Data and metadata standards in zoomorphology: a call to action

Lars Vogt

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 .

Standardization in Zoomorphology L. Vogt Universität Bonn

All Scientific Standards depend on some

Epistemic Virtue

Universität Bonn Standardization in Zoomorphology L. Vogt

One can distinguish two types of general Epistemic

Virtues:

Truth-to-Nature

Scientific Objectivity


Truth-to-Nature

Truth-Seeking

Methods


These are Standards of

Justification of

Scientific Reasoning

Provide Demarcation Criteria

Science vs Believe


Classic Methods & Criteria

Essentialism

Syllogistic

Demonstration


Classic Methods & Criteria

Essentialism

Syllogistic

Demonstration


Renaissance &

“Scientific Revolution”

Laboratory Method

&

Induction


Renaissance &


Laboratory Method

&

Induction


Modern Criteria of Testability

Verification

Principle

Induction



Falsificationism

Deduction




Deduction




Deduction


Scientific Objectivity

‘Objectifying’ Methods



Data Production

Provide Criteria for

Data Quality &

Documentation



Data Production

Provide Criteria for

Data Quality &

Documentation



Methods & Criteria

“Gentleman’s”

Objectivity



Methods & Criteria


Objectivity



Methods & Criteria


Objectivity


Modern Methods & Criteria

Reproducibility operational

Transparency




Transparency




Transparency


Standards based on

Convention

internationally standardized

Measurement Units


Standards based on

Technology:

Photography

Histology

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:

Photography

Histology

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.



“Web of Things”

Communicability

Semantic

Transparency

Compatibility


“Web of Things”

Communicability

Semantic

Transparency

Compatibility


“Web of Things”

Communicability

Semantic

Transparency

Compatibility


From a Presentation from Bendix et al.

2011: Introduction to the Workshop “Data repositories in environmental sciences

– concepts, definitions, technical solutions and user requirements”


Data Repositories

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



From a Presentation from Enke N & Gemeinholzer

B 2011: The user’s view on data sharing


Data Harvesters


Data Harvesters


Data Harvesters



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

Ontologies

Databases




Semantic Web

Ontologies

Databases




Semantic Web

Ontologies

Databases


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 current

Morphological 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.


Data Visualization





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

Standardization in Zoomorphology L. Vogt

Fox, P. & Hendler, J. (2011) Changing the

Equation on Scientific Data

Visualization. Science

331 (6018): 705-708.

Universität Bonn


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.




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 ontologybased 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.



Empirical

Grounding

Kuß et al.





Morphological

Data

Empirical

Grounding

Kuß et al.





User

Morphological

Data

Empirical

Grounding

Kuß et al.





User

Morphological

Data

Empirical

Grounding

Kuß et al.




If the Morphological

Community wants to participate in eScience , we have to develop the appropriate

Data and Metadata

Standards




General Scheme of a Scientific

Study

Thing or

Process

Standardization in Zoomorphology

Person or

Instrument

L. Vogt Universität Bonn

General Scheme of a Scientific

Study

Thing or

Process


Person or

Instrument


Morphology is about the

Form & Existence of Biological Material Entities


Morphological Data

Data are Descriptions about the Existence of Organisms , their supramolecular parts and the material and topological Properties of them

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



Transparent & Reproducible

Thing or

Process


Person or

Instrument



Thing or

Process


Person or

Instrument


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 .



Person or

Instrument

Thing or

Process

Some

Content


Communicable

Person or

Instrument

Thing or

Process

Some

Content


Communicable

Person or

Instrument

Thing or

Process

Some

Content



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

First Step towards

included

Minimum Information Checklists

Brazma et al.

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




Content Standard

Reproducibility &

Operational Transparency

What is relevant Content ?


Content Standard

Reproducibility &

Operational Transparency

What 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.

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 .




201-217.





Concept Standard

Semantic Transparency

What does a Concept/Term mean ?


201-217.




L. Vogt Universität Bonn Standardization in Zoomorphology



201-217.





Format Standard

Compatibility &

Computer Parsability

What Syntax for Content developing a general data standard in biology: chance and challenge for zoo-morphology. Zoomorphology 128(3) ,

201-217.




L. Vogt Universität Bonn Standardization in Zoomorphology



201-217.





Nomenclatural Standard

Communicability

Which Symbol/Word refers to which Concept?


