Leibniz Data Manager - A tool to search and explore digital artefacts across different repositories and evaluate their potential for re-use

可重复性确保以最小的努力验证科学发现。然而，科学数字制品，例如数据和计算方法，需要是可找到和可访问的，才能使用。有了这个建议，我们引入并开发了一个工具，它可以显著提高研究数据和其他科学制品的可查找性和利用率，即莱布尼茨数据管理器(LDM)。LDM将使研究人员能够基于其元数据在多个数字存储库中搜索和筛选数据集和其他科学制品，并探索它们与自己研究的相关性。对于信息基础设施提供商，LDM将基于可扩展和可适应的DCAT词汇表框架，通过语义连接现有数据目录和存储库，提供数据对象“展示案例”。目前，科学数据存储库的生态系统包括各种可用的类别和类型：特定于学科的存储库、跨学科的存储库、机构存储库以及它们的混合体。这种异构性带来了数据和元数据标准、API、文件格式、许可证信息、归档和出版指南、重用条款等方面的巨大差异。这也是为什么跨多个存储库的搜索被认为是希望重复使用数据但不确定在哪里查找的研究人员要执行的一项耗时的任务。通过这项提议，我们针对的是研究机构、基础设施、大学和公司之间共享的互操作性挑战，并将提供一个简单、小规模和开放的软件分发，它可以以一种方式连接数字存储库，使数据集和其他科学制品留在各自的存储库中，而LDM提供这些存储库存档的数据集的综合视图。因此，LDM-Explore项目将提供一个工具，帮助从以出版物或文章为基础的研究工作流程过渡到以信息为基础(关联数据)的研究工作流程。这将通过进一步开发基于CKAN的软件分发来实现，该软件分发允许使用DCAT等现有语义工具来将元数据标准映射到语义词汇表，从而允许跨数字存储库的元数据和数据的“深度索引”方法。这将通过连接来自不同类别的三个试点存储库来显示。有了这项技术，科学家将能够拥有一个简单、直观的用户界面，帮助他们在连接的存储库中搜索相关和相关的数据集，筛选相关数据，并最终朝着科学的重现性又迈进一步。

Reproducibility ensures the validation of scientific findings with minimal effort. However, scientific digital artefacts, e.g., data and computational methods, need to be findable and accessible in order to be used. With this proposal, we introduce and develop a tool which significantly increases the findability and exploitation of research data and other scientific artefacts, the Leibniz Data Manager (LDM). The LDM will enable researchers to search and screen for data sets and other scientific artefacts across multiple digital repositories based on their metadata and explore their relevance for their own research. For information infrastructure providers the LDM will offer data object ‘showcases’ by semantically connecting existing data catalogs and repositories, based on the extendable and adaptable DCAT vocabulary framework. At present, the ecosystem of scientific data repositories consists of a large variety of available categories and types: Discipline specific repositories, interdisciplinary repositories, institutional repositories, and mixtures thereof. With this heterogeneity comes large variation in terms of data and metadata standards, APIs, file formats, licence information, archival- and publication guidelines, terms of re-use, and others. This is also the reason why a search across multiple repositories is considered a time consuming task to be carried out by researchers who want to re-use data, but are unsure where to look for it. With this proposal, we target interoperability challenges that are shared among research institutes, infrastructures, universities and companies and will offer a simple, small-scale and open software distribution which can connect digital repositories in a way such that data sets and other scientific artefacts will stay in their respective repositories, with the LDM providing an integrated view of the data sets archived by these repositories. As such, the LDM-Explore project will provide a tool which can aid in the transition from a publication- or article-based to an information-based (linked-data) research workflow. This will happen by further developing a CKAN-based software distribution that allows for a method which is called ‘deep indexing’ of metadata and data across digital repositories, using the existing semantic tools like DCAT to map metadata standards to semantic vocabularies. This will be shown by connecting three pilot repositories from different categories. With this technology in place, scientists will be able to have a simple, intuitive user interface helping them to perform a search for relevant and related datasets across the connected repositories, screen for relevant data and ultimately take another step towards the reproducibility of science.