1. The Global Land Cover Facility is sponsored by NASA and the University of Maryland.The GLCF is a founding member of the Federation of Earth Science Information Partners. http://glcf.umiacs.umd.edu The Global Land Cover Facility Integrating Earth Science Data With Grid Technologies ProblemSolution Storage Resource Broker (SRB) SRB Architecture The Earth Science community generates large quantities of scientific data and being able to bring and use these data together presents a difficult challenge. Data are typically stored at many small, distributed repositories which have different access methods and query mechanisms. A typical workflow involves downloading all of the required data before processing or to work with data in iteration using small and manageable batches. By using data grid technologies, data can be viewed as belonging to one large virtual repository. Data access and retrieval is performed by referencing the data itself in a uniform namespace, independent of the data’s physical location and underlying storage format and medium. Data can be obtained from the grid when needed and services required to access the data grid can be provided through one access method. This simplifies working with data in a distributed environment. Through funding from a SEEDS grant, the University of Maryland, University of New Hampshire, and George Mason University are working together to create a data grid test-bed using the Storage Resource Broker (SRB) developed by the San Diego Supercomputer Center. Data is registered and organized in the SRB as objects and collections. Files are considered objects, the fundamental storage item. These objects then can be grouped together using collections and collections can be grouped together in another collection. In addition to these constructs, containers can be used to group together small files that should be read and written as one unit. For example, thumbnails and metadata files for a remote-sensing imagery can be placed in a container since these are typically retrieved together when requested. The figure on the left shows how Landsat satellite imagery could be organized inside the SRB. Data is registered into the SRB data grid with the MCAT server. Clients requesting data contact the MCAT to find where the needed data resides and directs the client to the appropriate SRB master. Each site with data runs an SRB master which serves data to the clients. The MCAT stores all of the necessary catalog information in database. Many popular databases are supported including Oracle, DB2, PostgreSQL, Informix, and Sybase. Data registered in the MCAT can also be loaded with relevant metadata. This allows clients to not only access data by name but also by querying and filtering against attributes. SRB masters support various native access methods to retrieve the data at each site. Data can be served transparently to the client without exposing the underlying storage--from simple filesystems to complex storage hierarchical systems like HPSS. Additional Features Parallel Transfers: Retrieval of data can be faster through the SRB as compared to traditional methods by using parallel transfers from one or many sites. Replication: Data registered can be replicated to multiple sites for reliability through redundancy or copied and moved to other sites transparent to the clients. Security: The Grid Security Infrastructure provides a common authentication mechanism and allows for granular access control on data stored in the grid. Utilities: Many utilities, such as inQ, mySRB, and the S-command suite, already exist for the input and output of data to the SRB and APIs for many of the popular languages provide solutions for custom applications. Planned Work At this time, the partners in this project have set up a basic test- bed with some minimal data registered. We plan to expand our holdings and make more data available in the current grid. The SRB has support for basic metadata information but is lacking in the storage and querying of spatial information. We plan on creating extensions to the SRB to integrate the MCAT with standard spatial database extenders such as the Informix Spatial Datablade. The GLCF also plans on modifying its current version of the Earth Science Data Interface (ESDI) to create a web-based query and download tool for all data registered in this test-bed.