Database evolution is a notoriously difficult task, and it is exacerbated by the necessity to evolve database-dependent applications. As science becomes increasingly dependent on sophisticated data management, the need to evolve an array of database-driven systems will only intensify. In this paper, we present an architecture for data-centric ecosystems that allows the components to seamlessly co-evolve by centralizing the models and mappings at the data service and pushing model-adaptive interactions to the database clients. Boundary objects fill the gap where applications are unable to adapt and need a stable interface to interact with the components of the ecosystem. Finally, evolution of the ecosystem is enabled via integrated schema modification and model management operations. We present use cases from actual experiences that demonstrate the utility of our approach.

The foundation of data oriented scientific collaboration is the ability for participants to find, access and reuse data created during the course of an investigation, what has been referred to as the FAIR principles. In this paper, we describe ERMrest, a collaborative data management service that promotes data oriented collaboration by enabling FAIR data management throughout the data life cycle. ERMrest is a RESTful web service that promotes discovery and reuse by organizing diverse data assets into a dynamic entity relationship model. We present details on the design and implementation of ERMrest, data on its performance and its use by a range of collaborations to accelerate and enhance their scientific output.

The pace of discovery in eScience is increasingly dependent on a scientist's ability to acquire, curate, integrate, analyze, and share large and diverse collections of data. It is all too common for investigators to spend inordinate amounts of time developing ad hoc procedures to manage their data. In previous work, we presented Deriva, a Scientific Asset Management System, designed to accelerate data driven discovery. In this paper, we report on the use of Deriva in a number of substantial and diverse eScience applications. We describe the lessons we have learned, both from the perspective of the Deriva technology, as well as the ability and willingness of scientists to incorporate Scientific Asset Management into their daily workflows.

Creating and maintaining an accurate description of data assets and the relationships between assets is a critical aspect of making data findable, accessible, interoperable, and reusable (FAIR). Typically, such metadata are created and maintained in a data catalog by a curator as part of data publication. However, allowing metadata to be created and maintained by data producers as the data is generated rather then waiting for publication can have significant advantages in terms of productivity and repeatability. The responsibilities for metadata management need not fall on any one individual, but rather may be delegated to appropriate members of a collaboration, enabling participants to edit or maintain specific attributes, to describe relationships between data elements, or to correct errors. To support such collaborative data editing, we have created ERMrest, a relational data service for the Web that enables the creation, evolution and navigation of complex models used to describe and structure diverse file or relational data objects. A key capability of ERMrest is its ability to control operations down to the level of individual data elements, i.e. fine-grained access control, so that many different modes of data-oriented collaboration can be supported. In this paper we introduce ERMrest and describe its fine-grained access control capabilities that support collaborative editing. ERMrest is in daily use in many data driven collaborations and we describe a sample policy that is based on a common biocuration pattern.

The overhead and burden of managing data in complex discovery processes involving experimental protocols with numerous data-producing and computational steps has become the gating factor that determines the pace of discovery. The lack of comprehensive systems to capture, manage, organize and retrieve data throughout the discovery life cycle leads to significant overheads on scientists' time and effort, reduced productivity, lack of reproducibility, and an absence of data sharing. In “creative fields” like digital photography and music, digital asset management (DAM) systems for capturing, managing, curating and consuming digital assets like photos and audio recordings, have fundamentally transformed how these data are used. While asset management has not taken hold in eScience applications, we believe that transformation similar to that observed in the creative space could be achieved in scientific domains if appropriate ecosystems of asset management tools existed to capture, manage, and curate data throughout the scientific discovery process. In this paper, we introduce DERIVA, a framework and infrastructure for asset management in eScience and present initial results from its usage in active research use cases.

Biomedical research depends upon increasingly high throughput instruments and sophisticated data analytics. In spite of the significant overhead of handling research data, there is little support for researchers to manage and organize data for purposes of exploration, analysis, and ultimately publication. Shared file systems with metadata coded into directory hierarchies and spreadsheets are the common practice. In this paper, we present a digital asset management approach and system for streamlining data operations and reducing data management overheads for biomedical researchers. It consists of data management tasks including storage, archival, annotation, search, cataloging, publication, and collaboration. We present a preliminary performance evaluation of a key component of the system, and we demonstrate the utility of this approach in a pilot deployment and user study.

One of the criteria for the Grid infrastructure is the ability to share resources with nontrivial qualities of service. However, sharing resources in Grids is complicated in that is requires the ability bridge the differing policy requirements of the resource owners to create a consistent cross-organizational policy domain that delivers the necessary capability to the end user while respecting the policy requirements of the resource owner. Further complicating the management of Grid resources is the need to coordinate resource usage, the diversity of resource types and the variety of different management modes that may be used. We present a unifying resource management framework in which we can address these issues. The fundamental underlying concept in this framework is the representation of various resource management activities in terms of an agreement. Agreements abstract local management policy by representing an underlying resource strictly in terms of policy terms which it is willing to assert, and in doing so provides the basis for building a variety of alternative Grid resource management strategies. We introduce the concepts of agreement based resource management. We present a general agreement model and examine current resource management systems in the context of this model. We then discuss how agreement based resource management is being used as the basis for standards activities and next generation resource management services.

