Abstract
We believe authors are the most authoritative in defining characters they record. Currently, it is professional curators to convert phenotype characters in publications from human language to computable language using ontology. Such a curation process is not only slow and costly, but it is also jeopardized by significant inter-curation variation issues that are well-known but not systematically addressed. In an effort to make scientific publication semantically clear at the time of publication, we are designing, developing and evaluating a series of ontology-aware software prototypes to support authors to produce phenotypic data that can be readily harvested by computers. One of this series, Measurement Recorder, has been developed to assist authors to define numerical measurements of characters. Two usability studies have conducted with 22 undergraduate students who majored in information science and 32 biology undergraduate students respectively.
Results obtained from the questionnaires and user interaction log data suggest that users can use the Measurement Recorder without training and find it easy to use. Users also appreciate semantic features that enhance data quality. A set of software design issues have also been identified and new features/modifications have been approved by three botanists on the team and implemented to address these issues. This module will be included in a larger Character Recorder platform where both categorical and numerical characters are supported. Future work includes representing the semantic data as RDF knowledge graph and characterizing the division of work between authors as domain knowledge providers and ontology engineers as knowledge formalizers.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Dahdul, W., Dececchi, T.A., Ibrahim, N., Lapp, H., Mabee, P.: Moving the mountain: analysis of the effort required to transform comparative anatomy into computable anatomy. Database (Oxford) 13
Mabee, P.M., et al.: Phenotype ontologies: the bridge between genomics and evolution. Trends Ecol. Evol. 22(7), 345–350 (2007)
Ware, M., Mabe, M.: The STM Report: an overview of scientific and scholarly journal publishing. 4th edn. International Association of STM Publishers (2015)
Camon, E.B., Barrell, D.G., Dimmer, E.C.: An evaluation of GO annotation retrieval for BioCreAtIvE and GOA. BMC Bioinf. 6, 17 (2005)
Söhngen, C., Chang, A., Schomburg, D.: Development of a classification scheme for disease-related enzyme information. BMC Bioinf. 12, 329 (2011)
Wiegers, T.C., Davis, A.P., Cohen, K.B., Hirschman, L., Mattingly, C.J.: Text mining and manual curation of chemical-gene-disease networks for the comparative toxicogenomics database (CTD). BMC 10, 326 (2009)
Endara, L., et al.: Building the “plant glossary”—a controlled botanical vocabulary using terms extracted from the floras of North America and China. Taxon 66(4), 953–966 (2017)
Dahdul, W., et al.: Annotation of phenotypes using ontologies: a gold standard for the training and evaluation of natural language processing systems. Database: J. Biol. Databases Curat. 2018 (2018)
Cui, H., et al.: CharaParser+ EQ: performance evaluation without gold standard. Proc. Assoc. Inf. Sci. Technol. 52(1), 1–10 (2015)
Cui, H., et al.: Incentivising use of structured language in biological descriptions: author-driven phenotype data and ontology production. Biodivers. Data J. 6 (2018)
Johnson, J., Henderson, A.: Conceptual Models: Core to Good Design. Morgan & Claypool Publishers
Funding
This work was supported by UA National Science Foundation # 1661485.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Zhang, L. et al. (2020). Enabling Authors to Produce Computable Phenotype Measurements: Usability Studies on the Measurement Recorder. In: Stephanidis, C., Antona, M., Ntoa, S. (eds) HCI International 2020 – Late Breaking Posters. HCII 2020. Communications in Computer and Information Science, vol 1293. Springer, Cham. https://doi.org/10.1007/978-3-030-60700-5_37
Download citation
DOI: https://doi.org/10.1007/978-3-030-60700-5_37
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-60699-2
Online ISBN: 978-3-030-60700-5
eBook Packages: Computer ScienceComputer Science (R0)