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  2. A User-centric Framework For Harmonizing Scientific Name Usage.
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  2. A User-centric Framework For Harmonizing Scientific Name Usage.

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A user-centric framework for harmonizing scientific name usage.

Walter G Berendsohn1, Olaf Bánki2, Markus Döring2,3

  • 1Freie Universität Berlin, Botanic Garden and Botanical Museum, Berlin, Germany Freie Universität Berlin, Botanic Garden and Botanical Museum Berlin Germany https://ror.org/046ak2485.

Biodiversity Data Journal
|April 6, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

Biodiversity data linkage is crucial but hindered by unreliable scientific names. A new framework helps users select optimal name-matching services for better data integration and FAIR data compliance.

Keywords:
biodiversity researchdata linkagename matchingname-matching servicestaxonomic aggregatorstaxonomic databasestaxonomic datasetstaxonomy

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Area of Science:

  • Biodiversity informatics and data science.
  • Taxonomy and nomenclature.
  • Information science and data management.

Background:

  • Digitized biodiversity resources are rapidly expanding, leading to diverse but fragmented datasets and services.
  • Scientific names, while central to biodiversity data, are often non-unique and prone to errors (e.g., misspellings, taxonomic changes), complicating data linkage.
  • Existing challenges in data linkage can demotivate data providers from integrating valuable datasets into a cohesive biodiversity information landscape.

Purpose of the Study:

  • To address the difficulties users face in identifying appropriate tools for biodiversity data linkage.
  • To propose a framework that simplifies the selection of optimal name-matching workflows for diverse user needs.
  • To enhance the integration of biodiversity data by improving the reliability and accessibility of scientific name linkage.

Main Methods:

  • Identifying and categorizing user needs and criteria for biodiversity data linkage.
  • Defining essential metadata for taxonomic datasets and name-matching services based on user needs.
  • Developing interactive tools that leverage metadata to guide users in selecting the best-fit name-matching services and datasets.

Main Results:

  • The proposed framework facilitates the selection of appropriate name-matching services, thereby improving biodiversity data linkage.
  • Standardized metadata requirements enhance the interoperability of taxonomic datasets and name-matching services.
  • The framework supports adherence to FAIR data principles (Findable, Accessible, Interoperable, Reusable) by enabling direct linking of external datasets via unique identifiers.

Conclusions:

  • A user-centric framework for selecting name-matching services is essential for overcoming challenges in biodiversity data linkage.
  • Improved data linkage through reliable scientific name identification supports critical research and societal questions.
  • Simplifying the process of choosing data linkage tools can increase data provider motivation and contribute to a more interconnected biodiversity information ecosystem.