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The importance of making ELN and registration systems semantically aware [Webinar]

One of the most valuable assets for any organisation is its data. Electronic Laboratory Notebooks (ELNs), registration and assay applications hold vast amounts of data and hold key information on experimental design, execution and results. However, most organisations are unable to fully utilise and unlock valuable insights from these resources.

Whilst the forms in which data is captured have structure, the language entered within a given field can be heterogeneous, unstructured free text or as attachments, with the ability to mine it limited to rudimentary text and keywords searches.

During this webinar you will learn how together SciBite and Dotmatics plan to offer a comprehensive data capture and management solution. We will discuss workflows that would allow our customers to structure ELN and Registration data at the point of entry ensuring consistent language is implemented across the organisation, and retrospectively unlocking data in accordance with the principals of FAIR (Findable, Accessible, Interoperable and Reusable) data. This would facilitate robust and reproducible search and analytics.

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Sam Shelton
Director of Alliances, SciBite

Sam leads partnerships and alliances at SciBite, working collaboratively with existing partners and developing new partnerships aligned to SciBite’s strategic goals. He has a strong technical background in the life sciences, with a PhD in Protein Biochemistry from the University of Nottingham and post-doctoral training in bioinformatics within the department of Neurosurgery at the University of California San Francisco.

Prior to Joining SciBite he held technical sales and commercial roles at Carl Zeiss and most recently led business development at Repositive, building relationships with contract research organisations, biotech’s and pharma companies, facilitating data exchange and search across multiomic datasets. He has a good grasp of the challenges of dealing with unstructured scientific data, and collaboratively developing practical solutions to overcome these.

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