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MAX offers a materials informatics ecosystem for automated high-throughput calculations and automatic storage of data in graph databases that enables FAIR sharing of all research data.
This is based on AiiDA as the working environment and on Materials Cloud as the cloud simulation and web dissemination and sharing platform.
The combination of AiiDA and Materials Cloud enables to:
implement, run and share workflows and turnkey solutions, as well as the resulting raw and curated data;
guarantee complete automatic provenance tracking, storage and preservation;
ensure reproducibility of computational research, its reuse, as well as data analytics.
These are joint efforts performed in close collaboration with MARVEL, a long-term Swiss effort coordinated by EPFL, and supported by a number of other projects: H2020 MarketPlace, H2020 Intersect, the swissuniversities P-5 “Materials Cloud” project, the EPFL Open Science Fund through the OSSCAR project, the European Research Council (ERC), the Swiss Platform for Advanced Scientific Computing (PASC), the H2020 NFFA, and the H2020 EMMC.
The “operating system” for FAIR materials science simulations: AiiDA
To discover novel materials and to design materials properties, researchers need to run thousands of HPC simulations. Managing these simulations and the resulting data is not trivial. The tools delivered by MaX to enable these high-throughput simulations is AiiDA, an automated interactive infrastructure and database for computational science based on the four “ADES” pillars of automation, data, environment and sharing (Pizzi et al, 2016).
AiiDA can manage and automate tens of thousands of simulations concurrently, scaling from local resources to next-generation supercomputers. At the same time, it stores automatically input and output data and, most importantly, the whole provenance (i.e., the connection between data and calculations, with a full description of how data was generated) ensuring full reproducibility.
Moreover, AiiDA’s powerful workflow engine is an enabler technology for the implementation of turn-key workflows. These encode the expertise of computational scientists, automating the data processing and the choice of parameters to obtain a converged result, so that materials properties can be computed also by non-experts.
These turn-key workflows allow to accelerate scientific discovery by extending the concept of reproducibility not only to re-run the same exact calculations, but also to perform similar simulations on new materials or with different parameters.
The FAIR dissemination platform for data and simulation services: Materials Cloud
AiiDA simplifies the task of sharing the results between researchers and of disseminating research results thanks to its coupling with the Materials Cloud, where data can be uploaded, visualized, analyzed and shared.
Thanks to AiiDA and the Materials Cloud, research data management and stewardship is streamlined, providing an integrated platform for FAIR data sharing, where data is:
Findable by DOIs and standardized metadata on the Materials Cloud Archive
Accessible via the Materials Cloud interface, giving graphical and interactive access both to curated data and to the raw AiiDA graphs to inspect the provenance
Interoperable thanks to the adoption of code-agnostic data formats for the relevant data structures that can be reused across different code plugins
Reusable by encouraging the use of open licenses when data is uploaded on the Archive, but most importantly reproducible thanks to the strong reproducibility guarantees of the provenance graph.
In addition to this, Materials Cloud acts also as a simulation platform, providing tools to enable running new simulations both on premises and in the cloud via the AiiDA lab platform, the Quantum Mobile and a number of online interactive tools.