Semantic Instance Anatomies

Semantic Morph∙D∙Base Making Morphology ready for eScience

L. Vogt, R. Baum, P. Bhatty, S. Meid, P. Grobe, C. Köhler, B. Quast DINA Meeting 2018 | Think Tank

Application Ontologies

| L. Vogt et al.: Semantic MDB

controls

DINA Meeting | February 2018

Background

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| Semantic Instance Anatomy

Background

Vogt (2008): Learning from Linnaeus: towards developing the foundation for a general structure concept for morphology. Zootaxa 1950: 123–152. Vogt (2016): Assessing similarity: on homology, characters and the need for a semantic approach to non-evolutionary comparative homology. Cladistics EarlyView. DOI: 10.1111/cla.12179 | L. Vogt et al.: Semantic MDB


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Background


Data-Graph

Assertional Statements

statements about instances/individuals

Partonomy

hierarchical organization



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Background


Data-Graph



Each part and quality has its Partonomy own URI and thus hierarchical can be organization Individually Referenced



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Background


Data-Graph



→ The Data-Graph can be Partonomy hierarchical organization Fragmented into sub-graphs



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Background


Ontology-Graph

Universal Statements

statements about universals/kinds

Taxonomy

hierarchical organization



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Background



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Background



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Background


This Description Method can be applied to any Descriptive (empirical) Data, e.g. Trait Data



Background

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Background

| Quantifying Similarity Between Morphological Descriptions

Instance Anatomies allow for Quantitative Comparison

Vogt (2017): Towards a semantic approach to numerical tree inference in phylogenetics. Cladistics EarlyView. DOI: 10.1111/cla.12195 | L. Vogt et al.: Semantic MDB


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Background


Instance Anatomies allow for Quantitative Comparison By Matching & Mapping nodes between Graphs, Graphs are Aligned using Algorithms



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Background


Instance Anatomies allow for Quantitative Comparison



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Background


Instance Anatomies allow for Quantitative Comparison This Alignment is based on a Quantitative Measure of Similarity



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Background


Instance Anatomies allow for Quantitative Comparison The possibility to Quantify Similarity between two descriptions provides a New Theoretical and Methodological Framework for Comparative Biology Vogt (2017): Towards a semantic approach to numerical tree inference in phylogenetics. Cladistics EarlyView. DOI: 10.1111/cla.12195 | L. Vogt et al.: Semantic MDB


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Background


Instance Anatomies allow for Quantitative Comparison Character Analysis becomes more Transparent and Reproducible, and more open to Critical Analysis Vogt (2017): Towards a semantic approach to numerical tree inference in phylogenetics. Cladistics EarlyView. DOI: 10.1111/cla.12195 | L. Vogt et al.: Semantic MDB


Background

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Background

| Area of Application I

Instance Anatomies allow for Identification of Units of Comparison

Unit of Comparison

Vogt (2016): Assessing similarity: on homology, characters and the need for a semantic approach to non-evolutionary comparative homology. Cladistics EarlyView. DOI: 10.1111/cla.12179 | L. Vogt et al.: Semantic MDB


Background

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| Area of Application II

Background

Instance Anatomies allow Separation of Description from Character Coding

Vogt (2017): The logical basis for coding ontologically dependent characters. Cladistics EarlyView. DOI: 10.1111/cla.12209 | L. Vogt et al.: Semantic MDB


Background

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Background

| Area of Application III

Graph-Based Numerical Tree Inference



Background

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Background

| Data Standards in the Age of eScience

eScience-Compliant Standards for a given (Meta)Data Statement

Content Standard

Which information is relevant?

reproducibility, operational transparency

Vogt (2009): The future role of bio-ontologies for developing a general data standard in biology: chance and challenge for zoomorphology. Zoomorphology 128, 3: 201-217. Vogt et al. (2013): The Need for Data Standards in Zoomorphology. Journal of Morphology 274, 793-808. Vogt (2013): eScience and the Need for Data Standards in the Life Sciences: In Pursuit of Objectivity rather than Truth. Systematics and Biodiversity 11(3), 257-270. | L. Vogt et al.: Semantic MDB


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Background



Content Standard


Concept Standard

What is the meaning of a concept?