We often encounter in distributed systems the need to model, access, and manage state. This state may be, for example, data in a purchase order, service level agreements representing resource availability, or the current load on a computer. We introduce two closely related approaches to modeling and manipulating state within a Web services (WS) framework: the Open Grid Services Infrastructure (OGSI) and WS-Resource Framework (WSRF). Both approaches define conventions on the use of the Web service definition language schema that enable the modeling and management of state. OGSI introduces the idea of a stateful Web service and defines approaches for creating, naming, and managing the lifetime of instances of services; for declaring and inspecting service state data; for asynchronous notification of service state change; for representing and managing collections of service instances; and for common handling of service invocation faults. WSRF refactors and evolves OGSI to exploit new Web services standards, specifically WS-addressing, and to respond to early implementation and application experiences. WSRF retains essentially all of the functional capabilities present in OGSI, while changing some syntax (e.g., to exploit WS-addressing) and also adopting a different terminology in its presentation. In addition, WSRF partitions OGSI functionality into five distinct composable specifications. We explain the relationship between OGSI and WSRF and the related WS-notification specifications, explain the common requirements that both address, and compare and contrast the approaches taken to the realization of those requirements.

Grid computing is concerned with the sharing and coordinated use of diverse resources in distributed "virtual organizations." The dynamic and multiinstitutional nature of these environments introduces challenging security issues that demand new technical approaches. In particular, one must deal with diverse local mechanisms, support dynamic creation of services, and enable dynamic creation of trust domains. We describe how these issues are addressed in two generations of the Globus Toolkit/spl reg/. First, we review the Globus Toolkit version 2 (GT2) approach; then we describe new approaches developed to support the Globus Toolkit version 3 (GT3) implementation of the Open Grid Services Architecture, an initiative that is recasting Grid concepts within a service-oriented framework based on Web services. GT3's security implementation uses Web services security mechanisms for credential exchange and other purposes, and introduces a tight least-privilege model that avoids the need for any privileged network service.

Computational grids are enabling collaboration between scientists and organizations to generate and archive extremely large datasets across shared, distributed resources. There is a need to visually explore such data throughout the life-cycle of projects. Practical exploration of large datasets requires visualization tools that can function in the same grid environment in which the data is created and stored. Resource management interfaces are an important structural component of grid computing environments because they enable uniform access to the wide variety of resources necessary for scientific work. We describe a new advance-reservation system for graphics resources; and an application of existing grid technology to create general-purpose active storage systems. We report our experience with prototype infrastructure and application components, involving experiments coupling end-to-end resources for interactive visual exploration of large data in representative distributed environments.

Grid technologies enable large-scale sharing of resources within formal or informal consortia of individuals and/or institutions: what are sometimes called virtual organizations. In these settings, the discovery, characterization, and monitoring of resources, services, and computations are challenging problems due to the considerable diversity; large numbers, dynamic behavior, and geographical distribution of the entities in which a user might be interested. Consequently, information services are a vital part of any Grid software infrastructure, providing fundamental mechanisms for discovery and monitoring, and hence for planning and adapting application behavior. We present an information services architecture that addresses performance, security, scalability, and robustness requirements. Our architecture defines simple low-level enquiry and registration protocols that make it easy to incorporate individual entities into various information structures, such as aggregate directories that support a variety of different query languages and discovery strategies. These protocols can also be combined with other Grid protocols to construct additional higher-level services and capabilities such as brokering, monitoring, fault detection, and troubleshooting. Our architecture has been implemented as MDS-2, which forms part of the Globus Grid toolkit and has been widely deployed and applied.

Applications designed to execute on "computational grids" frequently require the simultaneous co-allocation of multiple resources in order to meet performance requirements. For example, several computers and network elements may be required in order to achieve real-time reconstruction of experimental data, while a large numerical simulation may require simultaneous access to multiple supercomputers. Motivated by these concerns, we have developed a general resource management architecture for Grid environments, in which resource co-allocation is an integral component. We examine the co-allocation problem in detail and present mechanisms that allow an application to guide resource selection during the co-allocation process; these mechanisms address issues relating to the allocation, monitoring, control, and configuration of distributed computations. We describe the implementation of co-allocators based on these mechanisms and present the results of microbenchmark studies and large-scale application experiments that provide insights into the costs and practical utility of our techniques.

The development of applications and tools for high-performance "computational grids" is complicated by the heterogeneity and frequently dynamic behavior of the underlying resources; by the complexity of the applications themselves, which often combine aspects of supercomputing and distributed computing; and by the need to achieve high levels of performance. The Globus toolkit has been developed with the goal of simplifying this application development task, by providing implementations of various core services deemed essential for high-performance distributed computing. In this paper, we describe two large applications developed with this toolkit: a distributed interactive simulation and a teleimmersion system. We describe the process used to develop the applications, review the lessons learned and draw conclusions regarding the effectiveness of the toolkit approach.