Systematic Construction of Knowledge Graphs for Research-Performing Organizations
Research-Performing Organizations (e.g., research centers, universities) usually accumulate a wealth of data related to their researchers, the generated scientific results and research outputs, and publicly and privately-funded projects that support their activities, etc. Even though the types of da...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Information |
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| Online Access: | https://www.mdpi.com/2078-2489/13/12/562 |
| _version_ | 1797457151476629504 |
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| author | David Chaves-Fraga Oscar Corcho Francisco Yedro Roberto Moreno Juan Olías Alejandro De La Azuela |
| author_facet | David Chaves-Fraga Oscar Corcho Francisco Yedro Roberto Moreno Juan Olías Alejandro De La Azuela |
| author_sort | David Chaves-Fraga |
| collection | DOAJ |
| description | Research-Performing Organizations (e.g., research centers, universities) usually accumulate a wealth of data related to their researchers, the generated scientific results and research outputs, and publicly and privately-funded projects that support their activities, etc. Even though the types of data handled may look similar across organizations, it is common to see that each institution has developed its own data model to provide support for many of their administrative activities (project reporting, curriculum management, personnel management, etc.). This creates obstacles to the integration and linking of knowledge across organizations, as well as difficulties when researchers move from one institution to another. In this paper, we take advantage of the ontology network created by the Spanish HERCULES initiative to facilitate the construction of knowledge graphs from existing information systems, such as the one managed by the company Universitas XXI, which provides support to more than 100 Spanish-speaking research-performing organizations worldwide. Our effort is not just focused on following the modeling choices from that ontology, but also on demonstrating how the use of standard declarative mapping rules (i.e., R2RML) guarantees a systematic and sustainable workflow for constructing and maintaining a KG. We also present several real-world use cases in which the proposed workflow is adopted together with a set of lessons learned and general recommendations that may also apply to other domains. The next steps include researching in the automation of the creation of the mapping rules, the enrichment of the KG with external sources, and its exploitation though distributed environments. |
| first_indexed | 2024-03-09T16:18:03Z |
| format | Article |
| id | doaj.art-b78706fce0ac426b924afa47ee00ac45 |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-03-09T16:18:03Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj.art-b78706fce0ac426b924afa47ee00ac452023-11-24T15:37:10ZengMDPI AGInformation2078-24892022-11-01131256210.3390/info13120562Systematic Construction of Knowledge Graphs for Research-Performing OrganizationsDavid Chaves-Fraga0Oscar Corcho1Francisco Yedro2Roberto Moreno3Juan Olías4Alejandro De La Azuela5Ontology Engineering Group, Universidad Politécnica de Madrid, 28660 Boadilla del Monte, SpainOntology Engineering Group, Universidad Politécnica de Madrid, 28660 Boadilla del Monte, SpainOntology Engineering Group, Universidad Politécnica de Madrid, 28660 Boadilla del Monte, SpainUniversitas XXI, 28043 Madrid, SpainUniversitas XXI, 28043 Madrid, SpainUniversitas XXI, 28043 Madrid, SpainResearch-Performing Organizations (e.g., research centers, universities) usually accumulate a wealth of data related to their researchers, the generated scientific results and research outputs, and publicly and privately-funded projects that support their activities, etc. Even though the types of data handled may look similar across organizations, it is common to see that each institution has developed its own data model to provide support for many of their administrative activities (project reporting, curriculum management, personnel management, etc.). This creates obstacles to the integration and linking of knowledge across organizations, as well as difficulties when researchers move from one institution to another. In this paper, we take advantage of the ontology network created by the Spanish HERCULES initiative to facilitate the construction of knowledge graphs from existing information systems, such as the one managed by the company Universitas XXI, which provides support to more than 100 Spanish-speaking research-performing organizations worldwide. Our effort is not just focused on following the modeling choices from that ontology, but also on demonstrating how the use of standard declarative mapping rules (i.e., R2RML) guarantees a systematic and sustainable workflow for constructing and maintaining a KG. We also present several real-world use cases in which the proposed workflow is adopted together with a set of lessons learned and general recommendations that may also apply to other domains. The next steps include researching in the automation of the creation of the mapping rules, the enrichment of the KG with external sources, and its exploitation though distributed environments.https://www.mdpi.com/2078-2489/13/12/562knowledge graphresearch-performing organizationsdeclarative mapping rules |
| spellingShingle | David Chaves-Fraga Oscar Corcho Francisco Yedro Roberto Moreno Juan Olías Alejandro De La Azuela Systematic Construction of Knowledge Graphs for Research-Performing Organizations Information knowledge graph research-performing organizations declarative mapping rules |
| title | Systematic Construction of Knowledge Graphs for Research-Performing Organizations |
| title_full | Systematic Construction of Knowledge Graphs for Research-Performing Organizations |
| title_fullStr | Systematic Construction of Knowledge Graphs for Research-Performing Organizations |
| title_full_unstemmed | Systematic Construction of Knowledge Graphs for Research-Performing Organizations |
| title_short | Systematic Construction of Knowledge Graphs for Research-Performing Organizations |
| title_sort | systematic construction of knowledge graphs for research performing organizations |
| topic | knowledge graph research-performing organizations declarative mapping rules |
| url | https://www.mdpi.com/2078-2489/13/12/562 |
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