A repository for the publication and sharing of heterogeneous materials data

Abstract

National Materials Data Management and Service platform (NMDMS) is a materials data repository for the publication and sharing of heterogeneous materials scientific data and follows the FAIR principles: Findable, Accessible, Interoperable, and Reusable. To ensure data are ‘Interoperable, NMDMS uses a user-friendly semi-structured scientific data model, named dynamic container’, to define, exchange, and store heterogeneous scientific data. Then, a personalized yet standardized data submission subsystem, a rigorous project data review and publication subsystem, and a multi-granularity data query and retrieval subsystem collaboratively make data ‘Reusable’, ‘Findable’, and ‘Accessible’. Finally, China’s “National Key R&D Program: Material Genetic Engineering Key Special Project” has adopted NMDMS to publish and share its project data. There are 12,251,040 pieces of data published in NMDMS since 2018, under 87 categories and 1,912 user-defined schemas from 45 projects. The platform has been accessed 908875 times, and 2403,208 pieces of data have been downloaded. In short, NMDMS effectively accelerates the publication and sharing of material project data in China.

https://2DMat.ChemDX.org: Experimental data platform for 2D materials from synthesis to physical properties

“…[1][2][3][4][5][6][7][8][9][10][11] This shi has signicantly emphasized the values of "data" generated from experimental and computational processes, leading to the emergence of materials data platforms as indispensable tools in data-driven research. [12][13][14][15][16][17] These platforms facilitate convenient data collection, integration, utilization, and sharing. Various materials data platforms have been developed, collecting materials properties from published literature, such as the Perovskite Database, 18 Polymer Scholar, [19][20][21] and Starrydata2, 22 and electronic structures data obtained from density functional theory (DFT) calculations, such as AFLOWLIB, 23 JARVIS-DB, 24 Materials Project, 25 MatHub-3d, 26 NOMAD, 27,28 OQMD, 29,30 and TEDesignLab.…”

A bridge between trust and control: computational workflows meet automated battery cycling

“…16 Indeed, several frameworks capable of storing and distributing such integrated data are being built. 17–19…”

“…16 Indeed, several frameworks capable of storing and distributing such integrated data are being built. [17][18][19] However, a bridge between "trust" and "control", compatible with both computational and experimental data, yet targetting off-the-shelf instrumentation and reusing common soware tools, currently does not exist. For instance, the ARChemist project focuses on sample synthesis 20 and sample preparation, 21 and while its powder-bot used for X-ray diffraction analysis is interfaced with common diffractometers, 22 it is not driven as part of a computational workow.…”

What is missing in autonomous discovery: open challenges for the community

“…Unfortunately, constructing these relationships requires some degree of standardization and is highly discipline dependent. Attempts at universal materials formats 28,[49][50][51][52] and ontologies 53,54 exist to address this challenge, with much work remaining. Crystallography provides an excellent example of standardizing data formats for interoperability (protein data bank and crystallographic information les).…”