Ontology Alignment Evaluation Initiative - OAEI-2021 CampaignOAEI

Biodiversity and Ecology track (biodiv)

General description

The main aim of this track is to motivate and attract ontology matching systems to work on matching ontologies and thesauri used in the biodiversity and ecology domains. In the current edition, we decided to keep the matching task to find alignments between the Environment Ontology (ENVO) and the Semantic Web for Earth and Environment Technology Ontology (SWEET) as these two ontologies have frequent updates.

In 2020, we partnered with the AgroPortal project to include two new matching tasks involving important thesauri (originally developed in SKOS) in agronomy and environmental sciences: finding alignments between the AGROVOC thesaurus and US National Agricultural Library Thesaurus (NALT) and between the GEneral Multilingual Environmental Thesaurus (GEMET) and the Analysis and Experimentation on Ecosystems thesaurus (ANAEETHES).

We address this year the alignment of two new biological taxonomies with rather different but complementary scopes: the well-known, world-wide NCBI taxonomy, and TAXREF-LD [3], a more fined-grained, manually curated taxonomy that spans French metropolitan and overseas territories. A challenging aspect is the discrepancies between (1) the size and scope of both taxonomies, and (2) the RDF model to account for taxonomy and nomenclatural information.

The considered ontologies and thesauri are particularly useful for biodiversity and ecological research and are being used in various projects. They have been developed in parallel and are significantly overlapping. They are semantically rich and contain tens of thousands of classes. By providing semantic resources developed in SKOS, our objective is also to encourage the ontology alignment community to develop tools that can natively handle SKOS which is now the standard to encode vocabularies and terminologies and for which alignment is also a very important aspect.


The preliminary results have been generated and are available now (11.10.2021). Link to results page.


The biodiv dataset (2 ontologies, 6 thesauri and 4 reference alignments) can be downloaded here.

The evaluation of the track will be run with support of the MELT framework. This requires that you wrap your matching system in a way that allows us to execute it using MELT (see MELT evaluation for OAEI 2021).

Some mappings in the reference alignments have been extracted from the ontology and thesauri source files publicly available. We therefore ask the competitors to use only the source files provided in the dataset archive and ignore the original source files (available on AgroPortal or anywhere else) in the alignment process (including as background knowledge).


The schedule is available at the OAEI main page.

Former editions



[1] Naouel Karam, Abderrahmane Khiat, Alsayed Algergawy, Melanie Sattler, Claus Weiland, Marco Schmidt: Matching biodiversity and ecology ontologies: challenges and evaluation results. Knowledge Eng. Review 35: e9 (2020).

[2] Alsayed Algergawy, Naouel Karam, Friederike Klan, Clement Jonquet: Proceedings of the 2nd International Workshop on Semantics for Biodiversity co-located with 16th International Semantic Web Conference (ISWC 2017), Vienna, Austria, October 22nd, 2017. CEUR Workshop Proceedings 1933, CEUR-WS.org 2017

[3] F. Michel, O. Gargominy, S. Tercerie and C. Faron-Zucker: A Model to Represent Nomenclatural and Taxonomic Information as Linked Data. Application to the French Taxonomic Register, TAXREF. 2nd workshop on Semantics for Biodiversity (S4BioDiv), 2017.


We would like to thank Melanie Sattler (PANGAEA), who provided us with manual mappings between the ENVO and SWEET ontologies.

We would like to thank FAO AIMS and US NAL as well as the GACS project for providing mappings between AGROVOC and NALT.

We would like to thank Christian Pichot and the ANAEE France project for providing mappings between ANAEETHES and GEMET.

The track is supported in part by the AquaDiva, the NFDI4BioDiversity and the D2KAB projects.