RESUMO
A collaborative environmental eScience project produces a broad range of data, notable as much for its diversity, in source and format, as its quantity. We find that extensible markup language (XML) and associated technologies are invaluable in managing this deluge of data. We describe Fo X, a toolkit for allowing Fortran codes to read and write XML, thus allowing existing scientific tools to be easily re-used in an XML-centric workflow.
Assuntos
Sistemas de Gerenciamento de Base de Dados/tendências , Bases de Dados Factuais/tendências , Ecologia/métodos , Armazenamento e Recuperação da Informação/tendências , Internet , Minerais/química , Modelos Químicos , Software , Simulação por Computador , Ecologia/tendências , Disseminação de Informação/métodos , Interface Usuário-ComputadorRESUMO
We describe RMCS as one of the first tools for grid computing that integrates data and metadata management into a single job submission system. The system is easy to use, with client tools that are easy to install. Although the RMCS system was developed as a prototype, it is now in production use and a number of scientific studies have been completed using it.
Assuntos
Comportamento Cooperativo , Sistemas de Gerenciamento de Base de Dados/tendências , Bases de Dados Factuais/tendências , Ecologia/métodos , Armazenamento e Recuperação da Informação/tendências , Internet , Modelos Teóricos , Software , Simulação por Computador , Ecologia/tendências , Disseminação de Informação/métodos , Integração de Sistemas , Interface Usuário-ComputadorRESUMO
We review the work carried out within the eMinerals project to develop eScience solutions that facilitate a new generation of molecular-scale simulation work. Technological developments include integration of compute and data systems, developing of collaborative frameworks and new researcher-friendly tools for grid job submission, XML data representation, information delivery, metadata harvesting and metadata management. A number of diverse science applications will illustrate how these tools are being used for large parameter-sweep studies, an emerging type of study for which the integration of computing, data and collaboration is essential.