From big data to smart data: A genomic information systems perspective

• Published in: Proceedings of the ... International Conference on Research Challenges in Information Science pp. 1 - 11
• Main Authors: Palacio, Ana Leon, Lopez, Oscar Pastor
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.05.2018
• Subjects: Big Data; Bioinformatics; Conceptual Modelling; Data integrity; Data models; Data Quality; Diseases; Genomics; Smart Data
• ISSN: 2151-1357
• DOI: 10.1109/RCIS.2018.8406658

During the last two decades, data generated by Next Generation Sequencing Technologies have revolutionized our understanding of human biology and improved the study on how changes (variations) in the DNA are involved in the risk of suffering a certain disease. A huge amount of genomic data is publicly available and frequently used by the research community in order to extract meaningful and reliable gene-disease relationships. However, management of this exponential growth of data has become a challenge for biologists; under such a big data problem perspective, they are forced to delve into a lake of complex data spread in over thousand heterogeneous repositories, represented in multiple formats and with different levels of quality; but when data are used to solve a concrete problem only a small part of that "data lake" is really significant; this is what we call the "smart" data perspective. Using conceptual models and the principles of data quality management, adapted to the genomic domain, we propose a systematic approach to move from a big data to a smart data perspective. The aim of this approach is to populate an Information System with genomic data which must be accessible, informative and actionable enough to extract valuable knowledge.