15 The Open Grid Services Architecture, and data Grids Peter Z. Kunszt and Leanne P. Guy CERN,Geneva,Switzerland 15.1 INTRODUCTION Data Grids address computational and data intensive applications that combine very large datasets and a wide geographical distribution of users and resources [1, 2]. In addition to computing resource scheduling, Data Grids address the problems of storage and data man- agement, network-intensive data transfers and data access optimization, while maintaining high reliability and availability of the data (see References [2, 3] and references therein). The Open Grid Services Architecture (OGSA) [1, 4] builds upon the anatomy of the Grid [5], where the authors present an open Grid Architecture, and define the technologies and infrastructure of the Grid as ‘supporting the sharing and coordinated use of diverse resources in dynamic distributed Virtual Organizations (VOs)’. OGSA extends and com- plements the definitions given in Reference [5] by defining the architecture in terms of Grid services and by aligning it with emerging Web service technologies. Web services are an emerging paradigm in distributed computing that focus on sim- ple standards-based computing models. OGSA picks the Web Service Description Lan- guage (WSDL) [6], the Simple Object Access Protocol (SOAP) [7], and the Web Service Grid Computing – Making the Global Infrastructure a Reality. Edited by F. Berman, A. Hey and G. Fox  2003 John Wiley & Sons, Ltd ISBN: 0-470-85319-0 386 PETER Z. KUNSZT AND LEANNE P. GUY Introspection Language (WSIL) [8] from the set of technologies offered by Web services and capitalizes especially on WSDL. This is a very natural approach since in the dis- tributed world of Data Grid computing the same problems arise as on the Internet concerning the description and discovery of services, and especially the heterogeneity of data [9]. In this article the application of the OGSA is discussed with respect to Data Grids. We revisit the problem that is being addressed, the vision and functionality of Data Grids and of OGSA. We then investigate OGSA’s benefits and possible weaknesses in view of the Data Grid problem. In conclusion, we address what we feel are some of the shortcomings and open issues that expose potential areas of future development and research. The European Data Grid project (EU Data Grid project) aims to build a computational and data-intensive grid to facilitate the analysis of millions of Gigabytes of data generated by the next generation of scientific exploration. The main goal is to develop an infras- tructure that will provide all scientists participating in a research project with the best possible access to data and resources, irrespective of geographical location. All the Data Grid discussion presented in this chapter draws from existing concepts in the literature, but is strongly influenced by the design and experiences with data management in the context of the EU Data Grid project [10]. In particular, data management in the EU Data Grid project has focused primarily on file-based data management [11, 12]. However, the usage of the Web services paradigm to build a Grid infrastructure was always considered in the architecture and has lead to the definition of the Web Service discovery architecture WSDA [13]. 15.1.1 The vision In this section we summarize the Data Grid problem and the vision of the Grid as presented in the literature [1, 5, 14]. 15.1.2 Desirable features of Grids In the scientific domain there is a need to share resources to solve common problems and to facilitate collaboration among many individuals and institutes. Likewise, in com- mercial enterprise computing there is an increasing need for resource sharing, not just to solve common problems but to enable enterprise-wide integration and business-to-business (B2B) partner collaboration To be successful on a large scale, the sharing of resources should be FLEXIBLE, SECURE, COORDINATED, ROBUST, SCALABLE, UBIQUITOUSLY ACCESSIBLE, MEASURABLE (QOS METRICS), TRANSPARENT TO THE USERS The distributed resources themselves should have the following qualities: INTEROPERABLE, MANAGEABLE, AVAILABLE AND EXTENSIBLE THE OPEN GRID SERVICES ARCHITECTURE, AND DATA GRIDS 387 Grid computing attempts to address this very long list of desirable properties. The concept of the Virtual Organization (VO) gives us the first necessary semantics by which to address these issues systematically and to motivate these properties in detail. 15.1.3 Virtual organizations A Virtual Organization (VO) is defined as a group of individuals or institutes who are geographically distributed but who appear to function as one single unified organization. The members of a VO usually have a common focus, goal or vision, be it a scientific quest or a business venture. They collectively dedicate resources, for which a well-defined set of rules for sharing and quality of service (QoS) exists, to this end. Work is coordi- nated through electronic communication. The larger the VO, the more decentralized and geographically distributed it tends to be in nature. The concept of the VO is not a new one; VOs have existed for many years in the fields of business and engineering, in which consortia are assembled to bid for contracts, or small independent companies