New functionalities in 3.12.beta

Right, before we dive into summer, we want to inform you of some great new features in DISQOVER.

What’s new

The first new feature is something that a lot of users have been looking for: being able to extend your search terms with known synonyms. We already have the functionality to semantically recognize a wide range of terms. Now, after recognising a search term, additional synonyms are suggested, offering you a broader coverage of potential search results.

For example: before, when you entered a search term like “human”, DISQOVER showed you all the hits of that word in different data types and it also highlighted that this term has a semantic hit with an organism “human”.  Now, with the new release, you will be told that the concept “human” also has a synonym like “Humans” that could be used to add to your query string. This extends the number of hits for publications from 2.9 million (for “human”) to 17 million (for “human” or “Humans”). Just so you know: at all times you are in control to include or exclude synonyms.

Secondly, we’ve extended the functionalities of data federation. Data federation means that internal data in your local installation of DISQOVER can be enriched with data from the public version of DISQOVER. This is a unidirectional process to ensure that your internal data is only visible on the local set-up. Now, filters for public data can include your local data too. This gives you a truly integrated search experience of both local and public data.

For example, assume you have an internal data source with publications. One of the filters could be the publication type (journal article, review etc.), that is already used in the public DISQOVER system. Since the new release, it’s possible to have one filter capable of showing the relation types of internal and public publications. Applying a filter will, therefore, result in a list of entries that could be a combination of internal and external data.

Next, we have simplified the DISQOVER data ingestion process flow. You still have to import every data source with one similar instruction. But, up until now, this process had to be finalized with a series of instructions making the data federation possible, setting the data source metadata visualisation and starting the indexing process. These last three technical steps are now unified into one. This simplifies the whole Extract, Transform and Load (ETL) process and will further reduce the occurrence of potential problems during that process.

Other additions are:

  • A section overview for fast navigation through individual data records
  • The possibility to use images instead of labels in a facet. A first application will be the visualisation of chemical substructures as filter entries.

 

We hope you enjoy using these features as much as we did implementing them!

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