Structuring descriptive data of organisms [Elektronische Ressource] : requirement analysis and information models = Strukturierung organismischer Beschreibungsdaten / vorgelegt von Gregor Hagedorn

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Structuring Descriptive Data of Organisms — Requirement Analysis and Information Models (Strukturierung organismischer Beschreibungsdaten – Anforderungsanalyse und Informationsmodelle) Dissertation zur Erlangung des Doktorgrades der Fakultät Biologie, Chemie und Geowissenschaften der Universität Bayreuth vorgelegt von Gregor Hagedorn Institute for Plant Virology, Microbiology and Biosafety, Federal Biological Research Center for Agriculture and Forestry, Königin-Luise Str. 19, 14195 Berlin, Germany Bayreuth, Juni 2007 Vollständiger Abdruck der von der Fakultät für Biologie, Chemie und Geowissen-schaften der Universität Bayreuth genehmigten Dissertation zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften (Dr. rer. nat.). Schlagwörter: Bioinformatik; Biodiversität; Identifikation; Taxonomie; SDD; TDWG; DELTA; DeltaAccess; DiversityDescriptions. Keywords: bioinformatics; biodiversity; identification; taxonomy; ACM Computing Classification System: J.3 LIFE AND MEDICAL SCIENCES Die vorliegende Arbeit wurde unter der Leitung von Herrn Prof. Dr. G. Rambold (Lehrstuhl Pflanzensystematik, Abteilung Mykologie) angefertigt. Einreichung der Dissertation (Date of submission): 11. Juni 2007 Tag des wissenschaftlichen Kolloquiums (Date of examination): 28. November 2007 Prüfungsausschuss (Thesis Committee): Prof. Dr.
Publié le : lundi 1 janvier 2007
Lecture(s) : 22
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Source : D-NB.INFO/1006696822/34
Nombre de pages : 417
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Structuring Descriptive
Data of Organisms —
Requirement Analysis
and Information Models
(Strukturierung organismischer Beschreibungsdaten
– Anforderungsanalyse und Informationsmodelle)






Dissertation zur Erlangung des Doktorgrades
der Fakultät Biologie, Chemie und Geowissenschaften
der Universität Bayreuth


vorgelegt von
Gregor Hagedorn
Institute for Plant Virology, Microbiology and Biosafety,
Federal Biological Research Center for Agriculture and Forestry,
Königin-Luise Str. 19, 14195 Berlin, Germany
Bayreuth, Juni 2007 Vollständiger Abdruck der von der Fakultät für Biologie, Chemie und Geowissen-
schaften der Universität Bayreuth genehmigten Dissertation zur Erlangung des
akademischen Grades eines Doktors der Naturwissenschaften (Dr. rer. nat.).



Schlagwörter: Bioinformatik; Biodiversität; Identifikation; Taxonomie;
SDD; TDWG; DELTA; DeltaAccess; DiversityDescriptions.
Keywords: bioinformatics; biodiversity; identification; taxonomy;
ACM Computing Classification System:
J.3 LIFE AND MEDICAL SCIENCES
















Die vorliegende Arbeit wurde unter der Leitung von Herrn Prof. Dr. G. Rambold
(Lehrstuhl Pflanzensystematik, Abteilung Mykologie) angefertigt.

Einreichung der Dissertation (Date of submission): 11. Juni 2007
Tag des wissenschaftlichen Kolloquiums (Date of examination): 28. November 2007

Prüfungsausschuss (Thesis Committee):
Prof. Dr. Gerhard Rambold (Erstgutachter, advisor and first promoter)
Prof. Dr. Prof. Stefan Jablonski (Zweitgutachter, second promoter)
Prof. Dr. Ingolf Steffan-Dewenter (Vorsitzender, chairperson)
Prof. Dr. Sigrid Liede-Schumann
Prof. Dr. John Tenhunen









This is an Open Access publication distributed under the terms of the
Creative Commons Attribution-Noncommercial-Share Alike 3.0 License
(http://creativecommons.org/licenses/by-nc-sa/3.0/). G. Hagedorn Descriptive data in biology 3
Summary
Data that describe organisms in a structured form are indispensable not only for taxonomic and
identification purposes, but also many phylogenetic, genetic, or ecological analyses. By analyz-
ing existing information models and performing selected fundamental requirement analyses, the
present work contributes to a broadening of the understanding of these forms of data. It falls into
an interdisciplinary area between biology and information science.
