Research Data Management
Research data has proven to be a major asset for exploring scientific hypotheses across the biomedical industry. Using this data to their full potential is often not easy, especially when working across department and unit boundaries. This can be due to metadata that is inconsistently used or applied between sources, is missing or is used incorrectly.
Our RDM team can help you organize and manage your data so you can focus on the research questions and data analysis that you care about.
A semantic model allows you to standardize and harmonize structured data to make it comprehensible for both humans and machines. It is an essential step towards making data more FAIR and it facilitates data integration within and across R&D data domains.
The Hyve can create semantic models that cover distinct pharma and biomedical domains, such as small and large molecule research, omics, and clinical.
Rather than making existing data more FAIR, The Hyve can help you implement the FAIR principles by building and/or customizing data management infrastructure or systems and make both existing and newly collected research data FAIR.
The Hyve can run business analysis and solution design, in which we help your organization investigate the current state of data management and create a solution direction according to your use case. Fairspace is an example of a FAIR by Design software platform that was developed by The Hyve.
Knowledge graphs typically connect entities from multiple domains, with formal semantics provided by a semantic model. It serves as a flexible framework for data integration, harmonization, analytics, and sharing of data from multiple sources. This data, organized in a graph, can then be queried and navigated in a uniform manner.
The Hyve can build knowledge graphs that integrate data from different sources across pharma R&D, and cover pharmacological (small/large molecules), omics, and clinical data.
Data is difficult to find for researchers in any site, domain, or folder.
Users are unable to share their research data with other teams and collaborate.
Data is not integrated or reused easily within the company.
Querying data is time-consuming, complicated and involves manual processes.
Let's work together to overcome these challenges!
Pistoia Alliance is a global, not-for-profit, members’ organization with more than 100 members collaborating to lower barriers to innovation in life science and healthcare R&D. Pistoia Alliance projects intend to overcome common obstacles to innovation in these sectors and to transform R&D. The Hyve has been an active member of the alliance since 2016 and contributes to the FAIR principles initiatives within the community.
The FAIRplus consortium develops tools and guidelines to make life science data more FAIR. It has 22 partners from academia and the pharmaceutical industry, and runs from January 2019 to December 2022. The Hyve’s contribution to the consortium is the FAIRification of IMI datasets, the FAIRplus data management plan and the FAIR cookbook recipes.
“I had the pleasure of working with The Hyve and together develop Metatree, a solution to store metadata on samples measured in different projects. Their commitment and expertise were evident in every aspect of our collaboration, from the initial planning stages to the final delivery.â€
Frans van der Kloet, Biosystems data analysis group at SILS, University of Amsterdam
