data and metadata standards in zoomorphology : a call to action

Data and Metadata Standards inZoomorphology: A Call to Action

Lars Vogt

Universität BonnL. VogtStandardization in Zoomorphology

The Evolution of Scientific Standards

A Historical Perspective

Vogt (submitted) On Standards in Science: In Pursuit of Truth-to-Nature and Objectivity. In: Special Issue “Data platforms in integrative biodiversity research. Ecological Informatics.

All Scientific Standards depend on some

Epistemic Virtue


One can distinguish two types of general Epistemic

Virtues:

Truth-to-NatureScientific Objectivity


Truth-to-Nature

Truth-SeekingMethods


These are Standards of

Justification of Scientific Reasoning

Provide Demarcation CriteriaScience vs Believe


Classic Methods & Criteria

Plato


Essentialism

Syllogistic Demonstration

Aristotle

Classic Methods & Criteria

Plato


Essentialism

Syllogistic Demonstration

Aristotle

Standard is set bygeneral Principles of Logical Coherence

Leonardo da Vinci

Renaissance &“Scientific Revolution”

Francis Bacon


Laboratory Method&

Induction

Leonardo da Vinci

Renaissance &“Scientific Revolution”

Francis Bacon


Laboratory Method&

Induction

Standard is set bygeneral Principles of

Empirical Grounding

Modern Criteria of Testability

Rudolf Carnap


Verification PrincipleInduction



Falsificationism

DeductionKarl Popper



Falsificationism


Standard is set by moresophisticated Theories of

Empirical Grounding(e.g. Carnap) or

Logical Coherence(e.g. Popper)



Falsificationism


Standard is set by moresophisticated Theories of

Empirical Grounding(e.g. Carnap) or

Logical Coherence(e.g. Popper)

These Standards

DO NOT interest

Us Today!

Scientific Objectivity

‘Objectifying’ Methods



Data Production

Provide Criteria forData Quality & Documentation



Data Production

Provide Criteria forData Quality & Documentation


Reproducibility& operational Transparency

“Scientific Revolution” Methods & Criteria

Royal Society


“Gentleman’s”Objectivity


Royal Society



Experiment as Demonstration


Royal Society



Experiment as Demonstration

Standard is set bythe Verdict of

the eye wittnessing Gentlemen

Modern Methods & Criteria

Philosophical Transactions


Reproducibilityoperational

Transparency





Transparency

Standard is set byEditors andReviewers





Transparency

Standard is set byEditors andReviewersCurrent Status in

Morphology

Standards based on Convention

internationally standardized

Measurement Units


Standards based on Technology:

PhotographyHistology

Immunohistology


Daston & Galison (1992) The image of objectivity. Representations 40, 81-128.

see also Procedural Objectivity sensu Heintz (2000) Die Innenwelt der Mathematik. Zur Kultur und Praxis einer beweisenden Disziplin. Wien, Springer.

*

Standards based on Technology:

PhotographyHistology

Immunohistology


MechanicalObjectivity*

Daston & Galison (1992) The image of objectivity. Representations 40, 81-128.

see also Procedural Objectivity sensu Heintz (2000) Die Innenwelt der Mathematik. Zur Kultur und Praxis einer beweisenden Disziplin. Wien, Springer.

*


Are these Standardsstill sufficient

today?

“Web of Things”

CommunicabilitySemantic

TransparencyCompatibilityInternet &

Databases


“Web of Things”



Databases


Data Repositories

“Web of Things”



Databases


Data RepositoriesRequire highly

formalized Rules,Conventions & Formats


From a Presentation from Bendix et al. 2011: Introduction to the Workshop “Data repositories in environmental sciences – concepts, definitions, technical solutions and user requirements”


From a Presentation from Bach K 2011: A comparative evaluation on technical solutions of long-term data repositories related to biodiversity

Data Repositories


Do we really need more Standards in

Zoomorphology?


From a Presentation from Enke N & Gemeinholzer B 2011: The user’s view on data sharing

Data Harvesters


Data Harvesters

… benefit fromData and Metadata

Standards


Data Harvesters

… benefit fromData and Metadata

Standards


Commonly accepted Morphological Data and

Metadata Standards would increase Visibility of

Morphology


The Global View

What drives Progress in Science?

…in its early days mainly Experimentation & Theory

Hey, T. et al. (2009) The Fourth Paradigm: Data-Intensive Scientific Discovery. Microsoft Research, 284pp.





