DLIRJan 28, 2013

PDF articles metadata harvester

arXiv:1301.6591v110 citations
Originality Synthesis-oriented
AI Analysis

This work targets researchers and librarians by providing a tool for metadata extraction from PDFs, but it appears incremental as it builds on existing XMP standards without introducing major innovations.

The paper addresses the challenge of ensuring consistent metadata availability in scientific PDF articles by proposing a metadata harvester using XMP, aiming to improve metadata accessibility for internet-based journal discovery.

Scientific journals are very important in recording the finding from researchers around the world. The recent media to disseminate scientific journals is PDF. On scheme to find the scientific journals over the internet is via metadata. Metadata stores information about article summary. Embedding metadata into PDF of scientific article will grant the consistency of metadata readness. Harvesting the metadata from scientific journal is very interesting field at the moment. This paper will discuss about scientific journal metadata harvesters involving XMP.

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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