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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)

NFDI4Culture is establishing an infrastructure for research data on material and immaterial cultural heritage in the context of the German National Research Data Infrastructure (NFDI) in compliance with the FAIR principles. The NFDI4Culture Knowledge Graph is developed and integrated with the Culture Information Portal to aggregate diverse and isolated data from the culture research landscape and thereby increase the discoverability, interoperability and reusability of cultural heritage data. This paper presents the research data management strategy in the long-term project NFDI4Culture, which combines a CMS and a Knowledge Graph-based infrastructure to enable an intuitive and meaningful interaction with research resources in the cultural heritage domain.

Slides of the short paper presented at Qurator 2022.

Knowledge Extraction (KE) techniques are used to convert unstructured information present in texts to Knowledge Graphs (KGs) which can be queried and explored. Despite their potential for cultural heritage domains, such as Art History, these techniques often encounter limitations if applied to domain-specific data. In this paper we present the main challenges that KE has to face on art-historical texts, by using as case study Giorgio Vasari's The Lives of The Artists. This paper discusses the following NLP tasks for art-historical texts, namely entity recognition and linking, coreference resolution, time extraction, motif extraction and artwork extraction. Several strategies to annotate art-historical data for these tasks and evaluate NLP models are also proposed.

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.

Cultural heritage portals have the goal of providing users with seamless access to all their resources. This paper introduces initial efforts for a user-oriented restructuring of the German Digital Library (DDB). At present, cultural heritage objects (CHOs) in the DDB are modeled using an extended version of the Europeana Data Model (DDBEDM), which negatively impacts usability and exploration. These challenges can be addressed by exploiting ontologies, and building a knowledge graph from the DDB’s voluminous collection. Towards this goal, an alignment of bibliographic metadata from DDB-EDM to FRBR-Aligned Bibliographic Ontology (FaBiO) is presented.

Under the German government���s initiative ���NEUSTART Kultur���, the German Digital Library or Deutsche Digitale Bibliothek (DDB) is undergoing improvements to enhance user-experience. As an initial step, emphasis is placed on creating a knowledge graph from the bibliographic record collection of the DDB. This paper discusses the challenges facing the DDB in terms of retrieval and the solutions in addressing them. In particular, limitations of the current data model or ontology to represent bibliographic metadata is analyzed through concrete examples. This study presents the complete ontological mapping from DDB-Europeana Data Model (DDB-EDM) to FaBiO, and a prototype of the DDB-KG made available as a SPARQL endpoint. The suitabiliy of the target ontology is demonstrated with SPARQL queries formulated from competency questions

Archival records are essential sources of information for historians and digital humanists to understand history. For modern information systems they are often analysed and integrated into Knowledge Graphs for better access, interoperability and re-use. However, due to restrictions of the representation of RDF predicates temporal data within archival records is a challenge to model. This position paper explains requirements for modeling temporal data in archival records based on running research projects in which archival records are analysed and integrated in Knowledge Graphs for research and exploration.

An important part in European cultural identity relies on European cities and in particular on their histories and cultural heritage. Nuremberg, the home of important artists such as Albrecht Dürer and Hans Sachs developed into the epitome of German and European culture already during the Middle Ages. Throughout history, the city experienced a number of transformations, especially with its almost complete destruction during World War 2. This position paper presents TRANSRAZ, a project with the goal to recreate Nuremberg by means of an interactive 3D tool to explore the city’s architecture and culture ranging from the 17th to the 21st century. The goal of this position paper is to discuss the ongoing work of connecting heterogeneous historical data from various sources previously hidden in archives to the 3D model using knowledge graphs for a scientifically accurate interactive exploration on the Web.