semantic transparency



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Background



Content Standard


Concept Standard

What is the meaning of a concept? (some) Ontology Terms





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Background



Content Standard


Concept Standard


Nomenclatural Standard

Which words are used for referring to a specific concept?



communicability



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Background



Content Standard


Concept Standard



Which words are used for referring persistent to a specific concept? URIs



communicability



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Background



Content Standard


Concept Standard




Format Standard

Which syntax, which file format?



communicability

compatibility, computer-parsability



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Background



Content Standard


Concept Standard




Format Standard

Which syntax? Semantic Instance Anatomies



communicability




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Background



Content Standard


Concept Standard




still missing something! Nomenclatural Which words are used for referring persistent Standard to a specific concept? URIs communicability

Format Standard

Which syntax? Semantic Instance Anatomies compatibility, computer-parsability



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| Semantic Morph∙D∙Base Prototype

Semantic Morph∙D∙Base Prototype



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| Semantic Morph∙D∙Base Prototype

Semantic Morph∙D∙Base Prototype



Morphological Description Entry

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| Semantic Morph∙D∙Base: Morphological Description Entry


Creating a new Morphological Description Entry



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List of Morphological Description Entries



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Basic GUI of a Data Entry in the semantic MDB



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GUI design concept | L. Vogt et al.: Semantic MDB


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Editing a Morphological Description Entry: CC License



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Go to Description GUI



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Basic GUI of the Description Module in the semantic MDB



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Adding Parts to the Partonomy



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mouseover will provide Ontology Definition



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Formal Description of an Anatomical Structure: Shape



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Formal Description of an Anatomical Structure: Volume Measurement



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User Input



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Named Graph Class


User Input


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Named Graph Class

allows for Meaningful Fragmentation of the data based on sets of Named Graph User Input Resources that belong to specific Classes of Named Graphs



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Formal Description of an Anatomical Structure: Volume Measurement allows for Meaningful Fragmentation of the data based on sets ofDifferent Named Graph Defining Views User Input Resources that belong specific on the datato Classes of Named Graphs

=

Named Graph Class



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Formal Description of an Anatomical Structure: Volume Measurement Description Template = Common Data Model

Named Graph Class


User Input


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Named Graph Class

Comparability is provided Description Template = through the use of a Common Data Model Common Data Model for Anatomy that consists of Template-SubgraphsUser for Input storing user input.



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Content Standard


Concept Standard




Format Standard




communicability




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Content Standard

Which information is relevant? Common Data Model

Concept Standard




Format Standard




communicability




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Content Standard

Which information is relevant? Common Data Model

Concept Standard




Format Standard

Common Which syntax? Data Model &



communicability

compatibility, Semanticcomputer-parsability Instance Anatomies



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Formal Description of an Anatomical Structure: Input Control



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Formal Description of an Anatomical Structure: Weight Measurement



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Formal Description of an Anatomical Structure: Dynamically Adding Sub-Forms



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Formal Description of an Anatomical Structure: Dynamically Adding Sub-Forms



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Formal Description of an Anatomical Structure



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Formal Description of an Anatomical Surface

information pro. (OBI)



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Formal Description of an Anatomical Line



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Formal Description of an Anatomical Point



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Formal Description of an Anatomical Space



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Formal Description of a Portion of Organic Substance



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Formal Description of an Absence

absence statements



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Formal Description of a Group of Scattered Anatomical Structures



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Formal Description of a Set of Anatomical Entities



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Metadata Documentation detailed Provenance



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Metadata Documentation detailed Provenance



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NL-Description



Free-Text Approach


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NL-Description



Free-Text Approach


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Semantic Markup



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Semantic Markup



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Media Contents


Media Approach

OpenStreetMap technology | L. Vogt et al.: Semantic MDB


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Media Annotation

Regions of Interest (RoI)



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Media Annotation

planned: Semantic Annotation of RoI



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Semantic Graph View

with various defined Filters (Granularity Framework) GUI design concept | L. Vogt et al.: Semantic MDB


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Publishing a Data Entry



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Publishing a Data Entry

Each published entry will receive its own DOI



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Published Entry in the Entry List



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Starting a Revision




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| Summary Morphological Description Entry


Summary Morphological Description • Semantic Morph∙D∙Base enables the generation of highly formalized morphological descriptions in the form of Semantic Instance Anatomies.



