Organization
Erasmus University Rotterdam (EUR)
Location
The Netherlands
Industry
Education and research
Size
12,000+ employees
Use case
Analytics
Target data
Academic research data
Website
https://www.eur.nl/en
Erasmus University Rotterdam (EUR) is an international public research university in the Netherlands with more than 100 years of experience. Erasmus MC is the largest and one of the foremost academic medical centers and trauma centers in the Netherlands, whereas its economics and business school, Erasmus School of Economics and Rotterdam School of Management are well known in Europe and beyond. Currently, Erasmus University Rotterdam has been placed in the top 100 universities in the world by four prominent international ranking tables.
The university places a crucial emphasis on data, integrating data analysis and research methodologies into its programs and the execution of academic research, including the publication of papers. However, the evolving landscape of data utilization raises important privacy implications, prompting the university to navigate the balance between utilizing the full data potential and safeguarding individual privacy rights.
Do you use proprietary and/or personal data in your research and therefore cannot share it? Now, Erasmus University may be able to help you with this by creating a synthetic dataset.
As part of the research integrity solutions of the Erasmus University Rotterdam (EUR), EUR has announced the availability of the Syntho Engine which is now positioned as a data management solution & service for synthetic data generation. As for using the Syntho Engine, all Erasmus University researchers are encouraged to use the platform as much as possible.
Synthetic datasets mimic real datasets by preserving their statistical properties and the relationships between variables. It is important to note that this method also reduces disclosure risk to zero, as no record in the synthetic dataset represents a real individual.
By sharing synthetic datasets that mimic original datasets that could not otherwise be made open, researchers, the university and stakeholders can now facilitate data exploration while maintaining participant privacy. Synthetic data allows researchers to access more data that would not simply be possible with real personal data. This allows for data exploration with more data working toward earlier hypothesis validation and results in the research process.
By sharing synthetic datasets that mimic original datasets that could not otherwise be made open, researchers can ensure the reproducibility of their results. As an alternative to publishing and/or sharing real personal data for reproducibility purposes, researchers can now publish and/or share synthetic data.
Study courses continue to contain more analytics related tasks. As for this, representative data is needed to allow students to learn how to build and execute analytics solutions with representative data. Synthetic data can be made available as part of study courses to facilitate this and to allow students to learn to build analytics models in representative scenarios.
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