Ontologies for increasing the FAIRness of plant research data
The importance of improving the FAIRness (findability, accessibility, interoperability, reusability) of research data is undeniable, especially in the face of large, complex datasets currently being produced by omics technologies. Facilitating the integration of a dataset with other types of data in...
| Autores principales: | , , , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Frontiers Media
2023
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| Acceso en línea: | https://hdl.handle.net/10568/135742 |
| _version_ | 1855529312496648192 |
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| author | Dumschott, Kathryn Dörpholz, Hannah Laporte, Marie-Angelique Brilhaus, Dominik Schrader, Andrea Usadel, Björn Neumann, Steffen Arnaud, Elizabeth Kranz, Angela |
| author_browse | Arnaud, Elizabeth Brilhaus, Dominik Dumschott, Kathryn Dörpholz, Hannah Kranz, Angela Laporte, Marie-Angelique Neumann, Steffen Schrader, Andrea Usadel, Björn |
| author_facet | Dumschott, Kathryn Dörpholz, Hannah Laporte, Marie-Angelique Brilhaus, Dominik Schrader, Andrea Usadel, Björn Neumann, Steffen Arnaud, Elizabeth Kranz, Angela |
| author_sort | Dumschott, Kathryn |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | The importance of improving the FAIRness (findability, accessibility, interoperability, reusability) of research data is undeniable, especially in the face of large, complex datasets currently being produced by omics technologies. Facilitating the integration of a dataset with other types of data increases the likelihood of reuse, and the potential of answering novel research questions. Ontologies are a useful tool for semantically tagging datasets as adding relevant metadata increases the understanding of how data was produced and increases its interoperability. Ontologies provide concepts for a particular domain as well as the relationships between concepts. By tagging data with ontology terms, data becomes both human- and machine- interpretable, allowing for increased reuse and interoperability. However, the task of identifying ontologies relevant to a particular research domain or technology is challenging, especially within the diverse realm of fundamental plant research. In this review, we outline the ontologies most relevant to the fundamental plant sciences and how they can be used to annotate data related to plant-specific experiments within metadata frameworks, such as Investigation-Study-Assay (ISA). We also outline repositories and platforms most useful for identifying applicable ontologies or finding ontology terms. |
| format | Journal Article |
| id | CGSpace135742 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | Frontiers Media |
| publisherStr | Frontiers Media |
| record_format | dspace |
| spelling | CGSpace1357422025-12-08T10:29:22Z Ontologies for increasing the FAIRness of plant research data Dumschott, Kathryn Dörpholz, Hannah Laporte, Marie-Angelique Brilhaus, Dominik Schrader, Andrea Usadel, Björn Neumann, Steffen Arnaud, Elizabeth Kranz, Angela data ontologies plants The importance of improving the FAIRness (findability, accessibility, interoperability, reusability) of research data is undeniable, especially in the face of large, complex datasets currently being produced by omics technologies. Facilitating the integration of a dataset with other types of data increases the likelihood of reuse, and the potential of answering novel research questions. Ontologies are a useful tool for semantically tagging datasets as adding relevant metadata increases the understanding of how data was produced and increases its interoperability. Ontologies provide concepts for a particular domain as well as the relationships between concepts. By tagging data with ontology terms, data becomes both human- and machine- interpretable, allowing for increased reuse and interoperability. However, the task of identifying ontologies relevant to a particular research domain or technology is challenging, especially within the diverse realm of fundamental plant research. In this review, we outline the ontologies most relevant to the fundamental plant sciences and how they can be used to annotate data related to plant-specific experiments within metadata frameworks, such as Investigation-Study-Assay (ISA). We also outline repositories and platforms most useful for identifying applicable ontologies or finding ontology terms. 2023-11-30 2023-12-21T13:34:32Z 2023-12-21T13:34:32Z Journal Article https://hdl.handle.net/10568/135742 en Open Access application/pdf Frontiers Media Dumschott, K.; Dörpholz, H.; Laporte, M.A.; Brilhaus, D.; Schrader, A.; Usadel, B.; Neumann, S.; Arnaud, E.; Kranz, A. (2023) Ontologies for increasing the FAIRness of plant research data. Frontiers in Plant Science 14:1279694. ISSN: 1664-462X |
| spellingShingle | data ontologies plants Dumschott, Kathryn Dörpholz, Hannah Laporte, Marie-Angelique Brilhaus, Dominik Schrader, Andrea Usadel, Björn Neumann, Steffen Arnaud, Elizabeth Kranz, Angela Ontologies for increasing the FAIRness of plant research data |
| title | Ontologies for increasing the FAIRness of plant research data |
| title_full | Ontologies for increasing the FAIRness of plant research data |
| title_fullStr | Ontologies for increasing the FAIRness of plant research data |
| title_full_unstemmed | Ontologies for increasing the FAIRness of plant research data |
| title_short | Ontologies for increasing the FAIRness of plant research data |
| title_sort | ontologies for increasing the fairness of plant research data |
| topic | data ontologies plants |
| url | https://hdl.handle.net/10568/135742 |
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