© Geodise Project, University of Southampton, Data Management in Geodise Jasmin Wason, Zhuoan Jiao and Marc Molinari 12 May 2003, Southampton Challenges Large amount of data generated by engineering applications at different locations with different characteristics. Data traditionally stored in flat files – hard to search, locate and share. Geodise Database Toolbox Store data with additional descriptive information: Standard metadata User-defined application specific metadata Use both relational and XML databases - Oracle9i, Xindice, SQL Server. Provide a familiar interface for engineers – Matlab functions.

© Geodise Project, University of Southampton, Database Toolbox - Services Storage service Archive data in file systems, sent over GridFTP. Archive Matlab structure variables as XML documents in database. Support datagroup concept to aggregate related data. Location service to map logical data identities with physical storage locations. Metadata service Descriptive information can be added to data: Standard technical metadata (e.g. file size, format, date): mostly auto-generated. Application specific metadata: user defined. Query service Query over metadata to efficiently locate required data. Command-line and GUI interfaces. Authorisation service Access rights to data can be granted to authenticated users.

© Geodise Project, University of Southampton, Database Toolbox – Client Tools Archive data gd_archive Store files/ structures into archive with metadata. Define datagroup gd_datagroup, gd_datagroupadd Logically group together related data. Query data gd_query Query archive from script or GUI. Retrieve data gd_retrieve Retrieve archived data to local machine.

© Geodise Project, University of Southampton, XML Toolbox Convert proprietary format to XML and vice versa transparently, easy-to-use. Benefit: XML can be transferred, stored, and retrieved across the Grid. Four functions xml_save() xml_load() xml_format() xml_parse() Matlab Variables/Structures XML