Digitalization in chemicals R&D has promise to greatly accelerate innovation rates. In particular, data analytics and data-driven approaches to supplement traditional lab experimentation are attracting lots of interest. A major obstacle to this vision is the general lack of availability of data in a curated and contextualized form. This is despite many organizations investing in technologies to digitalize experimental data capture and move traditional paper-based lab notebooks to their digital counterparts.

Data intelligence fills the gap between R&D IT infrastructure designed for data capture and scientists’ need to extract these data in a meaningful way. This webinar covers an approach that combines data federation, contextualization and out-of-the-box scientific domain models to solve various complex data extraction use cases.