DBCLMay 11, 2024

T-curator: a trust based curation tool for LOD logs

arXiv:2405.07081v1h-index: 4Has Code
Originality Synthesis-oriented
AI Analysis

This addresses a domain-specific issue for companies using LOD logs, but it is incremental as it builds on prior work.

The paper tackles the problem of risky exploitation of Linked Open Data (LOD) query logs due to questionable provenance and quality, proposing an interactive trust-based curation tool to assist users in curating these logs before use.

Nowadays, companies are racing towards Linked Open Data (LOD) to improve their added value, but they are ignoring their SPARQL query logs. If well curated, these logs can present an asset for decision makers. A naive and straightforward use of these logs is too risky because their provenance and quality are highly questionable. Users of these logs in a trusted way have to be assisted by providing them with in-depth knowledge of the whole LOD environment and tools to curate these logs. In this paper, we propose an interactive and intuitive trust based tool that can be used to curate these LOD logs before exploiting them. This tool is proposed to support our approach proposed in our previous work Lanasri et al. [2020].

Code Implementations1 repo
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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