Towards Designing Conceptual Data Models for Big Data Warehouses: The Genomics Case

[EN] Data Warehousing applied in Big Data contexts has been an emergent topic of research, as traditional Data Warehousing technologies are unable to deal with Big Data characteristics and challenges. The methods used in this field are already well systematized and adopted by practitioners, while research in Big Data Warehousing is only starting to provide some guidance on how to model such complex systems. This work contributes to the process of designing conceptual data models for Big Data Warehouses proposing a method based on rules and design patterns, which aims to gather the information of a certain application domain mapped in a relational conceptual model. A complex domain that can benefit from this work is Genomics, characterized by an increasing heterogeneity, both in terms of content and data structure. Moreover, the challenges for collecting and analyzing genome data under a unified perspective have become a bottleneck for the scientific community, reason why standardized analytical repositories such as a Big Genome Warehouse can be of high value to the community. In the demonstration case presented here, a genomics relational model is merged with the proposed Big Data Warehouse Conceptual Metamodel to obtain the Big Genome Warehouse Conceptual Model, showing that the design rules and patterns can be applied having a relational conceptual model as starting point. This work has been supported by FCT - Fundação para a Ciên-cia e Tecnologia within the Project Scope: UID/CEC/00319/2019, the Doctoral scholarship PD/BDE/135100/2017 and European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internationalization Programme (COMPETE 2020) [Project nº 039479; Funding Reference: POCI-01-0247-FEDER-039479]. We also thank both the Spanish State Research Agency and the Generalitat Valenciana under the projects DataME TIN2016-80811-P, ACIF/2018/171, and PROMETEO/2018/176. Icons made by Freepik, from www.flaticon.com. Galvão, J.; León-Palacio, A.; Costa, C.; Santos, MY.; Pastor López, O. (2020). Towards Designing Conceptual Data Models for Big Data Warehouses: The Genomics Case. Springer Nature. 3-19. https://doi.org/10.1007/978-3-030-63396-7_1 Krishnan, K.: Data Warehousing in the Age of Big Data. Morgan Kaufmann is an imprint of Elsevier, Amsterdam (2013) Santos, M.Y., Costa, C.: Big Data: Concepts, Warehousing and Analytics. River Publishers, Aalborg (2020) Cuzzocrea, A., Moussa, R.: Multidimensional data