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Scientific Names Are Ambiguous as Identifiers for Biological Taxa: Their Context and Definition Are Required for Accurate Data Integration


Abstract and Figures

Biologists use scientific names to label the organisms described in their data; however, these names are not unique identifiers for taxonomic enti- ties. Alternative taxonomic classifications may apply the same name, associated with alternative definition or circumscription. Consequently, labelling data with scientific names alone does not unambiguously distinguish between taxon con- cepts. Accurate integration and comparison of biological data is req uired on taxon concepts, as defined in alternative taxonomic classifications. We have de- rived an abstract, inclusive model for the diverse representations of taxonomic concepts used by taxonomists and in taxonomic databases. This model has been implemented as a proposed standard XML schema for the exchange and com- parison of taxonomic concepts between data providers and users. The represen- tation and exchange of taxon definitions conformant with this schema will facilitate the development of taxonomic name/concept resolution services, al- lowing the meaningful integration and comparison of biological datasets, with greater accuracy than on the basis of name alone.
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Scientific names are ambiguous as identifiers for
biological taxa: their context and definition are required
for accurate data integration
Jessie B. Kennedy, Robert Kukla and Trevor Paterson.
School of Computing, Napier University, Edinburgh, EH10 5DT, U.K.
{j.kennedy, r.kukla, t.paterson}
Abstract. Biologists use scientific names to label the organisms described in
their data; however, these names are not unique identifiers for taxonomic enti-
ties. Alternative taxonomic classifications may apply the same name, associated
with alternative definition or circumscription. Consequently, labelling data with
scientific names alone does not unambiguously distinguish between taxon con-
cepts. Accurate integration and comparison of biological data is required on
taxon concepts, as defined in alternative taxonomic classifications. We have de-
rived an abstract, inclusive model for the diverse representations of taxonomic
concepts used by taxonomists and in taxonomic databases. This model has been
implemented as a proposed standard XML schema for the exchange and com-
parison of taxonomic concepts between data providers and users. The represen-
tation and exchange of taxon definitions conformant with this schema will
facilitate the development of taxonomic name/concept resolution services, al-
lowing the meaningful integration and comparison of biological datasets, with
greater accuracy than on the basis of name alone.
1 Introduction
Scientific names are inherently poor identifiers for organisms, because although
names are formalized and validated according to strict codes of nomenclature, the
same name can be applied by taxonomists to alternative taxonomic views of the ex-
tent or definition of a taxon (e.g. a species, genus etc.). Biologists (i.e. the 'users' of
taxonomic classifications) identify and label their data with scientific names, by iden-
tifying their organisms according to a particular taxonomic classification, as found for
example in field guides, but without recognizing and recording that taxonomic con-
text. As a consequence datasets cannot be reliably integrated on the basis of the scien-
tific names because the context or meaning of the name is not captured.
Taxonomic identification is emerging as a significant problem for the integration
and comparison of diverse datasets across all fields of biology from genomics to ecol-
ogy. For example, annotations of Genbank DNA sequences typically label the source
species according to the NCBI Taxonomy (
Whilst specifically disclaiming any 'taxonomic authority' NCBI attempts to provide a
single consensus view on taxonomy and represent name alterations and 'corrections'
by encoding synonym relationships for use by their search engines (for example the
2 Kennedy et al.
genus Fugu has recently been 'renamed' Takifugu). Such an approach cannot deal with
complex, changing and unrecorded relationships between names as used according to
alternative taxonomic views. For example, the alternate classification and reclassifica-
tion of Orangutans into separate species or subspecies means that sequence data might
be labelled according to a variety of alternative classifications. (Currently over 50,000
nucleotide sequences are ascribed to Pongo pygmaeus, with fewer than 100 for each
'subspecies' abelii and pygmaeus). It is not clear how the NCBI Taxonomy might
handle the alternative reclassification of these sub-species as species or whether the
50, 000 P. pygmaeus sequences include data that some taxonomists would ascribe to
abelii (species or subspecies). These problems impact on other areas of biology and
beyond. For example, the increase between 1996 and 2000 in the number of officially
endangered primate species is partly attributable to the decision in 2000 to accept the
reclassification of some subspecies (including Orangutan) at the species level [1].
Clearly consideration of species names in isolation, without the appropriate classifica-
tory context, makes it difficult to interpret biodiversity data such as the distribution of
Orangutans, when collected at different times, and labelled according to different
(unrecorded) classification contexts.
1.1 Taxonomy and Nomenclature
Taxonomists classify organisms into hierarchically ranked taxa according to their
evolutionary relatedness, based on any of a variety of types of biological evidence
(morphology, genetics, palaeontology etc.). Alternative classifications (taxonomic
revisions) arise over time reflecting new or alternative taxonomic opinion following
more detailed study, the discovery of new taxonomic information such as evidence
about relationships between taxa, description of new species, and increasingly mo-
lecular phylogenies based on DNA sequence comparison. Therefore taxonomy is
itself an investigative science, and taxonomic classifications represent partial and
evolving hypotheses rather than static identifications of absolute taxa. Any recorded
taxonomic classification represents an opinion, according to one authority, at a given
time. Relationships may be expressed or inferred between successive or alternative
taxonomies, relating the concepts (taxa) in one classification to concepts in another,
but without knowing the total genetic history of all life on earth it is not possible to
derive a final, 'true' classification of existing (and extinct) organisms.
Taxonomists use scientific names in order to label and communicate about the
taxonomic concepts that they create. Names are applied to the taxa in a given classifi-
cation according to the codified rules of nomenclature, based on 'typification' (i.e. by
reference to archived 'type' specimens) and following the principle of 'priority' where
names are dependent on the oldest type specimen included in the circumscription of a
taxon. This system provides stability to scientific names over time, as they are pre-
served in relation to their original use and type specimen. However, as a direct conse-
quence of the application of these rules the same valid scientific name will apply to
different views of a taxon according to different postulated taxonomic classifications.
Indeed it is also true that very similar taxonomic concepts may have different names
according to different classifications.
Taxonomic Concepts 3
Names therefore are a part of a 'taxon concept', and cannot be used to unambigu-
ously identify a concept. The identifiers used by experimental biologists to label or-
ganisms as a member or instance of a particular taxonomic concept should
unambiguously refer to the taxon concept itself: true integration therefore requires
unique identifiers for taxon concepts. We propose these concept identifiers should
minimally include the scientific name applied and the classification context. This
context is represented by the authorship of the concept, i.e. an 'According To' or
secundum (sec.) citation. Assigning identifiers for concepts allows simple resolution
of taxon concepts based on identity, particularly if GUIDs were to be adopted for
Taxonomic concepts are created and defined (or revised) in taxonomic publica-
tions. These publications may include various levels of detail defining each taxon,
which might include: character descriptions (i.e. a list of structure, attribute, value
triples), lists of archived specimens which are included in the taxon (specimen cir-
cumscription), relationships to other concepts in the same classification (including
parent-child relationships between a taxon and its subordinate taxa), relationships
with concepts in earlier alternative classifications, assignment of rank (family, genus,
species etc.) and application of a scientific name for this taxon. Individual taxono-
mists have different perceptions or models for what constitutes and defines a taxon.
