2017年
Semantic graph analysis for federated LOD surfing in life sciences
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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- 巻
- 10675
- 号
- 開始ページ
- 268
- 終了ページ
- 276
- 記述言語
- 英語
- 掲載種別
- 研究論文(国際会議プロシーディングス)
- DOI
- 10.1007/978-3-319-70682-5_18
- 出版者・発行元
- Springer Verlag
Currently, Linked Open Data (LOD) is increasingly used when publishing life science databases. To facilitate flexible use of such databases, we employ a method that uses federated query search along a path of class–class relationships. However, an effective method for federated query search requires analysis of the structure the relationships form for LOD datasets. Therefore, we constructed a graph of class–class relationships among 43 SPARQL endpoints and analyzed the connectivity of the graph. As a result, we found that (1) the sizes of connected components follow a power law
thus we should deal with the classes separately according to the size of connected components, (2) only the largest and second largest connected components have paths among classes from two or more SPARQL endpoints, and the datasets of each of the two connected components share ontologies, and (3) key classes that connect SPARQL endpoints are primarily upper-level concepts in the biological domain.
thus we should deal with the classes separately according to the size of connected components, (2) only the largest and second largest connected components have paths among classes from two or more SPARQL endpoints, and the datasets of each of the two connected components share ontologies, and (3) key classes that connect SPARQL endpoints are primarily upper-level concepts in the biological domain.
- リンク情報
- ID情報
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- DOI : 10.1007/978-3-319-70682-5_18
- ISSN : 1611-3349
- ISSN : 0302-9743
- ORCIDのPut Code : 43080663
- SCOPUS ID : 85033774920