Correction to: Data-Driven Materials Science: Status, Challenges, and Perspectives (Advanced Science, (2019), 6, 21, (1900808), 10.1002/advs.201900808)

Lauri Himanen, Amber Geurts, Adam Stuart Foster, Patrick Rinke

Onderzoeksoutput: Bijdrage aan wetenschappelijk tijdschrift/periodieke uitgaveArtikelWetenschappelijkpeer review

Samenvatting

Adv. Sci. 2019, 6, 1900808 In the originally published article, Table 1 and Table 2 did not contain timely data. The corrected entries of Table 1 and Table 2 are presented below. To correct these errors, two new entries have been added: QCArchive and NanoMine. Also, the entry for MARVEL NCCR has been renamed to Materials Cloud and corrected in Table 1 and Table 2; and the entries Open Quantum Materials Database (OQMD), SUNCAT, MaterialsZone, and Exabyte have been corrected in Table 2. Finally, the description for data upload and web API have been clarified in the caption of Table. The authors apologize for any misunderstanding these errors may have caused. Corrections to Table List of current major materials data non-commercial infrastructures. Note that some platforms are named after the leading research project and may host multiple services under different names. As contact person we listed the director(s) of each infrastructure, in such cases, where they were clearly identifiable. Data volume numbers reflect the state in April 2019 (Table presented.) Corrections to Table Services provided by the selected materials data infrastructures. Open Access: provides partial or full free access to data. Computational data: contains data originating from software simulations. Experimental data: contains data originating from experiments. Data upload: Allows upload of external data, services that support issuing Digital Object Identifiers have been marked with (DOI). Workflow management tools: provides or collaborates in the development of open-source software tools for workflow management. Web API: provides an interface for accessing data remotely with automated scripts. Data analysis tools: provides online or offline data analysis tools, including machine learning (Table presented.) a) Open Access to a subset of data.
Originele taal-2Engels
TijdschriftAdvanced Science
Volume7
Nummer van het tijdschrift2
DOI's
StatusGepubliceerd - 01 jan. 2020

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