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Evolution of Ontologies and Mappings

Ontologies are used in numerous research disciplines and commercial applications to uniformly and semantically annotate real-world objects. Due to a rapid development of application domains the corresponding ontologies are changed frequently to include up-to-date knowledge. These changes dramatically influence dependent data as well as applications/systems, for instance, ontology mappings, that semantically interrelate ontologies. The aim of the work includes the conceptual modelling and the implementation of a framework to systematically study the evolution and its consequences in different domains. Moreover, the robustness of existing match approaches will be analyzed w.r.t. ontology evolution. Based on this, match approaches will be newly designed or optimized.

Basic evolution framework for ontologies and mappings

Based on a generic framework suitable for analysis of evolution in instance data, ontologies, annotations and ontology mappings (see DILS 2008 paper), we study the evolution 16 currently developed Life Science Ontologies.

Detailed analysis results for 16 currently developed life science ontologies can be accessed here.

GOMMA System

Generic Ontology Matching and Mapping Management (GOMMA) - See GOMMA project site

GOMMA is our base framework for enhanced applications and analysis listed below.

Ontology Evolution

COntoDiff / CODEX

CODEX Logo
To effectively manage the evolution of ontologies it is essential to identify the difference (Diff) between ontology versions. Such a Diff supports the synchronization of changes in collaborative curation, the adaptation of dependent data such as annotations, and ontology version management. We propose a novel approach COnto-Diff to determine an expressive and invertible diff evolution mapping between given versions of an ontology. Our approach first matches the ontology versions and determines an initial evolution mapping consisting of basic change operations (insert/update/delete). To semantically enrich the evolution mapping we adopt a rule-based approach to transform the basic change operations into a smaller set of more complex change operations, such as merge, split, or changes of entire subgraphs.

For a start you can download a starting package which allows you to compute evolution mappings on your local computer: COntoDiff Start Package

The CODEX (Complex Ontology Diff Explorer) application allows for determining semantic (complex) changes between two versions of an ontology. The web application is based on COntoDiff which applies rules to iteratively compute the most compact (semantically richest) diff between two ontology versions.

CODEX is available under http://www.izbi.de/codex.

OnEX

OnEX Logo
We present OnEX (Ontology Evolution Explorer) to explore ontology changes and to understand their evolution more systematically. \onex is a web-based application that currently provides access up to 500 different versions of 16 well-known life science ontologies including Gene Ontology, NCI Thesaurus and selected OBO ontologies since 2002. The application shows evolution trends of these ontologies and make it possible to study the made changes in detail. More information about OnEX can be found here.
The system is available under http://www.izbi.de/onex.

Discovery of Evolving Ontology Regions

OnEX Logo
Ontologies are heavily used in life sciences and evolve continuously to incorporate new or changed insights. Often ontology changes affect only specific parts (regions) of ontologies making it valuable for ontology users and applications to know the heavily changed regions on the one hand and stable regions on the other hand. However, the size and complexity of life science ontologies renders manual approaches to localize changing or stable regions impossible. We therefore propose an approach to automatically discover evolving or stable ontology regions. We evaluate the approach by studying evolving regions in the Gene Ontology and the NCI Thesaurus. More information about the approach can be found in our DILS 2010 paper.

You can try out our prototype REx (Region Evolution Explorer) to discover (un)stable regions in popular life science ontologies.

Efficient versioning of large life science ontologies

Ontologies have become very popular in life sciences and other domains. They mostly undergo continuous changes and new ontology versions are frequently released. However, current analysis studies do not consider the ontology changes reflected in different versions but typically limit themselves to a specific ontology version which may quickly become obsolete. To allow applications easy access to different ontology versions we propose a central and uniform management of the versions of different biomedical ontologies. The proposed database approach takes concept and structural changes of succeeding ontology versions into account thereby supporting different kinds of change analysis. Furthermore, it is very space-efficient by avoiding redundant storage of ontology components which remain unchanged in different versions. We evaluate the storage requirements and query performance of the proposed approach for the Gene Ontology. More information

Mapping Stability

Annotation quality considering evolutionary changes

Ontology-based annotations associate objects, such as genes and proteins,with well-defined ontology concepts to semantically and uniformly describe object properties. Such annotation mappings are utilized in different applications and analysis studies whose results strongly depend on the quality of the used annotations. To study the quality of annotations we propose a generic evaluation approach considering the annotation generation methods (provenance) as well as the evolution of ontologies, object sources, and annotations. Thus, it facilitates the identification of reliable annotations, e.g., for use in analysis applications. We evaluate our approach for functional protein annotations in Ensembl and Swiss-Prot using the Gene Ontology. For more information see our DILS 2009 paper

