Enhancing the production and publication of evidence-based healthcare systems through linked data and semantic technologies
The healthcare and life-sciences sector has been an early adopter of linked data and semantic technologies driven from academic projects and research. There is widespread adoption and use of use of large open datasets and taxonomies to describe the clinical healthcare domain such as SNOMED-CT, RxNorm, MedDRA, WHO-ATC, and MeSH.
Through our work with the Cochrane Collaboration, Data Language has significant experience in the use of RDF based linked data in this field. We have worked together with Cochrane to developer a PICO ontology framework (Population, Intervention, Comparator and Outcome) for the expression of evidence in clinical trials and the construction of an extensive best of breed vocabulary drawing from, and linking out to, the open datasets widely used in the healthcare sector.
Building practical, maintainable, production ready data systems using the technologies that often dont make it out of the R & D labs
Life science vocabularies
Evidence based healthcare
The use of linked data to express and describe clinical evidence is an ideal mechanism for making published content machine interpretable.
Semantic metadata powers up search and discovery of scientific material
Allowing the creation of structured, well formed, evidenced based questions
How do you maximise the impact of evidence based health information when it is locked in text documents. The ability to ask questions across the set of knowledge, and to share insights between people and systems is constrained.
Develop domain specific models to describe the questions being answered. Describe these models with standards based vocabularies and associate them with the evidence. This unlocks the ability for your data to contribute to, and enrich the evidence ecosystem.
"Data Language have helped Cochrane transform from a document centric organisation to a data centric one. Their knowledge of linked data and data strategy is world class. They deliver."
I was impressed with how quickly the Data Language team was able to grasp the unique features of our content and with the great fit between the approaches they suggested and our needs and those of our users.
If you would like to know more about Data Language or have a project you would like to discuss with us, then please get in touch.