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

By

Chapman, Arthur
Belbin, Lee
Zermoglio, Paula
Wieczorek, John
Morris, Paul
Nicholls, Miles
Rees, Emily Rose
Veiga, Allan
Thompson, Alexander
Saraiva, Antonio
James, Shelley
Gendreau, Christian
Benson, Abigail
Schigel, Dmitry

Type

Article

Date of Publication

2020-3-20

Original Publication

Metabarcoding and metagenomics

Volume

4

Pages

1--47

Subjects

Darwin Core , data quality , data quality tests , fitness for use , framework , GBIF , profile , Standards , tests and assertions , vocabularies

Contributed by

Pensoft Publishers

Language

English

Published by

Bulgaria Pensoft Publishers 2017-

Identifiers

DOI: https://doi.org/10.3897/biss.4.50889

 

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.<br> 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.<br> 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.