The term “descriptive data” is understood here in a broad sense: As descriptions of individu-
als, populations, or taxa, intended for various purposes (e. g., genetic, phylogenetic, diagnostic,
taxonomic, or ecological), and covering a wide array of observation methods and data types (e. g.,
morphological, anatomical, genetic, physiological, molecular, or behavioral data). The position of
descriptive data in the context of biodiversity framework concepts (covering, e. g., nomenclatural
data, specimen collection data, or resource management) is discussed.
A number of fundamental problems arise when modeling biological descriptive data. The
ways in which existing data exchange formats, information models, and software applications ad-
dress them are studied and future possible solutions are outlined.
One such solution, the information model for the software “DiversityDescriptions (Delta-
Access)” is one of the results of this thesis and fully documented (Ch. 7). This entity relationship
model fully supports the concepts of the traditional DELTA data exchange format (Description
Language for Taxonomy; TDWG standard since 1986). If further improves on DELTA by intro-
ducing “modifiers” as a new terminology class, by introducing a more flexible system of hand-
ling statistical measures, by improving the handling of multilingual data sets, by supporting sub-
set and filter features for concurrent collaborative editing (instead of supporting these for report-
generation purposes alone), by supporting improved character attributes to create natural lan-
guage descriptions from structured descriptions, and by adding metadata for a data set to improve
the ability of data exchange without external documentation.
In preparation of a future improved information model for descriptive data, the results of three
requirement analyses are presented: a data-centric analysis of general concepts, a process-centric
analysis of identification tools, and a high-level use case analysis.
The first analysis (Ch. 4) is a structured inventory of fundamental approaches and problems
involved in collecting and summarizing scientific descriptions of organisms. It is informed in part
by current practices in information science, comparative data analysis, statistical, descriptive or
phylogenetic software applications, and data exchange formats in biodiversity informatics. At the
end three topics are discussed in particular detail (“Federation and modularization of termino-
logy”, “Modifiers”, and “Secondary classification resulting in description scopes”).
Except for phylogenetic analyses, identification is the most common usage of descriptive data.
The second analysis (Ch. 5) therefore studies the processes, data structures, presentational and
user interface requirements for printable and computer-aided identification tools (“keys”).
Finally, a general use case analysis is performed with the goal of creating a framework of
high-level use cases into which present as well as future requirements may be integrated (Ch. 6).
All three requirement analyses are explorative and do not fulfill formal criteria of software en-
gineering. They identify many requirements not addressed by the relational DiversityDescriptions
model. Some of these could only be explored and await future solutions. For others solutions are
proposed (some of which could already be incorporated into the design of SDD, an xml-based
TDWG standard since 2005): The traditional data types are changed into an extensible character
type model. The importance of data aggregation concepts was recognized to be fundamental.
Complementary to data aggregation, the present and potentially future use of data inheritance
along the lines of the taxonomic hierarchy is briefly studied. The concept of calculated characters
could be addressed only insofar as the mapping between values can potentially be generalized.
Character decomposition models are studied, but ultimately the traditional character concept,
supplemented with a forest of ontologies for compositional and generalization concept hierar-
4 Descriptive data in biology G. Hagedorn
chies, is preferred as a more general concept. Both the traditional character subset and character
applicability models can be integrated into concept hierarchies.
Zusammenfassung (German summary)
Strukturierte Beschreibungsdaten von Organismen sind nicht nur für Taxonomie und Bestim-
mung, sondern auch viele phylogenetische, genetische oder ökologische Analysen unentbehrlich.
Durch Analysen existierender Informationsmodelle und durch fundamentale Anforderungsana-
lysen leistet die vorliegende Arbeit einen Beitrag zum Verständnis dieser Daten. Sie ist interdis-
ziplinär zwischen Biologie und Informatik angelegt.
Der Begriff „Beschreibungsdaten“ wird in einem weiten Sinn definiert, nämlich als Beschrei-
bungen von Individuen, Populationen oder Taxa, gesammelt z. B. für genetische, phylogeneti-
sche, diagnostische, taxonomische oder ökologische Zwecke, und unter Einschluss diverser Da-
tentypen (z. B., morphologische, anatomische, genetische, physiologische, molekulare oder Ver-
haltensdaten). Die Abgrenzung von Beschreibungsdaten zu anderen Biodiversitätsdaten (z. B.
