This blog is the third of a four-part series that explores the importance of FAIR (Findable, Accessible, Interoperable, Reusable) principles for pharmaceutical companies looking for a data platform to tackle their most critical business problems.
Data is interoperable when it can be integrated with other data sources and when other applications can easily interface with it. In the pharmaceutical industry, MarkLogic has successfully been used for mission-critical applications within Johnson & Johnson and many other top global pharma companies.
Most of our pharma clients are using ontologies to great effect. By using ontologies, these companies get an enriched view of their data. Properties of data can be defined with authority across datasets, which improves the confidence in substantiating facts from the data.
An ontology can give you a centralised place to define your data, which leads to greater possibilities when integrating data. Datasets can be integrated from disparate sources and even from beyond the organisation itself. Some powerful outcomes of using ontologies include gaining greater insight into the connections within your data and even the possibility of inferring non-obvious facts.
For pharma companies, there is a rich ecosystem of ontology and linked datasets that can be used to enhance your own data. Sources like Snomed, RxNorm, UniProt and PubMed are all useful sources for R&D, and MarkLogic is able to easily integrate them into a Data Hub alongside a pharma company’s own data such as drug development data, clinical trials and market data as part of our Pharma Research Hub offering.
By integrating data, organisations can boost the insights delivered from their data, but perhaps more importantly, they can also get a ‘single source of truth’ knowledge base that can benefit the entire company. Knowledge and data will no longer be lost within small factions of the enterprise.
Consistently among the pharma companies we have engaged with, we see that the speed at which they can integrate data from disparate data sources using MarkLogic technology is dramatically faster than if they used traditional relational database technologies. Indeed, many companies begin speaking with us after a failed attempt at integrating data using a relational database with an extract, transform, load (ETL) pipeline.
MarkLogic does away with ETL and upfront modelling of your data, with the result being faster time to results and a greater agility to respond to changing business demands.
Duncan is a Solutions Engineer at MarkLogic with a particular interest in Linked Data, web applications and visualisations. Duncan has a background in web application development, having worked in several UK startups before specialising in Linked Data and enterprise data integration.
Duncan has spoken at meetups and conferences on topics such as graph visualisation, databases, Linked Data and JavaScript development.
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