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Metadata Harmonization in OTN – lessons learned: Following existing standards is vital for interoperability.
Metadata harmonization of spatial and non-spatial datasets and services is essential to enable a uniform way of querying metadata.
The first use case in this article focuses on metadata harmonization and describes how to understand the source data.
Use Case I: Metadata Harmonization: The first use case describes the specifics of the new GeoDCAT-AP standard, and the implementation of it on the OTN Hub with the corresponding metadata catalogues CKAN and Micka.
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Overall, the article particularly emphasizes five needs of wildlife health investigations: communication and collaboration; use of synergies and triangulation approaches; investments for the long term; systematic collection of metadata; and harmonization of definitions and methods.
In addition, the use of ontologies enables harmonization between ICEMR metadata and those from other standards in particular the NIAID/Genome Sequencing Centers for Infectious Diseases GSCID /Bioinformatics Resource Centers BRCRC) standard.
The software helps to ensure consistency in naming conventions, application of common business rules, and elimination of semantically duplicate metadata, thus helping to achieve harmonization across projects and research domains.
Task 2: Synonym analysis 1. Task 2.1: Computer-aided synonym analysis (a) Definition-duplicate analysis: identify definition duplicates (b) Relation analysis: identify relevant relation types by analyzing metadata given in the source glossaries (c) Harmonization and merging of entries 2.
Task 2.1: Computer-aided synonym analysis (a) Definition-duplicate analysis: identify definition duplicates (b) Relation analysis: identify relevant relation types by analyzing metadata given in the source glossaries (c) Harmonization and merging of entries .
The insertion rules include a harmonization step in which the model components are compared to existing metadata components in the caDSR.
"It's only metadata".
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