Full meta objects for flexible geoprocessing workflows: profiling WPS or BPMN?

The design and execution of scientific workflows is an important and necessary function within many disciplines. In the geospatial community, workflows are used to generate and quality assure new spatial datasets based on sequences of processing steps or complex modelling. Using BPMN for representing these workflows allows stakeholders to discuss the scientific conceptual approach behind this modelling whilst also being able to execute its encoding in XML. Previous research has focused on developing frameworks, including a BPMN workflow engine, capable of orchestrating OGC Web Processing Services and thus enabling construction of interoperable workflows comprised of distributed resources. These could populate, for example, the GEOSS repository. However, to date, such work has focused on executing workflows with direct access to the pre-defined data inputs and outputs, with a lack of flexibility and efficiency in semantic interoperability or data management during composition and execution. This article suggests a meta-approach based on two possible configurations that enable workflow orchestration at a meta level using a direct coupling with a metadata catalogue. The designs of a Web Processing Service profile and of a BPMN profile are presented as potential approaches to abstract the data interchange between the processing steps of a workflow. The paper concludes with a discussion of how these approaches may be extended and how complete workflows might be registered and managed using catalogues services

A Service Chain Discovery and Recommendation Scheme Using Complex Network Theory

Service chain discovery and recommendation are significant in services composition. A complex network module based algorithm using services invocable relations is proposed to search useful service chains on the network. Furthermore, a new scheme for discovering composite services processes automatically and recommending service chains by ranking their QoS is provided. Simulations are carried out and the results indicate that some useful service chains in the dataset provided by the WSC2009 can be found by the new algorithm

Web technologies for environmental big data

Recent evolutions in computing science and web technology provide the environmental community with continuously expanding resources for data collection and analysis that pose unprecedented challenges to the design of analysis methods, workflows, and interaction with data sets. In the light of the recent UK Research Council funded Environmental Virtual Observatory pilot project, this paper gives an overview of currently available implementations related to web-based technologies for processing large and heterogeneous datasets and discuss their relevance within the context of environmental data processing, simulation and prediction. We found that, the processing of the simple datasets used in the pilot proved to be relatively straightforward using a combination of R, RPy2, PyWPS and PostgreSQL. However, the use of NoSQL databases and more versatile frameworks such as OGC standard based implementations may provide a wider and more flexible set of features that particularly facilitate working with larger volumes and more heterogeneous data sources

A provenance metadata model integrating ISO geospatial lineage and the OGC WPS : conceptual model and implementation

Nowadays, there are still some gaps in the description of provenance metadata. These gaps prevent the capture of comprehensive provenance, useful for reuse and reproducibility. In addition, the lack of automated tools for capturing provenance hinders the broad generation and compilation of provenance information. This work presents a provenance engine (PE) that captures and represents provenance information using a combination of the Web Processing Service (WPS) standard and the ISO 19115 geospatial lineage model. The PE, developed within the MiraMon GIS & RS software, automatically records detailed information about sources and processes. The PE also includes a metadata editor that shows a graphical representation of the provenance and allows users to complement provenance information by adding missing processes or deleting redundant process steps or sources, thus building a consistent geospatial workflow. One use case is presented to demonstrate the usefulness and effectiveness of the PE: the generation of a radiometric pseudo-invariant areas bench for the Iberian Peninsula. This remote-sensing use case shows how provenance can be automatically captured, also in a non-sequential complex flow, and its essential role in the automation and replication tasks in work with very large amounts of geospatial data

Building an Online Learning and Research Environment to Enhance Use of Geospatial Data

Geospatial data availability, interoperability, and integration remain a problem today. Current spatial data infrastructures (SDIs) are of limited use particularly to non-expert user communities. GeoBrain, a NASA funded project, has aimed to address those challenges, facilitate easy use of geospatial data and overcome some limitations of current SDIs through building a data-intensive, Service-oriented Architecture (SOA) based online learning and research environment. By adopting the latest developing Web services and knowledge management technologies, this online environment enables easy, open, seamless, and on-demand discovery, access, retrieval, visualization and analysis of distributed geospatial data, information, services, and models from any computer connected to the Internet. Such an online environment is able to serve the different needs of global Earth sciences research and higher education communities, bridge gaps between data user needs and provider capabilities, and greatly enhance use of geospatial data

Uncertainty analysis in the Model Web

This thesis provides a set of tools for managing uncertainty in Web-based models and workflows.To support the use of these tools, this thesis firstly provides a framework for exposing models through Web services. An introduction to uncertainty management, Web service interfaces,and workflow standards and technologies is given, with a particular focus on the geospatial domain.An existing specification for exposing geospatial models and processes, theWeb Processing Service (WPS), is critically reviewed. A processing service framework is presented as a solutionto usability issues with the WPS standard. The framework implements support for Simple ObjectAccess Protocol (SOAP), Web Service Description Language (WSDL) and JavaScript Object Notation (JSON), allowing models to be consumed by a variety of tools and software. Strategies for communicating with models from Web service interfaces are discussed, demonstrating the difficultly of exposing existing models on the Web. This thesis then reviews existing mechanisms for uncertainty management, with an emphasis on emulator methods for building efficient statistical surrogate models. A tool is developed to solve accessibility issues with such methods, by providing a Web-based user interface and backend to ease the process of building and integrating emulators. These tools, plus the processing service framework, are applied to a real case study as part of the UncertWeb project. The usability of the framework is proved with the implementation of aWeb-based workflow for predicting future crop yields in the UK, also demonstrating the abilities of the tools for emulator building and integration. Future directions for the development of the tools are discussed