D4.4.2.3 1st Version of the Leibniz Data Manager

This deliverable describes the first version of the Leibniz Data Manager (LDM) for NFDI4Energy. The LDM emerges as a pivotal tool in the landscape of Research Data Management (RDM), addressing the myriad challenges posed by the explosion of digital data in scientific research. With its sophisticated infrastructure, the LDM aims to enhance the organization, storage, preservation, and sharing of research digital objects (RDOs), supporting scientific integrity, transparency, and reproducibility. A core objective is to uphold the FAIR principles—namely, to ensure data is findable, accessible, interoperable, and reusable. The LDM is structured around a knowledge graph-based framework integrated with advanced neuro-symbolic AI techniques, substantially enriching metadata with semantic information and enabling federated search capabilities across diverse knowledge sources, such as Wikidata and the ORKG. This functionality allows researchers to seamlessly query interconnected datasets and RDOs, overcoming traditional barriers like metadata heterogeneity and insufficient contextualization. The entity linking capabilities further augment datasets by drawing on extensive external knowledge bases, thus enhancing data discoverability and analysis potential. The LDM offers live code execution via Jupyter notebooks, allowing for interactive data exploration and real-time analysis. This feature not only broadens the analytical scope but also enables users to visualize and interpret datasets dynamically. LDM's open-source nature ensures accessibility and adaptability, promoting a culture of collaborative research and data sharing across disciplines, thereby nurturing a globally integrated research community. As the scientific community continues to evolve in handling complex data environments, LDM exemplifies how cutting-edge technologies can support effective and reproducible research practices, leading to impactful discoveries and innovations.