1. © Geodise Project, University of Southampton, 2003. http://www.geodise.org/ Data Management in Geodise Jasmin Wason, Zhuoan Jiao and Marc Molinari Engineering design and optimisation is a computationally intensive process where data may be generated at different locations with different characteristics. Data is traditionally stored in flat files with little descriptive metadata provided by the file system. Our focus is on providing data management by leveraging existing database tools that are not commonly used in engineering and making them accessible to users of the system. The main objectives are to provide: A data management service Securely store and retrieve data files and data structures to/from a distributed repository. Technical and application specific metadata added so data is easier to search for, locate and share. Metadata management services Web services provide API access to metadata in relational and XML databases. Related data aggregated into groups. A familiar interface for engineers Work with functions and variables rather than underlying XML, SOAP, SQL, XPath, etc.

2. © Geodise Project, University of Southampton, 2003. http://www.geodise.org/ Storage service Allows applications to archive files sent over GridFTP to file systems, and store data structures as XML in databases. A location service maps logical data identities with physical storage locations. Example: Archive data: >> fileID = gd_archive('C:\input.dat'); Retrieve data: >> gd_retrieve(fileID, 'E:\tmp' ) ans = E:\tmp\input.dat Metadata service The data can be stored with additional descriptive information detailing technical characteristics (e.g. format, size, date), ownership, and user-defined application domain specific metadata. Example: Define metadata and archive file: >> m.grids = 1; >> m.turb_model = 'sa'; >> fileID = gd_archive('C:\input.dat', m); Query service Querying over the metadata database can help to locate the needed data intuitively and efficiently, using the gd_query function or query GUI. Users only receive results for data they are authorised to access. Example: >> r = gd_query('standard.userID = me & grids < 2'); >> gd_display(r): standard.userID = me standard.ID = input_dat_8a184899-ad2d-4055-aad9-a1 grids = 1 Authorisation service An authenticated user may grant other users access rights to their data and this information is stored in the authorisation database. Example: >> m.grids = 1; >> m.access.users = {'userA', 'userB'}; >> m.access.groups = {'groupC'}; >> fileID = gd_archive ('C:\input.dat', m); Geodise Database Toolbox

3. © Geodise Project, University of Southampton, 2003. http://www.geodise.org/.NET Authorisation Service Location Service Java Metadata Archive & Query Services Data Management Implementation To increase the usability of file and metadata management services for engineers we have implemented a MATLAB Toolbox for archiving, querying and retrieval of data to and from a Geodise repository. Matlab Functions Java clients Globus Server Geodise Database Toolbox Metadata Database Client Grid Authorisation Database CoG Apache SOAP Location Database Refers to SOAP GridFTP

4. © Geodise Project, University of Southampton, 2003. http://www.geodise.org/ XML Toolbox Enables the conversion of Matlab variables and structures from proprietary format to XML and vice versa in transparent, easy-to-use way. The XML can then be transferred, stored, and retrieved across the Grid. Four functions: xml_save(), xml_load(), xml_format(), xml_parse() The XML Toolbox developed by the GEM project. Application of the XML Toolbox in Geodise.

5. © Geodise Project, University of Southampton, 2003. http://www.geodise.org/ Future Work Categorisation of metadata based on XML Schemas XML Schemas can be generated to describe user-defined metadata. Changes are made over time to metadata about a design. Use comparison and merge tool to detect changes and alter XML Schema. XML Schema work may include future integration of ontologies. Web query interface Auto generation of query interface based on XML Schemas. User certificate required for authentication. Computational steering with shared Matlab variables Temporary shared storage and update of Matlab variables. XML Toolbox Ability to read most XML files and convert these into Matlab struct variables and vice versa. Infrastructure Improved Web Service security and use of OGSA-DAI. Jython implementation of client toolbox.