Integrating and visualizing primary data from prospective and legacy taxonomic literature

• DOI: 10.3897/bdj.3.e5063
• Publication Date: 2015-05-12T16:08:49Z
• Authors: Jeremy Miller; Donat Agosti; Lyubomir Penev; Guido Sautter; Teodor Georgiev; Terry Catapano; David Patterson; David King; Serrano Pereira; Rutger Vos; Soraya Sierra
• Keywords: 0106 biological sciences; 070; QH301-705.5; XML markup; Spiders; Open access; XML; 15. Life on land; 01 natural sciences; Biodiversity informatics; markup; Araneae; General Research Article; Biology (General); Data mining; Taxonomy

Specimen data in taxonomic literature are among the highest quality primary biodiversity data. Innovative cybertaxonomic journals are using workflows that maintain data structure and disseminate electronic content to aggregators and other users; such structure is lost in traditional taxonomic publishing. Legacy taxonomic literature is a vast repository of knowledge about biodiversity. Currently, access to that resource is cumbersome, especially for non-specialist data consumers. Markup is a mechanism that makes this content more accessible, and is especially suited to machine analysis. Fine-grained XML (Extensible Markup Language) markup was applied to all (37) open-access articles published in the journal Zootaxa containing treatments on spiders (Order: Araneae). The markup approach was optimized to extract primary specimen data from legacy publications. These data were combined with data from articles containing treatments on spiders published in Biodiversity Data Journal where XML structure is part of the routine publication process. A series of charts was developed to visualize the content of specimen data in XML-tagged taxonomic treatments, either singly or in aggregate. The data can be filtered by several fields (including journal, taxon, institutional collection, collecting country, collector, author, article and treatment) to query particular aspects of the data. We demonstrate here that XML markup using GoldenGATE can address the challenge presented by unstructured legacy data, can extract structured primary biodiversity data which can be aggregated with and jointly queried with data from other Darwin Core-compatible sources, and show how visualization of these data can communicate key information contained in biodiversity literature. We complement recent studies on aspects of biodiversity knowledge using XML structured data to explore 1) the time lag between species discovry and description, and 2) the prevelence of rarity in species descriptions.