Nomenklatur, Sammlungsdaten, oder Medien- und Literaturressourcen), und das Konzept über-
greifender Rahmenkonzepte für Biodiversitätsdaten wird erläutert.
In der Arbeit werden grundlegende bei der Modellierung von Beschreibungsdaten auftretende
Probleme besprochen, vorhandene Lösungsansätze in Datenaustauschformaten, Modellen und
Programmen untersucht, und zukünftige Lösungen aufgezeigt.
Eine solche Lösung, das relationale Informationsmodell für die Software „DiversityDescript-
ions (DeltaAccess)“, ist ein Ergebnis dieser Arbeit und wird im Detail dokumentiert (Kap. 7).
Dieses Modell deckt die Konzepte des traditionellen DELTA-Datenaustauschformats (Descrip-
tion Language for Taxonomy; TDWG Standard seit 1986) vollständig ab. Darüber hinaus erwei-
tert es DELTA erheblich. Es führt eine neue Form von Beschreibungsvokabular („Modifizierer“),
ein flexibleres System für statistische Maße und erweiterte Merkmalsattribute zur Erzeugung
natürlichsprachlicher Beschreibungen aus strukturierten Daten ein. Weiterhin verbessert es die
Behandlung mehrsprachiger Datensammlungen, nutzt Filter auch für gemeinschaftliches Redi-
gieren (anstatt diese nur zur Berichterzeugung zu nutzen), und unterstützt Metadaten für Projekte.
Ein weiteres wesentliches Ergebnis dieser Arbeit sind die Resultate von drei Anforderungs-
studien, die eine solide Basis für künftige Weiterentwicklungen darstellen: Eine datenorientierte
Studie allgemeiner Konzepte, eine prozessorientierte Analyse von Bestimmungsmethoden, sowie
eine allgemeine „Use-Case“-Analyse.
Die erste Studie (Kap. 4) ist eine strukturierte Aufzählung grundlegender Probleme, welche
bei der Beschreibung und Charakterisierung von Organismen auftreten. Die Informationen dazu
basieren auf Datenverwaltungs- und statistischen Analysemethoden, wie sie in allgemein-statisti-
scher, phylogenetischer und taxonomischer Software (bzw. Datenaustauschformaten) vorkom-
men. Der allgemeine Teil wird ergänzt durch drei ausgewählte vertiefende Analysen: „Verteilte
und modularisierte Terminologie“, „Modifizierer“ und „Sekundäre Klassifikationen in Beschrei-
bungen“.
Die zweite Analyse (Kap. 5) untersucht Bestimmungsmethoden, welche die – neben phylo-
genetischen Analysen – wohl wichtigste Anwendung von Beschreibungsdaten sind. Die Prozesse,
Daten, Darstellungsformen und Benutzeroberflächen von gedruckten oder Computer-gestützten
Bestimmungshilfsmitteln werden detailliert in Hinsicht auf Anforderungen an das Informations-
modell untersucht.
Schließlich wird in der „Use-Case“-Analyse (Kap. 6) der allgemeine Gebrauch von Beschrei-
bungsdaten untersucht. Dabei wird eine Gliederung erstellt in welche gegenwärtige und künftige
Anforderungen integriert werden können.
Alle drei Anforderungsanalysen sind explorativ und erfüllen keine formalen Kriterien der
Softwareentwicklung. In ihnen werden viele Punkte erfasst die nicht durch DiversityDescriptions G. Hagedorn Descriptive data in biology 5
abgedeckt werden. Etliche Anforderungen und Probleme können nur herausgearbeitet werden
und müssen auf zukünftige Lösungen warten. Zum Teil können aber bereits mögliche Lösungen
präsentiert oder skizziert werden. Einige sind bereits in das Design von SDD, dem neuen xml-
basierten TDWG Standard für Beschreibungsdaten seit 2005, eingeflossen: Die traditionellen
Datentypen werden als erweiterbares Typsystem neu konzipiert; die Bedeutung von Datensum-
mierung und Synthese wird neu bewertet; die umgekehrte Bedeutung von Datenvererbung ent-
lang der taxonomischen Hierarchie wird kurz studiert. Berechnete Merkmale werden insoweit
abgedeckt, als sie eine einfache Abbildung zwischen zwei Merkmalen sind („mapping“). Merk-
mals-Dekompositionsmodelle werden untersucht, das traditionelle Merkmalskonzept jedoch als
das allgemeinere Konzept bevorzugt. Dieses wird durch mehrfache strukturelle und generalisie-
rende Ontologien (Konzepthierarchien) ergänzt. Sowohl traditionelle Untermengen („Subsets“)
als auch Merkmalsabhängigkeiten können hier integriert werden.