With the advent of Computers also Simulation…





With the advent of Computers also Simulation…

…and today, with Databases, Semantic Tools (e.g. Ontologies) and high-throughput Technologies also

Data Exploration.


Data-driven Science

“Web of Things”

Semantic Web

Databases

Ontologies


“Web of Things”

Semantic Web

Databases

Ontologies


Data-driven Science

“Web of Things”

Semantic Web

Databases

Ontologies


Data-driven Science

Intelligent Systems and Tools for

Data Exploration


Gray, J. (2009) Jim Gray on eScience: A Transformed Scientific Method. In: Hey

et al. (eds.) The Fourth Paradigm: Data-Intensive Scientific Discovery. Microsoft Research, xvii-xxxi.




The currentMorphological Record




Utilizing the Semantic Web

&Data Repositories




eScience


Data Integration

Wiley, H.S. (2011): Integrating Multiple Types of Data for Signaling Research: Challenges and Opportunities. Science Signaling 4: 160.


Data Integration

Wiley, H.S. (2011): Integrating Multiple Types of Data for Signaling Research: Challenges and Opportunities. Science Signaling 4: 160.

Next obvious Step:Integration of Morphology

Data Visualization


Data Visualization


Fox, P. & Hendler, J. (2011) Changing the Equation on Scientific Data Visualization. Science 331(6018): 705-708.

Rowe, T. & Frank, L.R. (2011) The disappearing third dimension. Science 331(6018): 712-714.


Integrating theScientific Record

Publications &

Databases

Penev et al. (2009): Data publication and dissemination of interactive keys

under the open access model – ZooKeys working example. ZooKeys 21: 1-17.

Publications & Databases



Semantic Tools

Ontologies


Semantic Tools

OntologiesOntologieshighly formalized controlled

defined Vocabularies


Semantic Enhancement


Ontologies & Data Annotation

Dadzie, A.-S. & Burger, A. (2005) Providing visualisation support for the analysis of anatomy ontology data. BMC Bioinformatics 6: 74.



Washington et al. (2009) Linking human diseases to animal models using ontology-based phenotype annotation. PLoS Biology 7: 11.



Kuß et al. (2008) Ontology-based visualization of hierarchical neuroanatomical structures. In: Botha et al. (eds.) Eurographics Workshop on Visual Computing for Biomedicine. The Eurographics Association: 6-16.




EmpiricalGrounding




MorphologicalData

EmpiricalGrounding




User

MorphologicalData

EmpiricalGrounding


If the MorphologicalCommunity wants to

participate in eScience,we have to develop

the appropriate

Data and MetadataStandards


What is the Difference between Data and

Metadata?


Data

ObjectThing orProcess

ObserverPerson orInstrument

Representation

SomeContent

General Scheme of a Scientific Study

SomeContent




Representation

SomeContent

General Scheme of a Scientific Study

SomeContent


Data

Morphology is about theForm & Existence

of Biological Material Entities


Data are Descriptions aboutthe Existence of Organisms, their supramolecular parts

and the material and topological Properties of them

Morphological Data

Composition, Form, Consistency, relative Position, Orientation, etc.



Metadata



Representation

SomeContentSome

Content


Transparent & Reproducible



Representation

SomeContentSome

Content



requires

DOCUMENTATION

Documentation of…

…all that is required for a Third Person to re-produce the same Content (i.e. Data).

All relevant information regarding the Object of Study and the Methods

applied and Instruments used during Data Production.


Documentation of…

…all that is required for a Third Person to re-produce the same Content (i.e. Data).

All relevant information regarding the Object of Study and the Methods

applied and Instruments used during Data Production.


Metadata

Observer

Object Representation

Thing orProcess

Person orInstrument

SomeContent

What, where, when, etc.

Methods,Instruments,

etc.What, where,

when, etc.What, where,

when, etc.


etc.What, where,

when, etc.


Metadata


Observer


Thing orProcess

Person orInstrument

SomeContent



etc.What, where,


when, etc.


etc.What, where,

when, etc.



Metadata

CommunicableTransparent & Reproducible

Observer


Thing orProcess

Person orInstrument

SomeContent



etc.What, where,


when, etc.


etc.What, where,

when, etc.



Metadata

Communicable

requires

STANDARDIZATION



How to develop aMetadata Standard

Developing Metadata Standards – an Example:

OMICS (Genomics, Transcriptonics, Proteomics, Metabolomics)


Commonly accepted Reporting Structure is required that specifies which Annotations should be included

Minimum Information Checklists

Brazma et al. (2001): Minimum information about a microarray experiment (MIAME) – towards tandards for microarray data. Nature 29: 365-371.

