Tag:machine-readable metadata

How can journals get closer to having rich metadata and ultimately more discoverable articles? This blog post overviews five machine-readable metadata elements most commonly requested by scholarly communication stakeholders across disciplines that publishers should prioritize.

What steps should scholarly publishers be taking to promote better travel routes and rules of the road for research metadata and data sharing to support discovery, assessment, and reuse, and what are the possibilities? Here are some key takeaways from the 2021 NISO Plus conference.

Jabin White, Vice President of Content Management for JSTOR and Portico, shares his thoughts on how metadata quality can be improved across academia, and how publishers can move from basic metadata concepts to creating enhanced metadata.

In this post, we go behind the scenes of Scholastica's typesetting service, which takes the legwork out of formatting articles by using advanced software to generate HTML, PDF, and XML article files all at once.

The quality of the machine-readable metadata associated with academic journal articles is virtually as important as the quality of the research itself. In this post, we overview the role of machine-readable metadata in article discovery and how Scholastica is helping journals produce the rich machine-readable metadata they need.

Metadata 2020's chief coordinator Laura Paglione discusses how the initiative got started and the stakeholders involved. The goal of Metadata 2020 is to understand how metadata is being used throughout the research lifecycle and to develop recommendations for improvement.