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Mapping heterogeneous research infrastructure metadata into a unified catalogue for use in a generic virtual research environment

机译:将异构研究基础结构元数据映射到统一目录中,以用于通用虚拟研究环境

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Virtual Research Environments (VREs), also known as science gateways or virtual laboratories, assist researchers in data science by integrating tools for data discovery, data retrieval, workflow management and researcher collaboration, often coupled with a specific computing infrastructure. Recently, the push for better open data science has led to the creation of a variety of dedicated research infrastructures (RIs) that gather data and provide services to different research communities, all of which can be used independently of any specific VRE. There is therefore a need for generic VREs that can be coupled with the resources of many different RIs simultaneously, easily customised to the needs of specific communities. The resource metadata produced by these RIs rarely all adhere to any one standard or vocabulary however, making it difficult to search and discover resources independently of their providers without some translation into a common framework. Cross-RI search can be expedited by using mapping services that harvest RI-published metadata to build unified resource catalogues, but the development and operation of such services pose a number of challenges.In this paper, we discuss some of these challenges and look specifically at the VRE4EIC Metadata Portal, which uses X3ML mappings to build a single catalogue for describing data products and other resources provided by multiple RIs. The Metadata Portal was built in accordance to the e-VRE Reference Architecture, a microservice-based architecture for generic modular VREs, and uses the CERIF standard to structure its catalogued metadata. We consider the extent to which it addresses the challenges of cross-RI search, particularly in the environmental and earth science domain, and how it can be further augmented, for example to take advantage of linked vocabularies to provide more intelligent semantic search across multiple domains of discourse. (C) 2019 Elsevier B.V. All rights reserved.
机译:虚拟研究环境(VRE),也称为科学门户或虚拟实验室,通过集成用于数据发现,数据检索,工作流管理和研究人员协作的工具(通常与特定的计算基础架构结合使用)来协助数据科学领域的研究人员。最近,对更好的开放数据科学的推动导致了各种专用研究基础设施(RI)的创建,这些基础设施可以收集数据并向不同的研究社区提供服务,所有这些基础设施都可以独立于任何特定的VRE使用。因此,需要能够同时与许多不同RI的资源同时耦合,易于定制以适应特定社区需求的通用VRE。这些RI产生的资源元数据很少都遵循任何一种标准或词汇,这使得难以在不进行某种转换的情况下独立于其提供者来搜索和发现资源。可以通过使用映射服务来加速跨RI搜索,该服务会收集RI发布的元数据来构建统一的资源目录,但是此类服务的开发和运营面临许多挑战。在本文中,我们讨论了其中一些挑战,并着眼于在VRE4EIC元数据门户网站上,该门户网站使用X3ML映射来构建单个目录,以描述由多个RI提供的数据产品和其他资源。元数据门户是根据e-VRE参考体系结构构建的,该体系结构是用于通用模块化VRE的基于微服务的体系结构,并使用CERIF标准来构造其分类的元数据。我们考虑了它在多大程度上解决了跨RI搜索的挑战,特别是在环境和地球科学领域,以及如何进一步扩展它,例如,利用链接的词汇来跨多个域提供更智能的语义搜索话语。 (C)2019 Elsevier B.V.保留所有权利。

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