.png){kind=icon}
返回
Modeling scientometric indicators using a statistical data ontology
.png){kind=icon}
OA
AI
DOI：10.1186/s40537-022-00562-x.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Scientometrics is the field of study and evaluation of scientific measures such as the impact of research papers and academic journals. It is an important field because nowadays different rankings use key indicators for university rankings and universities themselves use them as Key Performance Indicators (KPI). The purpose of this work is to propose a semantic modeling of scientometric indicators using the ontology Statistical Data and Metadata Exchange (SDMX). We develop a case study at Tecnologico de Monterrey following the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology. We evaluate the benefits of storing and querying scientometric indicators using linked data as a mean for providing flexible and quick access knowledge representation that supports indicator discovery, enquiring and composition. The semi-automatic generation and further storage of this linked data in the Neo4j graph database enabled an updatable and quick access model.
Keyword:
Graph database
Ontology generation
CRISP-DM
Neo4j
Query evaluation
期刊
IF:
6.4
论文数:
1.5K
被引数:
1.1W
机构
引用论文
.png){kind=icon}
Adding value to Linked Open Data using a multidimensional model approach based on the RDF Data Cube vocabulary使用基于RDF数据立方体词汇表的多维模型方法为链接的开放数据增加价值
OAAI
OAAI分享收藏Luminescence characteristics of quartz from the Southern Kenyan Rift Valley: Dose estimation using LM-OSL SAR肯尼亚南部裂谷石英的发光特征: 使用lm-osl SAR估算剂量
PREAI
分享收藏
查看更多内容