Articles tagged: Clean data

  1. Delivery of precision medicine through alignment of clinical data to ontologies

    Precision medicine is changing the way that we think about the treatment of disease, moving from broad-acting therapies to therapies tailored to the individual patient. This increasingly relies on real-world data (RWD), encompassing a diverse range of sources, spanning multi-omic molecular characterisation of the patient’s condition, clinical presentation, treatment, and broader medical histories.

  2. Sprinkling a little semantic enrichment into your data catalog

    This blog focuses on the use and value of data catalogs and Master Data Management (MDM) tools and how the additional layer of Semantics is required in order to truly see their value for enterprises looking to manage their data better.

  3. A day with the FAIRplus project: Implementing FAIR data principles

    Here's how some of the SciBite team got on at the FAIRplus Project SME and Innovation Forum.

  4. Machine Learning insights from Japanese language academic text

    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.

  5. 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.

  6. Using 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 organization. Here I’ll expand upon this and focus on mapping, building, and managing ontologies.

  7. Using 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.

  8. How ontology enrichment is essential in maintaining clean data

    Ontologies have become a key piece of infrastructure for organisations as they look to manage their metadata to improve the reusability and findability of their data. This is the final blog in our blog series 'Ontologies with SciBite'. Follow the blog series to learn how we've addressed the challenges associated with both consuming and developing ontologies.

  9. 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...

  10. 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!

  11. 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 organization, not text mining.

  12. 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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