[ Recorded Presentation] FAIR DATA, DATA Catalogs, and the foundations of AI artificial Intelligence
At the Paperless Lab Academy 2019 held last spring at the Lake Maggiore, we discuss intensively the archival part of the eData life cycle. Automation of the laboratory processes is all about data management.
The technology available nowadays allows definitely easier integration between systems of different type and with instruments and devices too. So many information can be collected adequately and in the most compliant manner. Yet the archiving tends to be seen as the very last step of a data and considered as the last item in a digitalization project.
Most of the topics discussed at the #PLA2019 were challenging this assumption. There is much more involved in archiving than just keeping those data in a safe place.
FAIR data principles presentation at #PLA2019
In fact, if approached at the right moment, the FAIR principles should be taken into consideration so that data are Findable, Accessible, Interoperable and Reusable.
Eric Little, at Osthus, presented the FAIR data principles and discussed how applying them could help to build Data Catalogs, where data is much easier to find, access and integrate across large organizations.
From then, advanced statistical methods could be applied to this framework in order to provide advanced analytics and ultimately AI-like capabilities. Find below the recorded presentation.
In a data-driven world, companies that succeed in gaining actionable insights through data management will be able to innovate faster, develop better
In an era dominated by technological innovation, the implementation of a laboratory information management system (LIMS) is one of the most important
The advent of Industry 4.0 technologies, such as the Internet of Things (IoT), Big Data analytics, artificial intelligence (AI), and advanced robotics