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Data driven approach has been used extensively for novel materials discovery in the field of materials science for the last ten years and it has been accelerate by emergence of useful data-infrastructures based on FAIR (findable, accessible, interoperable and reusable) data principles : NOMAD, OPTIMADE, Materials Project, AFLOW and OQMD. In order to facilitate utilization of these data-infrastructures, the data integration and classification of numerous kinds of metadata related to materials properties are required and then it helps this research community to perform more accurate prediction by artificial intelligence techniques. MatDX (Materials Data eXplorer) has been developed and focused on such integration and classification based on materials ontologies: classes and instances in material name, composition, compound, structure, property and applications. For the integration, MatDX has been developed as a kind of a data warehouse solution which can be a useful strategy for connecting multiple databases. Material tags have been introduced through classification by using the materials ontologies, and they are used to search and view detailed information for interesting materials in an easy and quick way. Further process of ‘Analysis’ functionality to visualize statistically meaningful relationships has been served in an interactive way.
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Data driven approach has been used extensively for novel materials discovery in the field of materials science for the last ten years and it has been accelerate by emergence of useful data-infrastructures based on FAIR (findable, accessible, interoperable and reusable) data principles : NOMAD, OPTIMADE, Materials Project, AFLOW and OQMD. In order to facilitate utilization of these data-infrastructures, the data integration and classification of numerous kinds of metadata related to materials properties are required and then it helps this research community to perform more accurate prediction by artificial intelligence techniques. MatDX (Materials Data eXplorer) has been developed and focused on such integration and classification based on materials ontologies: classes and instances in material name, composition, compound, structure, property and applications. For the integration, MatDX has been developed as a kind of a data warehouse solution which can be a useful strategy for connecting multiple databases. Material tags have been introduced through classification by using the materials ontologies, and they are used to search and view detailed information for interesting materials in an easy and quick way. Further process of ‘Analysis’ functionality to visualize statistically meaningful relationships has been served in an interactive way.
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The most important aim of these services is to enable researchers to discover new materials for target properties based on numerous research data. MatDX including three sub-categories of PubDX (for the published data), ExpDX (for the experimental data) and CalcDX (for the calculated data), is ready to be used through the address of http://materials.chemdx.org. |
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The most important aim of these services is to enable researchers to discover new materials for target properties based on numerous research data. MatDX including three sub-categories of PubDX (for the published data), ExpDX (for the experimental data) and CalcDX (for the calculated data), is ready to be used through the address of http://materials.chemdx.org. |
