Home Implementation Networks Current Implementation Networks Novel Materials Discovery (NOMAD)

NOMAD is part of the Dutch-German consortium FAIR Data Infrastructure (FAIR-DI), pillar A (www.fairdi.eu)

Active GO FAIR Implementation Network
The Novel Materials Discovery (NOMAD) Laboratory maintains the largest worldwide repository for input and output files of all important computational materials science computer programs. Based on its open-access data, it builds several Big-Data Services helping to advance materials science and engineering by recognizing that data is a crucial raw material of the 21st century. The NOMAD Repository started in 2013 as a joint endeavour of the Humboldt-Universität Berlin and the Fritz-Haber-Institut der Max-Planck-Gesellschaft in Berlin, and then advanced into the NOMAD European Centre of Excellence (CoE), https://nomad-coe.eu, established in fall 2015 by bringing together eight research groups and four high-performance computing (HPC) centres. Now, NOMAD is making steps towards sustainability by starting a nonprofit association (a Berlin based “gemeinnütziger eingetragener Verein (e.V.)”). Pillar A of this e.V. covers 3 of the five NOMAD CoE components, i.e. the Repository (raw data), the Archive (normalized data), and the Encyclopedia (graphical user interface for the presentation of the data). This “NOMAD Pillar” formed the GO FAIR IN.

Main purpose and objectives
Since all NOMAD facilities are meant to be available for many years we want to adopt the state-of-the-art methods in data organization and description. Therefore we want to make our systems FAIR compliant and not only apply current FAIR metrics but also contribute to their advancements.
To implement the FAIR principles we will adopt the Digital Object model pushed ahead by the C2CAMP Implementation Network, i.e. we see GO FAIR as an excellent basis to interact with other INs and to contribute actively to progress towards a more stable domain of digital data.
Guiding Purpose: Increased Interoperability through the stepwise implementation of the FAIR principles where FAIR DMP tools, Digital Objects and other GO FAIR results will play a role.


  1. Within GO FAIR NOMAD will present the state of the work and will apply FAIR metrics – once ready to us – to assess the FAIRness of its archive.
  2. NOMAD is willing to act as an early test candidate for FAIRmetrics to help optimizing the guidelines.
  3. NOMAD is eager to further develop its concepts together with other GO FAIR INs to achieve the coherence in data management and re-use.

Main tasks

  1. Aggregate relevant results in form of data (full input and output files of computational materials science studies) from different labs worldwide into the NOMAD Repository.
  2. Cleansing and normalizing these data sets, assigning PIDs in form of DOIs and unified metadata descriptions – all to be stored in the NOMAD Archive.
  3. Offer this archive to the interested materials-science community and beyond, based on free and open access.
  4. Offer help & support and guidance via an Encyclopedia, a user forum, courses and seminars to interested users with the intention to also improve data practices.

Download the manifesto here

Peter Wittenburg Peter.Wittenburg@mpi.nl

Are you interested in joining NOMAD IN? Please express your interest by filling in the form below. Your request will be forwarded to the IN coordinator, she/he will get in touch as soon as possible.


Members of the NOMAD leadership are
Matthias Scheffler (Coordinator); FHI Max Planck Society Berlin
Claudia Draxl (Deputy Coordinator); Humboldt University Berlin
Peter Wittenburg (GOFAIR Liaison); MPCDF, Max Planck Society, Garching
Raphael Ritz; MPCDF, Max Planck Society, Garching
Hermann Lederer; MPCDF, Max Planck Society
Markus Scheidgen; FHI-MPG and HU Berlin

Further collaborators and advisors include
Jose Maria Cela; Barcelona Supercomputing Centre
Nicolas Fabas; MPCDF, Max Planck Society, Garching
Luca Ghiringhelli; FHI-MPG Berlin
Xavier Gonze; University Louvain
Geoffroy Hautier; University Louvain
Janne Ignatius; CSC Finland
Francesc Illas; University of Barcelona
James Kermode; Warwick University
Kimmo Koski; CSC Finland
Dieter Kranzlmüller; Leibniz Supercomputing Centre, Garching
Markus Rampp; MPCDF, Garching
Gian-Marco Rignanese; University Louvain
Patrick Rinke Aalto; University Finland
Angel Rubio; MPI for the Structure of Dynamics of Matter, Hamburg
Jungho Shin; FHI-MPG and HU Berlin
Kristian Sommer Thygesen; Technical University of Denmark, Lyngby
Alessandro De Vita; King’s College London
Thomas Zastrow; MPCDF, Max Planck Society, Garching