Digital Scholarship @ CUA: It’s the Content, Not the Container!

By Royal Society (Gallica) [Public domain], via Wikimedia Commons
Is the PDF dead?

Beginning in 1666, academic scholarship becomes public through print academic journals. Today, in our electronically enabled universe the portable document format PDF has become the standard for scholarly communication. In 2008 the PDF became an International Organization of Standardization standard – ISO 32000-1:2008. The PDF (the container) made the transition of electronic and print scholarship possible. It is the content of academic research that furthers ideas and progress.

It may be time to rethink our dependence on the PDF. Two recent articles highlight new scholarship needs that are not served by the PDF.

Text and Data Mining Are Growing and Publishers Need to Support Their Use – An AAP-PSP Panel Report

Hypertext Markup Language HTML made researchers giddy with the promise of networked scholarship. The reality has become the hybrid paradigm of online journals and  the PDF which does not serve the pace and global reach of scholarship today. Beyond the marketing and analytics available from  text mining, there may be unforeseen connections in the data mining of a corpus of scholarship.

Challenging the print paradigm: Web-powered scholarship is set to advance the creation and distribution of research

The scholarly literature is rife with potential for data mining, across all fields. Just for starters: data mining could be used to better understand how perceptions of key historical events have shifted with time, as well as how philosophical conceptions of consciousness have evolved. These are just two of countless potential applications. Although data mining may feel like the province of the hard sciences, there is no epistemological reason why this is the case. Any field of scholarship could benefit from tools that detect patterns within the scholarly literature that are not apparent to the naked eye. A human being cannot easily digest 20,000 papers or monographs, but data mining software can do so with no trouble.

See this short history of Scholarly HTML . Imagine the possibilities of text mining across all disciplines. Can we do this with the digital format of scholarship today?

 

 

 

 

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