruments become more and more powerful the need for storage and computing is increasing day by day. This will also increase the number of users that could benefit from a geographical distributed computing grid infrastructure. Methods. In order to support new communities (users and resource providers), various activities have been started. Training has been considered very important, so tutorial for users and grid administrators are regularly organized. In addition great effort has been devoted to understanding the user needs, by defining appropriate use cases, and to supporting the user communities to port their applications on the grid environment (the so-called "gridification"). An important effort is also spent in developing new tools that could make the interaction between the final users and the grid as easy as possible. In particular web tools to submit jobs to the grid infrastructure have been deployed and used by some bioinformatics communities. In order to address the needs of users relying on high-level tools like Workflow managers (e.g. Taverna and other similar tools), a front-end web service has been developed. This web interface could be used as a bridge towards the EGI/IGI grid infrastructure. The IGI community is also providing a service that allows the exploitation of Relational Databases over the grid infrastructure, assuring a high level of security and privacy. Results. The usage of the standard EGI/IGI resources and services, together with the high level services that IGI is providing on top of the grid, has provided the end users with the capability of carrying out their high demanding computing activities in an easy and reliable way. In the past years, indeed, IGI has supported several bioinformatics communities to "gridify" many different applications such as: ASPic, PAML, MrBayes, CSTGrid, DNAfan, BLAST, BayeSSC, FT-Comar, Muscle, Gene Ontology DB analysis, ABCtoolbox, EMBOSS, Bowtie, SAMtools, Illumina Solexa data processing, AmpliconNoise, BioPython, HMMER. As a result the CPU consumed by various Italian bioinformatics groups on the IGI grid infrastructure has exceeded the 10 years in a few days of activity, thus hugely reducing the overall time needed for the execution of the jobs. Thanks to IGI the bioinformatics users have carried out their analysis in an easy and transparent way, both through simple web interfaces and through complex WorkFlow managers, reducing the time needed to get the results of about 2-3 orders of magnitude. The IGI infrastructure has also been exploited by the Computational Biology group of the Bologna University, in the frame of DUCK (Distributed Unified Computing for Knowledge, a collaboration between multidisciplinary Academic and Research Institutions located in the Emilia Romagna region), to run protein annotation application based on the Bologna Annotation Resource (BAR) method, and to perform massively parallel genome sequencing including about 18 millions of protein sequences. More than 150 computing nodes in the IGI grid infrastructure have been used, successfully dropping the computational times if compared to the computing resources of the local cluster available to the group. The protein annotation application reached a dropping factor of 120, i. e. the computation was performed in few weeks instead of years. Data management facilities offered by the Grid were also exploited to easily handle input and output files. To provide an easy-to-use service to the user communities IGI is developing a web portal that will hide the complexity of the authentication/authorization mechanisms and will also integrate the computing frameworks needed by the different user communities. A prototype of this portal can be easily set up for the bioinformatics community. Availability http://www.italiangrid.it/

A geotagged Short Message Service (SMS), such as those following Open Geospatial Consortium (OGC) Open GeoSMS (OGS) standard, is useful for many applications that require location based services field work. In OGS specification, a geotag is used as a hyperlink for retrieving detail information of given target at given location. This feature meets the interoperation requirements of time-sensitive, location-aware notification and monitoring services. This feature can give service providers to design more various and useful service scenarios, and these requirements make importantly to develop vendor specific Apps for realizing these service scenarios. A design pattern for OGS mobile client Apps will help to develop the Apps with relatively less effort. This paper focuses on a design for an OGS mobile client App and shows a Connector-Translator-Launcher (CTL) flow for smartphone environments. The CTL flow based mobile client App is based on Model-View-Controller (MVC) model. It applies pluggable modules for connecting geospatial services pointed by each geotag and translating geospatial content retrieved from such services. The App displays details information specified by a geotag following the OGS. The Android-based mobile client App was developed for OGC's OGC Web Services, Phase 8 (OWS-8). It was applied as a mobile tracking client in geospatial web service testbed scenarios for the Observation Fusion (Tracking) thread. Two pluggable modules were developed for the scenario application. One is a connector module for connecting to a track server, and another is a translator module for translating track information for displaying on map views.

Increasing availability of geo-spatial data, enabled by improvement of technologies in the field of spatial data collection, provides unprecedented opportunities in knowledge creation and distribution. Beside the integration of distributed spatial data, available in Spatial Data Infrastructures (SDIs), proper processing of data is crucial for knowledge discovery. This work proposes an ontology based spatial knowledge discovery framework based on Open Geospatial Consortium (OGC) standards. Data processing in geo-spatial domain is done using spatial clustering algorithm. It is implemented as the web processing service of this framework. Prediction of urban house price is taken as the case study.

