Abstract
If there is a domain where data management becomes an intensive Big Data issue, it is the genomic domain, due to the fact that the data generated day after day are exponentially increasing. A genomic data management strategy requires the use of a systematic method, intended to assure that the right data are identified, using the adequate data sources, and linking the selected information with a software platform based on conceptual models, which allows guaranteeing the implementation of genomic services with quality, efficient and valuable data. In this paper, we select the method called “SILE” –for Search, Identification, Load and Exploitation-, and we focus on validating its accuracy in the context of a concrete disease, the Colorectal Cancer. The main contribution of our work is to show how such methodological approach can be applied successfully in a real and complex clinical context, providing a working environment where Genomic Big Data are efficiently managed.
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Notes
- 1.
Research Center on Software Production Methods (PROS), http://www.pros.webs.upv.es/.
- 2.
Variation: Naturally occurring genetic differences among organisms in the same species [Scitable by Nature Education].
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HGVS Nomenclature: http://varnomen.hgvs.org/.
- 4.
Colorectal Cancer Atlas: http://colonatlas.org/index.html.
- 5.
The National Center of Biotechnology Information: https://www.ncbi.nlm.nih.gov/.
- 6.
Prognosis is defined as the likely course of a medical condition.
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Acknowledgement
The authors would like to thank members of the PROS Research Centre Genome group for the fruitful discussions regarding the application of CM in the medicine field. This work has been supported by the Spanish Ministry of Science and Innovation through project DataME (ref: TIN2016-80811-P) and the Research and Development Aid Program (PAID-01-16) of the Universitat Politècnica de València under the FPI grant 2137.
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León Palacio, A., García Giménez, A., Casamayor Ródenas, J.C., Reyes Román, J.F. (2018). Genomic Data Management in Big Data Environments: The Colorectal Cancer Case. In: Woo, C., Lu, J., Li, Z., Ling, T., Li, G., Lee, M. (eds) Advances in Conceptual Modeling. ER 2018. Lecture Notes in Computer Science(), vol 11158. Springer, Cham. https://doi.org/10.1007/978-3-030-01391-2_36
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