Custom implementations

Depending on your requirements, we are able to support you in integrating your own private data into the tools we created or build your own applications around your and our data. Our natural language processing, indexing, entity recognition services are available to streamline the development of powerful solutions from the Dimensions ‘toolbox’.

Integrate your data into a private Dimensions instance

The Dimensions data provides a view on the entire research community with all its facets – but you might be interested in seeing your own data which is strictly private side by side with our data.
This can be realized with a ‘Private Instance’ version of Dimensions: we are creating a physically separate instance of Dimensions and confidential client data can be integrated via a standardized import.

Example use cases 

Research funders — A Dimensions private instance allows you to integrate the submitted grant applications and analyze them side by side – to see the grant application history of a researcher, to identify emerging topics by looking at the grant applications or see automatically the context for an applicant covering publications indicators and network.

Publishers — Search and scan research manuscripts submitted in the past and more recently and explore immediately the context for the authors – both individually and taking their institutional context into account.

Custom applications – to efficiently realize tailored solutions involving Dimensions data

Sometimes, the standard ways in which Dimensions allow you to do things are not perfectly suited to support your use cases. For example, while key opinion leaders (KOL) is about expert identification, a KOL use case can be quite specific – depending on the context of the drug or product in question. The Dimensions team has built in the past custom applications tailored exactly to the needs of the specific KOL scenario required – and the workflow aspects of identifying the right experts – or for other parts of the research community reviewer candidates rather than KOLs.

Integrate Dimensions content into your applications

The Dimensions content is available via API, as a data set on Google BigQuery or as a bulk data delivery. Our team who knows the data and the Dimensions enrichment services inside out – if you are interested in dynamically linking the Dimensions data into your internal systems – we are there to help with the design and the realization. 

Example scenario

The Dimensions data and services is used by a publisher to automatically assign incoming manuscripts in their internal system to the right editor and suggest automatically the best matching reviewers – also taking citation and altmetric indicators into account.

Interested in learning what we can do for your organization? Get in touch with our team to request more information.