Fractalis: a scalable open-source service for platform-independent interactive visual analysis of biomedical data

Abstract Background Translational research platforms share the aim of promoting a deeper understanding of stored data by providing visualization and analysis tools for data exploration and hypothesis generation. However, such tools are usually platform bound and are not easily reusable by other systems. Furthermore, they rarely address access restriction issues when direct data transfer is not permitted. In this article, we present an analytical service that works in tandem with a visualization library to address these problems. Findings Using a combination of existing technologies and a platform-specific data abstraction layer, we developed a service that is capable of providing existing web-based data warehouses and repositories with platform-independent visual analytical capabilities. The design of this service also allows for federated data analysis by eliminating the need to move the data directly to the researcher. Instead, all operations are based on statistics and interactive charts without direct access to the dataset. Conclusions The software presented in this article has a potential to help translational researchers achieve a better understanding of a given dataset and quickly generate new hypotheses. Furthermore, it provides a framework that can be used to share and reuse explorative analysis tools within the community.


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Availability of data and materials All datasets and code on which the conclusions of the paper rely must be either included in your submission or deposited in publicly available repositories (where available and ethically appropriate), referencing such data using a unique identifier in the references and in the "Availability of Data and Materials" section of your manuscript. and hypothesis generation. However, such tools are usually platform-bound and are not easily 28 reusable by other systems. Furthermore, they rarely address access restriction issues when 29 direct data transfer is not permitted. In this article we present an analytical service that works 30 in tandem with a visualization library to address these problems. 31 Findings: Using a combination of existing technologies and a platform-specific data 32 abstraction layer we developed a service that is capable of providing existing web-based data 33 warehouses and repositories with platform-independent visual analytical capabilities. The 34 design of this service also enables federated data analysis by bringing the analysis to the data 35 and only present results to the researcher. 36