⚠️ Under Review

The Biodiversity Data Quality (BDQ) Standard

Title
The Biodiversity Data Quality (BDQ) Standard

Category
Technical Specification

Publisher
Biodiversity Information Standards (TDWG)

Status
Draft Standard for Review

Permanent IRI (for citations and links)
http://example.org/to_be_determined

Date version issued
2026-06-03

Date created
2025-05-10

This version
http://rs.tdwg.org/bdqffdq/2026-06-03

Latest version
http://rs.tdwg.org/bdqffdq/

Previous version

Bibliographic citation
TDWG Biodiversity Data Quality Interest Group Task Group 2: Data Quality Tests and Assertions. 2026. The Biodiversity Data Quality (BDQ) Standard. Biodiversity Information Standards (TDWG). http://rs.tdwg.org/bdqffdq/2026-06-03

Abstract
This is the landing and overview page for the Biodiversity Data Quality (BDQ) standard.
BDQ is a standard maintained by the Biodiversity Data Quality Maintenance Interest Group (to be constituted) and designed to facilitate the consistent development and use of a set of biodiversity data quality tests and assertions. The standard consists of vocabularies needed to define the tests, a guide to support the implementation of tests, a guide to support the interpretation of outputs of implemented tests, test data and expected responses from tests against this data to validate implemented tests.

Authors
Lee Belbin (Blatant Fabrications), Arthur D. Chapman (Australian Biodiversity Information Services), Paul J. Morris (Museum of Comparative Zoology, Harvard University), John Wieczorek (Rauthiflor LLC)

Creator
TDWG Biodiversity Data Quality Interest Group Task Group 2: Data Quality Tests and Assertions

Table of Contents

1 Introduction (non-normative)

Beyond data availability, data quality is the most significant challenge for users of biodiversity data. The Biodiversity Data Quality Standard (BDQ) establishes a comprehensive, common, and interoperable framework for evaluating the quality of biodiversity data as fitness for a particular use, rather than as an inherent characteristic of the data itself.

1.1 Purpose of the BDQ Standard (non-normative)

The BDQ standard establishes a community-defined, modular, and extensible environment for biodiversity data quality. BDQ defines a comprehensive set of Tests (bdqtest:), their inputs (InformationElements) and their structured output (Responses). BDQ initially focused on Darwin Core but structurally independent of it. BDQ is a formal Fitness for Use Framework (bdqffdq:) with five supporting vocabularies bdqval:, bdqdim:, bdqcrit:, bdqenh: and bdquc:.

At its core, BDQ focuses on the semantics of data quality. It defines what a Test means and precisely what information a Response must contain. BDQ intentionally avoids prescribing execution concerns (such as data loading or parallelization of Test execution) as well as human centric concerns (such as report presentation or remediation processes). By providing a consistent semantic layer focused on Test inputs and outputs, the standard allows for flexible application within diverse operational settings supporting both Quality Assurance filtering and Quality Control diagnostics. The presentation and serialization of Data Quality Reports is intentionally flexible, so long as the required Response elements are available to consumers.

The primary objective of the BDQ standard is to enhance interoperability. By formalizing Test descriptions and making Test outputs comparable and reusable across different organizations, software tools, and data pipelines, it reduces duplicated effort and ambiguity regarding "what was tested" and "what the outcome means." Ultimately, this enables data providers, aggregators, and researchers to consistently assess fitness for use, prioritize quality improvements, and support transparent, repeatable scientific decisions about the use of biodiversity data.

1.1.1 Purpose of this document (non-normative)

This document serves as the central gateway and index for the Biodiversity Data Quality (BDQ) standard. It provides a high level overview of the standard and contains links to the normative documents that formally define its specifications. Aditionally, it directs diverse audiences to supporting resources designed to facilitate the understanding and effective implementation of BDQ within their specific communities and operational environments.

1.2 Audience for the BDQ Standard (non-normative)

The BDQ standard is intended for:

  • Practitioners and data curators assessing and improving the fitness for use of biodiversity data.
  • Software developers implementing BDQ Tests and integrating Test inputs and outputs into data processing pipelines and software systems.
  • Researchers evaluating dataset suitability for particular analyses and research uses of biodiversity data.
  • Collection managers and data managers interpreting test results to support operational decisions and prioritization of data quality improvement efforts.
  • Standards developers and knowledge engineers aligning related work with BDQ vocabularies and extension points.

For practitioners, researchers, collection managers, and data managers, the BDQ Tests (bdqtest:) provide a shared, community-defined set of Test definitions that can be selected and run as suites to evaluate fitness for use for particular specified uses of biodiversity data.

