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Literature-driven Curation for Taxonomic Name Databases

Abstract

Digitized biodiversity literature provides a wealth of content for using biodiversity knowledge by machines. However, identifying taxonomic names and the associated semantic metadata is a difficult and labour intensive process. We present a system to support human assisted creation of semantic metadata. Information extraction techniques auto-matically identify taxonomic names from scanned documents. They are then presented to users for manual correction or verification. The tools that support the curation process include taxonomic name identification and mapping, and community-driven taxonomic name verification. Our research shows the potential for these information extrac-tion techniques to support research and curation in disciplines dependent upon scanned document

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