On October 28 to 29, 2020, the project QPTDat hosted the virtual workshop on FAIR Research Data in Plasma Medicine. This is a summary report of the workshop. The goal of the workshop was to bring together researchers in the field of plasma medicine with research data management experts to discuss requirements and possibilities for research data management in accordance with the FAIR principles. Research data management experts provided an overview over existing procedures and ideas for the provision and usage of quality assured research data, e.g. as a basis for data-driven science. On the other side, researchers in the field of plasma medicine and plasma technology introduced different use cases and pointed out specific demands and possible challenges. On this basis, approaches for the further development of an ontology, metadata standards, and quality criteria supporting a simplified publication and re-use of data in the field of plasma medicine were worked out in the course of the workshop., Funded by the German Federal Ministry of Education and Research (BMBF) under grants 16QK03A, 16QK03B, and 16QK03C.

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.

The Web of Data has grown explosively over the past few years, and as with any dataset, there are bound to be invalid statements in the data, as well as gaps. Natural Language Processing (NLP) is gaining interest to fill gaps in data by transforming (unstructured) text into structured data. However, there is currently a fundamental mismatch in approaches between Linked Data and NLP as the latter is often based on statistical methods, and the former on explicitly modelling knowledge. However, these fields can strengthen each other by joining forces. In this position paper, we argue that using linked data to validate the output of an NLP system, and using textual data to validate Linked Open Data (LOD) cloud statements is a promising research avenue. We illustrate our proposal with a proof of concept on a corpus of historical travel stories.

In der Soziologie werden Texte als soziale Phänomene verstanden, die als Mittel zur Analyse von sozialer Wirklichkeit dienen können. Im Laufe der Jahre hat sich eine breite Palette von Techniken in der soziologischen Textanalyse entwickelt, du denen quantitative und qualitative Methoden, sowie vollständig manuelle und computergestützte Ansätze gehören. Die Entwicklung des World Wide Web und sozialer Medien, aber auch technische Entwicklungen wie maschinelle Schrift- und Spracherkennung tragen dazu bei, dass die Menge an verfügbaren und analysierbaren Texten enorm angestiegen ist. Dies führte in den letzten Jahren dazu, dass auch Soziologen auf mehr computergestützte Ansätze zur Textanalyse setzten, wie zum Beispiel statistische ’Natural Language Processing’ (NLP) Techniken. Doch obwohl vielseitige Methoden und Technologien für die soziologische Textanalyse entwickelt wurden, fehlt es an einheitlichen Standards zur Analyse und Veröffentlichung textueller Daten. Dieses Problem führt auch dazu, dass die Transparenz von Analyseprozessen und Wiederverwendbarkeit von Forschungsdaten leidet. Das ’Semantic Web’ und damit einhergehend ’Linked Data’ bieten eine Reihe von Standards zur Darstellung und Organisation von Informationen und Wissen. Diese Standards werden von zahlreichen Anwendungen genutzt, darunter befinden sich auch Methoden zur Veröffentlichung von Daten und ’Named Entity Linking’, eine spezielle Form von NLP. Diese Arbeit versucht die Frage zu diskutieren, in welchem Umfang diese Standards und Tools aus der SemanticWeb- und Linked Data- Community die computergestützte Textanalyse in der Soziologie unterstützen können. Die dafür notwendigen Technologien werden kurz vorgsetellt und danach auf einen Beispieldatensatz der aus Verfassungstexten der Niederlande von 1883 bis 2016 bestand angewendet. Dabei wird demonstriert wie aus den Dokumenten RDF Daten generiert und veröffentlicht werden können, und wie darauf zugegriffen werden kann. Es werden Abfragen erstellt die sich zunächst ausschließlich auf die lokalen Daten beziehen und daraufhin wird demonstriert wie dieses lokale Wissen durch Informationen aus externen Wissensbases angereichert werden kann. Die vorgestellten Ansätze werden im Detail diskutiert und es werden Schnittpunkte für ein mögliches Engagement der Soziologen im Semantic Web Bereich herausgearbeitet, die die vogestellten Analysen und Abfragemöglichkeiten in Zukunft erweitern können.