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Summary Morphological Description • Semantic Morph∙D∙Base enables the generation of highly formalized morphological descriptions in the form of Semantic Instance Anatomies. • Semantic Instance Anatomies are Semantically Transparent and can be used by any interested scientist. If stored in a data repository (e.g. MDB), they are Openly Accessible.



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Summary Morphological Description • Semantic Morph∙D∙Base enables the generation of highly Main Problem of Morphology as a formalized morphological descriptions in the form of Discipline solved: Semantic Instance Anatomies. •

Morphological data is Not easily Semantic Instance Anatomies are Semantically Transparent Accessible. and can be used by any interested scientist. If stored in a Non-experts usually CANNOT USEAccessible. data repository (e.g. MDB), they are Openly morphological data, even if it would be accessible.



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Summary Morphological Description • Semantic Morph∙D∙Base enables the generation of highly formalized morphological descriptions in the form of Semantic Instance Anatomies. • Semantic Instance Anatomies are Semantically Transparent and can be used by any interested scientist. If stored in a data repository (e.g. MDB), they are Openly Accessible. • The Semantic Approach enables the development of a New Theoretical and Methodological Framework for Comparative Studies that are based on Phenotypic Data. | L. Vogt et al.: Semantic MDB


Specimen Entry

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| Semantic Morph∙D∙Base: Specimen Entry

Specimen Entry

Specimen Entry



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Specimen Entry

Specimen Entry



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Specimen Entry

Dynamically Changing Input Forms



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Specimen Entry

Dynamically Changing Input Forms



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Specimen Entry


Documenting Specimen History



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Specimen Entry

Blocking Information



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Specimen Entry

Blocking Information



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Specimen Entry


Saving & Re-Using Templates



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Specimen Entry


Specimen Collection Event



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Specimen Entry


Specimen Collection Location



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Specimen Entry

Describing the Habitat



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Specimen Entry

Adding Local Condition Measurements



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Specimen Entry


Taxon Determination Event



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Specimen Entry


Adding Further Events to the Specimen History



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Specimen Entry


Adding Further Events to the Specimen History



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Specimen Entry


New Panel Design for Specimen History



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Specimen Entry


Specimen Organism Attributes



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Specimen Entry

Specimen Repository



Specimen Entry

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| Semantic Morph∙D∙Base: Specimen Entry Data Scheme

Specimen Entry

General Planned Process Scheme

Information Artifact Ontology [IAO] Ontology for Biomedical Investigations [OBI] | L. Vogt et al.: Semantic MDB


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Specimen Entry

General Planned Process Scheme

NOT compliant with Darwin Core

Information Artifact Ontology [IAO] Ontology for Biomedical Investigations [OBI] | L. Vogt et al.: Semantic MDB


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Specimen Entry

Specimen Prep. Process Scheme



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Specimen Entry

Specimen Prep. Process Scheme



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Specimen Entry


Specimen Entry Data Scheme



Semantic Morph∙D∙Base Making Morphology ready for eScience

L. Vogt, R. Baum, P. Bhatty, S. Meid, P. Grobe, C. Köhler, B. Quast DINA Meeting 2018 | Think Tank

Application Ontologies

controls

Prototype: http://proto.morphdbase.de Source Code: https://github.com/MorphDBase/MDB-prototype Wiki: http://escience.biowikifarm.net



Sup.

Specimen Entry

| Specimen Data Scheme




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Specimen Entry





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Specimen Entry





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Background

| Solution to the Linguistic Problem of Morphology

Linguistic Problem of Morphology Lack of

• commonly accepted, standardized and taxonPersistent URIs and Ontology Terms independent Morphological Terminology;

triple statement: • commonly accepted, standardized and Solution involves RDF / OWL Subject Property Object formalized Method of Description;

• Demarcation Criterion for morphological entities. 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: 301325. | L. Vogt et al.: Semantic MDB


Sup.

Background

| Solution to the Linguistic Problem of Morphology

Linguistic Problem of Morphology Semantic Graph Lack of

• commonly accepted, standardized and taxonPersistent URIs and Ontology Terms independent Morphological Terminology; • commonly accepted, standardized and Solution involves RDF / OWL formalized Method of Description; • Demarcation Criterion for morphological entities.

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: 301325. | L. Vogt et al.: Semantic MDB


Semantic Instance Anatomies

Semantic Instance Anatomies

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