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

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.

Validating the Two Records of Mocquard’s Swampsnake, Tretanorhinus mocquardi Bocourt 1891 (Dipsadidae), in Colombia, with Comments on the Taxonomy of Mainland Swampsnakes

“…Colombian records include Striped Swampsnakes (T. taeniatus) from along the Pacific Coast (Dunn 1939;Peters and Orejas-Miranda 1970;Wallach et al 2014) and Mocquard's Swampsnakes (T. mocquardi) that correspond to two specimens deposited in the Museo de Herpetología Universidad de Antioquia (MHUA), Medellín, Colombia, and which are listed by the Global Biodiversity Information Facility (GBIF) (Daza 2018). Although T. mocquardi is a species expected to occur in Colombia since its known distribution includes Panama and Ecuador (Cisneros-Heredia 2005), its presence has not been recorded in the literature and information regarding the two presumptive records might contain uncertainties (Maldonado et al 2015;Marshall and Strine 2019;Chapman et al 2020). Data from online databases must be curated both taxonomically and geographically to guarantee reliability (Marshall and Strine 2019).…”

An inventory of biodiversity data sources for conservation monitoring

“…Several other databases, such as the Living Planet Index, also encourage data contributions through their website. Other options include working towards the mainstreaming of data papers by making the publishing of data mandatory in research project proposals and performance assessments [ 62 ], and adopting standards related to data citation, accessibility, metadata, and quality control in order to facilitate integration of data across data sets [ 60 , 63 , 64 ].…”

Conceptual design blueprint for the DiSSCo digitization infrastructure - DELIVERABLE D8.1

“…The precise mechanism to be used remains for further study but could, for example be based on ciphertext-policy attribute-based encryption (CP-ABE) [Bethencourt et al 2007] whereby suitably authorised users have a key that unlocks sensitive data encrypted by the owner/publisher. Alternatively, but less desirable is an approach based on stretched-perimeter access control, whereby 'policy enforcement points' are instantiated to the places where access policy is to be enforced [Burnap et al 2012]. Note, however that neither approach addresses the inherent trust issue, which is that once access has been given, there is little that can be done to prevent further (malicious) dissemination of the controlled sensitive data.…”

“…Improvement activities are normally performed by data curation and publishing teams (curators, collection managers, data publishers and data users, data aggregators). From first beginnings of establishing principles of data quality of GBIF data [Chapman 2005], there has been significant progress in recent years, largely through the work of TDWG volunteers in biodiversity information standards; specifically through the TDWG Data Quality Interest Group that has led to both a conceptual 'fitness for use' framework for quality assessment and improvement of natural sciences data [Veiga et al 2017] and a data quality solutions library of quality tests and assertions that can be applied to data *64 [Chapman et al 2020]. DiSSCo should consider adopting such a conceptual framework for quality assessment and improvement of natural sciences data and to selecting and implementing appropriate data quality tests and assertions to remediate data errors.…”