English

A Protocol for KG Construction Tasks Involving Users

Human-Computer Interaction 2025-05-14 v2 Artificial Intelligence Databases

Abstract

Knowledge graph construction (KGC) from (semi-)structured data is challenging, and facilitating user involvement is an issue frequently brought up within this community. We cannot deny the progress we have made with respect to (declarative) knowledge graph construction languages and tools to help build such mappings. However, it is surprising that no two studies report on similar protocols. This heterogeneity does not allow for comparing KGC languages, techniques, and tools. This paper first analyses studies involving users to identify the points of comparison. These gaps include a lack of systematic consistency in task design, participant selection, and evaluation metrics. Moreover, there needs to be a systematic way of analyzing the data and reporting the findings, which is also lacking. We thus propose and introduce a user protocol for KGC designed to address this challenge. Where possible, we draw and take elements from the literature we deem fit for such a protocol. The protocol, as such, allows for the comparison of languages and techniques for the RDF Mapping Language (RML) core functionality, which is covered by most of the other state-of-the-art techniques and tools. We also propose how the protocol can be amended to compare extensions (of RML). This protocol provides an important step towards a more comparable evaluation of KGC user studies.

Keywords

Cite

@article{arxiv.2412.16766,
  title  = {A Protocol for KG Construction Tasks Involving Users},
  author = {Ademar Crotti Junior and Christophe Debruyne},
  journal= {arXiv preprint arXiv:2412.16766},
  year   = {2025}
}

Comments

For associated repository, see https://github.com/chrdebru/kgc-user-study-protocol

R2 v1 2026-06-28T20:45:14.662Z