One and a half years ago we started to work with Amgen to help them improve the way they search and retrieve research data. They were looking for a solution that could aggregate and interlink their internal research data, enrich it with public data and provide an appealing, user-friendly interface for end-users.Read more
Displaying articles related to "Functionalities"
In the last few years, the number of public data sources integrated into DISQOVER has grown steadily and we crossed the triple digit barrier in 2016. Nevertheless, the number of data sources on our waiting list for integration is growing just as fast.Read more
One of our missions is to directly and indirectly help patients by aggregating and linking both private and public data. A direct help is to facilitate awareness about health and disease by providing proper information about prevention, diagnosis and treatment, amongst other things.Read more
We are very excited to announce the release of version 3.0 of our DISQOVER platform. After introducing federation in versions 2.x, we succeeded in unlocking a whole new dimension of semantic data in this 3.0 version with the typed links. But wait, there is more! We have also greatly increased usability and flexibility in areas such as discovery management, exporting and dashboards. Can't wait to learn more? Read on!Read more
In my previous blog, I tried to explain that the usage of different disease classifications or encodings in data sources like the US and EU clinical trial registries, doesn’t hamper the integration and linking of this kind of data.
Disease classifications are also used to precisely define diseases in other contexts like epidemiology, pharmacovigilance, toxicology, pharmacology, genetics, etc. This data is scattered across a plethora of data sources, maintained by different governmental and other non-profit organizations like research consortia and institutes or individual research groups. If they are keen on providing meaningful and useful data, data providers try to avoid using disease terms that aren’t defined precisely in an ontology.Read more
Companies that host their own setup of DISQOVER know that a crucial step in the process of making data available is the indexing. In the past few months, we have optimized this process. Indexing now runs up to 3 times faster while the logging has been more readable and more informative.Read more
We are delighted to inform you that DISQOVER, our linked open data platform, is now freely available for everybody. All you need is to do is create an account on DISQOVER.com and you too can begin finding more open data. DISQOVER contains 110+ public data sources that are converted into 5 star, semantic data formats by ONTOFORCE and its partners.Read more
Human beings, and to a greater extent scientists, try to order items for a purpose. In biomedical sciences, probably no other subject is more diversely ordered or classified as human conditions or diseases – hereinafter abbreviated as ‘diseases’. None of these classifications claims to be the one and only truth or is able to serve all purposes. Instead, many classifications co-exist and are widely accepted – or enforced – by the various stakeholders in life sciences: lab scientists, clinicians, pharmaceutical and biotech firms, regulatory bodies, governments, etc. With different classifications come different definitions of terms even if they are highly similar or have exactly the same meaning.
But what about searching, comparing and analyzing similar data where different diseases classifications are applied? Or what about compiling data about diseases that are produced and maintained for a specific purpose?Read more
Around 40 participants joined us for our ‘Big Data Workshop: Getting knowledge out of (Big) data’. Hans Constandt, CEO, and Filip Pattyn, Product Manager and Bioinformatician at ONTOFORCE, introduced and demonstrated DISQOVER – our platform to quickly discover insights out of vast amounts of data.Read more