The concept of semantic tagging and its potential for semantic enhancements to taxonomic papers is outlined and illustrated by four exemplar papers published in the present issue of ZooKeys. The four papers were created in different ways: (i) written in Microsoft Word and submitted as non-tagged manuscript (doi: 10.3897/zookeys.50.504); (ii) generated from Scratchpads and submitted as XML-tagged manuscripts (doi: 10.3897/zookeys.50.505 and doi: 10.3897/zookeys.50.506); (iii) generated from an author’s database (doi: 10.3897/zookeys.50.485) and submitted as XML-tagged manuscript. XML tagging and semantic enhancements were implemented during the editorial process of ZooKeys using the Pensoft Mark Up Tool (PMT), specially designed for this purpose. The XML schema used was TaxPub, an extension to the Document Type Definitions (DTD) of the US National Library of Medicine Journal Archiving and Interchange Tag Suite (NLM). The following innovative methods of tagging, layout, publishing and disseminating the content were tested and implemented within the ZooKeys editorial workflow: (1) highly automated, fine-grained XML tagging based on TaxPub; (2) final XML output of the paper validated against the NLM DTD for archiving in PubMedCentral; (3) bibliographic metadata embedded in the PDF through XMP (Extensible Metadata Platform); (4) PDF uploaded after publication to the Biodiversity Heritage Library (BHL); (5) taxon treatments supplied through XML to Plazi; (6) semantically enhanced HTML version of the paper encompassing numerous internal and external links and linkouts, such as: (i) vizualisation of main tag elements within the text (e.g., taxon names, taxon treatments, localities, etc.); (ii) internal cross-linking between paper sections, citations, references, tables, and figures; (iii) mapping of localities listed in the whole paper or within separate taxon treatments; (v) taxon names autotagged, dynamically mapped and linked through the Pensoft Taxon Profile (PTP) to large international database services and indexers such as Global Biodiversity Information Facility (GBIF), National Center for Biotechnology Information (NCBI), Barcode of Life (BOLD), Encyclopedia of Life (EOL), ZooBank, Wikipedia, Wikispecies, Wikimedia, and others; (vi) GenBank accession numbers autotagged and linked to NCBI; (vii) external links of taxon names to references in PubMed, Google Scholar, Biodiversity Heritage Library and other sources. With the launching of the working example, ZooKeys becomes the first taxonomic journal to provide a complete XML-based editorial, publication and dissemination workflow implemented as a routine and cost-efficient practice. It is anticipated that XML-based workflow will also soon be implemented in botany through PhytoKeys, a forthcoming partner journal of ZooKeys. The semantic markup and enhancements are expected to greatly extend and accelerate the way taxonomic information is published, disseminated and used.

BackgroundThe biodiversity domain, and in particular biological taxonomy, is moving in the direction of semantization of its research outputs. The present work introduces OpenBiodiv-O, the ontology that serves as the basis of the OpenBiodiv Knowledge Management System. Our intent is to provide an ontology that fills the gaps between ontologies for biodiversity resources, such as DarwinCore-based ontologies, and semantic publishing ontologies, such as the SPAR Ontologies. We bridge this gap by providing an ontology focusing on biological taxonomy.ResultsOpenBiodiv-O introduces classes, properties, and axioms in the domains of scholarly biodiversity publishing and biological taxonomy and aligns them with several important domain ontologies (FaBiO, DoCO, DwC, Darwin-SW, NOMEN, ENVO). By doing so, it bridges the ontological gap across scholarly biodiversity publishing and biological taxonomy and allows for the creation of a Linked Open Dataset (LOD) of biodiversity information (a biodiversity knowledge graph) and enables the creation of the OpenBiodiv Knowledge Management System.A key feature of the ontology is that it is an ontology of the scientific process of biological taxonomy and not of any particular state of knowledge. This feature allows it to express a multiplicity of scientific opinions. The resulting OpenBiodiv knowledge system may gain a high level of trust in the scientific community as it does not force a scientific opinion on its users (e.g. practicing taxonomists, library researchers, etc.), but rather provides the tools for experts to encode different views as science progresses.ConclusionsOpenBiodiv-O provides a conceptual model of the structure of a biodiversity publication and the development of related taxonomic concepts. It also serves as the basis for the OpenBiodiv Knowledge Management System.Electronic supplementary materialThe online version of this article (doi:10.1186/s13326-017-0174-5) contains supplementary material, which is available to authorized users.

