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

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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.