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Presentation given at the DHd2023 conference about the current state, next steps and future plans for data integration and data federation based on the NFDI4Culture Knowledge Graph. Also featuring details on the latest developments around the Culture Ontology and the Culture Graph Interchange Format (CGIF)., Funded by the German Research Foundation (DFG) – 441958017 (NFDI4Culture)

Proposal for the consortium for the for the historically oriented humanities in the German national research data infrastructure (Nationale Forschungsdateninfrastruktur, “NFDI”). The application contains the scope and objectives, the composition and governance of the consotrium as well as the research data management strategy and the originally proposed work programme. NFDI4Memory aims to establish systematic, sustainable links between research, memory institutions and infrastructures; to integrate historical source criticism into data management; to build a network of the historically oriented research communities; to shape the knowledge order for the digital future of the past; to advance the analog / digital interface of historical source material and data; to generate standards for historical research data and sustainability; and to contribute to education and citizen participation.

Slides of the short paper presented at Qurator 2022.

Presentation for NFDI InfraTalk: »Wikibase and the challenges and possibilities for RDM in NFDI4Culture«, organised by NFDI e.V., March 7, 2022. The NFDI InfraTalk series invitesscientists from different disciplines to present exciting topics around NFDI and research data management. In the March 2022 edition of the series, Prof. Dr. Ina Blümel, Dr. Lozana Rossenova andPaul Duchesne (TIB Hannover), andProf. Dr. Harald Sack (FIZ Karlsruhe) delivered two presentations on thetopic of "Wikibase and the challenges and possibilities of knowledge graphs for RDM in NFDI4Culture". These are the slides presented by Harald Sack @ FIZ Karlsruhe. The slides presented by the TIB team are available here: https://doi.org/10.5281/zenodo.6359283 Date: March 07, 2022 Recording of the InfraTalk on YouTube: https://www.youtube.com/watch?v=RPMkuDxHJtI &nbsp

The necessity and potential of systematic archiving and publication of digital research data is currently a hot topic in the scientific landscape, due to various benefits such as ensuring reproducibility of research results and providing the basis for data-driven science. This requires measures to ensure data quality and particularly a documentation of stored data by means of metadata, which is understandable to both humans and machines. Machine-actionable metadata is not only important for findability and interoperability of the data but also enables automated data processing. This contribution introduces a workflow for data and metadata, which uses programmatic data aggregation, electronic lab notebooks, ontology-based metadata, and blockchain protocols for partly automated processing and documentation of raw data as well as quality assured data publication, respectively. The practical relevance of the suggested (meta)data workflow is demonstrated at the example of highly resolved current measurements for pulsed dielectric barrier discharges in a nitrogen-oxygen gas mixture., This work was supported by the BMBF under grants 16QK03A, 16QK03B, 16QK03C and the DFG under grant 408777255.

We propose a management infrastructure for research data specially designed for plasma medicine and adjacent fields (low temperature plasma science). Systematically archiving and publishing data has become an increasingly important part of research. This often follows the idea of FAIR (Findable, Accessible, Interoperable, and Reusable) data [1]. We currently build a system that accompanies the researcher from planning the experiment through its execution to saving, publishing, and reusing of the originating data with meaningful metadata. The goal is to use a knowledge graph that the community of plasma scientists continuously augments and maintains. This knowledge graph is used to help researchers in finding the metadata that is necessary for each individual experiment. It will also be linked to knowledge graphs of other fields to increase interoperability across different fields of research and therefore the visibility of plasma research. This gives credit to the multitude of research methods used in this field. The knowledge graph provides options to define quality criteria, which ensure the findability and reusability of published data. As a first step towards this goal, we developed the data platform INPTDAT (https://www.inptdat.de/) to upload research data in a structure that is adapted to plasma research data. This structure follows the general plasma metadata schema, Plasma-MDS, which has been published recently [2] (see Fig. 1). Data published on INPTDAT and described by using Plasma-MDS can easily be found and cited by the owner as well as other researchers using its unique DOI (digital object identifier). The use of blockchain technology is another part of the intended infrastructure to make the publishing and citing of data safer and traceable. In the future, this system can also allow reputation monitoring. Together, these systems will support data exchange and thus enhance data-driven science in plasma medicine and beyond. References [1] M. D. Wilkinson, et al., Sci. Data, 3, 160018 (2016). [2] S. Franke, L. Paulet, J. Schäfer, D. O'Connell, and M. M. Becker, Sci. Data, 7, 439 (2020)., The Federal Ministry of Education and Research (BMBF) has supported this work under the grant marks 16QK03A, 16QK03B, and 16QK03C.

