Data management and heterogeneous data integration in Grid computing environments

Ensembles of distributed, heterogeneous resources, or Computational Grids, have emerged as popular platforms for deploying large-scale and resource-intensive applications. Large collaborative efforts are currently underway to provide the necessary software infrastructure. Grid computing raises challenging issues in many areas of computer science, bioinformatics, high energy physics and especially in the area of distributed computing, as Computational Grids cover increasingly large data, networks and span many organizations. In this paper we briefly motivate Grid computing and introduce its basic concepts. We then highlight a number of distributed computing research questions, and discuss both the relevance and the short-comings of research results when applied to Grid computing. We choose to focus on issues concerning the dissemination and retrieval of information from distributed networks and data integration on Computational Grid platforms. We feel that these issues are particularly critical at this time, and as we can point to preliminary ideas, work, and results in the Grid community and the distributed computing community. This paper is of interest to distributing computing researchers because Grid computing provides new challenges that need to be addressed, as well as actual platforms for experimentation and research.