Abteilung Datenbanken Leipzig (https://old.dbs.uni-leipzig.de)

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 [1]), we study the evolution 16 currently developed Life Science Ontologies.

Detailed analysis results for 16 currently developed life science ontologies can be accessed here [2].

GOMMA System

Generic Ontology Matching and Mapping Management (GOMMA) - See GOMMA project site [3]

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

Ontology Evolution

COntoDiff / CODEX

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. The source code of ContoDiff is available at GitHub [4]. 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.

OnEX

OnEX (Ontology Evolution Explorer) supports the exploration of ontology changes to better understand their evolution. \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 [5].

Rex - 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 and the Region Evolution Explorer (Rex) can be found here: - Region Evolution - DILS 2010 [6]. - REX - DILS 2014 [7] - REX - JBS 2015 [8]

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 [9]

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 [10]

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 [11]

Project Members

Funding

[16]

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

Publication(s):

PDF [17]

Google Scholar [18]
publication icon [19]Rost, C. [20]; Gomez, K. [21]; Christen, P. [22]; Rahm, E. [23]
Evolution of Degree Metrics in Large Temporal Graphs [24]
Conference on Database Systems for Business, Technology and Web (BTW) 2023
2023 [25]
PDF [26]

Google Scholar [27]
publication icon [28]Lin, Ying-Chi [29]; Hoffmann, Phillip [30]; Rahm, Erhard [31]
Enhancing Cross-lingual Semantic Annotations Using Deep Network Sentence Embeddings [32]
In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - Volume 5: HEALTHINF, pages 188-199. (Best Paper Award)
2021-02 [33]
PDF [34]

Google Scholar [35]
publication icon [36]Lin, Ying-Chi [37]; Christen, Victor [38]; Groß, Anika [39]; Kirsten, Toralf [40]; Domingos Cardoso, Silvio [41]; Pruski, Cédric [42]; Da Silveira, Marcos [43]; Rahm, Erhard [44]
Evaluating Cross-lingual Semantic Annotation for Medical Forms [45]
Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5 HEALTHINF: HEALTHINF, 145-155, 2020, Valletta, Malta. DOI: 10.5220/0008979901450155
2020-02 [46]
PDF [47]

Google Scholar [48]
[49]Christen, Victor [50]; Lin, Ying-Chi [51]; Groß, Anika [52]; Domingos Cardoso, Silvio [53]; Pruski, Cédric [54]; Da Silveira, Marcos [55]; Rahm, Erhard [56]
A learning-based approach to combine medical annotation results [57]
Data Integration in the Life Science (DILS) 2018
2018-11 [58]
PDF [59]

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[61]Lin, Ying-Chi [62]; Christen, Victor [63]; Groß, Anika [64]; Cardoso, Silvio Domingos [65]; Pruski, Cedric [66]; Da Silveira, Marcos [67]; Rahm, Erhard [68]
Evaluating and improving annotation tools for medical forms [69]
Proc. Data Integration in the Life Science (DILS) 2017
2017-11 [70]
PDF [71]

Google Scholar [72]
[73]Christen, Victor [74]; Groß, Anika [75]; Fisher, Jeffrey [76]; Wang, Qing [77]; Christen, Peter [78]; Rahm, Erhard [79]
Temporal group linkage and evolution analysis for census data [80]
Proc. 19th Int. Conf. on Extending Database Technology (EDBT), Venice, 2017
2017-03 [81]
PDF [82]

Google Scholar [83]
publication icon [84]Domingos Cardoso, Silvio [85]; Reynaud-Delaître, Chantal; Da Silveira, Marcos [86]; Lin, Ying-Chi [87]; Groß, Anika [88]; Rahm, Erhard [89]; Pruski, Cédric [90]
Towards a Multi-level Approach for the Maintenance of Semantic Annotations [91]
Proc. 10th Int. Joint Conf.on Biomedical Engineering Systems and Technologies (BIOSTEC 2017), HEALTHINF, Porto, Feb. 2017
2017-02 [92]
PDF [93]

Google Scholar [94]
[95]Domingos Cardoso, Silvio [96]; Pruski, Cédric [97]; Da Silveira, Marcos [98]; Lin, Ying-Chi [99]; Groß, Anika [100]; Rahm, Erhard [101]; Reynaud-Delaître, Chantal
Leveraging the Impact of Ontology Evolution on Semantic Annotations [102]
Knowledge Engineering and Knowledge Management. Proc. EKAW, Springer LNCS 10024 , pp. 68-82, 2016
2016-11 [103]-04
PDF [104]

