The OntoEnrich platform: using workflows

for quality assurance and axiomatic enrichment of ontologies

Manuel Quesada Martínez, Jesualdo Tomás Fernández-Breis,

Robert Stevens, Nathalie Aussenac-Gilles,

Daniel Karlsson

UK Ontology Network Meeting

Newcastle, April 14th 2016

Manuel  Quesada  Mar,nez          14th  April  2016,  Newcastle            2/7  

OntoEnrich

What is the OntoEnrich framework?

•  Systema(c  analysis  and  exploita(on  of  lexical  regulari(es  in  ontologies  labels.  

•  Principles  of  the  analysis  

–  Systema(c  naming.  

–  Re-­‐use  of  content.  

•  Web  pla=orm  

E.g. Taxonomic Relation suggested by the Systematic Naming

Foundations of lexical regularities

What is a lexical regularity?

A lexical regularity (LR) is a group of consecutive ordered words that appear in more than one class of an ontology.

* Image generated using the OntoEnrich web: SNOMED CT July 2015 International released ontology (right) and GO MF ontology (left)

•  Length  and  frequency.  

•  Alignments  with  other  classes  or  fragments  of  classes:  decomposi(ons.  

•  …  

Manuel  Quesada  Mar,nez          14th  April  2016,  Newcastle            3/7  

…

Methodology

General description

Report OntoEnrich Framework

Input Ontology

File

Stage 1: ontology processing and obtaining lexical regularities

Graph of tokens

Stage 2: NLP Module

Configuration Parameters

Lexical Regularity

Graph-based algorithms

Stage 3: Metrics Module •  Locality and modularity •  CPE

Characterisation module •  Lexical analysis quant. features •  Matches between regularities •  Matches with external ontologies R

epor

t

Lexical Regularity

•  Loc. and Mod

•  CPE

•  … … …

Graph-based algorithms

Pre-processing of labels

Stage 5: Relation Extraction Module

Candidate

Enrichment Patterns

Input Ontology File

Modified

Stage 4: Filtering

Lexical Regularity

Configuration Parameters

Manuel  Quesada  Mar,nez          14th  April  2016,  Newcastle            4/7  

Workflows in OntoEnrich

Based on previous experiments and recommendations

•  E.g.  WF1  -­‐  Lexical  Regularity  as  common  sub  summer:  

–  Calculate  the  lexical  analysis.  

–  Filter  1:  remove  sub-­‐regulari(es.  

–  Filter  2:  remove  LRs  that  are  not  classes.  

–  Metric  1:  apply  the  LCS  metric.  

–  Explora(on  of  LRs  guided  by  the  previous  metric.  

An OntoEnrich workflow combines different types of filters, metrics and steps to support the user in the inspection of LRs, and in deciding how interesting they are

http://sele.inf.um.es/ontoenrich-beta/documentation/videosWorkflow/Workflow1_Alta.mp4

Manuel  Quesada  Mar,nez          14th  April  2016,  Newcastle            5/7  

Workflows in OntoEnrich

Based on previous experiments and recommendations

•  E.g.  WF2  –  POS  tagging  and  lexical  suggest  logically  define  metric    

http://sele.inf.um.es/ontoenrich-beta/documentation/videosWorkflow/Workflow3_Alta.mp4

–  Calculate  the  lexical  analysis.  –  Filter  1:  select  LRs  that  are  or  

contains  adjec(ves.  –  Manual  inspec(on  of  LRs:  

•  Metric  1:  modularity.  •  Asserted  vs  inferred  model.  •  Metric  2:  lexical  suggest  logically  

define  metric.  –  Calculate  Metric  2  for  the  whole  set  

of  LRs  and  sort  the  set  by  it.  –  Explora(on  of  LRs  guided  by  the  

previous  metric.  

Manuel  Quesada  Mar,nez          14th  April  2016,  Newcastle            6/7  

UKON 2016 Demo

           See  you  in  the  demo  session        

               Try  online  with  your  own  ontology  at:    

             hNp://sele.inf.um.es/ontoenrich  

 

Thank  you  for  your  aNen(on  

Manuel  Quesada  Mar,nez                    manuel.quesada@um.es  

This project has been funded by the Ministerio de Economía y Competitividad and by the FEDER program through grant TIN2014-53749-C2-2-R, and by the Fundación Séneca de la Región de Murcia through grant 15295/PI/10.

Manuel  Quesada  Mar,nez          14th  April  2016,  Newcastle            7/7