mlsanityData to 7 Oct 2026

Nanopublication-Based Semantic Publishing and Reviewing: A Field Study with Formalization Papers

arXiv 2203.01608 ↗First posted 3 Mar 2022cs.DL cs.AIcited by 2

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Abstract (arXiv)

With the rapidly increasing amount of scientific literature,it is getting continuously more difficult for researchers in different disciplines to be updated with the recent findings in their field of study.Processing scientific articles in an automated fashion has been proposed as a solution to this problem,but the accuracy of such processing remains very poor for extraction tasks beyond the basic ones.Few approaches have tried to change how we publish scientific results in the first place,by making articles machine-interpretable by expressing them with formal semantics from the start.In the work presented here,we set out to demonstrate that we can formally publish high-level scientific claims in formal logic,and publish the results in a special issue of an existing journal.We use the concept and technology of nanopublications for this endeavor,and represent not just the submissions and final papers in this RDF-based format,but also the whole process in between,including reviews,responses,and decisions.We do this by performing a field study with what we call formalization papers,which contribute a novel formalization of a previously published claim.We received 15 submissions from 18 authors,who then went through the whole publication process leading to the publication of their contributions in the special issue.Our evaluation shows the technical and practical feasibility of our approach.The participating authors mostly showed high levels of interest and confidence,and mostly experienced the process as not very difficult,despite the technical nature of the current user interfaces.We believe that these results indicate that it is possible to publish scientific results from different fields with machine-interpretable semantics from the start,which in turn opens countless possibilities to radically improve in the future the effectiveness and efficiency of the scientific endeavor as a whole.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 11 of its 80 references that are in the map. First posted on arXiv 3 Mar 2022.

Builds on

11 of 80 references.

References · 11

  1. 2019A Survey on Recent Advances in Named Entity Recognition from Deep Learning modelscited by 117
  2. 2015Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Pathcited by 35
  3. 2020Domain-independent Extraction of Scientific Concepts from Research Articlescited by 11
  4. 2013Broadening the Scope of Nanopublicationscited by 5
  5. 2020Best Practices for Implementing FAIR Vocabularies and Ontologies on the Webcited by 5
  6. 2021Leveraging Structured Biological Knowledge for Counterfactual Inference: a Case Study of Viral Pathogenesiscited by 3
  7. 2020A Unified Nanopublication Model for Effective and User-Friendly Access to the Elements of Scientific Publishingcited by 2
  8. 2015Making Digital Artifacts on the Web Verifiable and Reliablecited by 1
  9. 2015A Framework to Explore the Knowledge Structure of Multidisciplinary Research Fieldscited by 1
  10. 2019Peer Reviewing Revisited: Assessing Research with Interlinked Semantic Commentscited by 1
  11. 2021Expressing High-Level Scientific Claims with Formal Semanticscited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.