This makes comparison of alternative taxon concepts problematic, even if the full
rationale for the classification is available. However, comparing components of con-
cept definitions might allow experienced Taxonomists to establish and record rela-
tionships between concepts with different GUIDs (e.g. two concepts can be
considered equivalent for some particular purpose).
1.2 The users of taxonomic classifications
The complex issues of ambiguity surrounding taxonomic classification and naming
are well understood by expert taxonomists, but their importance and consequences are
probably not considered relevant by experimental biologists who wish to use the
names as static identifiers for the organisms described in their data. The explosion in
biological data makes the accurate identification of source organisms critical. For
example a researcher will frequently wish to identify which available datasets contain
information on a particular organism of interest. Typically datasets are annotated by
scientific name. However, correct identification of these datasets requires matching
the taxonomic concepts as used in the source datasets, with the taxonomic concept of
interest to the researcher (as defined by their reference classification). This requires
either the use of identifiers for concepts, or comparison of the actual definitions of the
concepts of interest with the definitions used by the authors of each dataset. A corol-
lary of this is that datasets should be marked up with unambiguous taxonomic concept
identifiers, for example they should reference the identification guide or classification
system used by the researcher: identification by scientific name alone is insufficient.
By way of example a researcher wishing to access data on a fictitious species Aus
bus from globally distributed databases might minimally want to recover data about
any species that had ever been known as species Aus bus, or they might want to ex-
tend this query to recover information about all named species asserted to be synony-
4 Kennedy et al.
mous with Aus bus at some level. Alternatively, if they have precise knowledge of the
underlying concept described as species Aus bus they may only want to retrieve in-
formation about concepts closely related to their own concept of Aus bus, regardless
of their identifying names. Such detailed exploration of all species that overlap or are
equivalent with Aus bus is only possible if 'names' are resolved according to the con-
cepts to which they have been attached, so that data is retrieved on the basis of con-
cept comparison, regardless of nomenclatural issues. Firstly however we require a
common exchange schema to facilitate the representation, exchange and query of
In the following section we describe the current use of biological nomenclature and
present an example to illustrate the problems associated with relying upon scientific
names as identifiers for organisms. In section 3 we discuss the variety of approaches
taken by biologists when describing taxonomic concepts and in section 4 argue the
case for a standard schema to allow the exchange of this data to permit potential com-
parison and resolution of taxonomic concepts. In section 5 we present our work in
defining the Taxonomic Concept Schema, an XML exchange standard for taxonomic
concepts and names and compare this to other models in section 6. Finally some
conclusions are drawn in section 7.
2. Using Names As Identifiers Of Concepts
The formulation and application of valid scientific names for taxonomic groups is
governed by separate codes of nomenclature for botany, zoology, bacteria and viruses
(ICBN [2]; ICZN [3]; ICSP [4], ICTV [5]). According to these rules the name of a
taxon is usually determined by the oldest type specimen included in its circumscrip-
tion. The history of the fictitious genus Aus detailed in Figure 1 (and described more
fully online [6]) illustrates how the rules of nomenclature provide stability for names
throughout the history of taxonomic revisions, but automatically mean that names
cannot be used as unique, non-ambiguous identifiers of taxon concepts. In fact the use
of species names can never be truly separated from a taxonomic classification because
the rules of binomial nomenclature obscure the boundary between classification and
nomenclature for taxon names below the level of 'genus' (see for example [7]).
Where a full scientific name is used with attribution to the authors of the name and
of the taxonomic revision, this represents a clear identifier for a concept. However,
this level of detail is rare outwith specialist taxonomy. Most users and creators of
biological data are not expert in taxonomy, and the names or labels that they use to
refer to specimens and organisms include ad-hoc labels, common names or the (some-
times approximate or inaccurate) scientific name for a species or higher taxonomic
group. Published and electronically deposited data might therefore be labelled with a
variety of names, of varying precision and specificity. For example data about a par-
ticular species of 'daisy' can be found labelled as: lawn daisy, English lawn daisy,
european lawn daisy, USDA code BEPE2, APNI code 163507-3, ITIS TSN 36862,
Bellis perennis, Bellis perennis L., Bellis perennis L. Sp.Pl. 886, Bellis perennis L.
Species Plantarium 2 1753, Bellis perennnis L. Species Plantarium (1753): 886, Erig-
eron perennis (L.) Sessé & Moc., Conyzopsis bellis EHL Krause. Integration and
Taxonomic Concepts 5
resolution between such diverse and semantically distinct names is clearly non-trivial,
where even a 'single' name might be recorded with minor variations due to errors and
corrections in spelling, or there may be variation in the abbreviations used.
A growing number of taxonomic resources and databases are available online,
which seek to provide an integrated record of the names and taxonomic relationships
for a particular narrow or wide taxonomic range (e.g. FishBase,;
ITIS, These taxonomic databases require quite complex models
of taxonomic names in order to represent their data and to account for the needs of
their users. Historically such databases only represented single, aggregated views of
taxonomy, but it is now recognized that the issue of multiple classifications should be
addressed. This requires consideration both of the synonymies between names as used
in alternative classifications, and the application of the same name to different con-
cepts in alternative classifications. Current representations of synonymy between
names fail to capture the full complexity of these relationships which imply differ-
ences between concept definitions not simply between names.
Figure 1. Taxonomic history of the imaginary genus Aus L. 1758 (i) through four subsequent
revisions (ii v). Individual specimen organisms are represented by the symbols ¡, o, r etc.,
with nomenclatural type specimens infilled: p, ¢, ˜. In 1965 Archer split Aus bus Archer
1965 from Aus aus L.1758 (ii), which was in turn 'split' creating Aus cus Fry 1989 (iii). Discov-
ery of new specimens in 1991 caused Tucker to re-'lump' taxa in a single species Aus aus
L.1758 (iv), but according to Pargiter these new specimens indicated that bus (Archer) in fact
belonged in a separate new genus as Xus bus (Archer) Pargiter 2003 (v). Comparing the speci-
men circumscription of the various views on the taxa it is clear that the underlying concepts
referred to by the various names change over time. For example compare Aus aus L.1758 in (i)
versus (ii); or Aus bus Archer 1965 in (ii) and (iii); or the relationship of Aus bus with Xus bus.
3. Defining Taxonomic Concepts
A taxonomic concept is one view of what constitutes a taxonomic entity, be it a spe-
cies, genus or taxon of higher rank. Typically this would be represented as a pub-
lished opinion or hypothesis according to a given author team, and include a valid
scientific name as controlled by the rules of nomenclature. Care should be taken to
distinguish between published taxonomic concepts, representing taxonomists' classifi-
6 Kennedy et al.
cation hypotheses, and the publication of data by biologists who are only identifying
organisms according to some preexisting taxonomic concept, i.e. name usage [8].
