TY - JOUR A1 - Marco, Reidelbach A1 - Marcus, Weber T1 - From Documentation to Discovery - MaRDMO and the MaRDI Ecosystem JF - 2nd Conference on Research Data Infrastructure (CoRDI) Y1 - 2025 U6 - https://doi.org/10.5281/zenodo.16735889 ER - TY - JOUR A1 - Fischer, Kristina A1 - Gerber, Anja A1 - Koprucki, Thomas A1 - Noback, Andres A1 - Reidelbach, Marco A1 - Schrade, Torsten A1 - Thiery, Florian T1 - Windows on Data: Federating Research Data with FAIR Digital Objects and Linked Open Data JF - 2nd Conference on Research Data Infrastructure (CoRDI) Y1 - 2025 U6 - https://doi.org/10.5281/zenodo.16736222 ER - TY - JOUR A1 - Biernacka, Katarzyna A1 - Castro, Leyla Jael A1 - Fritzsch, Bernadette A1 - Grossmann, Yves Vincent A1 - Reidelbach, Marco A1 - Struck, Alexander A1 - Lanza, Giacomo A1 - Walter, David A1 - Ulusoy, Inga T1 - From Vision to Implementation: Current Practices and Challenges of Software Management Plans in Research JF - 2nd Conference on Research Data Infrastructure (CoRDI) Y1 - 2025 U6 - https://doi.org/10.5281/zenodo.16735302 ER - TY - CHAP A1 - Schembera, Björn A1 - Wübbeling, Frank A1 - Kleikamp, Hendrik A1 - Schmidt, Burkhard A1 - Shehu, Aurela A1 - Reidelbach, Marco A1 - Biedinger, Christine A1 - Fiedler, Jochen A1 - Koprucki, Thomas A1 - Iglezakis, Dorothea A1 - Göddeke, Dominik T1 - Towards a Knowledge Graph for Models and Algorithms in Applied Mathematics T2 - Metadata and Semantic Research. MTSR 2024 N2 - Mathematical models and algorithms are an essential part of mathematical research data, as they are epistemically grounding numerical data. To make this research data FAIR, we present how two previously distinct ontologies, MathAlgoDB for algorithms and MathModDB for models, were merged and extended into a living knowledge graph as the key outcome. This was achieved by connecting the ontologies through computational tasks that correspond to algorithmic tasks. Moreover, we show how models and algorithms can be enriched with subject-specific metadata, such as matrix symmetry or model linearity, essential for defining workflows and determining suitable algorithms. Additionally, we propose controlled vocabularies to be added, along with a new class that differentiates base quantities from specific use case quantities. We illustrate the capabilities of the developed knowledge graph using two detailed examples from different application areas of applied mathematics, having already integrated over 250 research assets into the knowledge graph. Y1 - 2025 SN - 9783031819735 U6 - https://doi.org/10.1007/978-3-031-81974-2_8 SN - 1865-0929 VL - 2331 SP - 95 EP - 109 PB - Springer Nature Switzerland CY - Cham ER - TY - JOUR A1 - Marco, Reidelbach T1 - MaRDMO: Future Gateway to FAIR Mathematical Data JF - E-Science-Tage 2025: Research Data Management: Challenges in a Changing World N2 - Mathematical research data plays a crucial role across scientific disciplines, yet its documentation and dissemination remain challenging due to the lack of standardized research data management practices. The MaRDMO Plugin addresses these challenges by integrating mathematical models, algorithms, and interdisciplinary workflows into the established framework of the Research Data Management Organiser (RDMO). Built on FAIR principles, MaRDMO enables structured documentation and retrieval of mathematical research data through guided questionnaires. It connects to multiple knowledge graphs, including MathModDB, MathAlgoDB, and the MaRDI Portal. Users can document and search for models, algorithms, and workflows via dynamic selection interfaces that also leverage other sources such as Wikidata. The plugin facilitates the export to the individual MaRDI services, ensuring data quality through automated validation. By embedding mathematical research data management into the widely adopted RDMO platform, MaRDMO represents a significant step toward making mathematical research data more findable, accessible, and reusable. Y1 - 2025 U6 - https://doi.org/10.11588/heibooks.1652.c23913 SP - 40 EP - 53 ER - TY - JOUR A1 - Schembera, Björn A1 - Wübbeling, Frank A1 - Shehu, Aurela A1 - Biedinger, Christine A1 - Fiedler, Jochen A1 - Reidelbach, Marco A1 - Schmidt, Burkhard A1 - Ferrer, Eloi A1 - Koprucki, Thomas T1 - FAIR Representation of Mathematical Research Data: MathModDB and MathAlgoDB as Knowledge Graphs for Mathematical Models and Numerical Algorithms JF - 2nd Conference on Research Data Infrastructure (CoRDI) Y1 - 2025 U6 - https://doi.org/10.5281/zenodo.16735911 ER - TY - JOUR A1 - Diederichs, Katja A1 - Krause, Celia A1 - Lemaire, Marina A1 - Reidelbach, Marco A1 - Windeck, Jürgen T1 - A Vision for Data Management Plans in the NFDI JF - ZENODO N2 - At present, data management plans (DMPs) are still often perceived as mere documents for funding agencies providing clarity on how research data will be handled during a funded project, but are not usually actively involved in the processes. However, they contain a great deal of information that can be shared automatically to facilitate active research data management (RDM) by providing metadata to research infrastructures and supporting communication between all involved stakeholders. This position paper brings together a number