We review the three most widely used XML schemas used to mark-up taxonomic texts, TaxonX, TaxPub and taXMLit. These are described from the viewpoint of their development history, current status, implementation, and use cases. The concept of “taxon treatment” from the viewpoint of taxonomy mark-up into XML is discussed. TaxonX and taXMLit are primarily designed for legacy literature, the former being more lightweight and with a focus on recovery of taxon treatments, the latter providing a much more detailed set of tags to facilitate data extraction and analysis. TaxPub is an extension of the National Library of Medicine Document Type Definition (NLM DTD) for taxonomy focussed on layout and recovery and, as such, is best suited for mark-up of new publications and their archiving in PubMedCentral. All three schemas have their advantages and shortcomings and can be used for different purposes.

Today, digitization of legacy literature is a big issue. This also applies to the domain of biosystematics, where this process has just started. Digitized biosystematics literature requires a very precise and fine grained markup in order to be useful for detailed search, data linkage and mining. However, manual markup on sentence level and below is cumbersome and time consuming. In this paper, we present and evaluate the GoldenGATE editor, which is designed for the special needs of marking up OCR output with XML. It is built in order to support the user in this process as far as possible: Its functionality ranges from easy, intuitive tagging through markup conversion to dynamic binding of configurable plug-ins provided by third parties. Our evaluation shows that marking up an OCR document using GoldenGATE is three to four times faster than with an off-the-shelf XML editor like XML-Spy. Using domain-specific NLP-based plug-ins, these numbers are even higher.

Abstract.-Most of the literature on natural history is hidden in millions of pages stacked up in our libraries. Various initiatives aim now at making these publications digitally accessible and searchable, applying xmlmark up technologies. The unique biological names play a crucial role to link content related to a particular taxon. Thus discovering and marking them up is extremely important. Since their manual extraction and markup is cumbersome and time-intensive, it needs be automated. In this paper, we present computational linguistics techniques and evaluate how they can help to extract taxonomic names automatically. We build on an existing approach for extraction of such names (Koning et al. 2005) and combine it with several other learning techniques. We apply them to the texts sequentially so that each technique can use the results from the preceding ones. In particular, we use structural rules, dynamic lexica with fuzzy lookups, and word-level language recognition. We use legacy documents from different sources and times as test bed for our evaluation. The experimental results for our combining approach (FAT) show greater than 99% precision and recall. They reveal the potential of computational linguistics techniques towards an automated markup of biosystematics publications.

This paper describes a set of guidelines for the citation of zoological and botanical specimens in the European Journal of Taxonomy. The guidelines stipulate controlled vocabularies and precise formats for presenting the specimens examined within a taxonomic publication, which allow for the rich data associated with the primary research material to be harvested, distributed and interlinked online via international biodiversity data aggregators. Herein we explain how the EJT editorial standard was defined and how this initiative fits into the journal’s project to semantically enhance its publications using the Plazi TaxPub DTD extension. By establishing a standardised format for the citation of taxonomic specimens, the journal intends to widen the distribution of and improve accessibility to the data it publishes. Authors who conform to these guidelines will benefit from higher visibility and new ways of visualising their work. In a wider context, we hope that other taxonomy journals will adopt this approach to their publications, adapting their working methods to enable domain-specific text mining to take place. If specimen data can be efficiently cited, harvested and linked to wider resources, we propose that there is also the potential to develop alternative metrics for assessing impact and productivity within the natural sciences.

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.

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