mlsanityData to 14 Oct 2026

SchemaLink: An Intelligent Web Editor for LinkML Schema Curation

arXiv 2608.12529 ↗First posted 12 Aug 2026cs.DB cs.AI cs.HCcited by 0

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Abstract (arXiv)

Motivation: LinkML is a suitable language for the representation of the structural and content constraints of different kinds of biomedical data. Even if it is a quite recent proposal, it has been applied in several biomedical contexts. Developing and maintaining LinkML schemas presents several challenges, particularly for novice curators. Non-expert bio-curators may struggle with LinkML syntax and best practices, requiring significant time and effort to develop well-structured schemas. Results: In this paper we propose SchemaLink, a web-based environment for the graphical construction and enhancement of LinkML schemas that address the following requirements: (i) introduce a graphical language for the specification of LinkML schemas, (ii) make uniform the specification of schemas in similar contexts, (iii) simplify the design and curation processes by exploiting a RAG-based approach to assist curators in creating new schemas from scratch and editing already developed ones. Several experimental analyses show the quality of the produced LinkML schemas through the AI-based editing facilities. Availability and Implementation: SchemaLink is available online at: https://SchemaLink.biodata.di.unimi.it. SchemaLink code and testing data are available as open-source on GitHub at: https://github.com/AnacletoLAB/schemalink-webapp,schemalink-api.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 9 of its 33 references that are in the map. First posted on arXiv 12 Aug 2026.

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9 of 33 references.

References · 9

  1. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  2. 2023Lost in the Middle: How Language Models Use Long Contextscited by 3,455
  3. 2024A Survey on LLM-as-a-Judgecited by 1,423
  4. 2023Structured prompt interrogation and recursive extraction of semantics (SPIRES): A method for populating knowledge bases using zero-shot learningcited by 50
  5. 2024Insights into LLM Long-Context Failures: When Transformers Know but Don't Tellcited by 36
  6. 2025Is Long Context All You Need? Leveraging LLM's Extended Context for NL2SQLcited by 30
  7. 2022Biolink Model: A Universal Schema for Knowledge Graphs in Clinical, Biomedical, and Translational Sciencecited by 13
  8. 2022PG-Schema: Schemas for Property Graphscited by 13
  9. 2025LinkML: An Open Data Modeling Frameworkcited by 6

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