Journal:Bridging data management platforms and visualization tools to enable ad-hoc and smart analytics in life sciences
| Full article title | Bridging data management platforms and visualization tools to enable ad-hoc and smart analytics in life sciences |
|---|---|
| Journal | Journal of Integrative Bioinformatics |
| Author(s) | Panse, Christian; Trachsel, Christian; Türker, Can |
| Author affiliation(s) | Functional Genomics Center Zurich |
| Primary contact | Email: cp at fgcz dot ethz dot ch |
| Year published | 2022 |
| Volume and issue | 19(4) |
| Article # | 20220031 |
| DOI | 10.1515/jib-2022-0031 |
| ISSN | 1613-4516 |
| Distribution license | Creative Commons Attribution 4.0 International |
| Website | https://www.degruyter.com/document/doi/10.1515/jib-2022-0031/html |
| Download | https://www.degruyter.com/document/doi/10.1515/jib-2022-0031/pdf (PDF) |
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Abstract
Core facilities, which share centralized research resources across institutions and organizations, have to offer technologies that best serve the needs of their users and provide them a competitive advantage in research. They have to set up and maintain tens to hundreds of instruments, which produce large amounts of data and serve thousands of active projects and customers. Particular emphasis has to be given to the reproducibility of the results. Increasingly, the entire process—from building the research hypothesis, conducting the experiments, and taking the measurements, through to data exploration and analysis—is solely driven by very few experts in various scientific fields. Still, the ability to perform data exploration entirely in real-time on a personal computer is often hampered by the heterogeneity of software, data structure formats of the output, and the enormous data file sizes. These impact the design and architecture of the implemented software stack.
At the Functional Genomics Center Zurich (FGCZ), a joint state-of-the-art research and training facility of ETH Zurich and the University of Zurich, we have developed the B-Fabric system, which has served for more than a decade an entire life sciences community with fundamental data science support. In this paper, we describe how such a system can be used to glue together data (including metadata), computing infrastructures (clusters and clouds), and visualization software to support instant data exploration and visual analysis. We illustrate our implemented daily approach using visualization applications of mass spectrometry (MS) data.
Keywords: accessible, findable, interoperable, and reusable (FAIR); integrations for data analysis; open research data (ORD); workflow
Introduction
Core facilities—which act as a discrete, centralized location for shared research resources for institutions or organizations[1]—aim to support scientific research where terabytes of archivable raw data are routinely produced every year.
References
- ↑ "Definitions". Research Core Facilities at Drexel University. Drexel University. 2023. https://drexel.edu/core-facilities/resources/definitions/.
Notes
This presentation is faithful to the original, with only a few minor changes to presentation, grammar, and punctuation. In some cases important information was missing from the references, and that information was added. The authors don't define "core facility" in the original text; a definition and citation is provided for this version.