6 Descriptive data in biology G. Hagedorn
Acknowledgements
Firstly, I am very grateful to my advisor Prof. Dr. G. Rambold (Bayreuth) for his interest in the
topic, discussions and advice, as well as great encouragement, support, and patience during the
long period of working on this thesis. He as well as others, especially Prof. R. Morris (Boston,
USA), but also Prof. Dr. G. Deml, Dr. D. Triebel, Prof. Dr. W. Gams, and Dr. O. Hering never
failed to encourage me to continue and finish the work.
I am very grateful to Prof. Dr. G. Rambold, Prof. R. Morris (Boston, USA), Prof. Dr. W. Ber-
endsohn (Berlin), Dr. M. Dallwitz (Giralang, Australia), Prof. Dr. W. Gams (Baarn, NL), Dr. F.
Bungartz (Galapagos Islands, Ecuador) and Dr. R. Pankhurst (Edinburgh, UK) for many enlight-
ening discussions and constructive criticism of the entirety or parts of this work. I am further
deeply indebted to the many other colleagues and friends who also have discussed problems, read
parts of the thesis, or answered questions. I would especially like to thank: J. Asiedu (Boston,
USA), Dr. N. Bailly (Paris, France), D. Barnier (Queensland, Australia), M. Choo (Perth/Kensing-
ton, Australia), N. Cross (†, USA), A. Ekrut (Berlin), C. Gallut (France), Dr. C. Germeier (Qued-
linburg), Dr. E. Gibaja Galindo, Prof. P. B. Heidorn (Urbana-Champaign, USA), D. Hobern (Co-
penhagen, Denmark), J. Ingenhaag (München), Prof. J. Kennedy (Edinburgh, UK), E. Kolster
(New Zealand), Prof. D. Maltais (Québec, Canada), D. Neubacher (München), Dr. T. Paterson
(Edinburgh, UK), Dr. G. Rousse (France), Dr. A. Rubner (Karlsruhe), Dr. M. Scholler (Karlsruhe),
Dr. S. Shattuck (Canberra, Australia), Dr. K. Thiele (Perth / Kensington, Australia), J.-M. Vanel
(France), R. Vignes Lebbe (Paris, France), G. Whitbread (Canberra, Australia), and Zhimin Wang
(Boston, USA).
While this thesis was in preparation, an international working group created an XML-based
data exchange standard for descriptive data (TDWG SDD, compare p. 20). The discussions in
this group strongly influenced the ideas in this thesis and the author is indebted to everybody con-
tributing to this working group during personal meetings or online discussions. Over 60 people
contributed to the SDD discussions, both by participating and organizing them. It is impossible to
list them all, but I want to thank them all. Much of the travel required for the international discus-
sions was supported through the following project grants (in chronological order): BioCase (Bio-
logical Collection Access Service for Europe, EU funding), BIOLOG-GLOPP and GBIF-D-Myk
(both BMBF funding), GBIF, and the TDWG infrastructure project (funded by The Gordon and
Betty Moore Foundation). The help is greatly appreciated.
Similarly, I thank all my work colleagues at the BBA and in projects for their support that en-
abled me to undertake this work, particularly A. Hansen, Prof. Dr. G. Deml, Prof. Dr. C. Reich-
muth, V. Ristau, Dr. O. Hering, Dr. H. Nirenberg, C. Hild, Dr. D. Triebel, Dr. M. Weiss, A. Kohl-
becker, J. Ingenhaag, and Prof. Dr. M. Piepenbring.
