NFDI4Ing

National Research Data Infrastructure for Engineering Sciences

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NFDI4Ing brings together the engineering communities and fosters the management of engineering research data. The consortium represents engineers from all walks of the profession. It offers a unique method-oriented and user-centred approach in order to make engineering research data FAIR – findable, accessible, interoperable, and re-usable.

Duration: 01.10.2020 till 30.09.2025
Donee: German Research Center for Artificial Intelligence GmbH
Sponsor: DFG German Research Foundation
Grant number: project number 442146713
Partner:

RWTH Aachen
TU Braunschweig
TU Darmstadt
TU Dresden
Deutsches Zentrum für Luft- und Raumfahrt (DLR)
Leibniz Universität Hannover (LUH)
TIB - Leibniz information centre for science and technology Universitätsbibliothek
FZ Jülich
Karlsruhe Institute of Technology (KIT)
TU München
Universität Stuttgart
…und weitere, vollständige Liste unter www.nfdi4ing.de

Application Field: Agricultural Robotics
Assistance- and Rehabilitation Systems
Electric Mobility
Logistics, Production and Consumer
SAR- & Security Robotics
Underwater Robotics
Space Robotics

Project details

Archetypes (“part projects”) and their area of engineering
Project structure with Archetypes, Base Services and Community Clusters
NFDI4Ing is one of the funded consortia of the NFDI initiative of DFG (www.dfg.de/en/research_funding/programmes/nfdi/index.html).

NFDI4Ing brings together the engineering communities and fosters the management of engineering research data. The consortium represents engineers from all walks of the profession. It offers a unique method-oriented and user-centred approach in order to make engineering research data FAIR – findable, accessible, interoperable, and re-usable.

NFDI4Ing has been founded in 2017. The consortium has actively engaged engineers across all five engineering research areas of the DFG classification. Leading figures have teamed up with experienced infrastructure providers. As one important step, NFDI4Ing has taken on the task of structuring the wealth of concrete needs in research data management. A broad consensus on typical methods and workflows in engineering research has been established: The archetypes.

So far, seven archetypes are harmonising the methodological needs:

ALEX: bespoke experiments with high variability of setups,
BETTY: engineering research software,
CADEN: provenance tracking of physical samples & data samples,
DORIS: high performance measurement & computation,
ELLEN: extensive and heterogeneous data requirements,
FRANK: many participants & simultaneous devices,
GOLO: field data & distributed systems.

A survey of the entire engineering research landscape in Germany confirms that the concept of engineering archetypes has been very well received. 95% of the research groups identify themselves with at least one of the NFDI4Ing archetypes.

NFDI4Ing plans to further coordinate its engagement along the gateways provided by the DFG classification of engineering research areas. Consequently, NFDI4Ing will support five community clusters. In addition, an overarching task area will provide seven base services to be accessed by both the community clusters and the archetype task areas. Base services address quality assurance & metrics, research software development, terminologies & metadata, repositories & storage, data security & sovereignty, training, and data & knowledge discovery. With the archetype approach, NFDI4Ing’s work programme is modular and distinctly methodoriented. With the community clusters and base services, NFDI4Ing’s work programme remains firmly user-centred and highly integrated.

NFDI4Ing has set in place an internal organisational structure that ensures viability, operational efficiency, and openness to new partners during the course of the consortium’s development. NFDI4Ing’s management team brings in the experience from two applicant institutions and from two years of actively engaging with the engineering communities. Eleven applicant institutions and over fifty participants have committed to carrying out NFDI4Ing’s work programme. Moreover, NFDI4Ing’s connectedness with consortia from nearby disciplinary fields is strong. Collaboration on cross-cutting topics is well prepared and foreseen. As a result, NFDI4Ing is ready to join the National Research Data Infrastructure.

Publications

2024

RoBivaL data corpus
Christian Backe, Malte Wirkus, Stefan Hinck, Jonathan Babel, Vadim Riedel, Nele Reichert, Andrej Kolesnikov, Tobias Stark, Jens Hilljegerdes, Hilmi Dogu Kücüker, Emir Barcic, Eduard Klink, Arno Ruckelshausen, Frank Kirchner
Zenodo, Apr/2024.
Comparative Study of Soil Interaction and Driving Characteristics of Different Agricultural and Space Robots in an Agricultural Environment
Malte Wirkus, Stefan Hinck, Christian Backe, Jonathan Babel, Vadim Riedel, Nele Reichert, Andrej Kolesnikov, Tobias Stark, Jens Hilljegerdes, Hilmi Dogu Kücüker, Arno Ruckelshausen, Frank Kirchner
In Journal of Field Robotics, Wiley, volume 41, pages 1-34, 2024.

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last updated 04.01.2024
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