Heterogeneous Relational Databases for a Grid-enabled Analysis Environment

Grid based systems require a database access mechanism that can provide seamless homogeneous access to the requested data through a virtual data access system, i.e. a system which can take care of tracking the data that is stored in geographically distributed heterogeneous databases. This system should provide an integrated view of the data that is stored in the different repositories by using a virtual data access mechanism, i.e. a mechanism which can hide the heterogeneity of the backend databases from the client applications. This paper focuses on accessing data stored in disparate relational databases through a web service interface, and exploits the features of a Data Warehouse and Data Marts. We present a middleware that enables applications to access data stored in geographically distributed relational databases without being aware of their physical locations and underlying schema. A web service interface is provided to enable applications to access this middleware in a language and platform independent way. A prototype implementation was created based on Clarens [4], Unity [7] and POOL [8]. This ability to access the data stored in the distributed relational databases transparently is likely to be a very powerful one for Grid users, especially the scientific community wishing to collate and analyze data distributed over the Grid

Integrated Solution Support System for Water Management

Solving water management problems involves technical, social, economic, political and legal challenges and thus requires an integrated approach involving people from different backgrounds and roles. The integrated approach has been given a prominent role within the European Union¿s Water Framework Directive (WFD). The WFD requires an integrated approach in water management to achieve good ecological status of all water bodies. It consists amongst others of the following main planning stages: describing objectives, assessing present state, identifying gaps between objectives and present state, developing management plan, implementing measures and evaluating their impacts. The directive prescribes broad participation and consultation to achieve its objectives. Besides the obvious desktop software, such an integrated approach can benefit from using a variety of support tools. In addition to tools for specific tasks such as numerical models and questionnaires, knowledge bases on options and process support tools may be utilized. Water stress, defined as the lack of water of appropriate quality is one issue related to, but not specifically addressed by the WFD. However, like in the WFD, a participatory approach could be used to mitigate water stress. Similarly various tools can or need to be used in such a complex process. In the AquaStress Integrated project the Integrated Solution Support System (I3S ¿ I-triple-S) is developed. One of the cornerstones of the approach taken in AquaStress is that organizing available knowledge provides sufficient information to improve the possibility to make a water stress mitigation process truly end-user driven, meaning that dedicated local information is only collected after specific need is expressed by the stakeholders in the process. The novelty of the I3S lies in the combination of such knowledge stored in knowledge-bases, with adaptable workflow management facilities and with specific task-oriented tools ¿ all originating from different sources. This paper describes the I3S

Data access and integration in the ISPIDER proteomics grid

Grid computing has great potential for supporting the integration of complex, fast changing biological data repositories to enable distributed data analysis. One scenario where Grid computing has such potential is provided by proteomics resources which are rapidly being developed with the emergence of affordable, reliable methods to study the proteome. The protein identifications arising from these methods derive from multiple repositories which need to be integrated to enable uniform access to them. A number of technologies exist which enable these resources to be accessed in a Grid environment, but the independent development of these resources means that significant data integration challenges, such as heterogeneity and schema evolution, have to be met. This paper presents an architecture which supports the combined use of Grid data access (OGSA-DAI), Grid distributed querying (OGSA-DQP) and data integration (AutoMed) software tools to support distributed data analysis. We discuss the application of this architecture for the integration of several autonomous proteomics data resources