Auto-populating ontologies: Data-extraction beyond single properties with ChemDataExtractor 2.0 and TableDataExtractor

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• Juraj Mavracic
• Monday 02 March 2020, 16:30-17:00
• Mott Seminar (531) room, top floor of the Mott Building, in the Cavendish Laboratory, West Cambridge..

If you have a question about this talk, please contact Bingqing Cheng .

The abundance of data found in heterogeneous sources, such as scientific publications, has forced the development of automated techniques for data extraction. Indeed, in many data-driven methodologies for materials science, the biggest problem is the lack of usable data to begin with, with databases being expensive to build and maintain.

With ChemDataExtractor 2.0 in combination with TableDataExtractor, we present a framework that goes beyond the extraction of single properties and enables the auto-population of user-defined ontologies of interest.

Thus, getting closer to seamless integration of heterogeneous data sources into the data-driven research framework.

This talk is part of the Machine learning in Physics, Chemistry and Materials discussion group (MLDG) series.

This talk is included in these lists:

• Hanchen DaDaDash
• Lennard-Jones Centre external
• Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
• Mott Seminar (531) room, top floor of the Mott Building, in the Cavendish Laboratory, West Cambridge.

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