title: Introducing Explorer of Taxon Concepts with a case study on spider measurement matrix building.
abstract: BACKGROUND
  Taxonomic descriptions are traditionally composed in natural language and published in a format that cannot be directly used by computers. The Exploring Taxon Concepts (ETC) project has been developing a set of web-based software tools that convert morphological descriptions published in telegraphic style to character data that can be reused and repurposed. This paper introduces the first semi-automated pipeline, to our knowledge, that converts morphological descriptions into taxon-character matrices to support systematics and evolutionary biology research. We then demonstrate and evaluate the use of the ETC Input Creation - Text Capture - Matrix Generation pipeline to generate body part measurement matrices from a set of 188 spider morphological descriptions and report the findings.
  
  
  RESULTS
  From the given set of spider taxonomic publications, two versions of input (original and normalized) were generated and used by the ETC Text Capture and ETC Matrix Generation tools. The tools produced two corresponding spider body part measurement matrices, and the matrix from the normalized input was found to be much more similar to a gold standard matrix hand-curated by the scientist co-authors. Special conventions utilized in the original descriptions (e.g., the omission of measurement units) were attributed to the lower performance of using the original input. The results show that simple normalization of the description text greatly increased the quality of the machine-generated matrix and reduced edit effort. The machine-generated matrix also helped identify issues in the gold standard matrix.
  
  
  CONCLUSIONS
  ETC Text Capture and ETC Matrix Generation are low-barrier and effective tools for extracting measurement values from spider taxonomic descriptions and are more effective when the descriptions are self-contained. Special conventions that make the description text less self-contained challenge automated extraction of data from biodiversity descriptions and hinder the automated reuse of the published knowledge. The tools will be updated to support new requirements revealed in this case study.
authors.affiliation: University of Arizona, Tucson, AZ, USA. hongcui@email.arizona.edu.
authors.forename: Hong
authors.identifier: http://orcid.org/0000-0003-0828-1102
authors.initials: H
authors.lastname: Cui
authors.affiliation: University of Arizona, Tucson, AZ, USA.
authors.forename: Dongfang
authors.initials: D
authors.lastname: Xu
authors.affiliation: University of Arizona, Tucson, AZ, USA.
authors.forename: Steven S
authors.initials: SS
authors.lastname: Chong
authors.affiliation: Museo Argentino de Ciencias, Naturales, CONICET, Buenos Aires, Argentina.
authors.forename: Martin
authors.initials: M
authors.lastname: Ramirez
authors.affiliation: University of Arizona, Tucson, AZ, USA.
authors.forename: Thomas
authors.initials: T
authors.lastname: Rodenhausen
authors.affiliation: Agriculture and Agri-Food Canada, Ottawa, Canada.
authors.forename: James A
authors.initials: JA
authors.lastname: Macklin
authors.affiliation: University of Illinois at Urbana-Champaign, Champaign, USA.
authors.forename: Bertram
authors.initials: B
authors.lastname: Ludäscher
authors.affiliation: University of Massachusetts at Boston and Harvard University Herbaria, Massachusetts, USA.
authors.forename: Robert A
authors.initials: RA
authors.lastname: Morris
authors.affiliation: Department of Geology & Geophysics, Yale University, New Haven, Connecticut, USA.
authors.forename: Eduardo M
authors.initials: EM
authors.lastname: Soto
authors.affiliation: Department of Geology & Geophysics, Yale University, New Haven, Connecticut, USA.
authors.forename: Nicolás Mongiardino
authors.initials: NM
authors.lastname: Koch
mesh_terms: D000818:Animals; D005075:Biological Evolution; D006801:Humans; D012984:Software; D013112:Spiders / Q000033:anatomy & histology*
keywords: ETC; Evaluation; Explorer of Taxon Concepts; Information extraction; Natural language processing; Phenotypic characters; Phenotypic traits; Spiders; Taxonomic morphological descriptions; Text mining