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Towards a Model-Driven Approach for Big Data Analytics in the Genomics Field

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Advances in Conceptual Modeling (ER 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13650))

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Abstract

The use of techniques such as Next Generation Sequencing has allowed a fast increase in data generation due to the reduction of processing costs. What at the beginning seemed to be an important step forward for the development of new approaches such as Precision Medicine, turned into an exponential growth of data that currently challenges healthcare professionals and researchers. Since the problems derived from the storage and management of vast amounts of heterogeneous data are well-known for the Big Data and Information Systems communities, the application of this knowledge to the genomic data domain can help to improve the management of the data, reduce the bottlenecks, and reveal new insights on the causes of human disease. In this way, this work is focused on the problem of data storage by proposing a Big Data architecture supported by a model-driven approach to ensure an efficient and dynamic storage of genomic data. The proposed architecture has been designed considering the main requirements for an efficient data integration and for supporting data analysis tasks.

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Notes

  1. 1.

    JSON schema specification: https://json-schema.org/.

  2. 2.

    Python Package Index: https://pypi.org/,.

  3. 3.

    https://hadoop.apache.org/.

  4. 4.

    https://hive.apache.org/.

  5. 5.

    https://spark.apache.org/.

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Acknowledgements

This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the R &D Units Project Scope: UIDB/00319/2020, and by the Spanish Ministry of Universities and the Universitat Politècnica de València under the Margarita Salas Next Generation EU grant.

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Authors and Affiliations

  1. ALGORITMI Research Centre, University of Minho, Guimarães, Portugal

    Ana Xavier Fernandes, Filipa Ferreira, Ana León & Maribel Yasmina Santos

  2. Valencian Research Institute for Artificial Intelligence (VRAIN), Universitat Politècnica de València, Camí de Vera S/N, Valencia, Spain

    Ana León

Authors
  1. Ana Xavier Fernandes
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  2. Filipa Ferreira
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  3. Ana León
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  4. Maribel Yasmina Santos
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Corresponding author

Correspondence to Ana Xavier Fernandes .

Editor information

Editors and Affiliations

  1. University of Twente, Enschede, The Netherlands

    Renata Guizzardi

  2. Johannes Kepler University Linz, Linz, Austria

    Bernd Neumayr

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Fernandes, A.X., Ferreira, F., León, A., Santos, M.Y. (2022). Towards a Model-Driven Approach for Big Data Analytics in the Genomics Field. In: Guizzardi, R., Neumayr, B. (eds) Advances in Conceptual Modeling. ER 2022. Lecture Notes in Computer Science, vol 13650. Springer, Cham. https://doi.org/10.1007/978-3-031-22036-4_1

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  • DOI: https://doi.org/10.1007/978-3-031-22036-4_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-22035-7

  • Online ISBN: 978-3-031-22036-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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