06.11.2024, 14:00 - 16:00
– Campus Golm, Building 9, Room 2.22 and via Zoom
Institutskolloquium
Graphon Models for Inhomogeneous Random Graphs
Olga Klopp (Paris), Nicolas Verzelen (Montpellier)
Karsten Tabelow (WIAS Berlin)
Like in all scientific disciplines research data in mathematics has become vast, it is complex and multifaceted, and, through the successful application of mathematics in interdisciplinary research, it is widespread in the scientific landscape. It ranges from information bases such as the standard reference data for special functions, tables and similar mathematical objects to highly complex data in scientific computing or scientific machine learning. The growing amount of research data challenges an old requirement in science: its reproducibility and the re-usability of results. In an attempt to answer this challenge at current level, the FAIR principles have been formulated. Yet, despite the existence of special solutions a comprehensive infrastructure for research data in science or in mathematics is missing that supports the research workflow and by the corresponding research data life cycle. Thus, the German Council for Scientific Information Infrastructures initiated the foundation of the German National Research Data Initiative (NFDI) to address the need for discipline specific research data infrastructures and to conform to the specifications of the European Open Science Cloud (EOSC). Similarly, the project GAIA-X aims at establising a data infrastructure for industry, science and administration in Europe, based on the European values of transparency, openness, data protection and security.
In this context the Mathematical Research Data Initiative (MaRDI) within the NFDI aims at developing a research data infrastructure for mathematics. We expect that it will be useful not only in mathematics but will have significant impact also in other scientific fields. Motivated by the needs and requests from the mathematical community as well as from other scientific disciplines that utilize quantitative methods, MaRDI aims to set standards for certified mathematical research data, the design of confirmable workflows, and to provide adequate services for the scientific community. Through this its designated goal is to realize the FAIR principles across the field of mathematics and its applications which will not least be a requirement in future project applictions.
In this talk, we will give an introduction into the notion of mathematical research data and the use cases for a corresponding infrastructure in the mathematical research process and the emerging national and international research data landscape. We will demonstrate how MaRDI and its concepts will contribute to future mathematical research and discuss the benefits of the FAIR use of mathematical research data.
*The colloquium will be conducted online - please see www.SFB1294.de for details.*