DPG Phi
Verhandlungen
Verhandlungen
DPG

Dresden 2020 – wissenschaftliches Programm

Die DPG-Frühjahrstagung in Dresden musste abgesagt werden! Lesen Sie mehr ...

Bereiche | Tage | Auswahl | Suche | Aktualisierungen | Downloads | Hilfe

MM: Fachverband Metall- und Materialphysik

MM 32: Topical Session: Data Driven Materials Science - Materials Data Management (joint session MM/CPP)

MM 32.2: Vortrag

Mittwoch, 18. März 2020, 10:45–11:00, BAR 205

Big data in materials science: Status of and needs for metadata and ontologies — •Maja-Olivia Lenz, Luca M. Ghiringhelli, Carsten Baldauf, and Matthias Scheffler — Fritz-Haber-Institut der Max-Planck-Gesellschaft, Berlin

In recent years, the amount of data in materials science has increased exponentially. Consequently, new ways to store and annotate data are necessary to ensure findability, accessibility, interoperability and re-usability, i.e. to fulfil the FAIR principles [1], and to do efficient, good and new science. Data describing and characterizing other data are called metadata. Often, the materials science community has no clear distinction between data and their metadata as it depends on the intended use of the data. In this talk, we present the NOMAD MetaInfo [2], a general descriptive and structured metadata scheme for materials simulations. Ontologies represent the next step on the semantic ladder, as they enrich pure (meta)data structures by relations and thereby enable semantic and syntactic interoperability between different software agents, people, and organizations. In fact, the NOMAD MetaInfo includes a number of relations between concepts and therefore goes beyond the simple metadata picture. It can be interpreted as a light-weight ontology and thus can easily be connected to other ontologies like the European Materials and Modeling Ontology, EMMO. We give an introduction to ontologies, explain why they are useful, and outline their role and current status in materials science.

[1] M. Wilkinson, et al., Sci Data 3, 160018 (2016).

[2] L. M. Ghiringhelli et al., npj Comput. Mater. 3, 46 (2017).

100% | Mobil-Ansicht | English Version | Kontakt/Impressum/Datenschutz
DPG-Physik > DPG-Verhandlungen > 2020 > Dresden