能源数据空间中的知识管理
Managing Knowledge in Energy Data Spaces
摘要：
能源领域的数据以前所未有的速度增长，通常由异构能源系统生成。尽管大数据驱动的技术可以为能源部门带来巨大潜力，但普遍采用仍然滞后。与受控数据交换和数据集成相关的若干挑战仍未完全实现。因此，针对能源数据孤岛开发了分散的应用程序，数据交换仅限于少数应用程序。在本文中，我们分析了与能源相关的数据应用程序的挑战和要求。我们还评估了使用能源数据生态系统（EDES）作为数据驱动的基础设施，以克服目前分散的能源应用程序的局限性。EDE的灵感来自于2014年底在德国发起的国际数据空间（IDS）倡议，其总体目标是将IDS参考架构模型的开发和使用带到欧洲/全球层面。参考体系结构模型由四个与业务、安全、数据和服务以及软件方面相关的体系结构组成。本文阐述了EDES和IDS参考架构在能源领域的实际场景中的适用性。分析的场景定位在欧盟资助的H2020项目PLATOON的背景下。
英文摘要：
Data in the energy domain grows at unprecedented rates and is usually generated by heterogeneous energy systems. Despite the great potential that big data-driven technologies can bring to the energy sector, general adoption is still lagging. Several challenges related to controlled data exchange and data integration are still not wholly achieved. As a result, fragmented applications are developed against energy data silos, and data exchange is limited to few applications. In this paper, we analyze the challenges and requirements related to energy-related data applications. We also evaluate the use of Energy Data Ecosystems (EDEs) as data-driven infrastructures to overcome the current limitations of fragmented energy applications. EDEs are inspired by the International Data Space (IDS) initiative launched in Germany at the end of 2014 with an overall objective to take both the development and use of the IDS reference architecture model to a European/global level. The reference architecture model consists of four architectures related to business, security, data and service, and software aspects. This paper illustrates the applicability of EDEs and IDS reference architecture in real-world scenarios from the energy sector. The analyzed scenario is positioned in the context of the EU-funded H2020 project PLATOON.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
