Over the 50 years how we collect and play music has changed dramatically from physical copies on Vinyl through to electronic mp3s. Each new technology often requires a new device and format to play yet it is still essentially just music.
Over the 50 years how we collect and play music has changed dramatically from physical copies on Vinyl through to electronic mp3s. Each new technology often requires a new device and format to play yet it is still essentially just music. As an end-user, you are simply wanting to listen to your ever-expanding music collection but are face with either using multiple devices or integrating your collection onto the latest format.
Many parallels can be drawn with scientific data. Science is an ever-advancing field, the increasing volume, variety and velocity of data generated through research activities require constant updates to the collection, storage and interrogation approaches.
Structured data architectures are frequently updated to satisfy these demands. Each time the architecture changes, all related connections, integrations and queries need to be reviewed and updated if necessary. Multiply this effort out by all the different sources of information used in Scientific Research and you have a large job on your hands in simply maintaining an existing environment even before you think about expanding it.
At the Open PHACTS closing meeting in Vienna recently, our Chief Scientific Officer Lee Harland spoke about the challenges facing life scientists and the constantly evolving data space in particular (full slides available). One of the elements of this was a look at the changes in the architecture of the popular Chembl database which relates drugs and other chemicals to their biological effects over the last few years..
Watch how even just the red section where all compounds are stored evolves from just two tables to 17 tables in just a few years. In life sciences, we face a dual challenge of not only incorporating data of the future but also the fact that existing data will not standstill.
SciBite’s entity extraction software approaches this conundrum from a different direction. Rather than worrying about the music format or what device is required to play it with, we focus on the raw data much akin to reading the notes themselves. The notes form a pattern which when cross-referenced with your memory are identified as a track you know or like regardless of how and where the music is played.
Substitute the notes with scientific text and your musical mind with SciBite’s Life Science vocabularies covering millions of concepts and you needn’t worry about if/how the data is structured or what format it is stored in, just focus on the content.
That’s music to my ears…
Sir Tim Berners-Lee, the creator of the Internet, defined a 5-star deployment scheme for open data. In recent customer discussions, we’ve talked about a similar scheme to describe the status of data across their organisation and how text analytics can help contextualise unstructured data.
ReadScientific knowledge can be represented as relationships between things. Thousands or millions of such relationships make a knowledge graph or network analysis. SciBite technology enables extraction of these relationships, and in doing so, can uncover knowledge that might otherwise have remained hidden
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