Finally, I would like to thank my wife Almut, my son Jakob, my mother and stepmother and
all other members of my family for the love and support they gave me throughout this work. G. Hagedorn Descriptive data in biology 7
Table of contents
1. Introduction .............................................................................................................................12
1.1. Biodiversity informatics.................................................................................................12
1.2. Descriptive data for identification and phylogeny .........................................................12
1.3. Other uses of descriptive data ........................................................................................15
1.4. Scope, motivation, and constraints of the current work .................................................15
2. Methods...................................................................................................................................18
2.1. Explorative requirement analyses ..................................................................................18
2.2. Survey of information models and software ..................................................................18
2.3. UML use cases ...............................................................................................................23
2.4. UML static class diagrams and ER models....................................................................24
2.5. Abbreviations .................................................................................................................26
3. Selected definitions .................................................................................................................27
3.1. Descriptive data in the context of biodiversity data .......................................................27
– Definition of ‘descriptive data’27
– Biodiversity ‘framework concepts’ ...........................................................................28
– Ambiguous or border-line cases of ‘descriptive data’ ...............................................30
3.2. The term ‘character’ .......................................................................................................31
3.3. Terms for ‘object parts’..................................................................................................33
3.4. Comparison of current usage of terms34
4. Fundamental aspects of description models ............................................................................36
4.1. Introduction ....................................................................................................................36
4.2. Context, recognition, and language................................................................................36
4.3. Natural language descriptions ........................................................................................39
4.4. Structured descriptions and the concept of terminology ................................................42
– Level of abstraction of descriptive information models ............................................42
– Generalization and terminology44
– Static versus dynamic terminology models ...............................................................45
– Reaching terminological stability ..............................................................................47
– Relation between terminology and software implementations..................................48
4.5. Data types.......................................................................................................................49
– Measurement scales...................................................................................................49
– Continuous versus discrete variables.........................................................................51
– Categorical versus quantitative (measurement) data .................................................52
– Singularity, extension and connectedness of categories............................................53
– Data types in computer programming .......................................................................55
– Unconstrained text.....................................................................................................56
– Molecular sequence data............................................................................................57
– Complex quantitative data types................................................................................59
– Media data .................................................................................................................60
– Implemented data type systems .................................................................................61
– Basic property types ..................................................................................................62
4.6. Mapping between data types ..........................................................................................66
– Mapping univariate continuous measurements to categories ....................................66
– Mappings within categorical data..............................................................................68
– Mapping complex quantitative data to categorical data ............................................69
– Mappings and definition of categories.......................................................................70
8 Descriptive data in biology G. Hagedorn
– Mapping unconstrained text to structured data..........................................................71
– Mappings involving more than two characters71
– Calculated characters.................................................................................................72
4.7. Coding status..................................................................................................................74
4.8. Character dependency ....................................................................................................76
– Character dependency in general...............................................................................76
– Character applicability rules ......................................................................................76
– Convertibility of applicability rules...........................................................................79
– Coexistence of character applicability rules ..............................................................81
– Cascading character applicability rules .....................................................................82
– Current support in some applications and data standards..........................................82
4.9. Raw data and data aggregation.......................................................................................83
– Introduction ...............................................................................................................83
– Standard aggregation methods...................................................................................85
– Inappropriate aggregation results...............................................................................87
– Aggregating aggregated data .....................................................................................88
– Data recording levels (sample data)...........................................................................89
– Linked observations...................................................................................................90
– Special aggregation cases ..........................................................................................92
– Aggregation within individuals .................................................................................93
– Boolean operators between states of categorical characters......................................95
– Boolean operators between characters.......................................................................98
4.10. Inheriting data ................................................................................................................99
– Data compilation versus data inheritance ..................................................................99
– Inductive inheritance (upwards) ................................................................................99
– Deductive inheritance (downwards) ........................................................................100
– Current models ........................................................................................................101
– Implicit data.............................................................................................................102
– Compatibility testing as a quality control measure..................................................103
4.11. Description storage models ..........................................................................................104
– Introduction104
– Categorical data: Character matrix vs. character state matrix .................................104
– Quantitative data and statistical measures ...............................................................110
– Value order in character data...................................................................................113
– Character decomposition models.............................................................................116
– Concept hierarchies .................................................................................................125
4.12. Descriptive ontologies..................................................................................................131
– Object composition131
– Multiplicity of objects in compositions ...................................................................141
– Spatial arrangement of objects in compositions ......................................................147
– Generalization of object parts (compositional concepts).........................................153
– Change of object concepts through temporal development.....................................162
– Properties.................................................................................................................164
– Methods ...................................................................................................................169
– Relations between properties and methods..............................................................176
4.13. Federation and modularization of terminology ............................................................180
– Introduction .............................................................................................................180
