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Open geospatial infrastructure for data management and analytics in interdisciplinary research

机译:跨学科研究中的数据管理和分析的开放地理空间基础设施

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摘要

The terms Internet of Things and Big Data are currently subject to much attention, though the specific impact of these terms in our practical lives are difficult to apprehend. Data-driven approaches do lead to new possibilities, and significant improvements within a broad range of domains can be achieved through a cloud-based infrastructure. In the agricultural sector, data-driven precision agriculture shows great potential in facilitating the increase in food production demanded by the increasing world population. However, the adoption rate of precision agriculture technology has been slow, and information and communications technology needed to promote the implementation of precision agriculture is limited by proprietary integrations and non-standardized data formats and connections. In this paper, an open geospatial data infrastructure is presented, based on standards defined by the Open Geospatial Consortium (OGC). The emphasis in the design was on improved interoperability, with the capability of using sensors, performing cloud processing, carrying out regional statistics, and provide seamless connectivity to machine terminals. The infrastructure was implemented through open source software, and was complemented by open data from governmental offices along with ESA satellite imagery. Four use cases are presented, covering analysis of nearly 50 000 crop fields and providing seamless interaction with an emulated machine terminal. They act to showcase both for how the infrastructure enables modularity and interoperability, and for the new possibilities which arise from this new approach to data within the agricultural domain.
机译:术语物联网和大数据目前受到很多关注,尽管这些术语在我们的实际生活中的具体影响很难被逮捕。数据驱动方法会导致新的可能性,通过基于云的基础设施可以实现广泛的域内的显着改进。在农业部门,数据驱动的精密农业表现出促进世界人口增加所需的粮食生产增加的巨大潜力。然而,精密农业技术的采用率较慢,促进精密农业的实施所需的信息和通信技术受专有的集成和非标准化数据格式和联系的限制。本文基于开放地理空间联盟(OGC)定义的标准,提出了开放的地理空间数据基础架构。设计中的重点是改进的互操作性,具有使用传感器的能力,执行云处理,进行区域统计数据,并为机器终端提供无缝连接。基础设施是通过开源软件实施的,并通过来自政府办公室的开放数据以及ESA卫星图像进行补充。提出了四种用例,覆盖了近50 000个裁剪领域的分析,并提供与仿真机终端的无缝相互作用。它们展示基础设施如何实现模块化和互操作性,以及从农业领域内的数据的新方法产生的新可能性。

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