PUBLISHING CLIMATE DATA AS LINKED DATA VIA VIRTUAL KNOWLEDGE GRAPHS

被引:3
|
作者
Wu, Jiantao [1 ,2 ]
Orlandi, Fabrizio [1 ,3 ]
O'Sullivan, Declan [1 ,3 ]
Dev, Soumyabrata [1 ,2 ]
机构
[1] ADAPT SFI Res Ctr, Dublin, Ireland
[2] Univ Coll Dublin, Sch Comp Sci, Dublin, Ireland
[3] Trinity Coll Dublin, Sch Comp Sci & Stat, Dublin, Ireland
来源
2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022) | 2022年
基金
欧盟地平线“2020”;
关键词
Heterogeneous Climate Data; Virtual Knowledge Graphs; Linked Data; SPARQL Query;
D O I
10.1109/IGARSS46834.2022.9884226
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
With the active development of ICT and Internet technologies in climate research, individuals often need to gather different and disparate datasets and preprocess them in preparation for downstream data analysis in order to have a more full understanding of the challenges. This preparatory procedure is often lengthy due to the primary issue that data providers cannot ensure a homogeneous data format for data integration purposes. To overcome this problem, this study proposes enhancing existing relational climate data by layering a virtual knowledge graph on top of the original databases provided by various data vendors. The primary benefit of doing this is that data consumers are able to simply integrate climate data with other data sources using Linked Data principles, and climate data producers do not have to modify their data to conform to standard knowledge graph protocols.
引用
收藏
页码:4090 / 4093
页数:4
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