For developers, standards developers, and knowledge engineers, the Fitness For Use Framework (bdqffdq:) and supporting vocabularies (bdqval:, bdqdim:, bdqcrit:, bdqenh:, and bdquc') contribute to the common semantic model used to define Tests, identify their inputs (Information Elements), and represent their outputs (Responses) in a consistent and interoperable way (in thebdqtest:vocabulary). No background in ontologies is required to understand or apply the Tests, though familiarity with RDF/OWL will be helpful for those working directly with the ontologies or exchangingData Quality Reports` as RDF.

1.3 Contributing TDWG Interest and Task Groups (non-normative)

The Authors acknowledge the fundamental importance of the work of:

  • The TDWG Data Quality Interest Group for providing a foundation and support for the underlying Task Groups.
  • The TDWG Data Quality Interest Group - Task Group 1 BDQFramework, which provided the Framework for the BDQ Tests.
  • The TDWG Data Quality Interest Group - Task Group 3 Data Quality Use Cases for providing recommendations on Use Cases.
  • The TDWG Annotations Interest Group as to how the Test results may be reported against records.

1.4 Associated Documents (non-normative)

See the list of the documents that comprise the standard in 3. Parts of the Standard (non-normative).

1.4.1 Background Documents (non-normative)

These documents are not part of the BDQ standard.

1.5 Status of the Content of this Document (normative)

Sections may be either normative (defines what is required to comply with the standard) or non-normative (supports understanding but is not binding) and are marked as such.

Any sentence or phrase beginning with "For example" or "e.g.", whether in a normative section or a non-normative section, is non-normative.

1.6 RFC 2119 key words (normative)

The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" are to be interpreted as described in RFC 2119.

1.7 Namespace abbreviations (non-normative)

In the BDQ Standard documents, IRIs are frequently abbreviated using namespace abbreviations. The abbreviations used anywhere in the BDQ Standard documents are listed in the following table.

Abbreviation Namespace
ac: http://rs.tdwg.org/ac/terms/
bdqcrit: https://rs.tdwg.org/bdqcrit/terms/
bdqdim: https://rs.tdwg.org/bdqdim/terms/
bdqenh: https://rs.tdwg.org/bdqenh/terms/
bdqffdq: https://rs.tdwg.org/bdqffdq/terms/
bdqtest: https://rs.tdwg.org/bdqtest/terms/
bdquc: https://rs.tdwg.org/bdquc/terms/
bdqval: https://rs.tdwg.org/bdqval/terms/
dc: https://purl.org/dc/elements/1.1/
dcat: http://www.w3.org/ns/dcat#
dcmitype: http://purl.org/dc/dcmitype/
dcterms: http://purl.org/dc/terms/
dqv: http://www.w3.org/ns/dqv#
dwc: http://rs.tdwg.org/dwc/terms/
dwciri: http://rs.tdwg.org/dwc/iri/
foaf: http://xmlns.com/foaf/0.1/
ldqd: http://www.w3.org/2016/05/ldqd#
mids: http://rs.tdwg.org/mids/elements/ (draft)
oa: http://www.w3.org/ns/oa#
owl: http://www.w3.org/2002/07/owl#
prov: http://www.w3.org/ns/prov#
rdf: http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: http://www.w3.org/2000/01/rdf-schema#
skos: http://www.w3.org/2004/02/skos/core#
tdwgutility: http://rs.tdwg.org/dwc/terms/attributes/
xsd: http://www.w3.org/2001/XMLSchema#

1.8 Referring to Terms (normative)

In any technical treatment of the BDQ standard, a precise reference to a class or property term SHOULD be made using its qualified name (the namespace prefix followed by the term local name; e.g., bdqffdq:InformationElement) and the namespace IRI corresponding to the namespace prefix (e.g., 'https://rs.tdwg.org/bdqffdq/terms' for bdqffdq:) MUST be provided. In less formal descriptions where the technical precision is not needed, the preferred label (skos:prefLabel, e.g., Information Element) or the term local name (e.g., InformationElement) MAY be used. You will find all of these methods of referring to BDQ-related terms throughout the BDQ documentation.

1.9 Notation Conventions (non-normative)

Throughout these descriptive documents, terms and phrases styled as inline code (e.g., Validation, Information Element, Data Quality Need) refer explicitly to classes, properties, or named individuals defined in the BDQ ontology bdqffdq: by their labels or by their term local name (e.g. InformationElement). Pluralized forms (e.g., Data Quality Reports) refer to multiple instances of the class.

Terms in text that are specific to the BDQ Standard are Capitalised (e.g. Test, Use Case), but where used generally they are in lowercase (e.g. test, use case).

When a word that is also a bdqffdq class name is not capitalized and styled as inline code, it should be interpreted as a general English phrase or concept, not as a specific ontology term. For example, specification is general while Specification means bdqffdq:Specification, and implementation carries the general meaning while Implementation means bdqffdq:Implementation). This convention is also used for qualified names such as bdqffdq:InformationElement, terms from other vocabularies, such as dwc:countryCode, and to denote some software artifacts such as sci_name_qc.

