IMIS

Publications | Institutes | Persons | Datasets | Projects | Maps | Infrastructure
[ report an error in this record ]basket (0): add | show Print this page

Developing standards for improved data quality and for selecting fit for use biodiversity data
Chapman, A.; Belbin, L.; Zermoglio, P.; Wieczorek, J.; Morris, P.; Nicholls, M.; Rees, E.R.; Veiga, A.; Thompson, A.; Saraiva, A.; James, S.; Gendreau, C.; Benson, A.; Schigel, D. (2020). Developing standards for improved data quality and for selecting fit for use biodiversity data. Biodiversity Information Science and Standards 4: e50889. https://dx.doi.org/10.3897/biss.4.50889
In: Biodiversity Information Science and Standards. Pensoft Publishers: Sofia. ISSN 2535-0897, more
Peer reviewed article  

Available in  Authors 

Author keywords
    data quality, profile, framework, fitness for use, standards, tests and assertions, data quality tests, vocabularies, Darwin Core, GBIF

Authors  Top 
  • Chapman, A.
  • Belbin, L.
  • Zermoglio, P.
  • Wieczorek, J.
  • Morris, P.
  • Nicholls, M.
  • Rees, E.R.
  • Veiga, A.
  • Thompson, A.
  • Saraiva, A.
  • James, S.
  • Gendreau, C.
  • Benson, A.
  • Schigel, D.

Abstract
    The quality of biodiversity data publicly accessible via aggregators such as GBIF (Global Biodiversity Information Facility), the ALA (Atlas of Living Australia), iDigBio (Integrated Digitized Biocollections), and OBIS (Ocean Biogeographic Information System) is often questioned, especially by the research community.

    The Data Quality Interest Group, established by Biodiversity Information Standards (TDWG) and GBIF, has been engaged in four main activities: developing a framework for the assessment and management of data quality using a fitness for use approach; defining a core set of standardised tests and associated assertions based on Darwin Core terms; gathering and classifying user stories to form contextual-themed use cases, such as species distribution modelling, agrobiodiversity, and invasive species; and developing a standardised format for building and managing controlled vocabularies of values.

    Using the developed framework, data quality profiles have been built from use cases to represent user needs. Quality assertions can then be used to filter data suitable for a purpose. The assertions can also be used to provide feedback to data providers and custodians to assist in improving data quality at the source. A case study, using two different implementations of tests and assertions based around the Darwin Core "Event Date" terms, were also tested against GBIF data, to demonstrate that the tests are implementation agnostic, can be run on large aggregated datasets, and can make biodiversity data more fit for typical research uses.


All data in the Integrated Marine Information System (IMIS) is subject to the VLIZ privacy policy Top | Authors