Ontology mapping stability

Ontology matching has been widely studied. However, the resulting ontology mappings can be rather unstable when the participating ontologies or utilized secondary sources (e.g., instance sources, thesauri) evolve. We propose an evolution-based approach for assessing ontology mappings by annotating their correspondences by information about similarity values for past ontology versions. These annotations allow us to assess the stability of correspondences over time and they can thus be used to determine better and more robust ontology mappings. The approach is generic in that it can be applied independently from the utilized match technique. We define different stability measures and show results of a first evaluation for the life science domain. More information

Project Members

Funding

Evolution von Ontologien und Mappings - Grant RA 497/18-1

Publication(s):

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Christen, Victor; Groß, Anika; Fisher, Jeffrey; Wang, Qing; Christen, Peter; Rahm, Erhard
Temporal group linkage and evolution analysis for census data
Accepted for the 19th International Conference on Extending Database Technology (EDBT), Venice, 2017
2017-03
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publication iconDomingos Cardoso, Silvio; Reynaud-Delaître, Chantal; Da Silveira, Marcos; Lin, Ying-Chi; Groß, Anika; Rahm, Erhard; Pruski, Cédric
Towards a Multi-level Approach for the Maintenance of Semantic Annotations
Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017), HEALTHINF, Porto, Portugal, February 21-23, 2017
2017-02


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Domingos Cardoso, Silvio; Pruski, Cédric; Da Silveira, Marcos; Lin, Ying-Chi; Groß, Anika; Rahm, Erhard; Reynaud-Delaître, Chantal
Leveraging the Impact of Ontology Evolution on Semantic Annotations
Knowledge Engineering and Knowledge Management. Vol. 10024 of the series Lecture Notes in Computer Science, pp. 68-82, 2016
2016-11-04
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Christen, Victor; Groß, Anika; Rahm, Erhard
A Reuse-based Annotation Approach for Medical Documents
Proc. 15th International Semantic Web Conference (ISWC), Springer LNCS 9981, pp. 135-150 , 2016
2016-10
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Groß, A.; Pruski, C.; Rahm, E.
Evolution of Biomedical Ontologies and Mappings: Overview of Recent Approaches
Computational and Structural Biotechnology Journal. Vol. 14, 2016, pp. 333-340
2016-09
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Christen, Victor; Hartung, Michael; Groß, Anika
Region Evolution eXplorer - A tool for discovering evolution trends in ontology regions
Journal of Biomedical Semantics 2015, 6:26
2015-06
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Christen, Victor; Groß, Anika; Hartung, Michael
REX - a tool for discovering evolution trends in ontology regions
Proc. 10th Intl. Conference on Data Integration in the Life Sciences (DILS), Lisbon, July 2014
2014-07
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Groß, A.
Evolution von ontologiebasierten Mappings in den Lebenswissenschaften
Dissertation, Universität Leipzig
2014-03
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Groß, A.; Dos Reis, J.C.; Hartung, M.; Pruski, C.; Rahm, E.
Semi-Automatic Adaptation of Mappings between Life Science Ontologies
Proc. 9th Intl. Conference on Data Integration in the Life Sciences (DILS), Montreal, July 2013
2013-07
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Hartung, M.; Groß, A.; Rahm, E.
COnto-Diff : Generation of Complex Evolution Mappings for Life Science Ontologies
Journal of Biomedical Informatics 46 (1): 15-32
2013-02-01
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Groß, A.; Hartung, M.; Kirsten, T.; Rahm, E.
GOMMA Results for OAEI 2012
Seventh International Workshop on Ontology Matching @ ISWC 2012
2012-11
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Groß, A.; Hartung, M.; Thor, A.; Rahm, E.
How do computed ontology mappings evolve? - A case study for life science ontologies
Joint Workshop on Knowledge Evolution and Ontology Dynamics @ ISWC 2012
2012-11
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Groß, A.; Hartung, M.; Prüfer, K.; Kelso, J.; Rahm, E.
Impact of Ontology Evolution on Functional Analyses
Bioinformatics 28 (20): 2671-2677
2012-10-10
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Christen, Victor
REx – eine Webapplikation zur Visualisierung der Evolution von Ontologien in den Lebenswissenschaften
Studentenkonferenz Informatik Leipzig (SKIL) 2012
2012-09
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publication iconGroß, A.; Hartung, M.; Thor, A.; Rahm, E.
How do Ontology Mappings Change in the Life Sciences?
Selected Poster @ Intl. Conference on Data Integration in the Life Sciences (DILS)
2012-06
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publication iconHartung, M.; Groß, A.; Rahm, E.
Determining and Analyzing Semantic Ontology Changes with CODEX
Demo @ Intl. Conference on Data Integration in the Life Sciences (DILS)
2012-06
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Groß, A.; Hartung, M.; Thor, A.; Rahm, E.
How do Ontology Mappings Change in the Life Sciences?
CoRR abs/1204.2731
2012-04
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Hartung, M.; Groß, A.; Rahm, E.
CODEX: Exploration of semantic changes between ontology versions
Bioinformatics 28 (6): 895-896
2012-03
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Kirsten, T.; Groß, A.; Hartung, M.; Rahm, E.
GOMMA: A Component-based Infrastructure for managing and analyzing Life Science Ontologies and their Evolution
Journal of Biomedical Semantics 2011, 2:6
2011-11
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Groß, A.; Hartung, M.; Kirsten, T.; Rahm, E.
Mapping Composition for Matching Large Life Science Ontologies
2nd International Conference on Biomedical Ontology (ICBO 2011)
2011-07
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Hartung, M.
Evolution von Ontologien in den Lebenswissenschaften
Dissertation, Universität Leipzig
2011-05