See also section 3.12 Naming Conventions (non-normative) in the BDQ Supplemental Information.

2 A Roadmap to the BDQ Standard (non-normative)

The Biodiversity Data Quality (BDQ) Standard is documented as a set of complementary resources, rather than as a single, linear specification. These resources are designed to support different audiences and goals, such as interpreting test results, implementing BDQ Tests in software, or defining new Tests and Use Cases.

This section provides a reader‑focused roadmap to that document set. Its purpose is to help readers quickly identify the most appropriate entry point based on their immediate needs, without restating the purpose, principles, or detailed content of the BDQ Standard, which are described elsewhere in this document and in the normative specifications. The table below maps common reader intentions to the primary BDQ resources that address them. It is intended solely as a navigational aid; each linked document remains the authoritative source for its respective content.

The Biodiversity Data Quality (BDQ) Standard
Some Key Concepts: Test Types and Test Inputs and Outputs in the Users Guide.
The BDQ Definition of "Test" in BDQ Tests: Concepts and Use.
Readers & Interpreters of Test Results Implementers of Tests Designers of New Tests
Start with:
📗 BDQ Tests Quick Reference Guide
Concise descriptions of BDQ Tests. First stop for understanding Tests and their outcomes.
 Start with:
📗 BDQ Tests Quick Reference Guide
Overview of Test purposes and outcomes; index into detailed Test definitions.
 Start with:
📙 Tutorial: From Use Case to Test
Recommended starting point for designing a new BDQ Test.
📗 BDQ User’s Guide
Explains how to interpret BDQ Test results and what they imply for data quality and use decisions.
See also Use Cases 		📗 BDQ Implementer’s Guide
Explains how to implement BDQ Tests: inputs, outputs, edge cases, and how to use the Test descriptions and vocabularies in software.
See also Use Cases 		📗 Fitness For Use Framework Ontology: Concepts and Use
Explains the normative concepts and logic for describing data quality needs and reports.
See also the Fitness For Use Framework bdqffdq: Term List and OWL Ontology.
📘 Test Vocabulary & Definitions
The bdqtest: Term-List, complete normative definitions of the Tests themselves, for readers who need exact meanings or wish to trace provenance.
See also the Index to Tests by Use Case 		📘 BDQ Tests: Concepts and Use
Explanations and Normative Guidance on the Tests and their Uses.
See also the bdqtest: Term List
and serialized versions: RDF/XML, Turtle, JSON-LD, and the bdquc: Use Case Vocabulary, 		📘 The bdquc: Use Case Vocabulary
Describes each of the uses of data that the bdqtest: Tests are designed to support.
See also the supporting controlled vocabularies for criteria, dimensions, enhancements, and other elements needed to specify new Tests. bdqval: Vocabulary, bdqcrit: Vocabulary, bdqdim: Vocabulary, bdqenh: Vocabulary.
📙 Tutorial: From Use Case to Test
Worked examples that clarifies the logic of test design. 		📘 Conformance Testing Implementations
Guidance on how to use the provided Test Conformance Testing Data to evaluate whether your Test implementation produces the expected results.
See also the Conformance Testing Data and the Guide to Marking Synthetic Data. 		📘 BDQ Tests Vocabulary & Canonical Definitions
The bdqtest: Term List, providing examples of how existing Tests are formally defined and versioned; useful patterns for new Test design.
📙 Tutorial: From Use Case to Test
Worked example that clarifies the logic behind Tests you implement.
📓 Supplemental Information
Background, rationale, and historical context for BDQ Tests. Helpful but not required for routine interpretation. 		📓 Supplemental Information
Background and rationale that clarify why Tests and implementations are structured as they are. 		📓 Supplemental Information
Background, history, and rationale that help inform new Test designs.

3 Parts of the Standard (non-normative)

This standard is comprised of the following documents and artifacts:

Note: These sections in this document are marked as non-normative, however, most of the documents linked out to here contain normative content.

Note: See the TDWG Standards Documentation Specification (SDS), the TDWG Vocabulary Maintenance Specification (VMS) and the TDWG Standards Metadata document for an explanation of concepts such as landing page, distribution file, term-list, and vocabulary extension and for an explanation of the structure of TDWG resource IRIs and their uses.

3.1 BDQ Tests Quick Reference Guide (non-normative)

The Quick Reference Guide is a simple, informative reference and the first place to look for the most commonly used information about the Tests.

3.2 Guides (non-normative)

Note: This section in this document is non-normative, however, the documents linked to here contain substantal normative content.