201-217.








Data are Descriptions about the Existence of Organisms , , their supramolecular Parts and the material and topological Properties of them



Data are Descriptions about the Existence of Organisms , , their supramolecular Parts and the material and topological Properties of them


Problems with Morphological

Terminology

Problem equivalent structures possess different denotations differing structures possess identical denotations


Problems with Morphological

Terminology

Reason some terms are based on homology hypotheses (which at their turn are based on morphological descriptions) some terms refer to functions, some to development, others to forms taxon-specific terminologies continuous change of meaning of a term individual preferences


The Linguistic Problem of

Morphology*

Lack of commonly accepted, standardized and taxonindependent morphological terminology (Definitions free of homology assumptions) commonly accepted, standardized and formalized method of description

* 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.

Standardization in Morphology L. Vogt Universität Bonn


Morphology*



Zootaxa 1950, 123-152.





Morphology*



Zootaxa 1950, 123-152.




2 underlying General

Problems


1


Vogt ( in press ) Sings and

Terminology

– Science caught between language and perception. BIONOMINA.



Terminology




Terminology




Terminology




Terminology




Terminology




Terminology




Terminology




Terminology




Terminology




Terminology




Terminology





Communication about individual

Entities (i.e. Particulars)

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

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










2


2 Basic Types of organizational

Hierarchies:

Taxonomies

Partonomies


Taxonomy: by Subsumption

(Class-Subclass Hierarchy) genus differentia

Aristotelian Definition necessary property definition of parent class inherited definition part sufficient property essence of the group distinguishing definition part


Topological Aspects intrinsic 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

Wholes through 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 multicellular level part-of relations cellular level part-of relations molecular level

Vogt (2010) Spatio-structural granularity of biological material entities.

BMC Bioinformatics 11, 289.


These two types of Hierarchies can be applied in various ways due to the inherent Complexity of Biological Material Entities


We can do the same for

Functional

Aspects of Biological Material

Entities

Functional Terminology: Taxonomy

Functional Organization: Partonomy


We can do the same for

Functional


Entities

Functional Terminology: Taxonomy

Functional Organization: Partonomy


…and for

Developmental


Entities

Developmental Terminology: Taxonomy

Developmental Organization: Partonomy


…and for

Developmental


Entities

Developmental Terminology: Taxonomy

Developmental Organization: Partonomy


…and for

Evolutionary


Entities

Homology based Terminology: Taxonomy

Lineage Organization: Partonomy

Phylogeny, Genealogy, Gene-trees, etc.


…and for

Evolutionary


Entities

Homology based Terminology: Taxonomy

Lineage Organization: Partonomy

Phylogeny, Genealogy, Gene-trees, etc.


Classificatory Aspects

Different properties have been used

Classification of Taxa: Taxonomy


Classificatory Aspects

Different properties have been used

Classification of Taxa: Taxonomy





Problems of many Anatomy Ontologies

Model-Organism and Vertebrate centered

Not applicable in a broad taxonomic Approach

try to define Organ for all Metazoa …

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

Irrealistic basic Assumptions*

*

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









Presupposition of most

*











Reality of most

*











Reality of most

*





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


oomorphological tandards onsortium officially supported by



oomorphological tandards onsortium officially supported by



oomorphological tandards onsortium

Goal

Promote Mechanism that

• Develop Minimum Information Checklists

• Standardize the Description of

Anatomical Structures

• Exchange and Integrate

Morphological Data & Metadata

• Develop and Establish a General

Morphological Data & Metadata

Report Standard


oomorphological tandards onsortium

Organization

• Open Membership

• International Working Body

• Collaboration with Societies & Journals


Data and metadata standards in zoomorphology: a call to action

Epistemic Virtue

Truth-to-Nature

Scientific Objectivity

Truth-to-Nature

Truth-Seeking

Methods

Justification of

Scientific Reasoning

Science vs Believe

Essentialism

Essentialism

Laboratory Method

&

Laboratory Method

&

Verification

Principle

Induction

Deduction

Deduction

Deduction

Scientific Objectivity

‘Objectifying’ Methods

Data Production

Data Quality &

Documentation

Data Production

Data Quality &

Documentation

internationally standardized

Measurement Units

Photography

Histology

Immunohistology

Photography

Histology

Immunohistology

Communicable

Communicable

First Step towards

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