– Managed federations................................................................................................180 G. Hagedorn Descriptive data in biology 9
– Terminology modules..............................................................................................181
– Extending shared terminology definitions...............................................................182
– Terminology modules and class hierarchy ..............................................................183
– Models to support multiple distributed terminologies.............................................185
– Conclusions .............................................................................................................188
4.14. Modifiers ......................................................................................................................189
– Introduction189
– Definition.................................................................................................................191
– Current usage of modifier-related concepts.............................................................192
– Modifier sets and sequences ....................................................................................199
– Modifier combinations.............................................................................................199
– Modifiers as an alternative to character proliferation..............................................201
– Modifier classes.......................................................................................................203
– Character- versus value-modifiers...........................................................................214
4.15. Secondary classification resulting in description scopes215
– Introduction .............................................................................................................215
– Mating type and sex.................................................................................................217
– Generations, life cycle, and developmental stages ..................................................218
– Other classifier concepts..........................................................................................219
– Generalized term for sex, generation, life cycle stages, etc.....................................220
– Context of secondary classifier data ........................................................................221
– Classifier-related characters.....................................................................................221
– Existing models of handling secondary classifiers ..................................................222
– Summary and conclusions .......................................................................................227
5. Identification methods...........................................................................................................229
5.1. Introduction ..................................................................................................................229
5.2. Classification of identification methods.......................................................................230
– Kind of data used for identification .........................................................................230
– Levels of interaction ................................................................................................230
– Phases of interactive identification..........................................................................231
– Structural classification of identification keys.........................................................233
– Propositional versus object matching metaphors.....................................................238
– “Promorph” and “looks like” metaphors .................................................................238
– Radford's classification............................................................................................240
– Other classification criteria for identification keys..................................................240
5.3. Presentation styles of identification keys .....................................................................242
– Printable branching keys..........................................................................................242
– Computer-aided branching keys ..............................................................................247
– Printable multi-access keys......................................................................................249
– Computer-aided multi-access keys ..........................................................................251
– Tabular keys ............................................................................................................256
5.4. Requirement summary .................................................................................................257
5.5. Linking multiple keys...................................................................................................259
– Transferring progress information between multi-access keys ...............................260
– Transferring progress information between branching and multi-access keys........262
5.6. Equality criteria and error tolerance.............................................................................264
5.7. Character ranking and guidance...................................................................................267
– Authored character guidance267
10 Descriptive data in biology G. Hagedorn
– Algorithmic character guidance...............................................................................270
– Combining algorithmic with authored character guidance......................................276
– Alternative algorithms .............................................................................................276
– Presentation of character guidance in multi-access keys.........................................277
6. Use case analysis ...................................................................................................................277
6.1. Introduction ..................................................................................................................277
6.2. Roles and agents (use case actors)278
6.3. Information acquisition ................................................................................................280
– Project management.................................................................................................280
– Definition of terminology........................................................................................281
– Descriptions .............................................................................................................288
6.4. Information retrieval ....................................................................................................297
– Selection of language and audience representations................................................298
– Selection of branching keys.....................................................................................298
– Querying container level metadata ..........................................................................300
– Querying natural language description data ............................................................300
– Querying coded description data .............................................................................300
6.5. Information review and interpretation301
– Analysis of data quality and completeness..............................................................301
– Analysis of character correlation303
– Analysis of character applicability304
– Aggregating descriptions.........................................................................................305
– Creation of class hierarchies....................................................................................306
– Analysis of character evolution ...............................................................................306
– Creation of diagnostic subsets .................................................................................307
6.6. Identification ................................................................................................................308
– Identification keys ...................................................................................................308
– Switching between branching and multi-access keys..............................................309
– Confirmation of identification309
– Failure of identification ...........................................................................................310
– Identification of potential taxon concepts................................................................311
– Creation of branching keys......................................................................................312
– Dynamic character recommendations for identification purposes...........................313
– Character recommendations for identification purposes based on the
phylogeny314
6.7. Information application ................................................................................................315
– Report generation.....................................................................................................315
– Taxon pages.............................................................................................................319
– Data exchange and archival exports ........................................................................320
6.8. Open aspects.................................................................................................................322
7. Information model for DiversityDescriptions 1.9 .................................................................322
7.1. Introduction ..................................................................................................................322
7.2. Logical model for DiversityDescriptions 1.9 ...............................................................324
– Packages and subsystems ........................................................................................324
– Package: Terminology.............................................................................................325
– Package: Descriptions..............................................................................................329
– Package: Resources .................................................................................................331
7.3. Physical model for DiversityDescriptions 1.9..............................................................332

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