These two documents provide overviews and normative guidance of the subjects they cover. The details of the individual terms in each vocabulary are provided in the corresponding term list documents.

These Guides are explanatory documents including some normative guidance targeting particular perspectives on the standard for particular audiences.

3.3 Vocabularies (non-normative)

Note: This section in this document is non-normative, however, the documents linked to here contain normative content.

3.3.1 Foundational Vocabularies (non-normative)

The Foundational Vocabularies cover the two main parts of the standard - the practical (the Tests) and the theoretical (the Framework).

3.3.2 Supporting Vocabularies (non-normative)

The Supporting Vocabularies are controlled vocabularies used in the technical definitions of the Tests.

3.3.3 Landing Page IRIs (non-normative)

Note: For each of the following documents the landing page IRI will resolve to the term list document when HTML is requested.

Note: None of these links will work until deployment of the standard, but they are included here to show the intended structure of the IRIs and to provide a complete list of the landing page, term list IRIs, and related RDF metadata documents for the standard.

3.4 Additional Documents (non-normative)

3.4.1 Supplemental Information (non-normative)

The non-normative Supplemental Information includes the rationale for, the history of, and the challenges met while describing the Tests.

3.4.2 Tutorial (non-normative)

The non-normative Tutorial provides a worked through example of the thought process in defining a 'Use Case' and a Test that supports the Use Case.

3.5 Distribution Files (non-normative)

3.5.1 Tests (non-normative)

The Test definitions are provided in various serializations. Of these, the bdqtest_term_versions.csv is the canonical archive of all Tests versions, both recommended and historical. The documentation about the details of Tests for this standard are generated from this file. CSV files listing just the current test versions are also provided,

3.5.2 Test Conformance Testing Data (non-normative)

Test Confomance Testing Data are intended for implementers to use to evaluate whether Test Implementations produce the Expected Responses.

3.5.3 Fitness For Use Framework (non-normative)

The Fitness For Use Framework is provided as an OWL ontology.

3.5.4 RDF Serializations of Supporting Controlled Vocabularies (non-normative)

4 Implementations (non-normative)

The BDQ standard does not include implementations of Tests, but there are external implementations of the Tests that are available for use and demonstration of the standard. These implementations are not part of the standard, but they are provided as resources for implementers and users of the standard.

4.1 Java Implementation (non-normative)

While not part of the BDQ standard, a validated JavaÂź implementation of the Tests is provided in the event_date_qc, sci_name_qc, geo_ref_qc and rec_occur_qc libraries. Also see bdqtestrunner, which demonstrates conformance of these libraries with the provided Test Conformance Testing Data.

4.2 BDQEmail (non-normative)

While not part of the BDQ standard, GBIF Norway has developed a tool called BDQEmail that allows users to submit records for testing and receive results via email. This tool wraps the Java implementation of the Tests with an email and large language model processing system and provides an accessible way for users to evaluate the quality of their biodiversity data using the BDQ Tests without needing to implement the Tests themselves. The tool (gbif-norway/bdq-multirecord-agent) is described at: https://www.gbif.no/services/index.html.

5 Contributions and Acknowledgments (non-normative)

5.1 Acknowledgments (non-normative)

The Authors gratefully acknowledge all those who have commented on the GitHub issues during the development of the BDQ standard, and all those who have contributed to discussions at various workshops in São Paulo, Brazil; Canberra, Australia; Monash, Australia; Leiden, The Netherlands; Gainesville, USA; and Seattle, USA, and at Biodiversity Information Standards (TDWG) annual meetings (in Jönköping, Sweden; Santa Clara de San Carlos, Costa Rica; Ottawa, Canada; Dunedin, New Zealand; Leiden, The Netherlands; Sofia, Bulgaria; Hobart, Australia; and Ginowa, Japan; and the various virtual meetings). The Authors are also grateful for all those who responded to our email questions.

We'd also gratefully acknowledge the continued support of the Biodiversity Information Standards (TDWG) Executive over the 10 years of this project.

5.1.1 Funding and Support for Meetings (non-normative)

We acknowledge the financial support of The Atlas of Living Australia and Biodiversity Information Standards (TDWG) for Lee Belbin and Arthur Chapman to attend two face-to-face meetings for the development of the BDQ standard, and the Atlas of Living Australia for support of John Wieczorek to attend meetings in Canberra Australia. The Museum of Comparative Zoology provided support for Paul Morris; VertNet, Kurator, and Rauthflor LLC provided support for John Wieczorek. The United States National Science Foundation through funding of the Kurator project, provided time for Paul Morris, Robert Morris and David Lowery for early work on the project.

The SĂŁo Paulo Research Foundation (FAPESP), the Universidade de SĂŁo Paulo (USP) provided facilities, and with the Global Biodiversity Information Facility and others, supported participants to attend the meeting in SĂŁo Paulo, Brazil. The US National Science Foundation through iDigBio provided support for the meeting in Gainesville, Florida.

