From a Conceptual Model to a Knowledge Graph for Genomic Datasets
| Autor: | Anna Bernasconi, Stefano Ceri, Arif Canakoglu |
|---|---|
| Jazyk: | angličtina |
| Předmět: |
0301 basic medicine
Computer science 0206 medical engineering Next Generation Sequencing 02 engineering and technology computer.software_genre Conceptual schema 03 medical and health sciences Semantic search Knowledge graph Information retrieval business.industry Open data Genomics Metadata 030104 developmental biology Data access Graph (abstract data type) Conceptual model Data integration business computer 020602 bioinformatics Knowledge graph Semantic search Conceptual model Data integration Genomics Next Generation Sequencing Open data |
| Zdroj: | Lecture Notes in Computer Science Lecture Notes in Computer Science-Conceptual Modeling Conceptual Modeling ISBN: 9783030332228 ER Conceptual Modeling-38th International Conference, ER 2019, Salvador, Brazil, November 4–7, 2019, Proceedings |
| ISSN: | 0302-9743 1611-3349 |
| DOI: | 10.1007/978-3-030-33223-5_29 |
| Popis: | Data access at genomic repositories is problematic, as data is described by heterogeneous and hardly comparable metadata. We previously introduced a unified conceptual schema, collected metadata in a single repository and provided classical search methods upon them. We here propose a new paradigm to support semantic search of integrated genomic metadata, based on the Genomic Knowledge Graph, a semantic graph of genomic terms and concepts, which combines the original information provided by each source with curated terminological content from specialized ontologies. |
| Databáze: | OpenAIRE |
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