temporarily form a VO to share skills, reduce costs, and expand their market access. In the commercial context, VOs may be set up for anything from a single enterprise entity to complex B2B relationships. In scientific communities such as High Energy Physics (HEP), astrophysics or medical research, scientists form collaborations, either individually or between their respective institutes, to work on a common set of problems or to share a common pool of data. The term Virtual Organization has only recently been coined to describe such collaborations in the scientific domain. VOs may be defined in a very flexible way so as to address highly specialized needs and are instantiated through the set of services that they provide to their users/applications. Ultimately, the organizations, groups and individuals that form a VO also need to pay for the resources that they access in some form or another – either by explicitly paying money for services provided by Grid service providers or by trading their own resources. Grid resource and service providers may choose to which VOs they can offer their resources and services. The models for paying and trading of resources within a VO will probably be vastly different in the scientific and business domains. In the vision of the Grid, end users in a VO can use the shared resources according to the rules defined by the VO and the resource providers. Different VOs may or may not share the same resources. VOs can be dynamic, that is, they may change in time both in scope and in extension by adjusting the services that are accessible by the VO and the constituents of the VO. The Grid needs to support these changes such that they are transparent to the users in the VO. 15.1.4 Motivation for the desirable features in Data Grids In the specific case of Data Grids, the members of a VO also share their collective data, which is potentially distributed over a wide area ( SCALABLE ). The data needs to be accessible from anywhere at anytime ( FLEXIBLE, UBIQUITOUS ACCESS ); however, the user is not necessarily interested in the exact location of the data ( TRANSPARENT ). The access to the data has to be secured, enabling different levels of security according to the needs 388 PETER Z. KUNSZT AND LEANNE P. GUY of the VO in question, while at the same time maintaining the manageability of the data and its accessibility ( SECURE, COORDINATED, MANAGEABLE ). The reliability and robustness requirements in the existing communities interested in Data Grids are high, since the computations are driven by the data – if the data are not accessible, no computation is possible ( ROBUST, AVAILABLE ). In many VOs, there is a need to access existing data – usually through interfaces to legacy systems and data stores. The users do not want to be concerned with issues of data interoperability and data conversion ( INTEROPERABLE, EXTENSIBLE ). In addition, some Data Grids also introduce the concept of Virtual Data, [15] in which data needs to be generated by a series of computations before it is accessible to the user. 15.2 THE OGSA APPROACH The OGSA views the Grid as an extensible set of Grid services. A Grid service is defined as ‘a Web service that provides a set of well-defined interfaces and that follows specific conventions’ [14]. Virtual Organizations are defined by their associated services, since the set of services ‘instantiate’ a VO. In OGSA each VO builds its infrastructure from existing Grid service components and has the freedom to add custom components that have to implement the necessary interfaces to qualify as a Grid service. We summarize the requirements that motivate the OGSA as stated in References [1, 4, 14] and the properties it provides to the Grid (see previous section for the discussion of properties) in Table 15.1. Table 15.1 Requirements mentioned in References [1, 4, 14] for OGSA. We try to map each requirement to the properties that grid systems are supposed to have on the basis of the requirements given in Section 15.2. The primary property is highlighted. An analysis of these requirements is given in the next section Requirement Property 1 Support the creation, maintenance and application of ensembles of services maintained by VOs. COORDINATED, TRANSPARENT, SCALABLE, EXTENSIBLE , MANAGEABLE 2 Support local and remote transparency with respect to invocation and location. TRANSPARENT , FLEXIBLE 3 Support multiple protocol bindings (enabling e.g. localized optimization and protocol negotiation). FLEXIBLE , TRANSPARENT, INTEROPERABLE, EXTENSIBLE, UBIQ.ACCESSIBLE 4 Support virtualization in order to provide a common interface encapsulating the actual implementation. INTEROPERABLE , TRANSPARENT, MANAGEABLE 5 Require mechanisms enabling interoperability. INTEROPERABLE , UBIQ.ACCESSIBLE 6 Require standard semantics (like same conventions for error notification). INTEROPERABLE 7 Support transience of services. SCALABLE, MANAGEABLE, AVA I L A B L E , FLEXIBLE 8 Support upgradability without disruption of the services. MANAGEABLE, FLEXIBLE , AVAILABLE THE OPEN GRID SERVICES ARCHITECTURE, AND DATA GRIDS 389 Table 15.2 Current elements of OGSA and elements that have been mentioned by OGSA but are said to be dealt with elsewhere. We also refer to the requirement or to the Grid capability that the elements address. Please be aware that this is a snapshot and that the current OGSA service specification might not be reflected correctly Responsibility Interfaces Requirements addressed Information & discovery GridService.FindServiceData Registry.