A minimal representation of a taxon concept is therefore a scientific name plus ci-
tation of definition (i.e. an attribution). In this respect any first usage of a scientific
name represents an original taxon concept, as published by the author of the name. As
the rules of nomenclature require the original author to be included as part of the
name, e.g. Aus aus L. 1758, this combination does not uniquely distinguish the origi-
nal concept in a taxonomic database, as the same name might be valid for subsequent
revision concepts, which should be distinguished by recording the originator of the
concept, in addition to the author of the name (as part of the full scientific name), e.g.
Aus aus L. 1758 sec. Fry 1989. Recording the originating (sec.) authorship for a con-
cept therefore distinguishes between concepts, but does not provide any information
with which to compare different concepts. The meaningful comparison of defined
concepts would require the user to consult and interpret the original citations, where
available. Any computer-assisted automatic comparison and resolution of concepts
will require that the elements of the concept definition are stored as part of the elec-
tronic representation of the concept in the taxonomic database sources.
We have modelled how taxon concepts can be represented with varying complex-
ity by a range of creators and users of concepts (including taxonomists, database pro-
viders and experimental biologists). Detailed analysis of the components that are used
by taxonomic databases or found in taxonomic publications to define their taxon con-
cepts includes (i) specimen and taxon circumscriptions, (ii) character descriptions or
circumscriptions and (iii) relationships with other taxon concepts.
There are a wide variety of relationships that might be expressed between taxon
concepts, which have been considered in detail by others (e.g. [9]; see online docu-
mentation, section 2.3 [10]). These relationships may implicitly or explicitly represent
set-based relationships defining the extent of overlap with or inclusion of other con-
cepts, or they may capture 'nomenclatural' relationships. However, the description of
types of relationships is complicated by the interdependence of nomenclature and
classification. A strict interpretation of terms such as synonymy, homonymy etc.
implies relationships between the definitions of names, and it is questionable whether
a relationship between names can be asserted in the absence of the context or usage of
those names. Any relationship between taxon names at least minimally considers
relationships between the type specimens determining the names. In the Taxonomic
Concept Schema (TCS) model presented in this paper a 'nomenclatural' relationship is
expressed as a relationship between two concepts, implying between the names of the
4. The Requirement for Data Exchange Standards
Given that there are an increasing number of important database providers of taxo-
nomic information, and a large potential user base amongst biologists and non-
scientists, it is necessary to facilitate data exchange between the providers and the
users, so that data can be integrated from multiple sources, without losing or misrep-
resenting the semantics of the data according to the providers' information models.
Taxonomic Concepts 7
This is necessary both from the perspective of database providers who wish to aggre-
gate information from multiple data sources into a single representation of taxonomy
without duplication of concepts, as well as for taxonomically naive users who wish to
integrate data from multiple database providers. If no exchange standard is globally
adopted, it will be necessary for any application or service that seeks to query multi-
ple taxonomic databases to implement bespoke query and exchange protocols for each
provider. It would then be impossible to develop standard mechanisms to match or
resolve concepts between different sources, and no guarantee of any protocol’s stabil-
ity or longevity.
The need for data exchange standards across the domains of biology, particularly
in the context of biodiversity studies, has been identified by GBIF [11] and SEEK
[12] amongst others. The common approach being taken to provide these standards is
the development of XML Schemas that define the data transfer structure as an XML
document, including the structure of the metadata associated with the actual data. This
approach mirrors that already taken to provide Data Description, or ' Mark-up' Lan-
guages such as EML (EcologicalML [13]), CML (ChemicalML [14]) and GML
(GeographyML [15]). The necessary information exchange standards for taxonomy
might include those for taxon concepts, Specimen Records, Collection Details, Publi-
cations, Observation Data, Geographical Location and People (i.e. Authors etc.).
Standards and protocols for some of these facets are already available or under devel-
opment, including: DIGIR [16] and ABCD [17] for detailing and exchanging infor-
mation regarding biological specimens; TaxMLit allowing the complete mark-up of
the content of taxonomic work [18], and a number of standards for publication infor-
mation (MODS [19]; XOBIS [20]; XMLMARC [21]; etc.).
In order to achieve global data exchange standards it is necessary that the standards
process should be open and inclusive, and it is desirable that proposed standards
should be consistent, and well documented. TDWG (International Taxonomic Data-
bases Working Group, has taken a lead in providing an international
forum for the development of standards for biological data exchange. Current stan-
dards being developed (as XML schema) include: the ABCD Task Group On Access
to Biological Data (providing standards for transfer and discovery of biological col-
lection data sets); the SDD Task Group on Structure of Descriptive Data (developing
a standard for storing and transferring detailed, character-based, descriptions of
specimens or taxa) and the Taxonomic Names Task Group on Taxonomic Concept
Standards (developing a standard for storing and transferring information about taxon
concepts and names, the work we present in section 5). Because of the overlap be-
tween these three proposed schemas (for example in their use of taxonomic names
and concepts and their referral to specimens and collections) it is proposed to modu-
larize their implementation to allow reuse of each other's data structures. Furthermore,
because each type of document will need to provide similar metadata elements de-
scribing the data transferred in a document (for example the source, ownership, ver-
sion etc.) it is proposed that documents conforming to each of these three schemata
are wrapped in a common format descriptor document.
8 Kennedy et al.
5. The TDWG Taxon Concept Schema (TCS)
Considered in abstraction, models for both a taxon name and a taxon concept consist
of a label plus definition plus author. Therefore, as demonstrated by Pyle [22], a
taxon concept can be represented as a taxon name (protonym) plus definition plus
author. Taxonomic definitions of names include the type specimen for that name and
application of the rules of nomenclature, whereas the taxonomic definition of a con-
cept might take several explicit (or implicit) forms. A model for names that includes
relationships between names might be considered as incorporating elements of a con-
cept model as the relationships between names actually refers to both the usage con-
text and typification of that name.
Because of the structural similarity between elements of names and concepts, and
to encourage a more rigorous representation of taxonomic identifiers (as defined con-
cepts rather than somewhat ambiguous names), an XML schema is proposed for the
representation and exchange of information regarding taxon concepts. Because the
schema includes a representation of names it will be possible to use this schema to
represent names as being concepts that lack definitions (i.e. as nominal concepts).
By making explicit the differences in composition between various types of taxon
concept definition, the schema will allow users to be aware of the variable accuracy or
quality of resolution, whether based solely upon names or upon more richly defined
taxon concepts. Various service providers, such as uBio ( and Spe-
cies2000 (, are providing rich mechanisms for resolving names
across distributed taxonomic databases. However, resolution services based on taxon
concepts as represented by the TCS should provide more meaningful comparison of
taxonomic identifiers.