5.2 Contributions (non-normative)

5.2.1 Authors (non-normative)

We recognize four people as authors of the standard, having contributed consistently over the last decade and having been heavily engaged in writing the BDQ Test Descriptions and the documentation for the BDQ standard.

  • Lee Belbin (Blatant Fabrications Pty Ltd): Convener of TDWG Data Quality Task Group 2 (Data Quality Tests and Assertions); Test descriptions; author of the BDQ standard documents; Test Conformance Testing Data.
  • Arthur D. Chapman (Australian Biodiversity Information Services): Co-convener of the TDWG Data Quality Interest Group; Test descriptions; author of the BDQ standard documents; vocabularies.
  • Paul J. Morris (Museum of Comparative Zoology, Harvard University): Test descriptions; Fitness For Use Framework ontology; Java Test implementations in filteredpush packages; author of the BDQ standard documents; Test Conformance Testing Data.
  • John Wieczorek (Rauthiflor LLC): Test descriptions; Test implementations; author of the BDQ standard documents; Darwin Core liaison.

5.2.2 Contributors (non-normative)

There were many people who have made notable contributions at various times during the development of the BDQ standard.

  • Paula F. Zermoglio (Instituto de Investigaciones en Recursos Naturales, AgroecologĂ­a y Desarrollo Rural (IRNAD, CONICET-UNRN), San Carlos de Bariloche): Convener of TDWG Data Quality Task Group 4 (Best Practices for Development of Vocabularies of Value); Test descriptions; vocabulary development.
  • Alexander Thompson (iDigBio): Key contributions to initial development of Test descriptions; migrated Test descriptions into Markdown tables in GitHub issues.
  • Yi-Ming Gan (Royal Belgian Institute of Natural Sciences): Contributed to Test evaluation; explanatory workflow diagrams; editing the documents of the BDQ standard.
  • AntĂłnio Mauro Saraiva (Universidade de SĂŁo Paulo): Co-convenor of the TDWG Data Quality Interest Group; development of the Framework for Data Quality (TDWG Data Quality Task Group 1); facilitated Test development workshop.
  • Allan Koch Veiga (Universidade de SĂŁo Paulo): Developed the Framework on Data Quality as his doctoral dissertation (Veiga 2016), Convener of the TDWG Data Quality Task Group 1 (Framework for Data Quality).
  • David Lowery (Museum of Comparative Zoology, Harvard University): Initial development of ontology representation of Framework on Data Quality; developer of kurator-ffdq Java class representation of the Framework.
  • Christian Gendreau (Agriculture and Agri-Food Canada): Initial contributions to data quality discussions; vocabulary definitions and early Test development.
  • Tim Robertson (Global Biodiversity Information Facility): Contributions to Test descriptions; clarification of GBIF vocabulary and API resources for the BDQ Tests.
  • Dmitry Schigel (Global Biodiversity Information Facility): Initial contributions to data quality discussions and vocabulary definitions; GBIF Representative to the Data Quality Interest Group in early years.
  • Robert A. Morris (late, of UMass Boston): Competency questions for the ontology of the Data Quality Framework; guided initial development of the ontology representation of the Framework.
  • Miles Nicholls (Atlas of Living Australia): Convener of TDWG Data Quality Task Group 3 (Data Quality Use Cases); Use Case analysis.
  • Emily Rose Rees (Atlas of Living Australia): Use Case analysis in TDWG Data Quality Task Group 3 (Data Quality Use Cases).
  • Abigail Benson (U.S. Geological Survey): Initial contributions to data quality discussions and vocabulary definitions.

6 Glossary (non-normative)

The glossary of terms used in the BDQ standard includes acronyms and these terms that are additional to the terms used in the bdqffdq, bdqval:, bdqcrit:, bdqdim:, and bdqenh: vocabularies or in one of the two tables that reference the Test Vocabulary Terms or the Test Label Components. Note: ‘Darwin Core terms’ refer to Darwin Core Terms (Darwin Core Maintenance Group 2021).

Note: Some terms are definied differently within different documents to align with the context of those documents. For example, in the BDQ Supplemental Information Document, the Table in #5.2 describes the GitHub Tags that were used when preparing the Tests. These Tags and their definitions sometimes differ from the definitions used with the BDQ Standard. The definitions in the Glossary here do however take precedence for the Standard.

