Developing Standards for Improved Data Quality and for Selecting Fit for Use Biodiversity Data

Biodiversity Information Science and Standards

article

Arthur D Chapman¹  Lee Belbin²  Paula F Zermoglio³  John Wieczorek⁴  Paul J Morris⁵  Miles Nicholls⁶  Emily Rose Rees²  Allan Koch Veiga⁷  Alexander Thompson⁸  Antonio Mauro Saraiva⁷  Shelley A James⁹  Christian Gendreau^1,10  Abigail Benson^1,11  Dmitry Schigel^1,10 

[1] Australian Biodiversity Information Services;The Atlas of Living Australia;VertNet;Museum of Vertebrate Zoology, University of California;Museum of Comparative Zoology, Harvard University;Atlas of Living Australia;University of Sao Paulo;iDigBio;Department of Biodiversity;Global Biodiversity Information Facility - Secretariat;U.S. Geological Survey

关键词: data quality;    profile;    framework;    fitness for use;    standards;    tests and assertions;    data quality tests;    vocabularies;    Darwin Core;    GBIF;   

DOI  :  10.3897/biss.4.50889

来源: Pensoft

【 摘 要 】

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.

【 授权许可】

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