Currently, the research work of SIG (Spatial Information Grid) technology mostly emphasizes on the spatial data sharing in grid environment, while the importance of spatial computing resources is ignored. In order to implement the sharing and cooperation of spatial computing resources in grid environment, this paper does a systematical research of the key technologies to construct Spatial Computing Node based on the WPS (Web Processing Service) specification by OGC (Open Geospatial Consortium). And a framework of Spatial Computing Node is designed according to the features of spatial computing resources. Finally, a prototype of Spatial Computing Node is implemented and the relevant verification work under the environment is completed.

This paper presents an approach to GWS (GeospatialWeb Service) discovery through the semantic annotation of WPS (Web Processing Service) service descriptions. The rationale behind this work is that search engines that use appropriate semantic-based similarity measures in the matching process are more accurate in terms of precision and recall than those based on syntactic matching alone. The lack of semantics in the description of services using a standard such as WPS prevents the use of such a matching process and is considered a limitation of GWS discovery. The GWS discovery approach presented is based on the consideration of semantics in the service description method and in the matching process. The description of services is based on a semantic lightweight meta-model instantiated in the WPS 2.0 standard, extending the description of the service through metadata tags. The matching process is performed in three steps (functionality matching step, I/O (Input/Output) matching step and non-functional matching step). Its core is a semantic similarity measure that combines logical and non-logical matching methods. Finally, the paper presents the results of an experiment applying the proposed discovery approach on a GWS corpus, showing promising results and the added value of the three-step matching process.

The development of efficient parallelization strategies for numerical simulation methods of fluid, gas and plasma mechanics remains one of the key technology challenges in modern scientific computing. The numerical models of gas and plasma dynamics based on the Navier-Stokes and electrodynamics equations require enormous computational efforts. For such cases, the use of parallel and distributed computing proved to be effective. The Grid computing environment could provide virtually unlimited computational resources and data storage, convenient task launch and monitoring tools, graphical user interfaces such as web portals and visualization systems. However, the deployment of traditional CFD solvers in the Grid environment remains very limited because basically it requires the cluster computing architecture. This study explores the applicability of distributed computing and Grid technologies for solving the weak-coupled problems of fluid, gas and plasma mechanics, including techniques of flow separation control like using plasma actuators to influence boundary layer structure. The adaptation techniques for the algorithms of coupled computational fluid dynamics and electrodynamics problems for distributed computations on grid and cloud infrastructure are presented. A parallel solver suitable for the Grid infrastructure has been developed and the test calculations in the distributed computing environment are performed. The simulation results for partially ionized separated flow behind the circular cylinder are analysed. Discussion includes some performance metrics and parallelization effectiveness estimation. The potential of the Grid infrastructure to provide a powerful and flexible computing environment for fast and efficient solution of weak-coupled problems of fluid, gas and plasma mechanics has been shown.

Abstract. Geographic information science (GIScience) education has undergone enormous changes over the past years. One major factor influencing this change is the role of the geospatial web in GIScience. In addition to the use of the web for enabling and enhancing GIScience education, it is also used as the infrastructure for communicating and collaborating among geospatial data and users. The web becomes both the means and the content for a geospatial education program. However, the web does not replace the traditional face-to-face environment, but rather is a means to enhance it, expand it and enable an authentic and real world learning environment. This paper outlines the use of the web in both the delivery and content of the GIScience program at Curtin University. The teaching of the geospatial web, web and cloud based mapping, and geospatial web services are key components of the program, and the use of the web and online learning are important to deliver this program. Some examples of authentic and real world learning environments are provided including joint learning activities with partner universities.

Flooding remains the most widely distributed natural hazard in Europe, leading to significant economic and social impact. Earth observation data is presently capable of making fundamental contributions towards reducing the detrimental effects of extreme floods. Technological advance makes development of online services able to process high volumes of satellite data without the need of dedicated desktop software licenses possible. The main objective of the case study is to present and evaluate a methodology for mapping of flooded areas based on MODIS satellite images derived indices and using state-of-the-art geospatial web services. The methodology and the developed platform were tested with data for the historical flood event that affected the Danube floodplain in 2006 in Romania. The results proved that, despite the relative coarse resolution, MODIS data is very useful for mapping the development flooded area in large plain floods. Moreover it was shown, that the possibility to adapt and combine the existing global algorithms for flood detection to fit the local conditions is extremely important to obtain accurate results.

In a service-oriented environment, an individual geospatial Web service is not sufficient to solve a complex real-world geospatial problem. Service composition, the process of chaining multiple services together, is required. Manual composition of Web services is laborious and requires much work of domain experts. Automatic service composition, if successful, will eventually widen the geospatial users market. This chapter reviews current efforts related to automatic service composition in both general information technology domain and geospatial domain. Key considerations in the geospatial domain are discussed and possible solutions are provided.