Label Definition Context
Actual Parameter The value that is provided when a function or method is called. Actual parameters are the real data that are passed to a function to replace the formal parameters. In the function f(x) = x^2, x is a formal parameter that can be replaced by the actual parameter value 4, and thus be evaluated as f(4) = 4^2 = 16. In VALIDATION_GENUS_FOUND, the formal parameter bdqval:sourceAuthority may take the actual parameter "GBIF Backbone Taxonomy". bdqffdq:
ALA The Atlas of Living Australia (ALA) is a collaborative, digital, open infrastructure that pulls together Australian biodiversity data from multiple sources, making it accessible and reusable. Biodiversity Data Aggregator
Ambiguous Used to report where bdqdim:Conformance is not satisfied due to Information Elements not being unambiguously resolvable by a Source Authority. Data Quality
Atlas of Living Australia The Atlas of Living Australia (ALA) is a collaborative, digital, open infrastructure that pulls together Australian biodiversity data from multiple sources, making it accessible and reusable. Biodiversity Data Aggregator
BDQ Biodiversity Data Quality Standard. This document. TDWG Standard
BDQIG Biodiversity Data Quality Interest Group TDWG Interest Group
BISON USGS Biodiversity Information Serving Our Nation (BISON) is a unique, Web-based Federal mapping resource for species occurrence data in the United States and its Territories. Biodiversity Data Aggregator
CORE Tests that are useful for evaluating biodiversity data quality as represented by the values of Darwin Core terms. CORE tests address identified user needs, are widely applicable, informative, unambiguous, well defined, and straight forward to implement. The CORE Tests have become the Tests defined in the BDQ standard. Tests
CRIA Centro de ReferĂȘncia em Informação Ambiental (Reference Center for Environmental Information) is a network to make information about Brazil’s biodiversity accessible to all. Biodiversity Data Aggregator
CRS Coordinate Reference System - (also referred to as 'spatial reference system'). A coordinate system defined in relation to a standard reference or datum (Chapman & Wieczorek 2020). Tests
Darwin Core Darwin Core. A Standard intended to facilitate the sharing of information about biological diversity. Host of the dwc:namespace dwc: TDWG standard
Database of record An information system which holds an authoritative or master record of some data. Records in a database of record are held to be correct over different values for the same records that might be found in other datasets. This is in distinction from aggregated datasets, derived research dataset, datasets for portals and other holders of non-authoritative copies of the data. BDQ standard
DCMI DCMI Metadata Terms. (Dublin Core). Hosts dc:Namespace dc: Standard
DefaultSourceAuthority A provided default bdqval:sourceAuthority that is used when a required bdqval:Parameter specifying a bdqval:sourceAuthority has not been provided at the time the Test is run. bdqffdq:hasAuthoritiesDefaults
DefaultValue A preselected value (e.g., year, elevation) to be used where a required bdqval:Parameter value has not been provided at the time the Test is run. bdqffdq:hasAuthoritiesDefaults
Dimension See bdqffdq:DataQualityDimension. bdqffdq:
DO NOT IMPLEMENT Tests that are not CORE and not recommended to be implemented with the current level of understanding for one or more reasons: Available vocabularies are ambiguous; the Test is too complex to implement concisely; implementation is expected to lead to ambiguous or inaccurate results. Tests
Dublin Core International Metadata Standard (DCMI). Standard
DwC Darwin Core. A Standard intended to facilitate the sharing of information about biological diversity. Host of the dwc:namespace dwc: TDWG standard
EPSG European Petroleum Survey Group database contains many definitions of coordinate reference systems and coordinate transformations which may be global, regional, national, or local in application. Geodetic Parameter Dataset
EVALUATION The third part of a standard Test name, describing what a Test is testing, as in TESTTYPE_INFORMATIONELEMENT_EVALUATION, e.g. STANDARD in VALIDATION_COUNTRYCODE_STANDARD Tests
Formal Parameter A placeholder defined in the function or method signature. It represents the input that the function expects. In the function f(x) = x^2, x is a formal parameter of the function f. In "VALIDATION_GENUS_FOUND", bdqval:sourceAuthority is a formal parameter. bdqffdq
Framework The Fitness for Use Framework, the body of work that provides a fundamental structure for the BDQ Tests. The Fitness for Use Framework is derived from (Veiga 2016) and is the outcome of the TDWG Data Quality Task Group 1: Framework on Data Quality (Veiga et al. 2017). bdqffdq
Framework Ontology A model of the Framework (Veiga 2016, Veiga et al. 2017) as an OWL ontology, present as the bdqffdq: vocabulary in the BDQ standard. bdqffdq
GBIF Global Biodiversity Information Facility is an international network and data infrastructure funded by the world’s governments and aimed at providing anyone, anywhere, open access to data about all types of life on Earth. Biodiversity Data Aggregator
