MaRDI: Mathematical Research Data Initiative Extension Proposal

The MaRDI consortium is the central National Research Data Infrastructure (NFDI) initiative for mathematics in Germany. Since 2021 MaRDI has successfully established an integrated infrastructure supporting the FAIR - Findable, Accessible, Interoperable and Reusable - principles specifically for mathematical research data. This includes the development of the MaRDI Portal, a central access point to over 15 services, and the creation of the MaRDI Knowledge Graph (KG), semantically connecting millions of mathematical research objects. Through curated KGs such as MathModDB and MathAlgoDB, benchmark infrastructures, workflow documentation tools, and dedicated training offerings, MaRDI has laid the foundation for an ecosystem tailored to the confirmability and reproducibility of mathematical research. Building on these achievements, the second phase of MaRDI focuses on expanding the (re)usability, scalability, and reach of its services, workflows, and models. The overarching goal is to embed structured mathematical data and knowledge as a cornerstone of reproducible mathematical research. It aims to further integrate the mathematical community, to include new research domains, enhance intelligent access to data through AI-based assistants, and extend collaborations with both academia and industry. The emphasis on community involvement – particularly through the development of editorial workflows and user-friendly contribution interfaces, and training and outreach is planned to foster a culture of FAIR data management aligning with local and global initiatives. The work program is organized into seven Task Areas, each addressing a cross-cutting theme within the diversity of mathematical research data. These Task Areas include mathematical workflows, the development of guidelines and metadata standards, the curation and expansion of databases, the provision of benchmarking infrastructures, and the implementation of targeted training and outreach programs. The central MaRDI Portal will be continuously developed to serve as the technological backbone of all services. The governance ensures that the services are continuously aligned with user needs and technological developments. Particular attention will be given to supporting FAIR workflows, confirming results through interoperable formats and data documentation tools as well as to modular training programs adapted to different target groups. The work program is designed to be responsive, scalable, and focused on real-world use cases, with clearly defined deliverables, milestones, and mechanisms for evaluation and feedback.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-16
DOI
https://doi.org/10.5281/zenodo.22797146
Primary Topic
Mathematics, Computing, and Information Processing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

MaRDI: Mathematical Research Data Initiative Extension Proposal

The MaRDI Consortium
Zenodo (CERN European Organization for Nuclear Research)
Mathematics, Computing, and Information Processing
article

MaRDI: Mathematical Research Data Initiative Extension Proposal

The MaRDI Consortium
article en

Abstract

The MaRDI consortium is the central National Research Data Infrastructure (NFDI) initiative for mathematics in Germany. Since 2021 MaRDI has successfully established an integrated infrastructure supporting the FAIR - Findable, Accessible, Interoperable and Reusable - principles specifically for mathematical research data. This includes the development of the MaRDI Portal, a central access point to over 15 services, and the creation of the MaRDI Knowledge Graph (KG), semantically connecting millions of mathematical research objects. Through curated KGs such as MathModDB and MathAlgoDB, benchmark infrastructures, workflow documentation tools, and dedicated training offerings, MaRDI has laid the foundation for an ecosystem tailored to the confirmability and reproducibility of mathematical research. Building on these achievements, the second phase of MaRDI focuses on expanding the (re)usability, scalability, and reach of its services, workflows, and models. The overarching goal is to embed structured mathematical data and knowledge as a cornerstone of reproducible mathematical research. It aims to further integrate the mathematical community, to include new research domains, enhance intelligent access to data through AI-based assistants, and extend collaborations with both academia and industry. The emphasis on community involvement – particularly through the development of editorial workflows and user-friendly contribution interfaces, and training and outreach is planned to foster a culture of FAIR data management aligning with local and global initiatives. The work program is organized into seven Task Areas, each addressing a cross-cutting theme within the diversity of mathematical research data. These Task Areas include mathematical workflows, the development of guidelines and metadata standards, the curation and expansion of databases, the provision of benchmarking infrastructures, and the implementation of targeted training and outreach programs. The central MaRDI Portal will be continuously developed to serve as the technological backbone of all services. The governance ensures that the services are continuously aligned with user needs and technological developments. Particular attention will be given to supporting FAIR workflows, confirming results through interoperable formats and data documentation tools as well as to modular training programs adapted to different target groups. The work program is designed to be responsive, scalable, and focused on real-world use cases, with clearly defined deliverables, milestones, and mechanisms for evaluation and feedback.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 8%
Mathematics, Computing, and Information Processing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.