The TCS schema was derived by composing an abstract model of taxonomic con-
cepts as discussed above, which seeks to account for all the facets that different data
providers and users might wish to include in their definition of a taxon concept. This
was facilitated by detailed consultation with representatives of several taxonomic
databases and researchers with an active interest in modelling and implementing
taxonomic information systems (see acknowledgments). The abstract model has been
represented as an XML schema that defines the structure of XML documents for the
exchange of information about taxonomic concepts. This exchange schema aims to
capture data as understood by the data owners without distortion, and facilitate the
query of different data resources according to the common schema model. The full
schema and documentation can be found at The TDWG review
process is open and inclusive, giving the opportunity to any interested party to com-
ment and suggest amendments to the proposal.
An overview detailing some of the elements of the transfer schema is shown in
Figure 2. Each Dataset will carry MetaData detailing the source of the transferred
document. To allow cross-referencing within the document, Vouchers (Specimen
records), Publications and TaxonConcepts are given local identifiers (IDs) that could
be substituted with global IDs (GUIDs) if these are available (see below). As well as
recording the details of TaxonConcepts (which can include Relationships with other
TaxonConcepts, see Figure 3), the transfer document may also be used to detail third
party RelationshipAssertions between existing TaxonConcepts.
Taxonomic Concepts 9
Because the model represented by the schema aims to be inclusive no 'components'
of a taxon concept definition are required by the schema, but are optional constituents
of a concept as represented by a given provider. However, in order to be useful, a
minimal representation would generally include both a Name and details of the con-
cept authorship (i.e. AccordingTo, or sec.). The representation of a full scientific
name (NameDetailed) that conforms to the requirements of all existing codes of No-
menclature has been developed outside the project (by the Linnean Core interest
group [23]) and integrated into the schema.
The various elements of the schema materialize information defining the concept
according to the original authors of the concept. This might include details of the
concept's Relationships to other pre-existing concepts, including its circumscription
by (inclusion of) other (lower rank) taxon concepts, or its membership of higher rank
concepts. Further Relationships may detail similarity or overlap with concepts created
by other authors. These latter relationships can be considered 'horizontal' in the sense
that they can relate concepts defined according to different taxonomic classifications,
whilst the hierarchical relationships between concepts within a classification are 'ver-
tical'. A full list of the types of relationships that may be expressed between two con-
cepts is provided online [10].
The manner in which a concept may be circumscribed by 'Character' data is as yet
undefined in the schema, and would require a formal model for representing character
descriptions. Various structured models for character data have been proposed (see
for example [24]), and the SDD working group of TDWG is developing a schema for
specimen or taxon descriptions that could be included or referenced within a TCS
CharacterCircumscription. The TCS schema does however provide the mechanism for
circumscribing concepts by reference to identifiers of specimen records (Vouchers in
the schema). Individual specimens that circumscribe a taxon can be labelled accord-
ing to whether they are accepted holotypes, isotypes, neotypes etc. for that taxon,
according to the codes of nomenclature.
The structure of the TCS schema allows internal reference and reuse of 'top-level'
elements (i.e. TaxonConcepts, RelationshipAssertions, Voucher and Publication re-
cords). Indeed it is hoped to standardize the representation of Publications and
Vouchers (including Specimens) across the TDWG schemas (see above). Where any
of these reusable elements are globally defined and resolvable via Globally Unique
Identifiers (GUIDs) it will be possible to represent them in transfer documents simply
by reference to this GUID (see below).
Some taxonomic work is concerned with re-using existing taxonomic concepts. For
example a taxonomist creating a revision of a large taxon may accept various included
taxa according to the work of various other published taxonomists, but wish to record
opinions about the relationships between these concepts. Where these relationships
are not created as part of a new concept definition they are treated as 'third party' in
the schema, and stored as RelationshipAssertions with an AccordingTo authority.
10 Kennedy et al.
Figure 2. (legend overleaf).
Figure 3. (legend overleaf).
Taxonomic Concepts 11
Figure 2. Overview of the Proposed TDWG TCS XML Schema. The major components of the
schema for transferring taxonomic concepts are shown diagrammatically (XML Elements are
shown in boxes, with XML attributes listed [below]; generated with software).
Each document would carry MetaData recording source and creation details of the DataSet,
together with the details of the taxonomic concept information represented. To allow cross-
referencing within the document Vouchers (Specimen records), Publications and TaxonCon-
cepts are given local identifiers (ids), which could be substituted with global IDs (GUIDs) if
these are available. As well as recording the details of TaxonConcepts (which can include
Relationships with other TaxonConcepts, see Figure 3), the transfer document may also be used
to detail third party RelationshipAssertions between existing TaxonConcepts
Figure 3. XML Schema Diagram for a Taxon Concept. A portion of the proposed TDWG TCS
schema for transferring Taxonomic Concepts is shown diagrammatically (generated with software). Any combination of the optional component elements would be used
to detail TaxonConcept definitions according to the data model of the data provider, but typi-
cally at least Name and AccordingTo would be required ('Nomenclatural Concepts' may only
provide Name). For these two components the detail recorded in different data sources will
vary, so a simple string representation will always be provided, whether or not detailed decom-
position is possible. The Relationship element allows the TaxonConcept to be defined in rela-
tion to existing TaxonConcepts. This can include hierarchical relationships to parent or child
taxa in the same classification, or synonymy and set based relationships with TaxonConcepts
defined in alternative classifications, based on the extent to which two concepts are congruent
or overlap. SpecimenCircumscriptions list the specimen details (Vouchers in Figure 2) that the
TaxonConcept is CircumscribedBy, but the nature of CharacterCircumscriptions is as yet
undefined. The PlaceholderType allows standards developed as other schemas to be incorpo-
rated; provision of the ProviderSpecificData element allows application specific extensions to
the representation of a Taxon Concept.
5.1 Globally Identified Taxonomic Concepts
At present each taxonomic database has its own internal (and sometimes external)
identifiers for taxon names or concepts (e.g. TSN numbers used by ITIS etc.). These
are not represented in the core TCS transfer schema, as there is no guarantee that any
given database ID would map uniquely to a TCS concept nor remain stable over time.
The TCS schema was devised to allow exchange of concepts together with their
definitions, and could be used to represent concepts stored in any global repository or
local cache. To provide a stable and resolvable identifier for these concepts it would
be highly desirable if GUIDs for taxon concepts were adopted. These could be as-
signed and maintained locally (by data owners) or globally according to agreed inter-
national policies, and would provide a stable reference to a taxon concept as
represented according to TCS (i.e. minimally Name plus AccordingTo). Once imple-
mented concept GUIDs would simplify the mark-up of any biological data, according
to available defined concepts, and could assist data retrieval based on concept iden-
tity. Provision of GUIDs would also help reduce the redundancy and overlap between
different data providers who currently reproduce alternative representations of the
'same' concept. Discussion within TDWG, SEEK, GBIF and the wider biological
12 Kennedy et al.
community is investigating the feasibility of providing GUIDs not only for taxon
concepts, but also for other stable concepts such as Publications and Specimens.
The availability of stable GUIDs with which any biologist can annotate their data
to unambiguously record the organisms described in their work will greatly facilitate
the interpretation, integration and accurate reuse of data across the whole of biology
and beyond. Furthermore, eventually it should be possible for a given researcher to
chose to recognize and use concepts as provided and defined by a preferred taxo-
nomic resource (e.g. ITIS) or even to capture uncertainty by using less well-defined
concepts, or collections of possible concepts were identifications are uncertain.
