A Protocol for KG Construction Tasks Involving Users
This addresses the problem of heterogeneous evaluation methods in KGC research, facilitating more consistent and comparable user studies, though it is incremental as it builds on existing literature.
The paper tackles the lack of comparability in knowledge graph construction (KGC) user studies by proposing a standardized protocol for task design, participant selection, and evaluation metrics, enabling systematic comparison of languages and tools like RML.
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.