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Kropp, H.
Berechnung von Diff-Evolution-Mappings zwischen geänderten Produktkatalogen
BTW Studierendenprogramm 2011
2011-03

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Bellahsene, Z.; Bonifati, A.; Rahm, E. (eds.)
Schema Matching and Mapping
Springer-Verlag, Data-Centric Systems and Applications
2011-02
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Hartung, M.; Terwilliger, J.; Rahm, E.
Recent advances in schema and ontology evolution
Schema Matching and Mapping, Springer-Verlag
2011-02
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Hartung, M.; Groß, A.; Rahm, E.
Rule-based Generation of Diff Evolution Mappings between Ontology Versions
CoRR abs/1010.0122
2010-10
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Groß, A.; Hartung, M.; Kirsten, T.; Rahm, E.
On Matching Large Life Science Ontologies in Parallel
7th International Conference on Data Integration in the Life Sciences (DILS 2010)
2010-08
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Hartung, M.; Groß, A.; Kirsten, T.; Rahm, E.
Discovering Evolving Regions in Life Science Ontologies
7th International Conference on Data Integration in the Life Sciences (DILS 2010)
2010-08
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Hartung, M; Loebe, F; Herre, H.; Rahm, E.
Management of Evolving Semantic Grid Metadata Within a Collaborative Platform
Information Sciences, Volume 180, Issue 10, 15 May 2010, Pages 1837-1849
2010-05
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Kirsten, T.; Hartung, M.; Groß, A.; Rahm, E.
Efficient Management of Biomedical Ontology Versions
LNCS 5872, pp.574-583, 4th Intl. Workshop on Ontology Content (Part of the OTM Conferences & Workshops)
2009-11
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Hartung, M.; Kirsten, T.; Groß, A.; Rahm, E.
OnEX: Exploring changes in life science ontologies
BMC Bioinformatics 2009, 10:250
2009-08
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Groß, A.; Hartung, M.; Kirsten, T.; Rahm, E.
Estimating the Quality of Ontology-based Annotations by Considering Evolutionary Changes
Proc. 6th Data Integration in the Life Sciences (DILS) Conf., Springer LNCS 5647, 2009
2009-07
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Hartung, M.; Kirsten, T.; Groß, A.; Rahm, E.
Exploring changes in life science ontologies with OnEX
Poster at 7th Leipzig Research Festival for Life Sciences 2008 and 6th Intl. Workshop on Data Integration in the Life Sciences (DILS) 2009
2009-07
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Thor, A.; Hartung, M.; Groß, A.; Kirsten, T.; Rahm, E.
An Evolution-based Approach for Assessing Ontology Mappings - A Case Study in the Life Sciences
Proc. of 13. GI-Fachtagung für Datenbanksysteme in Business, Technologie und Web (BTW), 2009
2009-03
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Groß, A.; Hartung, M.; Kirsten, T.; Rahm, E.
Evolution-based analysis of functional protein annotation
Poster at 7th Leipzig Research Festival for Life Sciences 2008
2008-12
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Hartung, M.; Kirsten, T.; Rahm, E.
Analyzing the Evolution of Life Science Ontologies and Mappings
Proc. of 5th Int. Workshop on Data Integration in the Life Sciences (DILS), Springer LNCS 5109, 2008
2008-06

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Hartung, M.
Management von Ontologien in den Lebenswissenschaften
Tagungsband zum 20. GI-Workshop über Grundlagen von Datenbanken (20th GI-Workshop on the Foundations of Databases), Apolda (Thüringen)
2008-05