5.2 Resolving Taxon Names and Concepts
The proposed schema was initially conceived in the context of SEEK's requirement
for a taxonomic concept/name resolution service with which to resolve taxonomic
names as recorded in ecological data sets, following the realisation that resolution by
name alone is insufficient, and in the absence of identification through GUID refer-
enced taxon concepts [12]. Typical scenarios would involve the matching of names as
provided by users querying the system with the names as found in the metadata of
global data repositories, by resolution through the defined concepts provided by taxo-
nomic name providers and servers.
By capturing the individual components of concept definitions, according to any
data model, the schema will allow matching to be performed on any combination of
the individual components. The type and accuracy of the comparison performed may
vary according to the requirements of the user, i.e. concept matching should be 'fit for
the purpose'. For example, a match on the abbreviated scientific name Aus bus, will
be of lower quality (or precision) than matches specifically to the full, attributed name
Aus bus L. 1758 sec. Fry 1989. For some experimental purposes the loose match to
Aus bus will be sufficient, but for others greater precision is necessary. A related
notion is that comparison matches may be of higher or lower quality, and a 'reliability'
score might be provided for different concepts returned by the resolution service.
Where the concepts are fully defined in terms of the components of the TCS
model, matching on the actual definitions might be possible. When possible this will
allow very high quality matches, for example, where resolution is on the basis of
comparing full specimen circumscriptions. Alternatively, resolution only on the basis
of name-bearing type specimens would provide a less precise, lower quality resolu-
tion, which might still be 'fit for purpose'. Whilst it might be possible to assign 'qual-
ity scores' to different components of the concept definition model, in practice it
might be necessary to weight these scores to reflect the particular taxon model fa-
voured by a user, or the purposes for which they wish to represent a taxon concept.
This would allow users to differentially value the alternative components of a concept
definition, and recognize higher value in matches according to their favoured criteria.
Implementation of a name/concept resolution service would therefore need to include
its own quality model for matching, but allow users flexibility in weighting the com-
parison algorithms or interpreting the results.
Taxonomic Concepts 13
6. TCS in Comparison to Other Models for Taxonomy
As stressed earlier the TCS schema and underlying model aims to be inclusive of all
other models of taxonomy, and allow data from any data source to be accurately rep-
resented. A strength of the TCS schema is that it supports many recent innovative
models and implementations of taxonomic information as well as dealing with legacy
data. Several of these models have been developed specifically to allow the represen-
tation of multiple, alternative taxonomic views (HICLAS [25,26]; PROMETHEUS
[27]; BERLIN/IOPI [7-9]; TAXONOMER [22]; NOMENCURATOR [28]; uBIO, rather than the standardized single view represented by many global
taxonomic checklists (e.g. ITIS; Species2000
In the TCS model the taxon concept is the core object, which includes name,
attribution and definition elements. Whilst many database models also represent a
central notion of a taxon object, typically the name is used as an identifier for this
object. The Nomencurator database model [28] tracks nomenclatural history using a
dual name and publication based model to represent potential taxa by 'name usage'.
'Annotations' are used to record relationships between these name usages, providing
an implicit notion of taxon concepts. As such Nomencurator was designed to reflect
the manner in which taxonomists work in recording revisions, tracking the
development of taxonomic theories by changes in name usage. However, as there is
no representation of a taxon concept it is not possible to use the model to define taxa,
nor does it readily provide identifiable and exchangeable concepts that can be shared
amongst the various users of taxonomy. It should be possible to map each
Nomencurator 'name usage' (i.e. name plus publication) to a unique TCS taxon
concept, using Name and AccordingTo elements.
The Potential Taxon notion, i.e. the representation of subjective views of a taxon,
forms the basis of the Berlin IOPI model for botanical databases [8,9]. In this rich and
complex model botanical information can be linked to potential taxa (i.e. name plus
circumscription reference) rather than to name alone. Such information can include
nomenclatural and systematic relationships as well as linked specimen determinations
and character descriptions. Alternate taxonomic classifications are related to potential
taxa rather than names, closely corresponding to the TCS model. As with Nomencura-
tor it is envisaged that it will be desirable to present a 'Preferred View' of taxonomy to
users, by filtering according to preferred reference authorities. A number of databases
implement the Berlin model, including the MoReTax database [29, 9] which defines
fundamental, set-based relationships which can be expressed between potential taxa.
These relationships are included in the types of relation representable in the TCS [10].
The Taxonomer database model [22] also represents potential taxa, by the intersec-
tion of a Name and a Reference, called an Assertion. Assertions of the first usage of
that name are treated as a special case, as the name (or Protonym) provides the label
for the taxon concept. Protonyms form the name for later revised opinions on a taxon
concept as implicitly or explicitly circumscribed in a subsequent publication, repre-
sented in the model by an Assertion. Protonyms therefore provide common handle for
both the name and any taxon concepts or Potential Taxa that use this name. TCS
represents protonyms as the Name components of Original taxon concepts, and TCS
Revision taxon concepts may express various synonymy relationships to the Original
Concepts sharing a taxonomic name. As with TCS taxon concepts, Assertions may be
14 Kennedy et al.
linked by concept relationships (such as those defined by Geoffroy and Berendsohn
[31]), and can have attached specimen determinations and character descriptions (as
text based 'Excerpts'). In the Taxonomer model, however, common names are repre-
sented not as individual concepts (or assertions) but as an attribute of an Assertion
(which must be or include a Protonym).
The uBio model of taxonomic information underlying their Taxonomic Name Ser-
vice ( seeks to separate 'objective' nomenclatural information into a
consensual reference model (NameBank), whilst representing classification informa-
tion in a separate but linked model of subjective opinions (ClassificationBank). uBio
assert that this separation whilst providing a rich representation of taxon concepts
through classification relationships will allow nomenclaturists to work with bare
names and represent relationships between them, without referring to concepts. The
justification being that whereas many aspects of nomenclature are not disputed, taxo-
nomic classifications are inherently unstable, disputed hypotheses. On the other hand
the TCS does not represent names independently, and relationships must be expressed
through a concept that bears a particular name. This reflects our opinion that it is
difficult to find any instances where names are used for identification and communi-
cation of taxa without at least an implied notion of the concept to which they apply.
Datasets containing only name information, are represented by 'nominal concepts'
which capture all concepts that share the same name.
As with the Berlin and uBio models, the Prometheus taxonomic database model,
which is based on specimen circumscription, clearly distinguishes nomenclatural from
classification information [27] and was built to support the working practices of tax-
onomists performing botanical revisions. In this model naming is an automatic feature
of typification in the specimen circumscription. Alternative classification views,
based on specimen circumscription, can readily be compared on the basis of set-based
relationships (such as those defined in the MoReTax/Berlin model [9]).