Developing Metadata Standards – an Example:

OMICS (Genomics, Transcriptonics, Proteomics, Metabolomics)


Commonly accepted Reporting Structure is required that specifies which Annotations should be included

Minimum Information Checklists

Brazma et al. (2001): Minimum information about a microarray experiment (MIAME) – towards tandards for microarray data. Nature 29: 365-371.

First Step towards Standardization…


What does a Modern METADATA Standard

account for?

Content Standard Reproducibility &

Operational TransparencyWhat is relevant Content ?



Insufficient!

Vogt (2009) The future role of bio-ontologies for developing a general data standard in biology: chance and challenge for zoo-morphology. Zoomorphology 128(3), 201-217.

Content Standard Reproducibility &

Operational TransparencyWhat is relevant Content ?





Concept Standard Semantic Transparency

What does a Concept/Term mean ?




Format Standard Compatibility &

Computer ParsabilityWhat Syntax for Content

Transmission?




Nomenclatural Standard Communicability

Which Symbol/Word refers to which Concept?


But what aboutDATA Standards

in Zoomorphology?

Data are Descriptions aboutthe Existence of Organisms, their supramolecular Parts


Morphological Data






Morphological Data




Terminology

Problem equivalent structures possess different denotations

Problems with Morphological Terminology

differing structures possess identical denotations


Problems with Morphological Terminology


Reason some terms are based on homology hypotheses

some terms refer to functions, some to development, others to forms

taxon-specific terminologies

continuous change of meaning of a term

individual preferences

(which at their turn are based on morphological descriptions)

Universität BonnL. VogtStandardization in Morphology

Vogt (2008) Learning from Linnaeus: towards developing the foundation for a general structure concept for morphology. Zootaxa 1950, 123-152.

Vogt (2009) The future role of bio-ontologies for developing a general data standard in biology: chance and challenge for zoo-morphology. Zoomorphology 128, 3: 201-217.

Vogt et al. (2010) The linguistic problem of morphology: structure versus homology and the standardization of morphological data. Cladistics 26, 3: 301-325.

*

The Linguistic Problem of Morphology*

(Definitions free of homology assumptions)

Lack of commonly accepted, standardized and taxon- independent morphological terminology

commonly accepted, standardized and formalized method of description





*





Reference System of Biology(Inventory & Data Management)

Important for allsupra-molecular biological

Data





*





Reference System of Biology(Inventory & Data Management)

Important for allsupra-molecular biological

Data

Meaning &

Reference of

Terms is

problematic


2 underlying General Problems

1


Language & Epistemology

Terms as TextualRepresentationsof Real Entities

Observer



Real Entitiesobjects, processes,

qualities, states

textual/graphical Representational

Artifactsof Real Entities

Cognitive Representations

of Real Entities

Vogt (in press) Sings and Terminology – Science caught between language and perception. BIONOMINA.

Observer




qualities, states




of Real Entities

Observation, Measurement


Observer




qualities, states




of Real Entities

Observation, Measurement

Communication


Observer




qualities, states




of Real Entities

Communication


Observer




qualities, states




of Real Entities

CommunicationReference


Observer




qualities, states




of Real Entities

CommunicationReference


?

Observer




qualities, states




of Real Entities

Communication

indirect Reference



Are there differences regarding Reference

between differentTypes of Terms?


Proper Names&

Unambiguous Reference


Vogt (submitted) On Standards in Science: In Pursuit of Truth-to-Nature and Objectivity. In: Special Issue “Data platforms in integrative biodiversity research. Ecological Informatics

Communication about individual Entities (i.e. Particulars)




qualities, states









qualities, states



Communication







qualities, states



Communication

SupermanDC-Comic

Hero







qualities, states



Communication

‘Superman’

SupermanDC-Comic

Hero







qualities, states



Communicationdirect Referencethrough Ostensive

Definitions

‘Superman’

SupermanDC-Comic

Hero







qualities, states



Communication

e.g.