(Un)RegisterService HandleMap.FindByHandle Service Data Elements Grid Service Handleand Grid Service Reference 1,2,4,5,6 Dynamic service creation Factory.CreateService 1,7 Lifetime management GridService.SetTerminationTime, GridService.Destroy 1,7 Notification NotificationSource. (Un)SubscribeToNotificationTopic NotificationSink.DeliverNotification 5 Change management CompatibilityAssertion data element 8 Authentication Impose on the hosting environment SECURE Reliable invocation Impose on hosting environment ROBUST Authorization and policy management Defer to later SECURE Manageability Defer to later MANAGEABLE As mentioned before, OGSA focuses on the nature of services that makes up the Grid. In OGSA, existing Grid technologies are aligned with Web service technologies in order to profit from the existing capabilities of Web services, including • service description and discovery, • automatic generation of client and server code from service descriptions, • binding of service descriptions to interoperable network protocols, • compatibility with higher-level open standards, services and tools, and • broad industry support. OGSA thus relies upon emerging Web service technologies to address the requirements listed in Table 15.1. OGSA defines a preliminary set of Grid Service interfaces and capa- bilities that can be built upon. All these interfaces are defined using WSDL to ensure a distributed service system based on standards. They are designed such that they address the responsibilities dealt with in Table 15.2. The GridService interface is imposed on all services. The other interfaces are optional, although there need to be many service instances present in order to be able to run a VO. On the basis of the services defined, higher-level services are envisaged such as data management services, workflow management, auditing, instrumentation and monitoring, problem determination and security protocol mapping services. This is a nonexhaustive list and is expected to grow in the future. 390 PETER Z. KUNSZT AND LEANNE P. GUY OGSA introduces the concept of Grid Service Handles (GSHs) that are unique to a service and by which the service may be uniquely identified and looked up in the Handle Map. GSHs are immutable entities. The Grid Service Reference (GSR) is then the description of the service instance in terms of (although not necessarily restricted to) WSDL and gives the user the possibility to refer to a mutable running instance of this service. OGSA envisages the possibility of a hierarchical structure of service hosting environments, as they demonstrate in their examples. Another essential building block of OGSA is the standardized representation for service data, structured as a set of named and typed XML fragments called service data elements (SDEs). The SDE may contain any kind of information on the service instance allowing for basic introspection information on the service. The SDE is retrievable through the GridService port type’s FindServiceData operation implemented by all Grid services. Through the SDE the Grid services are stateful services, unlike Web services that do not have a state. This is an essential difference between Grid services and Web services: Grid services are stateful and provide a standardized mechanism to retrieve their state. 15.3 DATA GRID SERVICES There has been a lot of effort put into the definition of Data Grid services in the existing Grid projects. Figure 15.1 shows the Global Grid Forum GGF Data Area concept space, Grid Data Management System Management metadata Subcollections Replica CatalogCollections Global namespaceLogical objects Replica Management Quality of Service Network transfer Data transport Data modelReplica MetadataPhysical objects Data Storage deviceStorage properties Storage ManagerStorage Access Protocol Storage Systems Application experiment (data source) Remote Resources ApplicationMiddleware Caching ACL/CAS AuthorizationAuthentication Security Services Figure 15.1 The concept space of the GGF data area (from the GGF data area website). THE OPEN GRID SERVICES ARCHITECTURE, AND DATA GRIDS 391 namely, their domains of interest. In this article we address the same concept space. Examples of Data Grid architectures are given in References [2, 15–21]. 