Knowledge and Instance Mapping: architecture for premeditated interoperability of disparate data for materials
Abstract Predicting and elucidating the impacts of materials on human health and the environment is an unending task that has taken on special significance in the context of nanomaterials research over the last two decades. The properties of materials in environmental and physiological media are dyn...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-02-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-024-03006-8 |
| _version_ | 1797275896909922304 |
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| author | Jaleesia D. Amos Zhao Zhang Yuan Tian Gregory V. Lowry Mark R. Wiesner Christine Ogilvie Hendren |
| author_facet | Jaleesia D. Amos Zhao Zhang Yuan Tian Gregory V. Lowry Mark R. Wiesner Christine Ogilvie Hendren |
| author_sort | Jaleesia D. Amos |
| collection | DOAJ |
| description | Abstract Predicting and elucidating the impacts of materials on human health and the environment is an unending task that has taken on special significance in the context of nanomaterials research over the last two decades. The properties of materials in environmental and physiological media are dynamic, reflecting the complex interactions between materials and these media. This dynamic behavior requires special consideration in the design of databases and data curation that allow for subsequent comparability and interrogation of the data from potentially diverse sources. We present two data processing methods that can be integrated into the experimental process to encourage pre-mediated interoperability of disparate material data: Knowledge Mapping and Instance Mapping. Originally developed as a framework for the NanoInformatics Knowledge Commons (NIKC) database, this architecture and associated methods can be used independently of the NIKC and applied across multiple subfields of nanotechnology and material science. |
| first_indexed | 2024-03-07T15:20:36Z |
| format | Article |
| id | doaj.art-1063b45ae87243269d41dd1b432ec1df |
| institution | Directory Open Access Journal |
| issn | 2052-4463 |
| language | English |
| last_indexed | 2024-03-07T15:20:36Z |
| publishDate | 2024-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj.art-1063b45ae87243269d41dd1b432ec1df2024-03-05T17:38:49ZengNature PortfolioScientific Data2052-44632024-02-0111111510.1038/s41597-024-03006-8Knowledge and Instance Mapping: architecture for premeditated interoperability of disparate data for materialsJaleesia D. Amos0Zhao Zhang1Yuan Tian2Gregory V. Lowry3Mark R. Wiesner4Christine Ogilvie Hendren5Center for the Environmental Implications of Nano Technology (CEINT)Center for the Environmental Implications of Nano Technology (CEINT)Center for the Environmental Implications of Nano Technology (CEINT)Center for the Environmental Implications of Nano Technology (CEINT)Center for the Environmental Implications of Nano Technology (CEINT)Center for the Environmental Implications of Nano Technology (CEINT)Abstract Predicting and elucidating the impacts of materials on human health and the environment is an unending task that has taken on special significance in the context of nanomaterials research over the last two decades. The properties of materials in environmental and physiological media are dynamic, reflecting the complex interactions between materials and these media. This dynamic behavior requires special consideration in the design of databases and data curation that allow for subsequent comparability and interrogation of the data from potentially diverse sources. We present two data processing methods that can be integrated into the experimental process to encourage pre-mediated interoperability of disparate material data: Knowledge Mapping and Instance Mapping. Originally developed as a framework for the NanoInformatics Knowledge Commons (NIKC) database, this architecture and associated methods can be used independently of the NIKC and applied across multiple subfields of nanotechnology and material science.https://doi.org/10.1038/s41597-024-03006-8 |
| spellingShingle | Jaleesia D. Amos Zhao Zhang Yuan Tian Gregory V. Lowry Mark R. Wiesner Christine Ogilvie Hendren Knowledge and Instance Mapping: architecture for premeditated interoperability of disparate data for materials Scientific Data |
| title | Knowledge and Instance Mapping: architecture for premeditated interoperability of disparate data for materials |
| title_full | Knowledge and Instance Mapping: architecture for premeditated interoperability of disparate data for materials |
| title_fullStr | Knowledge and Instance Mapping: architecture for premeditated interoperability of disparate data for materials |
| title_full_unstemmed | Knowledge and Instance Mapping: architecture for premeditated interoperability of disparate data for materials |
| title_short | Knowledge and Instance Mapping: architecture for premeditated interoperability of disparate data for materials |
| title_sort | knowledge and instance mapping architecture for premeditated interoperability of disparate data for materials |
| url | https://doi.org/10.1038/s41597-024-03006-8 |
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