连续集成、流处理和企业数据操作中的连续元数据

IF 1.3 3区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
M. Underwood
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引用次数: 1

摘要

摘要元数据的实现倾向于支持集中式的静态元数据。这种描述与过去十年对大数据、云原生架构和流媒体平台的关注不一致。大数据速度可能需要相应的元数据动态视图。调查了这些趋势,包括DevOps、CI/CD、DataOps和数据结构。审查了几个特定的云原生工具,并确定了它们当前元数据使用中的弱点。提出了更好地利用流媒体平台范式的功能的实现,其中元数据在动态上下文中不断收集。确定了未来的云原生软件功能,这些功能可以使流式元数据能够支持实时数据融合或通过实时本体更新微调自动推理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Continuous Metadata in Continuous Integration, Stream Processing and Enterprise DataOps
ABSTRACT Implementations of metadata tend to favor centralized, static metadata. This depiction is at variance with the past decade of focus on big data, cloud native architectures and streaming platforms. Big data velocity can demand a correspondingly dynamic view of metadata. These trends, which include DevOps, CI/CD, DataOps and data fabric, are surveyed. Several specific cloud native tools are reviewed and weaknesses in their current metadata use are identified. Implementations are suggested which better exploit capabilities of streaming platform paradigms, in which metadata is continuously collected in dynamic contexts. Future cloud native software features are identified which could enable streamed metadata to power real time data fusion or fine tune automated reasoning through real time ontology updates.
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来源期刊
Data Intelligence
Data Intelligence COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
6.50
自引率
15.40%
发文量
40
审稿时长
8 weeks
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