9 Geostatistical mapping can be defined as analytical production of maps by using field observations, auxiliary 10 information and a computer program that calculates values at locations of interest. The purpose of this guide 11 is to assist you in producing quality maps by using fully-operational open source software packages. It will first 12 introduce you to the basic principles of geostatistical mapping and regression-kriging, as the key prediction 13 technique, then it will guide you through software tools — R+gstat/geoR, SAGA GIS and Google Earth — 14 which will be used to prepare the data, run analysis and make final layouts. Geostatistical mapping is further 15 illustrated using seven diverse case studies: interpolation of soil parameters, heavy metal concentrations, 16 global soil organic carbon, species density distribution, distribution of landforms, density of DEM-derived 17 streams, and spatio-temporal interpolation of land surface temperatures. Unlike similar books from the “use 18 R” series, or purely GIS user manuals, this book specifically aims to bridge the gap between statistical and 19 geographical computing. Materials presented in this book have been used for the five–day advanced training 20 course “GEOSTAT: spatio-temporal data analysis with R+SAGA+Google Earth”, that is periodically organized 21 by the author and collaborators. Visit the book’s homepage to obtain a copy of the data sets and scripts used 22 in the exercises. 23 This is an Open Access Publication! 24

A Practical Guide to Geostatistical Mapping

The paper discusses the GOLD project (Grid-based Information Models to Support the Rapid Innovation of New High Value-Added Chemicals) whose principal aim is to carry out research and development into enabling technologies to support the formation, operation and termination of virtual organizations. The paper discusses the outcome of this research, which is the GOLD Middleware infrastructure. The infrastructure has been implemented in the form of a set of Middleware components, which address issues such as trust, security, contract monitoring and enforcement, information management and coordination. We discuss all these issues in turn and more importantly we demonstrate how current WS standards can be used to implement these issues. In addition, the paper follows a top down approach starting with a brief outline on the architectural elements derived during the requirements engineering phase and demonstrates how these elements were mapped onto actual services that were implemented according to service-oriented architecture principles and related technologies. Copyright © 2008 John Wiley & Sons, Ltd.

GOLD infrastructure for virtual organizations

Virtual Research Environments are innovative, web-based, community-oriented, comprehensive, flexible, and secure working environments conceived to serve the needs of modern science. We overview the existing initiatives developing these environments by highlighting the major distinguishing features. We envisage a future where regardless of geographical location, scientists will be able to use their Web browsers to seamlessly access data, software, and processing resources that are managed by diverse systems in separate administration domains via Virtual Research Environments. We identify and discuss the major challenges that should be resolved to fully achieve the proposed vision, i.e., large-scale integration and interoperability, sustainability, and adoption.

/pdf/virtual-research-environments-an-overview-and-a-research-2zdb6ei3pw.pdf

Virtual Research Environments: An Overview and a Research Agenda

The Geoprocessing Web

Virtual Research Environment Collaborative Landscape Study

We investigate the requirements of Scientific Workflows in context of the Business Process Execution Language for Web Services (BPEL4WS/ BPEL. The complexity, unpredictability and inter-dependency of the components in a scientific workflow often demand flexibility in a workflowlanguage in order to support; 1) exception handling, 2) recovery from uncertain situations, 3) user interactions to facilitate interactive steering and monitoring, 4) dynamism to adapt to the changing environment, 5) compensation handling to roll back, and 6) support for dynamic selection of services. We illustrate these requirements with examples taken from a real scientific workflow; the e-HTPX project for high throughput protein crystallography. In this paper, we discuss the application of BPEL, which is widely regarded as the de-facto standard for orchestrating Web Services for Business Workflows with a large set of features to support complex requirements. These features, along with other standard tools, can be adapted to fulfill the requirements of Scientific Workflows.

Evaluation of BPEL to Scientific Workflows

SUMMARY The Sakai Project (http://www.sakaiproject.org) is developing a collaborative environment that provides capabilities that span teaching and learning as well as e-Research applications. By exploiting the significant requirements overlap in the collaboration space between these areas, the Sakai community can harness significant resources to develop an increasingly rich set of collaborative tools. While collaboration is a significant element of many e-Research projects, there are many other important elements including portals, data repositories, compute resources, special software, data sources, desktop applications, and content management/e-Publication. The successful e-Research projects will find ways to harness all of these elements to advance their science in the most effective manner. It is critical to realize that there is not a single software product that can meet the requirements for such a rich e-Research effort. Realizing that multiple elements must be integrated together for best effect leads us to focus on understanding the nature of integration and working together to improve the cross-application integration. This leads us not to drive towards a single toolkit (such as Sakai or Globus), but instead to a meta-toolkit containing well-integrated applications. When considering a technology for use, perhaps the most important aspect of that technology is how well it integrates with other technologies. Copyright c � 2007 John Wiley & Sons, Ltd.

/pdf/using-the-sakai-collaborative-toolkit-in-e-research-4kpoolzwxq.pdf

Using the Sakai collaborative toolkit in e‐Research applications

Introduction Motivation and requirements Creating and using research data Managing and using digital information Collaboration, trust and security Domain differences and usability VRE architecture: the technology E-infrastructure and grid resources Desktop environments and the web Desktop environments and the web Example 1: E-infrastructure for social science research Example 2: E-infrastructure for experimental facilities Conclusions: lessons learned and limitations.

Virtual research environments : from portals to science gateways

Increasingly, understanding complex problems in computational chemistry requires the
use of several applications as components of computational workflows. Unfortunately,this process is severely hindered by a lack of data interchange standards. The eCCP and
eMinerals UK eScience projects are developing a framework to facilitate the interoperability of such applications. Data sets are serialised in a way that conforms to
existing XML languages, including the Chemical Markup Language, and collaboratively designed extensions. Various methods are used to express relationships between data
sets, based on the XLink standard. Explicit semantics are associated to data sets by mappings to concepts specified in OWL ontologies. 

These mappings make use of RDF
and XPointer standards and enable the users of framework data to work with its logical structure. This provides a number of advantages, including the ability to work with data that conforms to differing data models. Framework tools are under development that will enable the manipulation of such data, being designed with an emphasis on easy integration into the current working practices of computational communities, such as the UK’s Collaborative Computational Projects.

Towards data integration for computational chemistry

This paper presents work undertaken to integrate the future UK national Shibboleth infrastructure with the UK's National Grid Service (NGS). Our work, ShibGrid, provides both transparent authentication for portal based Grid access and a credential transformation service for users of other Grid access methods. The ShibGrid support for portal-based transparent Grid authentication is provided as a set of standards-based drop-in modules which can be used with any project portal as well as the NGS project in which they are initially deployed. The ShibGrid architecture requires no changes to the UK national Shibboleth authentication infrastructure or the NGS security infrastructure and provides access for users both with and without UK e-Science certificates. In addition to presenting both the architecture of Shib- Grid and its implementation, we additionally place the ShibGrid project within the context of other efforts to integrate Shibboleth with Grids.

ShibGrid: Shibboleth Access for the UK National Grid Service

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