The requirements for simple data discovery and exchange between database pro-
viders has favoured the development and implementation of simple generic data query
and retrieval protocols, which use simple models for the underlying data structure (for
example, the successful DIGIR [16] protocol with the underlying Darwin Core data
representation [30]). Whilst such flat, unstructured representations of taxonomic in-
formation are certainly simple, they may not be adequate for representing semanti-
cally complex information. Species2000 ( has developed a Standard
Dataset model for exchanging name-based species information according to a single
aggregated view of taxonomy, derived from various database sources. Although there
is no explicit statement on what 'defines' a named species concept in this model, each
species can be recognized as a 'concept' according to the originating source database,
or a recorded taxonomic scrutinizer, and could therefore be represented in TCS as a
(not well defined) Taxon Concept. The synonymy relationships captured in Spe-
cies2000 are purely nomenclatural, as the synonyms do not belong to any alternative
conceptual hierarchy. Representing such synonymies in TCS would require that each
name be represented by a nominal concept.
Whilst the details captured in each of these theoretical and implementation models
of taxonomy vary greatly, they tend to converge on a central representation of a po-
tential taxon or taxon concept. TCS can therefore accommodate the salient features of
Taxonomic Concepts 15
these models, as well as representing database models that use a more traditional
representation of taxonomic names as the identifiers.
7. Conclusion
The computerized systems and databases used by biologists and the bioinformatics
community are largely blind to the problems inherent in the (ambiguous) identifica-
tion of organisms by scientific name alone. As we have discussed, accurate integra-
tion of biological data sets is problematic due to many reasons including errors in
documenting taxonomic names; the lack of standards for capturing the definition of
taxonomic concepts; the inherent ambiguity the taxon definitions associated with
taxonomic names; the lack of understanding of this ambiguity by users of biological
names; and finally the lack of a global repository for taxonomic concepts with GUIDs
which can be used to refer to and aid matching concepts for data annotation and inte-
gration. Solutions to these problems require ensuring that references to biological taxa
in data sets cite the scientific name in the context of a particular classification, which
we have modelled as the defining attributes of a Taxon Concept. Data integration can
then be achieved either on Concept identity, or on individual components of a defined
concept. Where it is not possible to ascribe defined concepts to datasets (such as with
legacy data) poorly defined nominal concepts can be used (i.e. concepts with a name
but no definition), thus making explicit the deficient quality of the taxon identifica-
tion. The schema has been used to map data from a variety of sources and is currently
being used as the basis for a taxonomic name/concept resolution service in the SEEK
This work was carried out under the auspices of TDWG and jointly funded by GBIF
[12] and SEEK [11], supported by the US National Science Foundation. We are most
grateful for detailed and helpful discussions on aspects of individual taxonomic mod-
els with representatives of the Berlin Model, GBIF, IPNI, ITIS, Nomencurator, Spe-
cies2000, Taxonomer, Vegbank, and colleagues within SEEK and TDWG.
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... For most species-level distribution research, standards for aggregating data consist of resolving deviant spellings, grammatical differences (e.g., hyphens and spaces), or synonymous names, but do not necessarily account for different taxon concepts circumscribed by a species name (Kennedy, Kukla & Paterson, 2005;Giangrande, 2003;Pyle, 2004, Patterson et al., 2010Mora et al., 2011;Patterson et al., 2016;Remsen, 2016). Systematic and phylogenetic research continuously reclassifies the biological entities circumscribed by a name; thus unless different data sources explicitly reference the same (or compatible) authoritative treatments, it cannot be assumed that they monitor the same taxonomic concept even when they use the exact same name (Ytow, Morse & Roberts, 2001;Pyle, 2004;Kennedy, Kukla & Paterson, 2005;Franz, Peet & Weakley, 2008;Franz & Peet, 2009;Boyle et al., 2013;Cui et al., 2016;Remsen, 2016). ...
... For most species-level distribution research, standards for aggregating data consist of resolving deviant spellings, grammatical differences (e.g., hyphens and spaces), or synonymous names, but do not necessarily account for different taxon concepts circumscribed by a species name (Kennedy, Kukla & Paterson, 2005;Giangrande, 2003;Pyle, 2004, Patterson et al., 2010Mora et al., 2011;Patterson et al., 2016;Remsen, 2016). Systematic and phylogenetic research continuously reclassifies the biological entities circumscribed by a name; thus unless different data sources explicitly reference the same (or compatible) authoritative treatments, it cannot be assumed that they monitor the same taxonomic concept even when they use the exact same name (Ytow, Morse & Roberts, 2001;Pyle, 2004;Kennedy, Kukla & Paterson, 2005;Franz, Peet & Weakley, 2008;Franz & Peet, 2009;Boyle et al., 2013;Cui et al., 2016;Remsen, 2016). This is problematic especially for unstable taxa, for which different taxonomic studies suggest reorganizations and disputed relationships (Ytow, Morse & Roberts, 2001). ...
Full-text available
Integrative modeling methods can now enable macrosystem-level understandings of biodiversity patterns, such as range changes resulting from shifts in climate or land use, by aggregating species-level data across multiple monitoring sources. This requires ensuring that taxon interpretations match up across different sources. While encouraging checklist standardization is certainly an option, coercing programs to change species lists they have used consistently for decades is rarely successful. Here we demonstrate a novel approach for tracking equivalent names and concepts, applied to a network of 10 regional programs that use the same protocols (so-called “Pollard walks”) to monitor butterflies across America north of Mexico. Our system involves, for each monitoring program, associating the taxonomic authority (in this case one of three North American butterfly fauna treatments: Pelham, 2014; North American Butterfly Association, Inc., 2016; Opler & Warren, 2003) that shares the most similar overall taxonomic interpretation to the program’s working species list. This allows us to define each term on each program’s list in the context of the appropriate authority’s species concept and curate the term alongside its authoritative concept. We then aligned the names representing equivalent taxonomic concepts among the three authorities. These stepping stones allow us to bridge a species concept from one program’s species list to the name of the equivalent in any other program, through the intermediary scaffolding of aligned authoritative taxon concepts. Using a software tool we developed to access our curation system, a user can link equivalent species concepts between data collecting agencies with no specialized knowledge of taxonomic complexities.
... existing classification arise with the addition of new species and an improved understanding of the relationships between the sister species (Kennedy et al., 2005). Information on biodiversity is vital for ecological and environmental assessments and subsequent evolutionary studies (Meredith et al., 2019). ...
Phylogenetic relationships are often challenging to resolve in recent/younger lineages when only a few loci are used. Ultra Conserved Elements (UCE) are highly conserved regions across taxa that help resolve shallow and deep divergences. We utilised UCEs harvested from whole genomes to assess the phylogenetic position and taxonomic affiliation of an endangered endemic owlet in the family Strigidae – Forest Owlet Athene blewitti. The taxonomic placement of this species has been revised multiple times. A multigene study attempted to address the question but showed a discrepancy across datasets in its placement of the species within genus Athene. We assembled a dataset of 5018 nuclear UCE loci with increased taxon sampling. Forest Owlet was found to be an early split from the Athene clade but sister to other Athene; and consistent across three approaches ‐ maximum likelihood, bayesian, and the multispecies coalescence. Divergence dating using fossil calibrations suggest that the Athene lineage split from its ancestor about 7.6 my, and Forest Owlet diverged about 5.2 my. This estimate is consistent with previous multigene approaches and confirms the role of climate‐aridification across the Indian peninsula in species diversification. Despite osteological differences from other Athene, we suggest the placement of the Forest Owlet as a member of the Athene to emphasise its evolutionary relationship.