15.3.1 The data In most of the existing architectures, the data management services are restricted to the handling of files. However, for many VOs, files represent only an intermediate level of data granularity. In principle, Data Grids need to be able to handle data elements – from single bits to complex collections and even virtual data, which must be generated upon request. All kinds of data need to be identifiable through some mechanism – a logical name or ID – that in turn can be used to locate and access the data. This concept is identical to the concept of a GSH in OGSA [14], so in order to be consistent with the OGSA terminology we will call this logical identifier the Grid Data Handle (GDH) (see below). The following is a nondefinitive list of the kinds of data that are dealt with in Data Grids. • Files: For many of the VOs the only access method to data is file-based I/O, data is kept only in files and there is no need for other kind of data granularity. This simplifies data management in some respect because the semantics of files are well understood. For example, depending on the QoS requirements on file access, the files can be secured through one of the many known mechanisms (Unix permissions, Access Control Lists (ACLs), etc.). Files can be maintained through directory services like the Globus Replica Catalog [3], which maps the Logical File Name (LFN) to their physical instances, and other metadata services that are discussed below. • File collections: Some VOs want to have the possibility of assigning logical names to file collections that are recognized by the Grid. Semantically there are two different kinds of file collections: confined collections of files in which all files making up the collection are always kept together and are effectively treated as one – just like a tar or zip archive – and free collections that are composed of files as well as other collections not necessarily available on the same resource – they are effectively a bag of logical file and collection identifiers. Confined collections assure the user that all the data are always accessible at a single data source while free collections provide a higher flexibility to freely add and remove items from the collection, but don’t guarantee that all members are accessible or even valid at all times. Keeping free collections consistent with the actual files requires additional services. • Relational databases: The semantics of data stored in a Relational Database Manage- ment System (RDBMS) are also extremely well understood. The data identified by a GDH may correspond to a database, a table, a view or even to a single row in a table of the RDBMS. Distributed database access in the Grid is an active research topic and is being treated by a separate article in this volume (see Chapter 14). • XML databases and semistructured data: Data with loosely defined or irregular struc- ture is best represented using the semistructured data model. It is essentially a dynami- cally typed data model that allows a ‘schema-less’ description format in which the data is less constrained than in relational databases [22]. The XML format is the standard in which the semistructured data model is represented. A GDH may correspond to any XML data object identifiable in an XML Database. 392 PETER Z. KUNSZT AND LEANNE P. GUY • Data objects: This is the most generic form of a single data instance. The structure of an object is completely arbitrary, so the Grid needs to provide services to describe and access specific objects since the semantics may vary from object type to object type. VOs may choose different technologies to access their objects – ranging from proprietary techniques to open standards like CORBA/IIOP and SOAP/XML. • Virtual data: The concept of virtualized data is very attractive to VOs that have large sets of secondary data that are derived from primary data using a well-defined set of procedures and parameters. If the secondary data are more expensive to store than to regenerate, they can be virtualized, that is, only created upon request. Additional services are required to manage virtual data. • Data sets: Data sets differ from free file collections only in that they can contain any kind of data from the list above in addition to files. Such data sets are useful for archiving, logging and debugging purposes. Again, the necessary services that track the content of data sets and keep them consistent need to be provided. 15.3.1.1 The Grid data handle GDH The common requirement for all these kinds of data is that the logical identifier of the data, the GDH, be globally unique. The GDH can be used to locate the data and retrieve information about it. It can also be used as a key by which more attributes can be added to the data through dedicated application-specific catalogs and metadata services. There are many possibilities to define a GDH, the simplest being the well- known Universal Unique IDentifier (UUID) scheme [23]. In order to be humanly readable, a uniform resource identifier (URI)-like string might be composed, specifying the kind of data instead of the protocol, a VO namespace instead of the host and then a VO-internal unique identifier, which may be a combination of creation time and creation site and a number (in the spirit of UUID), or another scheme that may even be set up by the VO. The assignment and the checking of the GDH can be performed by the Data Registry (DR) (see below). Similar to the GSH, a semantic requirement on the GDH is that it must not change over time once it has been assigned. The reason for this requirement is that we want to enable automated Grid services to be able to perform all possible operations on the data – such as location, tracking, transmission, and so on. This can easily be achieved if we have a handle by which the data is identified. One of the fundamental differences between Grids and the Web is that for Web services, ultimately, there always is a human being at the end of the service chain who can take corrective action if some of the services are erroneous. On the Grid, this is not the case anymore. If the data identifier is neither global nor unique, tracking by automated services will be very difficult to implement – they would need to be as ‘smart’ as humans in identifying the data based on its content. 