Semantification of Space Data - A Feasibility Study

被引：0

作者：

Engel, Felix ^{[1
]}

Krdzavac, Nenad ^{[1
]}

Tuncay, Erhun Giray ^{[1
]}

Klinger, Axel ^{[1
]}

Hughes, John ^{[2
]}

机构：

[1] German Natl Lib Sci & Technol TIB, Hannover, Lower Saxony, Germany

[2] CALTECH, Jet Prop Lab, Pasadena, CA USA

来源：

2023 ACM/IEEE JOINT CONFERENCE ON DIGITAL LIBRARIES, JCDL | 2023年

关键词：

Knowledge graph; Natural language processing; Extracting semantics;

D O I：

10.1109/JCDL57899.2023.00065

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a new approach to the semantic representation of NASA planetary mission data. The Open Archival Information Systems (OAIS) Information Model (IM) is used as a model to represent this data in a Knowledge Graph (KG). To prepare the data for this requirement, a machine learning approach is used to extract information (entities) and connect to Wikidata. A demo shows the advantages of using federated SPARQL queries over the created KG and Wikidata.

引用

页码：295 / 296

页数：2

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