geodetic coordinate reference system A coordinate reference system based on a geodetic datum, used to describe positions on the surface of the earth (Chapman and Wieczorek 2020). Tests
geodetic datum A mathematical model that uses a reference ellipsoid to describe the size and shape of the surface of the earth and adds to it the information needed for the origin and orientation of coordinate systems on that surface (Chapman and Wieczorek 2000). Tests
Global Biodiversity Information Facility Global Biodiversity Information Facility (GBIF) is an international network and data infrastructure funded by the world’s governments and aimed at providing anyone, anywhere, open access to data about all types of life on Earth. Biodiversity Data Aggregator
GUID Globally Unique Identifier. In this document, the GUID for a Test is a UUID (128-bit universally unique identifier) which identifies the Test. Tests
iDigBio Integrated Digitized BioCollections is the United States of America National Resource for Advancing Digitization of Biodiversity Collections (ADBC) funded by the National Science Foundation. Biodiversity Data Aggregator
Immature / Incomplete Tests where substantial work is needed to develop the Specification to the point where the test can be reliably and usefully implemented. This may indicate work that is wholly internal to the test specification such as developing a consistent Expected Response or may indicate that external work is needed to develop an agreed vocabulary for values of the tested term. An Immature/Incomplete test may be made CORE, Supplementary, or DO NOT IMPLEMENT when relevant criteria are satisfied. Tests
IRI Internationalized Resource Identifier is an internet protocol standard which builds on the Uniform Resource Identifier (URI) protocol by greatly expanding the set of permitted characters. Standard
ISO International Organization for Standardization. Standard
ISO / DCMI Standard Tag used in the GitHub version of the Tests to indicate that a test references either an ISO or a DCMI Standard GitHub Tag
Java Java is a registered trademark of Oracle and/or its affiliates. BDQ standard
NAME A BDQ GitHub label to indicate that the Test is related to Darwin Core terms in the dwc:Taxon Class. bdqffdq:InformationElement
NEEDS WORK Tag used in the GitHub version of the Tests to indicate that a test description needs further work before conclusion. GitHub Tag
non-printing characters ASCII 0-32 and 127 decimal. Non-printing characters or formatting marks that are not displayed when printing. These may include pilcrow, space, non-breaking space, tab character, etc. For the purposes of the Tests they are treated as bdqval:Empty. Data
null A value that is used in some databases to signify that a value is unknown or missing. It may be represented in serializations of data outside of database environments by strings such as "NULL", "Null", "null". "/n", "9999", "NA", etc. These serializations should be treated as bdqval:NotEmpty. Data
OA Web Annotation Vocabulary specifies the set of RDF classes, predicates and named entities that are used by the Web Annotation Data Mode. Hosts the namespace oa: W3C Standard
OTHER A bdq GitHub label to indicate that the Test is related to Darwin Core terms other than Classes dwc:Taxon, dwc:Location or dwc:Event. bdqffdq:InformationElement
OWL Web Ontology Language. A Semantic Web language designed to represent rich and complex knowledge about things. Hosts the namespace owl: W3C Standard
Parameterized Pertains to a Test that allows a bdqffdq:Parameter to be set prior to the test being run. Where a bdqffdq:Parameter value has not been provided, a default is specified within the test. Tests
Python A high-level, general-purpose programming language known for its readability and versatility. Python Software Foundation. Programming language
QA bdqffdq:QualityAssurance. The process of evaluating data for fitness for some use and selecting just those data that are fit for that use. See also User's Guide #2.1. Data Quality
QC bdqffdq:QualityControl. The process of identifying data that are not fit for particular uses, with the goal of improving the data quality. The tests may propose changes to improve the quality of the data. See also User's Guide #2.1. Data Quality
RDF Resource Description Framework - a W3C standard for modeling, interchanging, and linking structured data on the web. Hosts the namespace rdf: W3C Standard
RDFS A semantic extension of RDF using the namespace rdfs: W3C Standard
Response.comment A human readable interpretation of the results of a Test. A shortcut for bdqffdq:hasResponseComment Data Quality Report
Response.qualifier Additional structured information that qualifies the Response, intended as an extension point for uncertainty. A shortcut for bdqffdq:ResponseQualifier, bdqffdq:hasResponseQualifier Data Quality Report
Response.result The element in a Response containing the value returned by a Test. A shortcut for bdqffdq:ResponseResult, bdqffdq:hasResponseResult, bdqffdq:hasResponseResultValue Data Quality Report
Response.status A metadata element in a Response indicating whether a particular Test was able to be performed or not. A shortcut for bdqffdq:ResponseStatus, bdqffdq:hasResponseStatus Data Quality Report