15.3.1.2 The Grid data reference For reasons of performance enhancement and scalability, a single logical data unit (any kind) identified by a GDH may have several physical instances – replicas – located THE OPEN GRID SERVICES ARCHITECTURE, AND DATA GRIDS 393 throughout the Grid, all of which also need to be identified. Just like the GSH, the GDH carries no protocol or instance-specific information such as supported protocols to access the data. All this information may be encapsulated into a single abstraction – in analogy to the Grid Service Reference – into a Grid Data Reference (GDR). Each physical data instance has a corresponding GDR that describes how the data can be accessed. This description may be in WSDL, since a data item also can be viewed as a Grid resource. The elements of the GDR include physical location, available access protocols, data lifetime, and possibly other metadata such as size, creation time, last update time, created by, and so on. The exact list and syntax would need to be agreed upon, but this is an issue for the standardization efforts in bodies like GGF. The list should be customizable by VOs because items like update time may be too volatile to be included in the GDR metadata. In the OGSA context, the metadata may be put as Service Data Elements in the Data Registry. 15.3.1.3 The data registry The mapping from GDH to GDR is kept in the Data Registry. This is the most basic service for Data Grids, which is essential to localize, discover, and describe any kind of data. The SDEs of this service will hold most of the additional information on the GDR to GDH mapping, but there may be other more dedicated services for very specific kinds of GDH or GDR metadata. To give an example, in Data Grids that only deal with files – as is currently the case within the EU DataGrid project – the GDH corresponds to the LFN and the GDR is a combination of the physical file name and the transport protocol needed to access the file, sometimes also called Transport File Name (TFN) [16–18]. The Data Registry corresponds to the Replica Catalog [24] in this case. 15.3.2 The functionality and the services In this section we discuss the functionalities of Data Grids that are necessary and/or desirable in order to achieve the Data Grid vision. 15.3.2.1 VO management Virtual Organizations can be set up, maintained and dismantled by Grid services. In particular, there needs to be functionality provided for bootstrapping, user management, resource management, policy management and budget management. However, these func- tionalities are generic to all kinds of Grids, and their detailed discussion is beyond the scope of this article. Nevertheless, it is important to note that since VOs form the organic organizational unit in Grids, VO management functionalities need to be supported by all services. Some of these issues are addressed by the services for control and monitoring (see below). 15.3.2.2 Data transfer The most basic service in Data Grids is the data transfer service. To ensure reliable data transfer and replication, data validation services need to be set up. Data validation after 394 PETER Z. KUNSZT AND LEANNE P. GUY transfer is a QoS service that might not be required by all VOs. For file-based Data Grids, there is already an ongoing effort to provide a reliable file transfer service for the Grid [3]. 15.3.2.3 Data storage Data Grid storage services will be provided by many resources. There will be very prim- itive storage systems with limited functionality as well as high-level systems for data management such as RDBMSs or Storage Resource Managers [18]. All may provide high-quality Grid services, but with vast range of available functionality. The require- ments on the data store depend very much on the kind of data (see Section 15.3.1). Two common QoS additions are Resource allocation: The ability to reserve directly (through advance reservation) or indi- rectly (through quotas) sufficient space for data to be transferred to the store later. Lifetime management: The ability to specify the lifetime of the data directly (times- tamps and expiration times), or indirectly (through data status flags like permanent, durable, volatile). 