数据科学的扩展:数据集标准化

Standards Pub Date : 2023-11-30 DOI:10.3390/standards3040028
Nuno Pessanha Santos
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引用次数: 0

摘要

随着科学技术的不断进步,处理能力和数据越来越多,数据分析技术的实施也更加直接。幸运的是,现有的在线数据存储能力也顺应了这一趋势,大量的数据可以免费或以低廉的价格在线存储。正如任何科学领域的每一次演变(或革命)一样,组织和共享这些数据对于促进新的研究或快速验证已获得的结果至关重要。为此,我们必须保证现有数据集与开发的软件(无论是商业软件还是开源软件)之间的互操作性。本文探讨了这一问题,分析了当前建立数据标准的举措,并对一些现有的在线数据集存储平台进行了比较。通过优势、劣势、机会和威胁(SWOT)分析,我们可以更好地理解提高该领域效率所应采取的战略,这直接取决于数据的特性。数据集标准的制定将直接加强学术界与产业界之间的合作和数据共享,通过直接的互操作性加快研发速度。
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The Expansion of Data Science: Dataset Standardization
With recent advances in science and technology, more processing capability and data have become available, allowing a more straightforward implementation of data analysis techniques. Fortunately, available online data storage capacity follows this trend, and vast amounts of data can be stored online freely or at accessible costs. As happens with every evolution (or revolution) in any science field, organizing and sharing these data is essential to contribute to new studies or validate obtained results quickly. To facilitate this, we must guarantee interoperability between existing datasets and developed software, whether commercial or open-source. This article explores this issue and analyzes the current initiatives to establish data standards and compares some of the existing online dataset storage platforms. Through a Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis, it is possible to better understand the strategy that should be taken to improve the efficiency in this field, which directly depends on the data’s characteristics. The development of dataset standards will directly increase the collaboration and data sharing between academia and industry, allowing faster research and development through direct interoperability.
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