Google Scholar [105]
[106]Christen, Victor [107]; Groß, Anika [108]; Rahm, Erhard [109]
A Reuse-based Annotation Approach for Medical Documents [110]
Proc. 15th International Semantic Web Conference (ISWC), Springer LNCS 9981, pp. 135-150 , 2016
2016-10 [111]
PDF [112]
further information [113]
Google Scholar [114]
[115]Groß, A. [116]; Pruski, C. [117]; Rahm, E. [118]
Evolution of Biomedical Ontologies and Mappings: Overview of Recent Approaches [119]
Computational and Structural Biotechnology Journal. Vol. 14, 2016, pp. 333-340
2016-09 [120]
PDF [121]
further information [122]
Google Scholar [123]
[124]Christen, Victor [125]; Hartung, Michael [126]; Groß, Anika [127]
Region Evolution eXplorer - A tool for discovering evolution trends in ontology regions [128]
Journal of Biomedical Semantics 2015, 6:26
2015-06 [129]
PDF [130]

Google Scholar [131]
[132]Christen, Victor [133]; Groß, Anika [134]; Hartung, Michael [135]
REX - a tool for discovering evolution trends in ontology regions [136]
Proc. 10th Intl. Conference on Data Integration in the Life Sciences (DILS), Lisbon, July 2014
2014-07 [137]
PDF [138]
further information [139]
Google Scholar [140]
[141]Groß, A. [142]
Evolution von ontologiebasierten Mappings in den Lebenswissenschaften [143]
Dissertation, Universität Leipzig
2014-03 [144]
PDF [145]

Google Scholar [146]
[147]Groß, A. [148]; Dos Reis, J.C. [149]; Hartung, M. [150]; Pruski, C. [151]; Rahm, E. [152]
Semi-Automatic Adaptation of Mappings between Life Science Ontologies [153]
Proc. 9th Intl. Conference on Data Integration in the Life Sciences (DILS), Montreal, July 2013
2013-07 [154]
PDF [155]
further information [156]
Google Scholar [157]
[158]Hartung, M. [159]; Groß, A. [160]; Rahm, E. [161]
COnto-Diff : Generation of Complex Evolution Mappings for Life Science Ontologies [162]
Journal of Biomedical Informatics 46 (1): 15-32
2013-02 [163]-01
PDF [164]

Google Scholar [165]
[166]Groß, A. [167]; Hartung, M. [168]; Kirsten, T. [169]; Rahm, E. [170]
GOMMA Results for OAEI 2012 [171]
Seventh International Workshop on Ontology Matching @ ISWC 2012
2012-11 [172]
PDF [173]

Google Scholar [174]
[175]Groß, A. [176]; Hartung, M. [177]; Thor, A. [178]; Rahm, E. [179]
How do computed ontology mappings evolve? - A case study for life science ontologies [180]
Joint Workshop on Knowledge Evolution and Ontology Dynamics @ ISWC 2012
2012-11 [181]
PDF [182]
further information [183]
Google Scholar [184]
[185]Groß, A. [186]; Hartung, M. [187]; Prüfer, K. [188]; Kelso, J. [189]; Rahm, E. [190]
Impact of Ontology Evolution on Functional Analyses [191]
Bioinformatics 28 (20): 2671-2677
2012-10 [192]-10
PDF [193]
further information [194]
Google Scholar [195]
[196]Christen, Victor [197]
REx – eine Webapplikation zur Visualisierung der Evolution von Ontologien in den Lebenswissenschaften [198]
Studentenkonferenz Informatik Leipzig (SKIL) 2012
2012-09 [199]
PDF [200]

Google Scholar [201]
publication icon [202]Groß, A. [203]; Hartung, M. [204]; Thor, A. [205]; Rahm, E. [206]
How do Ontology Mappings Change in the Life Sciences? [207]
Selected Poster @ Intl. Conference on Data Integration in the Life Sciences (DILS)
2012-06 [208]
PDF [209]

Google Scholar [210]
publication icon [211]Hartung, M. [212]; Groß, A. [213]; Rahm, E. [214]
Determining and Analyzing Semantic Ontology Changes with CODEX [215]
Demo @ Intl. Conference on Data Integration in the Life Sciences (DILS)
2012-06 [216]
PDF [217]
further information [218]
Google Scholar [219]
[220]Groß, A. [221]; Hartung, M. [222]; Thor, A. [223]; Rahm, E. [224]
How do Ontology Mappings Change in the Life Sciences? [225]
CoRR abs/1204.2731
2012-04 [226]
PDF [227]
further information [228]
Google Scholar [229]
[230]Hartung, M. [231]; Groß, A. [232]; Rahm, E. [233]
CODEX: Exploration of semantic changes between ontology versions [234]
Bioinformatics 28 (6): 895-896
2012-03 [235]
PDF [236]
further information [237]
Google Scholar [238]
[239]Kirsten, T. [240]; Groß, A. [241]; Hartung, M. [242]; Rahm, E. [243]
GOMMA: A Component-based Infrastructure for managing and analyzing Life Science Ontologies and their Evolution [244]
Journal of Biomedical Semantics 2011, 2:6
2011-11 [245]
PDF [246]
further information [247]
Google Scholar [248]
[249]Groß, A. [250]; Hartung, M. [251]; Kirsten, T. [252]; Rahm, E. [253]
Mapping Composition for Matching Large Life Science Ontologies [254]
2nd International Conference on Biomedical Ontology (ICBO 2011)
2011-07 [255]
PDF [256]
further information [257]
Google Scholar [258]
[259]Hartung, M. [260]
Evolution von Ontologien in den Lebenswissenschaften [261]
Dissertation, Universität Leipzig
2011-05 [262]


