IRCRApr 16, 2020

Toward Efficient Web Publishing with Provenance of Information Using Trusty URIs: Applying the proposed model with the Quran

arXiv:2004.07609v1
AI Analysis

This addresses the issue of unstable data references for web publishers and linked data systems, though it appears incremental as it builds on existing URI-based approaches.

The research tackled the problem of ensuring data provenance stability on the web by proposing a methodology using Trusty URIs to create stable references, and the results showed high applicability with no overhead cost in loading time.

This research presents a methodology for trusting the provenance of data on the web. The implication is that data does not change after publication and the source of the data is stable. There are different data that should not change over time, such as published information in books and similar documents as well as news or events reported on the web. If the data change after publication on the web, the web pages that reference the unstable data will lose points of interest or link to different resources. With the current move to linked data and the semantic web, this is becoming a greater obstacle to be solved. This research presents a methodology for establishing trusted information using an encoded reference of the data embedded in its URI, which creates a stable reference of the data and a method for ensuring its provenance stability. After applying the methodology, the results showed that the methodology is highly applicable and has no overhead cost over the loading time. The novel solution can be applied directly to any data portals or web content management systems.

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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