... The adoption of PIDs in monography implies that we may need to carefully reengineer traditional approaches to linking biodiversity data via taxon concepts represented as scientific names (Kennedy et al. 2005). Indeed, it is in monographs where taxon concepts are put into practice and taxon names are proposed (McDade 1995). ...
... The hierarchy of systematic classification of organisms into taxa is based on the various biological pieces of evidence, i.e. morphology, genetics, palaeontology, etc. Taxonomic revisions to the existing classification arise with the addition of new species and understanding the relationships between the sister species (Kennedy et al., 2005). Information on biodiversity is vital for ecological and environmental assessments and subsequent evolutionary studies (Meredith et al., 2019). ...
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Phylogenetic relationships are often challenging to resolve in recent/younger lineage when only a few loci are used. Ultra Conserved Elements (UCE) are highly conserved regions across taxa that help resolve shallow and deep divergences. We utilized UCEs harvested from whole genomes to assess the phylogenetic position and taxonomic affiliation of an endangered endemic owlet in the family Strigidae – the Forest Owlet Athene blewitti . The taxonomic placement of this species has been revised multiple times. A multigene study attempted to address the question but showed a discrepancy across datasets in its placement of the species within genus Athene . We assembled a dataset of 5018 nuclear UCE loci with increased taxon sampling. Forest Owlet was found to be an early split from the Athene clade but sister to other Athene; and consistent across three approaches - maximum likelihood, bayesian, and the multispecies coalescence. Divergence dating using fossil calibrations suggest that the Athene lineage split from its ancestor about 7.6Mya, and the Forest Owlet diverged about 5.2Mya, consistent with previous multigene approaches. Despite osteological differences from other Athene , we suggest the placement of the Forest Owlet as a member of the Athene to emphasize its evolutionary relationship. Graphical Abstract HIGHLIGHTS Phylogenomics using genome-wide nuclear markers yielded a well-supported topology for Athene and Glaucidium lineages. Three different methods of phylogenetic tree construction showed that Forest Owlet is an early split from all other Athene species. Divergence dating in the bayesian framework puts the Forest Owlet age between 5.0my to 5.5my.
... Adapting scientific processes and hypotheses to the most economic or available methodology and technical feasibility is problematic. Massive innovation from new technologies, such as barcoding, deep learning, or information science, however, should not bring us to a decline in our understanding of species, and in consequence their naming (e.g., Kennedy et al. 2005;Garnett et al. 2020;Cellinese et al. 2021). This would be extremely detrimental to taxonomy as a science. ...
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... For accessing the information on a taxon, it is necessary to know its currently accepted name. However, since any binomialvia the genus name-expresses a hypothesis on the phylogenetic affinities of a given taxon, scientific names do change over time, as our knowledge progresses [3][4][5]. While globally unique identifiers (GUIDs [6]), as the LSIDs [7] can be used to univocally address a taxon name, are useful in web services which allow machine-machine communication, they can hardly be used for querying a database manually. ...
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... Despite the wealth of possible connections between biodiversity data objects, the most commonly shared identifier that spans sequences, specimens, and publications remains the taxonomic name (Sarkar 2007;Patterson et al. 2010). We rely on names to integrate data, despite the potential ambiguity in what a given taxonomic name "means" (Kennedy et al. 2005;Franz and Cardona-Duque 2013). Unfortunately, it is often difficult to obtain information on a taxonomic name, either to track its origins and subsequent use, or to verify that it has been correctly used. ...
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... Indeed, several studies have pointed to the existence of important problems in GBIF data, such as errors and incorrect species nomenclature usage (Evenhuis, 2007;Smith, Johnston, & L€ ucking, 2016;Vecchione et al., 2000). Those studies paid superficial attention to the use of updated taxonomic classification, and the consequences of such neglect emerge as a noteworthy issue for different fields of biology, from genomics to ecology (Kennedy, Kukla, & Paterson, 2005). ...
The increase of free and open online biodiversity databases is of paramount importance for current research in ecology and evolution. However, little attention is paid to using updated taxonomy in these “biodiversity big data” repositories and the quality of their taxonomic information is often questioned. Here we assess how reliable is the current use of nomenclatural classification in the distributional information available from two biodiversity information networks: GBIF and the Brazilian SpeciesLink. We use as a study case the records of Auchenipteridae, a Neotropical fish family that has been subject to recent taxonomical reviews. A data filtering procedure was applied to identify and quantify the inaccuracies in the taxonomical status of the records in three steps: assessment of identification accuracy at the family, genus or species level; current validity of species name; and assignation of inaccurate species records to different categories of classification quality. Synonyms, nonexistent combinations, and outdated combinations were reassigned to currently valid species. A total of 9148 records of Auchenipteridae fishes were analyzed, of which 4165 were from GBIF and 4983 from SpeciesLink, deriving from 46 and 31 sources, respectively. After correcting all possible records following the taxonomic data filtering steps, 6988 records (76.4% of the original) were adequate for describing species distributions, while 2160 remained inaccurate. The most inaccurate records at the species level were due to the use of outdated nomenclatures, resulting in non-valid combinations of species and genus, and synonymy. Our results evidence a large taxonomic inconsistency among records, and, most importantly, that taxonomic information obtained from repositories should be used with caution. Many inaccuracy issues may be embedded in the biodiversity databases’ records, which could lead researchers to provide an incomplete or even mistaken perspective of the variations in the natural world.
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The schema outlined below – 'taXMLit' -is designed to accommodate taxonomic literature. It covers all of the components of taxonomic publications and the taxon treatments contained within them other than the actual characters, which are dealt with by other projects. This explanation is written in conjunction with version 1.3 of taXMLit, which should be consulted for additional information. Many of the elements in the schema are annotated, and these annotations are not always reproduced below, although they are present in some of the figures. Both taxonomists and those who need taxonomic information require greater access to material held in natural history museums and similar large biological repositories and their libraries. These repositories hold a wealth of inadequately accessible resources that describe and explain the diversity and depth of life on earth. Mining these data for research, conservation, drug discovery, protected area management, disease control, education, enjoyment of the natural world, etc., is difficult, time consuming, and often leads to redundant efforts. What should be a seamless, open "book" of knowledge consists, instead, of disparate, unintegrated sets of data -some in electronic form but most still on paper, and both published and unpublished. Information held in museums centers on the following types of biological datasets: specimen collections, taxonomic databases, published taxonomic literature, geographical information systems, and unpublished archival materials. Making these information sources available is part of a larger, worldwide effort to enable easy access to the complete range of data required to understand individual species and their environmental and evolutionary relationships. This will require the establishment of cross-linkages between, and simultaneous access to, datasets from such information sources throughout the world. TaXMLit is one step needed to implement that vision.
