Database systems were a solution to the problem of shared access to heterogeneous files created by multiple autonomous applications in a centralized environment. To make data usage easier, the files were replaced by a globally integrated database. To a large extent, the idea was successful, and many databases are now accessible through local and longhaul networks. Unavoidably, users now need shared access to multiple autonomous databases. The question is what the corresponding methodology should be. Should one reapply the database approach to create globally integrated distributed database systems or should a new approach be introduced?We argue for a new approach to solving such data management system problems, called multidatabase or federated systems. These systems make databases interoperable, that is, usable without a globally integrated schema. They preserve the autonomy of each database yet support shared access.Systems of this type will be of major importance in the future. This paper first discusses why this is the case. Then, it presents methodologies for their design. It further shows that major commercial relational database systems are evolving toward multidatabase systems. The paper discusses their capabilities and limitations, presents and discusses a set of prototypes, and, finally, presents some current research issues.

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The Earth System Curator is a National Science Foundation sponsored project developing a metadata formalism for describing the digital resources used in climate simulations. The primary motivating observation of the project is that a simulation/model's source code plus the configuration parameters required for a model run are a compact representation of the dataset generated when the model is executed. The end goal of the project is a convergence of models and data where both resources are accessed uniformly from a single registry. In this paper we review the current metadata landscape of the climate modeling community, present our work on developing a metadata formalism for describing climate models, and reflect on technical challenges we have faced that require new research in the area of Earth Science Informatics.Keywords Climate data portal . Climate modeling . world. To be successful, these projects must be able to access datasets generated at different modeling centers and moreover, the datasets themselves must exhibit a level of uniformity that enables integration and intercomparison. Such uniformity can be achieved by making datasets available in common data formats and adhering to formal metadata conventions.To that end, one of the goals of the NSF-sponsored Earth System Curator project (DeLuca et al. 2005) is to develop a metadata formalism for describing the digital resources used in climate simulations. The primary motivating observation of the project is that a model's source code plus the configuration parameters required for a model run are a compact representation of the dataset generated when the model is executed. This observation implies that a comprehensive description of a climate model run is a complete and accurate description of the dataset produced by the model. Despite this connection between models and datasets, the climate community is currently treating the two resources as distinct entities. Those providing data infrastructure (e.g., data portals, search interfaces, retrieval mechanisms) typically begin addressing datasets only after they have been generated, ignoring the steps of the modeling process that led up to the generated dataset. Meanwhile, those providing modeling infrastructure are building tools to facilitate the enormously complex processes of development, assembly, and execution of model codes. But, despite the complexity involved in configuring a model run, the typical output dataset used for analysis is annotated with only a limited amount of metadata (e.g., standard field names, units, horizontal and vertical dimensions). This is an enormous disadvantage for those trying to discover or analyze a dataset based on properties of the original model, and this is the key issue that Curator attempts to address.The Curator project seeks to blur the line between models and datasets on the premise that a detailed description of a model run is the basis for generating the dataset. The end goal is a convergence of models and data where both kinds of resources can be ac...

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