Pointing and Calling the Name

Name Label on a Photograph

Taxon Name Label on a Type Specimen







qualities, states



Communication

In the Internet:

Unique Persistent Identifiers,e.g. DOIs, LSIDs, GUIDs…


General Terms&

Reference

Communication about general Types of Entities (i.e. Universals/Classes)




qualities, states







qualities, states



Communication





qualities, states



Communication

NO direct Reference





qualities, states



Communication

NO direct Reference

Reference requires

Definition of essential Properties

Aristotelian Definitions

2


Dealing with Complexity

Terminology and the Organization of Morphological

Knowledge

2 Basic Typesof organizational

Hierarchies:

TaxonomiesPartonomies


Taxonomy: by Subsumption (Class-Subclass Hierarchy)

Aristotelian Definition

necessary propertydefinition of parent classinherited definition part

sufficient propertyessence of the groupdistinguishing definition part

genus

differentia


Topological Aspectsintrinsic material and topological properties

Morphological Terminology: Taxonomy

Morphological Terminology distinguishes more general from more specialized Types/Kinds

e.g. ‘Neuron’ is_a type of ‘Cell’


Partonomy: by Parthood (Part-Whole Hierarchy)


Parts are related to their

Wholesthrough

direct proper Parthood relations


Individual Partonomy of a particular Specimen


Parts of parts of an Organism

e.g. ‘Head’ is_part_of ‘Body’



General Levels of Organization: Partonomy

Vogt (2010) Spatio-structural granularity of biological material entities. BMC Bioinformatics 11, 289.

molecular level

cellular level

multicellular level

part-of relations

part-of relations

These two types of Hierarchies can be applied in various ways

due to theinherent Complexity

of Biological Material Entities


We can do the same forFunctional

Aspects of Biological Material Entities

Functional Terminology: Taxonomy

Functional Organization: Partonomy


We can do the same forFunctional


Functional Terminology: Taxonomy

Functional Organization: Partonomy


Formin relation to

causal Processes

…and forDevelopmental


Developmental Terminology: Taxonomy

Developmental Organization: Partonomy


…and forDevelopmental


Developmental Terminology: Taxonomy

Developmental Organization: Partonomy


Formin relation to

causal Processes involved in

Growth/Change of Form

…and forEvolutionary


Homology based Terminology: Taxonomy

Lineage Organization: PartonomyPhylogeny, Genealogy, Gene-trees, etc.


…and forEvolutionary


Homology based Terminology: Taxonomy

Lineage Organization: PartonomyPhylogeny, Genealogy, Gene-trees, etc.


Formin relation to

Past Processes

Classificatory AspectsDifferent properties have been used

Classification of Taxa: Taxonomy


Classificatory AspectsDifferent properties have been used

Classification of Taxa: Taxonomy


Conclusion for StandardizationWe should take it

Step-by-Step, distinguish the different aspects and

first focus on the Basics: intrinsic Material and

Topological Properties


Ontologies&

Morphological Standards


Problems withcurrently available

Anatomy Ontologies

Conceptual Shortcomings*is a Synapse a cell-part or a cell aggregate or a…?

Lack of Framework for Integrating different Perspectives* anatomy, function, development, evolution

Problems of many Anatomy OntologiesModel-Organism and Vertebrate centered

Vogt (2010) Spatio-structural granularity of biological material entities. BMC Bioinformatics 11, 289. Vogt et al. (2011) Top-level categories of constitutively organized material entities. PLoS ONE 6(4): e18794

*

Not applicable in a broad taxonomic Approachtry to define Organ for all Metazoa…

Irrealistic basic Assumptions*






*


Irrealistic basic Assumptions*Presupposition of most

Anatomy Ontologies






*


Irrealistic basic Assumptions*Reality of most

biological Objects






*


Irrealistic basic Assumptions*Reality of most

biological Objects

We need an

Anatomy

Reference

Ontology



Basic Principles for a Cross-SpeciesMorphologicalTerminology

1. Use of Aristotelian Definitions (Class-Subclass Hierarchy)

Definition Neuron:A Neuron is a Cell that…




2. Taxon-Independent: Definitions contain NO Reference to a specific Taxon



2. Taxon-Independent: Definitions contain NO Reference to a specific Taxon

3. Homology-Free: Definitions contain NO Assumptions about underlying Putative Homology

Call to Action


Call to Action


officially supported by

oomorphological tandards onsortium

ZSC

Call to Action


officially supported by


ZSC

Thank You for Your Attention !



ZSC Goal

Promote Mechanism that

• Standardize the Description of Anatomical Structures

• Exchange and Integrate Morphological Data & Metadata

• Develop and Establish a General Morphological Data & Metadata Report Standard

• Develop Minimum Information Checklists



ZSC Organization

• Open Membership

• International Working Body

• Collaboration with Societies & Journals

data and metadata standards in zoomorphology : a call to action

Documents

standards of data production

scientific reasoning

standards of justification

popperthese standards

carnap orlogical coherencee

pursuit of truth

special issue data platforms

demarcation criteriascience