Roman numerals Numbers written with the characters I, V, X, L, C, D, and M in the latin alphabet, each letter representing an integer and combined to form arbitrary integers. Roman numerals are interpreted as the equivalent integer for months (e.g., "X" as "10") in certain Tests. Roman numerals may not be unambiguously interpreted for other Darwin Core terms such as dwc:day or in text fields as they may mean unknown or something else entirely. Data
SDS TDWG Standards Documentation Standard TDWG Standard
SKOS Simple Knowledge Organization System. Hosts the namespace skos: W3C Standard
SPACE A BDQ GitHub label to indicate that the Test is related to Darwin Core terms in the dwc:Location Class. bdqffdq:InformationElement
SRS spatial reference system - see CRS (Chapman and Wieczorek 2020). Tests
Supplementary Tests regarded as not CORE because of one or more reasons: Not widely applicable; not clearly matched to an identified data quality need; not informative concerning the "quality" or lack of quality of the data; likely to return a high percentage of either NOT_COMPLIANT or POTENTIAL_ISSUE records. A Supplementary Test MAY be implemented in a local implementation if a suitable Use Case exists. Tests
TDWG Biodiversity Information Standards Standards
Term-Action The last two components of the Label in the BDQ GitHub. Test descriptors, useful in filtering Tests in CSV files. Example: "COUNTRYCODE_STANDARD" GitHub
Test A composition of a bdqffdq:DataQualityNeed with a bdqffdq:DataQualityMethod that links it to an instance of a bdqffdq:Specification, these instances being composed of InformationElements, Arguments, and Parameters. See the Conceptual map diagram BDQ standard
Test (technical) A composition of an instance of a subclass of bdqffdq:DataQualityNeed (which expresses a data quality need in the abstract) with an instance of a subclass of bdqffdq:DataQualityMethod, which links it to an instance of a bdqffdq:Specification (which spells out how to concretely evaluate the need). These class instances are composed with bdqffdq:InformationElements, bdqffdq:Arguments, and bdqffdq:Parameters. For example, the Test VALIDATION_COUNTRY_FOUND. BDQ standard
TestField Column heading in the Markdown of the Tests in the tdwg/bdq GitHub that list all the normative and informative metadata elements that describe a Data Quality Test. Tests
Test Type There are four types of Tests: Validation (bdqffdq:Validation), Amendment (bdqffdq:Amendment), Issue (bdqffdq:Issue), and Measure (bdqffdq:Measure). Tests
TG1 [Biodiversity Data Quality Interest Group - Task Group 1: Framework on Data Quality] (https://www.tdwg.org/community/bdq/tg-1/) TDWG Task Group
TG2 Biodiversity Data Quality Interest Group - Task Group 2: Data Quality Tests and Assertions TDWG Task Group
TG3 Biodiversity Data Quality Interest Group - Task Group 3: Data Quality Use Cases TDWG Task Group
TG4 Biodiversity Data Quality Interest Group - Task Group 4: Best Practices for Development of Vocabularies of Values TDWG Task Group
TIME A BDQ GitHub label to indicate that the Test is related to Darwin Core terms in the dwc:Event Class. bdqffdq:InformationElement
VertNet VertNet is a network of individuals, organizations and institutions that explore, study and care about and share vertebrate species data globally. Biodiversity Data Aggregator
VOCABULARY Tag used in the GitHub version of the Tests to indicate that a Test requires a controlled Vocabulary. GitHub Tag
whitespace Characters such as spaces and tabs that affect rendering of printed or displayed output, but which themselves are not printed. 1) A field that only includes whitespace is treated as bdqval:Empty. 2) In bdqffdq:Validation, Tests that require the look up of a bdqval:sourceAuthority, leading and/or trailing whitespace will cause the Test to fail as no pre-processing is carried out on the data. These leading and trailing whitespaces may be stripped out in a subsequent bdqffdq:Amendment and thus pass when the bdqffdq:Validation Test is run again. Data
XSD W3C XML Schema Definition Language facilities describing the structure and constraining the contents of XML documents. Hosts the namespace xsd: W3C Standard

7 References (non-normative)

We have used the formatting recommended by Pensoft, see https://checklist.pensoft.net/about#AuthorsGuidelines.

8 Cite BDQ (non-normative)

To cite BDQ in general, use the peer-reviewed article:

Chapman AD, Belbin L, Zermoglio PF, Wieczorek J, Morris PJ, Nicholls M, Rees ER, Veiga AK, Thompson A, Saraiva AM, James SA, 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://doi.org/10.3897/biss.4.50889

To cite this document specifically, use the following:

TDWG Biodiversity Data Quality Interest Group Task Group 2: Data Quality Tests and Assertions. 2026. The Biodiversity Data Quality (BDQ) Standard. Biodiversity Information Standards (TDWG). http://rs.tdwg.org/bdqffdq/2026-06-03

Biodiversity Information Standards (TDWG)

This content made open by Biodiversity Information Standards (TDWG) is licensed under a Licensed under a Creative Commons Attribution 4.0 International (CC BY) License.