of ideas developed and collected during interdisciplinary workshops of the Data Management Planning Working Group (infra-dmp), which is part of the section Common Infrastructures of the National Research Data Infrastructure (NFDI) in Germany. We present our vision of a possible future role of DMPs, templates, and tools in the upcoming NFDI service architecture. Y1 - 2024 U6 - https://doi.org/10.5281/zenodo.10570653 ER - TY - CHAP A1 - Reidelbach, Marco A1 - Schembera, Björn A1 - Weber, Marcus T1 - Towards a FAIR Documentation of Workflows and Models in Applied Mathematics T2 - Mathematical Software – ICMS 2024 N2 - Modeling-Simulation-Optimization workflows play a fundamental role in applied mathematics. The Mathematical Research Data Initiative, MaRDI, responded to this by developing a FAIR and machine-interpretable template for a comprehensive documentation of such workflows. MaRDMO, a Plugin for the Research Data Management Organiser, enables scientists from diverse fields to document and publish their workflows on the MaRDI Portal seamlessly using the MaRDI template. Central to these workflows are mathematical models. MaRDI addresses them with the MathModDB ontology, offering a structured formal model description. Here, we showcase the interaction between MaRDMO and the MathModDB Knowledge Graph through an algebraic modeling workflow from the Digital Humanities. This demonstration underscores the versatility of both services beyond their original numerical domain. Y1 - 2024 U6 - https://doi.org/10.1007/978-3-031-64529-7_27 VL - 14749 SP - 254 EP - 262 PB - Springer Nature Switzerland CY - Cham ET - Lecture Notes in Computer Science ER - TY - CHAP A1 - Schembera, Björn A1 - Wübbeling, Frank A1 - Kleikamp, Hendrik A1 - Biedinger, Christine A1 - Fiedler, Jochen A1 - Reidelbach, Marco A1 - Shehu, Aurela A1 - Schmidt, Burkhard A1 - Koprucki, Thomas A1 - Iglezakis, Dotothea A1 - Göddeke, Dominik T1 - Ontologies for Models and Algorithms in Applied Mathematics and Related Disciplines T2 - Metadata and Semantic Research - MTSR 2023 N2 - In applied mathematics and related disciplines, the modeling-simulation-optimization workflow is a prominent scheme, with mathematical models and numerical algorithms playing a crucial role. For these types of mathematical research data, the Mathematical Research Data Initiative has developed, merged and implemented ontologies and knowledge graphs. This contributes to making mathematical research data FAIR by introducing semantic technology and documenting the mathematical foundations accordingly. Using the concrete example of microfracture analysis of porous media, it is shown how the knowledge of the underlying mathematical model and the corresponding numerical algorithms for its solution can be represented by the ontologies. Y1 - 2023 U6 - https://doi.org/10.1007/978-3-031-65990-4_14 SP - 161 EP - 168 PB - Springer Nature Switzerland CY - Cham ET - Communications in Computer and Information Science ER - TY - JOUR A1 - Benner, Peter A1 - Danabalan, Renita A1 - Gödekke, Dominik A1 - Kastner, Lars A1 - Krause, Tabea A1 - Mietchen, Daniel A1 - Reidelbach, Marco A1 - Schembera, Björn A1 - Schubotz, Moritz A1 - Sinn, Rainer A1 - Tabelow, Karsten T1 - Research Data Management Planning in Mathematics N2 - Research data are crucial in mathematics and all scientific disciplines, as they form the foundation for empirical evidence, by enabling the validation and reproducibility of scientific findings. Mathematical research data (MathRD) have become vast and complex, and their interdisciplinary potential and abstract nature make them ubiquitous in various scientific fields. The volume of data and the velocity of its creation are rapidly increasing due to advancements in data science and computing power. This complexity extends to other disciplines, resulting in diverse research data and computational models. Thus, proper handling of research data is crucial both within mathematics and for its manifold connections and exchange with other disciplines. The National Research Data Infrastructure (NFDI), funded by the federal and state governments of Germany, consists of discipline-oriented consortia, including the Mathematical Research Data Initiative (MaRDI). MaRDI has been established to develop services, guidelines and outreach measures for all aspects of MathRD, and thus support the mathematical research community. Research data management (RDM) should be an integral component of every scientific project, and is becoming a mandatory component of grants with funding bodies such as the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation). At the core of RDM are the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. This document aims to guide mathematicians and researchers from related disciplines who create RDM plans. It highlights the benefits and opportunities of RDM in mathematics and interdisciplinary studies, showcases examples of diverse MathRD, and suggests technical solutions that meet the requirements of funding agencies with specific examples. The document is regularly updated to reflect the latest developments within the mathematical community represented by MaRDI. Y1 - 2023 U6 - https://doi.org/10.5281/zenodo.10018245 ER -