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Taxonomic research, as a field of biological sciences, is fundamentally an exercise in information management. Modern computer technology offers the potential for both streamlining the taxo- nomic process, and increasing its accuracy. Effective use of computer technology to successfully manage taxonomic information is predicated upon the implementation of data models that accommodate the diverse forms of information important to taxonomic researchers. Although sophisticated data models have been developed to manage some information relevant to taxo- nomic research (e.g., natural history specimen information; descriptive data relating to morpho- logical and molecular characters of specimens), similarly robust models for managing information about taxonomic names and how they are applied to taxonomic concepts, though they exist, have not attained widespread use and adoption. Herein I describe portions of a relational data model developed to manage information relevant to taxonomic names and concepts. The core entities of the described portions of this model are Agents, References, and Assertions (along with their associated Protonyms). Agents (people and organizations) in this context refer primarily to taxonomic authorities. References are broadly defined as date-stamped information (usually, but not exclusively, in the form of a publication), as documented by the Agents who serve as the Reference authors. Assertions consist of basic elemental information about the treatment of taxonomic names by taxonomic authorities as documented in a particular Reference, and correspond to what many authors refer to as taxon "concepts". Protonyms are a special subset (subtype) of Assertions, which constitute original descriptions of taxonomic names (serving to unite multiple assertions pertaining to the same taxonomic name), and include elements of botanical Protologues and Basionyms. I also illustrate how these core entities can serve as a foundation for taxonomic names and concepts as integrated with other datasets, such as biological specimens and observations (and, by extension, geographic distributions and character matrices). The broadest data content source used to populate and test the data model is derived from a systematic revision of the reef-fish family Pomacanthidae (marine angelfishes). Additional datasets used to test the imple- mentation of the data model include specimen data from the Department of Natural Sciences, Bishop Museum; nomenclatural data from The Catalog of Fishes; and nomenclatural and bio- geographic data from two published taxonomic catalogs (insects and terrestrial mollusks in Hawai'i).
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The concept of a "potential taxon" as a name- and literature-related data area in botanical databases is introduced. A potential taxon is a name with taxon circumscription information attached to it by means of one or more literature references. As a compromise solution between linking information in database systems entirely to specimen data or only to accepted names, using potential taxa can effectively preserve information links without hindering rapid database input and information processing. It is suggested that a potential taxon be cited by its name, followed by the abbreviation "sec." (for secundum = according to) and at least one of the literature references used to define it.
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Summary Berendsohn, W. G.: A taxonomic information model for botanical databases: the IOPI Model. ϑ Taxon 46: 283-309. 1997. ϑ ISSN 0040-0262. A comprehensive information model for the recording of taxonomic data from literature and other sources is presented, which was devised for the Global Plant Checklist database project of the International Organisation of Plant Information (IOPI). The model is based on an approach using hierarchical decomposition of data areas into atomic data elements and ϑ in parallel ϑ abstraction into an entity relationship model. It encompasses taxa of all ranks, nothotaxa and hybrid formulae, "unnamed taxa", cultivars, full synonymy, misapplied names, basionyms, nomenclatural data, and differing taxonomic concepts (potential taxa) as well as alternative taxonomies to any extent desired. The model was developed together with related models using a CASE (Computer Aided Software Engineering) tool. It can help designers of biological information systems to avoid the widely made error of over-simplification of taxonomic data and the resulting loss in data accuracy and quality.
Evolutionary studies are generating increasing numbers of phylogenies which, in turn, sometimes result in changes to hierarchical organization and therefore changes in taxonomic nomenclature. A three-layered data model for a nomenclature database has been developed in order to elucidate the information structure in nomenclature and as a means to organize and manage a large, dynamic knowledge-base. In contrast to most other taxonomic databases, the model is publication-oriented rather than taxon-oriented and dynamic rather than static, in order to mimic the processes that taxonomists use naturally. The three-layered structure requires data integrity localized to each publication, instead of global data integrity, which relaxes constraints common to taxonomic databases and permits multiple taxonomic opinions: taxon names are made available as metadata within the model. Its prototype implementation, written in C++, has an autonomous self-identification mechanism to avoid spurious data-inflation in a publication-oriented data model. Self-identification is also desirable for distributed implementations of the nomenclature database. Publication-oriented design also will make maintenance easier than for taxon-oriented databases, much of the maintenance workload being amenable to automation. The three-layered data model was designed for use by taxonomists, but is also able to provide concise, reduced expression for non-experts required in biodiversity research, for example.
A model for representing taxonomic data in a flexible and dynamic system capable of handling and comparing multiple simultaneous classifications is presented. The Prometheus Taxonomic Model takes as its basis the idea that a taxon can be circumscribed by the specimens or taxa of lower rank which are said to belong to it. In this model alternative taxon concepts are therefore represented in terms of differing circumscriptions. This provides a more objective way of expressing taxonomic concepts than purely descriptive circumscriptions, and is more explicit than merely providing pointers to where circumscriptions have been published. Using specimens as the fundamental elements of taxon circumscription also allows for the automatic naming of taxa based upon the distribution and priority of types within each circumscription, and by application of the International Code of Botanical Nomenclature. This approach effectively separates the process of naming taxa (nomenclature) from that of classification, and therefore enables the system to store multiple classifications. The derivation of the model, how it compares with other models, and the implications for the construction of global data sets and taxonomic working practice are discussed.
INTRODUCTION Many words have been written on the subject of the Machine-Readable Cataloging (MARC) Program: the events that led to the pilot project, the development of the format, the operational Distribution Service, the influence of MARC on standardization, and the impetus it gave to library automation projects and to the creation of networks here and abroad. This article serves to gather together all aspects of the national and international MARC system. Much of what follows has been fairly well documented in many published reports, journal articles, etc., and therefore this article relies heavily on that material. A Bibliography based on the article's main headings has been included for those readers who wish to explore any aspect of MARC in greater depth.
Smart data structures and dumb code work a lot better than the other way around. --Lesson 9 from Eric Steven Raymond's The Cathedral and the Bazaar. La perfection est atteinte non quand il ne reste rien à ajouter, mais quand il ne reste rien à enlever. [You know you've achieved perfection in design, not when you have nothing more to add, but when you have nothing more to take away.] --Antoine Saint-Exupéry.
An information-theoretic view has been applied to biological classification to capture taxonomic concepts as taxonomic data entities and to develop a system for managing these concepts and the lineage relationships among them. In order to develop the data model, it has been necessary to apply explicit definitions to several taxonomic terms that generally have not been precisely defined and to coin and define several new terms and concepts. Methods are outlined for comparing interacting classifications and querying hierarchical taxonomic databases. A program/database system called HICLAS, which provides an X-Window interface to query classification data, is available on the Internet.