15.3.2.4 Data management In all existing Data Grids, data management is one of the cornerstones of the architecture. The data management services need to be very flexible in order to accommodate the peculiarities and diverse requirements on QoS of the VOs and their peculiarities with respect to different kinds of data (see previous section) and data access. In the vision of a Data Grid, the data management services maintain, discover, store, validate, transfer and instantiate the data for the user’s applications transparently. Because of the multitude of different kinds of data, it is essential that the data can be described and validated in the Data Grid framework. In the previous section, we introduced the concept of GDHs and GDRs as well as a ser- vice for their mapping, the Data Registry. These are the core concepts of data management. In addition, we have the following data management functionalities in Data Grids: Registration of data: The first obvious functionality is to register new or existing data on the Grid. The data will receive a GDH; first instances will have to be described through their GDR, and the corresponding mappings need to be registered in the DR. This functionality may be part of the DR or set up as a separate data registration service. Materialization of virtual data: This functionality of the data management services will materialize virtual data according to a set of materialization instructions. These instructions include references to the executables and any input datasets required, as well as to any additional job parameters. All information pertaining to the materialization of virtual data [...]... Presented at Global Grid Forum, Toronto, Canada, 2001 25 Carman, M., Zini, F., Serafini, L and Stockinger, K (2002) Towards an economy-based optimisation of file access and replication on a data grid, International Workshop on Agent based Cluster and Grid Computing at International Symposium on Cluster Computing and the Grid (CCGrid 2002) Berlin, Germany: IEEE Computer Society Press THE OPEN GRID SERVICES... Deliverable 2.2, http://edms.cern.ch/document/332390 18 Shoshani, A et al (2002) SRM Joint Functional Design – Summary of Recommendations, GGF4 Informational Document Toronto 2002, http://www.zib.de/ggf/data/Docs/GGF4-PA-Arie Shoshani-SRM Joint func design .doc 19 Foster, I and Kesselman, C A Data Grid Reference Architecture, GRIPHYN-2001-12, http://www.griphyn.org/documents/document server/technical reports.html... 9 Gannon, D et al The Open Grid Services Architecture and Web Services; Chapter 9 of this book 10 EU DataGrid Data Management Workpackage WP2, http://cern.ch /grid- data-management/ 11 Guy, L., Laure, E., Kunszt, P., Stockinger, H and Stockinger, K Data Replication in Data Grids, Informational document submitted to GGF5, Replication-WG, http://cern.ch /grid- data-management/docs/ReplicaManager/ReptorPaper.pdf... Nick, J M and Tuecke, S The physiology of the grid, An Open Grid Services Architecture for Distributed Systems Integration http://www.globus.org/ogsa/, Chapter 8 of this book 15 The Griphyn Project Whitepaper, http://www.griphyn.org/documents/white paper/white paper4.html 16 Jones, B (ed.), The EU DataGrid Architecture, EDG Deliverable 12.4, http://edms.cern.ch/document/333671 17 Hoschek, W., Jaen-Martinez,... the most desirable properties of Grids OGSA does not elaborate further on QoS metrics: The Grid property MEASURABLE is not addressed by any OGSA requirement in Table 15.1 We agree that this area is fundamental to the success of Grids in general and needs to be dealt with in the very near future There needs to be not only agreed metrics of QoS, but definitions from each Grid service on how it will enhance... Data management and transfer in high performance computational grid environments Parallel Computing, 28(5), 749–771 4 Tuecke, S., Czajkowski, K., Foster, I., Frey, J., Graham, S and Kesselman, C (2002) Grid Service Specifications, February 15, 2002, http://www.globus.org/ogsa 5 Foster, I., Kesselman, C and Tuecke, S (2001) The anatomy of the grid International Journal of Supercomputer Applications, 15(3)... C., Moore, R., Rajasekar, A and Wan, M (1998) The SDSC storage resource broker Proc CASCON ’98 Conference, 1998 21 Luekig, L et al (2001) The D0 experiment data grid – SAM, Proceedings of the Second International Workshop on Grid Computing GRID2 001 Denver: Springer-Verlag, pp 177–184 22 Abiteboul, S., Buneman, P and Suciu, D (1999) Data on the Web: From Relations to Semistructured Data and XML San... the service has changed radically It is not up to the Grid to solve the issues of migrating data that has to be kept ‘forever’ to new storage technologies, but it should provide an access point that does not change over time – the GDH The GDR may also change radically, the schema of the data it 401 THE OPEN GRID SERVICES ARCHITECTURE, AND DATA GRIDS Grid registry Site1 Security Data registry Metadata... set up a security infrastructure spanning all possible protocols There needs to be a lot of effort put into this domain also from the Grid community to check how existing Grid security infrastructures might interoperate with Web service security mechanisms For Data Grids, authorization and accounting will be particularly complex for certain VOs Experience shows that global authorization schemes do... services, including Grid services, are designed such that the modules 404 PETER Z KUNSZT AND LEANNE P GUY are highly interoperable There is no uniform protocol required that each service has to speak WSDL descriptions are there to ensure interoperability The notification framework for passing messages between Grid services is addressing this property explicitly It resembles the concepts of the Grid monitoring . INTEROPERABLE, MANAGEABLE, AVAILABLE AND EXTENSIBLE THE OPEN GRID SERVICES ARCHITECTURE, AND DATA GRIDS 387 Grid computing attempts to address this very long list. definition of Data Grid services in the existing Grid projects. Figure 15.1 shows the Global Grid Forum GGF Data Area concept space, Grid Data Management