Our group has been working with different aspects of distributed and parallel processing of databases in relational, object-oriented, and XML data models. Classic techniques for distributed design and query processing in relational database systems have been revisited to address dynamic issues in high performance computing and flexibility challenges of XML documents.
More recently, large-scale scientific data combined with process activities management have introduced challenges to the database and software engineering communities, among several other computer science research areas. Regarding scientific data, challenges are the heterogeneous data formats that encompass relational, XML, binary, and flat files.
Our group has been addressing these challenges by capitalizing on our extensive experience in distributed data management. Since each scientific experiment tends to produce and manage its own data, in specific formats, with its own activities (and programs), managing large scale distributed data and activities gets difficult as the amount of heterogeneous data grows.
Keywords: database clusters; distribution; distributed query processing; provenance data management; scientific data processing; parallel databases; scientific workflows
You can get more specific information about our research group on:
[link] MATTOSO, M. ; BRAGANHOLO, V. ; LIMA, A. ; MURTA, L. . Distributed Database Research at COPPE/UFRJ. Brazilian Computer Society Special Interest Group on Databases. Vol 2, No 2, 2011.