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Sprinkling a little Semantic Enrichment into your Data Catalogue
This blog focuses on the use and value of Data Catalogues and Master Data Management tools, and how the additional layer of Semantics is required in order to truly see their value for enterprises looking to better manage their data.
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A day with the FAIRplus project: Implementing FAIR data principles in industrial life science research
Here's how some of the SciBite team got on at the FAIRplus SME and Innovation Forum.
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Unlocking insight from scientific literature in under-supported languages through Machine Learning approaches
In this blog, we delve into how we applied novel machine learning and curation methods to Japanese language literature, techniques we believe are transferable to other under-supported languages.
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What exactly is a Knowledge Graph: Using Semantic Enrichment to connect the dots
At a time where more and more of our customer projects revolve around knowledge graph creation, we thought it was about time we blogged on what exactly a knowledge graph is and explain a bit more about how our semantic enrichment technology is being used to facilitate the production of such a powerful data model.
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The 12 days of Machine Learning tips for creating labelled training data
On the first day of Christmas SciBite gave to me... 12 top tips for creating labelled Machine Learning training data.
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SciBite brings together world’s top life science leaders for annual User Group Meeting
Cambridge, UK – SciBite, the award-winning semantic technology company, recently hosted its annual User Group Meeting at the Wellcome Genome Campus in Cambridge UK, where discussions around ontologies, deep learning and FAIR data dominated the day.
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SciBite gathers ‘clean data’ inspired life science leaders at US-based customer meeting
Last week SciBite hosted its annual US-based customer meeting in Boston MA, gathering representatives from 12 of the world’s major life sciences organisations and sparking ‘clean data’ discussions.
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How to use Ontologies to unlock the full potential of your Scientific Data – Part 2
This blog post focuses on mapping, building and managing ontologies. In my previous blog, I described what ontologies are and how you can use them to make the best use of scientific data within your organisation. Here I’ll be expand upon this and focus on mapping, building and managing ontologies.
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How to use Ontologies to unlock the full potential of your Scientific Data – Part 1
In the first of this two-part blog, I describe what ontologies are and how you can use them to make the best use of scientific data within your organisation.
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The SciBite difference – It’s all about your data
In this blog post SciBite's CSO and Founder Lee Harland addresses a very common question we are often asked by potential customers and partners...
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A Hacker’s Guide to Understanding Bio-ontology Jargon
Perfect for those new to bio-ontologies or who work with ontologists - a whole new vocabulary deciphered!
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SciBite Acquires FactBio
Award-winning life science technology provider acquires exciting semantic data management startup
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High Performance Ontology Engineering
One of the key aims of SciBite is to help our customers work with public ontologies in text mining applications. While these ontologies are very valuable resources, they are often built for the purpose of data organisation, not text mining.
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The 5 Star of Structured Data
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.
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