Gobe Hobona

Orchestration of Grid-Enabled Geospatial Web Services in Geoscientific Workflows

The need for computational resources capable of processing geospatial data has accelerated the uptake of geospatial web services. Several academic and commercial organizations now offer geospatial web services for data provision, coordinate transformation, geocoding and several other tasks. These web services adopt specifications developed by the Open Geospatial Consortium (OGC) - the leading standardization body for Geographic Information Systems. In parallel with efforts of the OGC, the Grid computing community has published specifications for developing Grid applications. The Open Grid Forum (OGF) is the main body that promotes interoperability between Grid computing systems. This study examines the integration of Grid services and geospatial web services into workflows for Geoscientific processing. An architecture is proposed that bridges web services based on the abstract geospatial architecture (ISO19119) and the Open Grid Services Architecture (OGSA). The paper presents a workflow management system, called SAW-GEO, that supports orchestration of Grid-enabled geospatial web services. An implementation of SAW-GEO is presented, based on both the Simple Conceptual Unified Flow Language (SCUFL) and the Business Process Execution Language for Web Services (WS-BPEL or BPEL for short).

Semantically-assisted geospatial workflow design

The value of service oriented architectures has been demonstrated in several studies. A key aspect of the advantage of web services is their orchestration into complex business workflows. The Organization for the Advancement of Structured Information Systems (OASIS) has recently approved an industry-wide standard for workflow specification, the Business Process Execution Language (BPEL). The Open Geospatial Consortium (OGC), a member of OASIS, has adopted BPEL for its series of interoperability experiments. This paper presents a study concerned with the use of ontology in assisting geospatial web service orchestration. A methodology for calculating the degree of suitability of various candidate workflows is proposed. The implementation of a prototype plug-in for Eclipse-based BPEL editors is discussed. The proposed system presents candidate workflows based on semantic descriptions of feature, coverage and processing services. An evaluation of the system, based on a workflow involving a variety of geospatial web services is also presented.

Multidimensional visualisation of degrees of relevance of geographic data

The ever‐increasing number of spatial data sets accessible through spatial data clearinghouses continues to make geographic information retrieval and spatial data discovery major challenges. Such challenges have been addressed in the discipline of Information Retrieval through ranking of data according to inferred degrees of relevance. Spatial data, however, present an additional challenge as they are characteristically made up of geometry, attribute and, optionally, temporal components. As these components are mutually independent of one another, this paper suggests that they be ranked independently of one another. The representation of the results of the independent ranking of these three components of spatial data suggests that representation of the results of the ranking process requires an alternative approach to currently used textual ranked lists: visualisation of relevance in a three‐dimensional visualisation environment. To illustrate the possible application of such an approach, a prototype browser is presented.

Spatially clustered associations in health related geospatial data

Overlaying maps using a desktop GIS is often the first step of a multivariate spatial analysis. The potential of this operation has increased considerably as data sources an dWeb services to manipulate them are becoming widely available via the Internet. Standards from the OGC enable such geospatial ‘mashups’ to be seamless and user driven, involving discovery of thematic data. The user is naturally inclined to look for spatial clusters and ‘correlation’ of outcomes. Using classical cluster detection scan methods to identify multivariate associations can be problematic in this context, because of a lack of control on or knowledge about background populations. For public health and epidemiological mapping, this limiting factor can be critical but often the focus is on spatial identification of risk factors associated with health or clinical status. In this article we point out that this association itself can ensure some control on underlying populations, and develop an exploratory scan statistic framework for multivariate associations. Inference using statistical map methodologies can be used to test the clustered associations. The approach is illustrated with a hypothetical data example and an epidemiological study on community MRSA. Scenarios of potential use for online mashups are introduced but full implementation is left for further research.

Ontology-Based Geospatial Approaches for Semantic Awareness in Earth Observation Systems

Current work towards making earth observation systems semantically aware attempts to improve user experience by allowing more flexibility in the way that users interact with earth observation systems. Such improvements may occur directly by making data discovery more semantically-flexible, and indirectly in providing intelligent functionality that removes some of the load from users in interpretation of data and processes. Semantic awareness in earth observation systems may be addressed from four different angles: semantics and information modelling; semantic data management; semantic data discovery and semantic data processing. Each of these areas is the subject of ongoing and developing research in the broader geospatial community, has been applied in a number of different situations and systems, and presents particular challenges for earth observation systems. The Global Earth Observation System of Systems (GEOSS) is a large, global, heterogeneous earth observation system and provides a case study of the use of different methods for achieving semantic awareness in each of these four areas. Furthermore, an example architecture for an earth observation system that involves multiple aligned ontologies illustrates the challenges posed by real world, heterogeneous systems. In combination, the review of related work, applications and challenges in each of the four areas, together with the GEOSS case study and example architecture provide an indication of the state of the art in semantic research as it applies to earth observation system. Furthermore, this summary provides a hint towards the future for semantics in earth observation systems and the need for additional work in this area.

Qualifying geospatial workflow models for adaptive controlled validity and accuracy

Sharing geospatial data and geoprocessing models within a system like GEOSS (Global Earth Observation System of Systems) is challenging to interoperability concepts and technology. Standardisation bodies, providers, researchers and policies ensure progress towards this goal. Nonetheless, the availability of these services questions the use and reuse of information resources in terms of their appropriate context, scale, sensitivity and quality. The outcome(s) delivered from a workflow chaining data and processes that were not necessarily elaborated with the implicit aim of this workflow, may vary accordingly. Decisions to modify or adapt the workflow needs to be controlled. Qualifying a workflow model with additional metadata associated with the chosen datasets and the chosen sub-models is essential to help scientists in assessing the reliability of outcomes but also to refine the corresponding GEOSS-based model. This paper investigates different approaches to control the validity of such workflow and for assessing its quality and sensitivity. A meta-model integrating metadata measures compatible with current standards is investigated.