In order for scientific communication to be effective, scientific publications and their data must be freely available. This is also required by high-level scientific publications: publications manuscript should be provided together with the links to the original data, and after the release of the publication, – also reveal research data supporting the results.
A new framework was needed to address a number of important scientific research challenges. On the one hand, there was a need for a single national system, allowing check if scientific research do not duplicate each other or can be reused repeatedly.
On the other, it was important not only to make scientific research data publicly available to the general public but also to ensure its security. Third, the objectivity of scientific knowledge is subject to high demands, and authors and other researchers needed to be able to return to and verify the original data.
The infrastructure designed and implemented by “Novian Technologies” ensured efficient, reliable, and long-term data storage, data format maintenance, and the possibility to expand the solution in the future.
Both disk storage and tape libraries were used to implement the solution, and the hierarchical file system combined the features of these technologies – data availability and storage efficiency. During the project, information security and data integrity measures and many other innovative technological solutions were implemented.
The project, launched in 2012, was completed in 2015, and 15 science and training and medical institutions contributed to its implementation. The created archive can collect and store empirical data of research in various fields of science, as well as other information related to this research, for a long time. Users are provided with a variety of analytical tools, data exchange, electronic services, and other functionalities.
Besides, the national scientific data archive was linked to the biomedical data archive of one of the biggest hospitals in Lithuania, Santaros clinics, multidimensional data visualization, grouping, classification and analysis tools were introduced, and the possibility to process scientific data from the archive with parallel and distributed computational resources was performed, allowing for data analysis requiring high levels of computing resources.