It is generally agreed that research results obtained in academia should be published. This includes making also the complete data underlying a publication available.
It is also commonly agreed that data-driven research together with proper data infrastructures play a key role for future research. In materials science, this concerns theoretical approaches as much as experiments. Both require a thorough description of the data. More specifically, data must be connected to established metadata and to workflows of their production. In order to avoid fragmentation, all sub-communities need to be brought together.
A first key workshop in this direction was organized 2016, bringing together key players from different atomistic-simulation codes and research areas. The goal and the outcome of this workshop was published in Refs. [1,2]. The following development of an open, flexible, and hierarchical metadata classification system, as achieved by the NOMAD Centre of Excellence , was indeed challenging. Extensive metadata, generic as well as those specific to the different codes, have been developed . Obviously, as codes are continuously updated and extended, and new codes are being developed, this is an ongoing process.
The advantage of the status reached so far will only fully become apparent when the same will have been achieved also for experimental data. The sample material used in the experimental study corresponds to the input file of a calculation; the experimental condition (T, p, environment) and the experimental equipment to the computer code. A not fully solved challenge is the definition of the sample materials. Obviously, closely coupled to the definition of metadata is the description of workflows in the sample preparation and running of the experiment.
To meet these challenges and bring people from the different communities together, we are organizing this Metadata Workshop.
 Ghiringhelli LM, Carbogno C, Levchenko S, Mohamed F, Huhs G, Lüder M, Oliveira M, Scheffler M, "Towards a Common Format for Computational Materials Science Data", Psi-k Scientific Highlight of the Month No. 131. http://psi-k.net/download/highlights/Highlight_131.pdf.
 Ghiringhelli LM, Carbogno C, Levchenko S, Mohamed F, Hus G, Lüder M, Oliveira M, Scheffler M, "Towards Efficient Data Exchange and sharing for Big-Data Driven Materials Science: Metadata and Data Formats", npj Comput Mater 3, 46 (2017).
Topics and Speakers
For topics see the program.
The list of invited speakers will be continuously updated.
How to participate
|mid of January 2019||Registration opens|
|April 30, 2019||Registration closes|
|early May 2019||Acceptance announcements|
|July 8, 2019||Start of the conference|
These two workshops are sponsored by