This document includes the complete list and descriptions of the Participant Projects (PPs) and related Infrastructure-Use-Cases (IUCs) the consortium NFDI-MatWerk referred to within its proposal. For the NFDI-MatWerk proposal, refer to https://doi.org/10.5281/zenodo.5082837. Methodically, the consortium proceeded by identifying so-called Participant Projects within its research community. PPs represent the heterogeneity of this research domain in all its facets. They usually face diverse but recurring challenges in the context of research data management from a user or scientist's perspective. Such challenges, resulting from the PPs, were accumulated to shape the so-called Infrastructure-Use-Cases (IUCs). For this end, the consortium identified recurring technological user needs from the PPs and isolated them into individually necessary functionalities of the aimed research data management infrastructure for NFDI-MatWerk. The consortium plans to reiterate this process as the project starts, to manage a continuous integration and feedback-loop from a strict user-centered perspective and thus ensure relevance of the developed solutions. For more information on the consortium NFDI-MatWerk refer to www.nfdi-matwerk.de. For questions about this method, refer to the contacts listed under www.nfdi-matwerk.de/kontakt/.

The field of Materials Science is concerned with, e.g., properties and performance of materials. An important class of materials are crystalline materials that usually contain “dislocations” -- a line-like defect type. Dislocation decisively determine many important materials properties. Over the past decades, significant effort was put into understanding dislocation behavior across different length scales both with experimental characterization techniques as well as with simulations. However, for describing such dislocation structures there is still a lack of a common standard to represent and to connect dislocation domain knowledge across different but related communities. An ontology offers a common foundation to enable knowledge representation and data interoperability, which are important components to establish a “digital twin”. This paper outlines the first steps towards the design of an ontology in the dislocation domain and shows a connection with the already existing ontologies in the materials science and engineering domain.

The findability (F), accessibility (A), interoperability (I), and re-usability (R) of research data are essential and acknowledged factors for an efficient re-use of data, e.g. for data driven science. However, in the field of plasma technology there is currently a lack of common standards and tools to publish data according to these FAIR data principles. To address this issue, the present contribution reports on the development of a modular metadata model for the representation of subject- and method-specific metadata in the field of plasma technology, which is based on the core plasma metadata schema, Plasma-MDS (https://arxiv.org/abs/1907.07744). The linking and semantic description of the metadata modules are carried out via ontologies. The developed tools and services are made available via a plasma technology knowledge graph and the data platform https://www.inptdat.de/. They are intended to be reviewed and further developed by the low-temperature plasma community to provide a common basis for open science and research data management according to the FAIR principles., Funded by the German Federal Ministry of Education and Research (BMBF) under grants 16QK03A, 16QK03B, and 16QK03C.

During recent years the number of online platforms sharing research data for re-analysis has grown strongly. Almost every subject-specific research community has realized that data sharing can lead to faster, better and more accurate further developments. In order to support science to reinvent itself, to be more dynamic and effective, it is mandatory to implement open science. Nowadays some of the main trends are to make science as open and reproducible as possible, to create repository-like platforms around subject-specific communities, where results of research can be published as datasets or reusable resources, and to make the shared data FAIR. There is an increased interest for FAIR-ification of the published research data and for providing the necessary services to generate reproducible content from and for experiments as well as numerical modelling and simulation. In order to reach the open science goal for subject-specific research communities, criteria for curation and FAIR-ification of their published data have to be established. In this contribution, we discuss some of the challenges raised by the implementation of open science and the technical possibilities to reach this objective within the plasma technology community. Our approach in this direction is to refine the data platform for plasma technology INPTDAT (https://www.inptdat.de) by adding new features like (i) linking and enriching research metadata by means of a knowledge graph, based on a subject-specific ontology; (ii) quality assurance, reputation monitoring and reproducibility track with the aid of blockchain technology. Within the framework of the joint project QPTDat we are about to develop these features as external services which will provide knowledge and support for the entire plasma technology community, especially for other online platforms and portals acting in this field. The Plasma Technology Ontology as a Service (PTOaaS) will support the FAIR-ification of the data, e.g. by providing a standardized vocabulary for semantic annotations. Using smart contracts, the Plasma Technology Blockchain as a Service (PTBaaS) will enable, i.a. automation of curation processes, verification of quality criteria, and reputation monitoring., The German Federal Ministry of Education and Research (BMBF) funded this work under grant marks 16QK03A, 16QK03B, and 16QK03C.

Wikidata, the free knowledge base in the Wikimedia movement, is used by various Wikimedia projects and third parties to provide machine-readable information and data. Its data quality is managed and monitored by its community using several quality control mechanisms, recently including formal schemas in the Shape Expressions language. However, larger schemas can be tedious to write, making automatic inference of schemas from a set of exemplary Items an attractive prospect. This thesis investigates this option by updating and adapting the RDF2Graph program to infer schemas from a set of Wikidata Items, and providing a web-based tool which makes this process available to the Wikidata community. Though the resulting schemas are usually not fit for direct validation, they can still be useful as a form of describing the layout of an area of Wikidata’s data model, a way to notice potential issues in the source data, or a basis for a manually curated schema., master-thesis-final.tar.gz is a tarball of the thesis' source code, from which it should be possible to build the thesis by running `make`; master-thesis-Lucas-Werkmeister.pdf is the PDF built directly by PDFLaTeX; and master-thesis-Lucas-Werkmeister-signed.pdf is a signed version of master-thesis-Lucas-Werkmeister.pdf, signed with the PortableSigner software using the author's certificate from the KIT CA.