Towards Automated Management and Analysis of Heterogeneous Data within Cannabinoids Domain

K. Koga, M. Spichkova, N. Mantri
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引用次数: 2

Abstract

Cannabinoid research requires the cooperation of experts from various field biochemistry and chemistry to psychological and social sciences. The data that have to be managed and analysed are highly heterogeneous, especially because they are provided by a very diverse range of sources. A number of approaches focused on data collection and the corresponding analysis, restricting the scope to a sub-domain. Our goal is to elaborate a solution that would allow for automated management and analysis of heterogeneous data within the complete cannabinoids domain. The corresponding integration of diverse data sources would increase the quality and preciseness of the analysis. In this paper, we introduce the core ideas of the proposed framework as well as present the implemented prototype of a cannabinoids data platform.
大麻素领域异构数据的自动化管理与分析
大麻素的研究需要从生物化学和化学到心理和社会科学等各个领域的专家的合作。必须管理和分析的数据是高度异构的,特别是因为它们是由非常多样化的来源提供的。许多方法侧重于数据收集和相应的分析,将范围限制在子领域。我们的目标是精心设计一个解决方案,允许在完整的大麻素领域内自动管理和分析异构数据。不同数据源的相应集成将提高分析的质量和准确性。在本文中,我们介绍了所提出的框架的核心思想,并提出了大麻素数据平台的实现原型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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