Google Scholar [263]
[264]Kropp, H. [265]
Berechnung von Diff-Evolution-Mappings zwischen geänderten Produktkatalogen [266]
BTW Studierendenprogramm 2011
2011-03 [267]

further information [268]
Google Scholar [269]
[270]Bellahsene, Z. [271]; Bonifati, A. [272]; Rahm, E. (eds.) [273]
Schema Matching and Mapping [274]
Springer-Verlag, Data-Centric Systems and Applications
2011-02 [275]
PDF [276]

Google Scholar [277]
[278]Hartung, M. [279]; Terwilliger, J. [280]; Rahm, E. [281]
Recent advances in schema and ontology evolution [282]
Schema Matching and Mapping, Springer-Verlag
2011-02 [283]
PDF [284]
further information [285]
Google Scholar [286]
[287]Hartung, M. [288]; Groß, A. [289]; Rahm, E. [290]
Rule-based Generation of Diff Evolution Mappings between Ontology Versions [291]
CoRR abs/1010.0122
2010-10 [292]
PDF [293]

Google Scholar [294]
[295]Groß, A. [296]; Hartung, M. [297]; Kirsten, T. [298]; Rahm, E. [299]
On Matching Large Life Science Ontologies in Parallel [300]
7th International Conference on Data Integration in the Life Sciences (DILS 2010)
2010-08 [301]
PDF [302]

Google Scholar [303]
[304]Hartung, M. [305]; Groß, A. [306]; Kirsten, T. [307]; Rahm, E. [308]
Discovering Evolving Regions in Life Science Ontologies [309]
7th International Conference on Data Integration in the Life Sciences (DILS 2010)
2010-08 [310]
PDF [311]
further information [312]
Google Scholar [313]
[314]Hartung, M [315]; Loebe, F [316]; Herre, H. [317]; Rahm, E. [318]
Management of Evolving Semantic Grid Metadata Within a Collaborative Platform [319]
Information Sciences, Volume 180, Issue 10, 15 May 2010, Pages 1837-1849
2010-05 [320]
PDF [321]
further information [322]
Google Scholar [323]
[324]Kirsten, T. [325]; Hartung, M. [326]; Groß, A. [327]; Rahm, E. [328]
Efficient Management of Biomedical Ontology Versions [329]
LNCS 5872, pp.574-583, 4th Intl. Workshop on Ontology Content (Part of the OTM Conferences & Workshops)
2009-11 [330]
PDF [331]
further information [332]
Google Scholar [333]
[334]Hartung, M. [335]; Kirsten, T. [336]; Groß, A. [337]; Rahm, E. [338]
OnEX: Exploring changes in life science ontologies [339]
BMC Bioinformatics 2009, 10:250
2009-08 [340]
PDF [341]
further information [342]
Google Scholar [343]
[344]Groß, A. [345]; Hartung, M. [346]; Kirsten, T. [347]; Rahm, E. [348]
Estimating the Quality of Ontology-based Annotations by Considering Evolutionary Changes [349]
Proc. 6th Data Integration in the Life Sciences (DILS) Conf., Springer LNCS 5647, 2009
2009-07 [350]
PDF [351]

Google Scholar [352]
[353]Hartung, M. [354]; Kirsten, T. [355]; Groß, A. [356]; Rahm, E. [357]
Exploring changes in life science ontologies with OnEX [358]
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 [359]
PDF [360]

Google Scholar [361]
[362]Thor, A. [363]; Hartung, M. [364]; Groß, A. [365]; Kirsten, T. [366]; Rahm, E. [367]
An Evolution-based Approach for Assessing Ontology Mappings - A Case Study in the Life Sciences [368]
Proc. of 13. GI-Fachtagung für Datenbanksysteme in Business, Technologie und Web (BTW), 2009
2009-03 [369]
PDF [370]

Google Scholar [371]
[372]Groß, A. [373]; Hartung, M. [374]; Kirsten, T. [375]; Rahm, E. [376]
Evolution-based analysis of functional protein annotation [377]
Poster at 7th Leipzig Research Festival for Life Sciences 2008
2008-12 [378]
PDF [379]
further information [380]
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[382]Hartung, M. [383]; Kirsten, T. [384]; Rahm, E. [385]
Analyzing the Evolution of Life Science Ontologies and Mappings [386]
Proc. of 5th Int. Workshop on Data Integration in the Life Sciences (DILS), Springer LNCS 5109, 2008
2008-06 [387]

further information [388]
Google Scholar [389]
[390]Hartung, M. [391]
Management von Ontologien in den Lebenswissenschaften [392]
Tagungsband zum 20. GI-Workshop über Grundlagen von Datenbanken (20th GI-Workshop on the Foundations of Databases), Apolda (Thüringen)
2008-05 [393]

URL:
https://old.dbs.uni-leipzig.de/de/research/projects/evolution_of_ontologies_and_mappings