The management of the exponential growth of data that Next Generation Sequencing techniques produce has become a challenge for researchers that are forced to delve into an ocean of complex data in order to extract new insights to unravel the secrets of human diseases. Initially, this can be faced as a Big Data-related problem, but the genomic data have particular and relevant challenges that make them different from other Big Data working domains. Genomic data are much more heterogeneous; they are spread in hundreds of repositories, represented in multiple formats, and have different levels of quality. In addition, getting meaningful conclusions from genomic data requires considering all of the relevant surrounding knowledge that is under continuous evolution. In this scenario, the precise identification of what makes Genome Data Management so different is essential in order to provide effective Big Data-based solutions. Genomic projects require dealing with the technological problems associated with data management, nomenclature standards, and quality issues that only robust Information Systems that use Big Data techniques can provide. The main contribution of this paper is to present a Big Data-driven approach for managing genomic data, that is adapted to the particularities of the domain and to show its applicability to improve genetic diagnoses, which is the core of the development of accurate Precision Medicine.

管理下一代测序技术产生的数据呈指数级增长已成为研究人员面临的挑战，他们被迫深入研究复杂数据的海洋，以提取新的见解来解开人类疾病的秘密。最初，这可以作为与大数据相关的问题来面对，但是基因组数据具有特殊且相关的挑战，这使得它们不同于其他大数据工作领域。基因组数据更加异质；它们分布在数百个存储库中，以多种格式表示，并且具有不同的质量级别。此外，从基因组数据中获得有意义的结论需要考虑持续进化的所有相关周围知识。在这种情况下，准确识别基因组数据管理如此不同的原因对于提供有效的基于大数据的解决方案至关重要。基因组项目需要处理与数据管理、命名标准和质量问题相关的技术问题，而只有使用大数据技术的强大信息系统才能提供这些技术问题。本文的主要贡献是提出一种大数据驱动的基因组数据管理方法，该方法适用于该领域的特殊性，并展示其在改善基因诊断方面的适用性，这是发展精准精准医学的核心. 只有使用大数据技术的强大信息系统才能提供的质量问题。本文的主要贡献是提出一种大数据驱动的基因组数据管理方法，该方法适用于该领域的特殊性，并展示其在改善基因诊断方面的适用性，这是发展精准精准医学的核心. 只有使用大数据技术的强大信息系统才能提供的质量问题。本文的主要贡献是提出一种大数据驱动的基因组数据管理方法，该方法适用于该领域的特殊性，并展示其在改善基因诊断方面的适用性，这是发展精准精准医学的核心.