=Paper=
{{Paper
|id=Vol-1747/D104_ICBO2016
|storemode=property
|title=Updates to the AberOWL Ontology Repository
|pdfUrl=https://ceur-ws.org/Vol-1747/D104_ICBO2016.pdf
|volume=Vol-1747
|authors=Miguel Ángel Rodríguez-García,Luke Slater,Imane Boudellioua,Paul Schofield,Georgios Gkoutos,Robert Hoehndorf
|dblpUrl=https://dblp.org/rec/conf/icbo/Rodriguez-Garcia16
}}
==Updates to the AberOWL Ontology Repository ==
https://ceur-ws.org/Vol-1747/D104_ICBO2016.pdf
Updates to the AberOWL ontology repository
Miguel Ángel Rodrı́guez-Garcı́a 1∗, Luke T Slater 2 , Imene Boudellioua 1 , Paul N
Schofield 2 , Georgios V Gkoutos 3 , Robert Hoehndorf 1
1
Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal
23955-6900, KSA
2
College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational
Biology, University of Birmingham, B15 2TT, United Kingdom
3
University of Cambridge, Downing Street, CB2 3EG, England, UK
ABSTRACT and query these ontologies (i.e., AberOWL is used as a “Reasoning
A large number of ontologies have been developed in the as a Service” provider).
biological and biomedical domains, which are mostly expressed
in the Web Ontology Language (OWL). These ontologies form a 1.2 Manual curation of ontologies:
logical foundation for our knowledge in these domains, and they are We have also manually curated the ontologies in AberOWL,
in widespread use to annotate biomedical and biological datasets. assigning a set of ‘topics’ to them and allowing users to
The use of the semantics provided by ontologies requires the use browse the ontologies through these means. The set of topics
of automated reasoning – inferring new knowledge by evaluating were extracted from the ontology EMBRACE Data and Methods
the asserted axioms. AberOWL is an ontology repository which (EDAM) [4] which is essentially a taxonomy of well established
utilises an OWL 2 EL reasoner to provide semantic access to terms with synonyms and definitions related primarily within
classified ontologies. Since our original presentation of the AberOWL bioinformatics. The annotations covered 177 different EDAM topics
framework, we have developed several additional tools and features spanning all EDAM top-level topics such as: Medicine, Biology,
which enrich its ability to integrate and explore data, make use of Data management, Laboratory techniques, Computer science,
the semantic and inferred content of ontologies. Here we present Chemistry, Mathematics, Physics, Ontology and terminology
an overview of AberOWL and the enhancements and new features and Literature and reference. For instance, the Amphibian
which have been developed since its conception. AberOWL is freely Gross Anatomy Ontology (AAO) was classified with the topics
available at http://aber-owl.net. eukaryotes, anatomy, and amphibians, and the Ascomycete
Phenotype Ontology (APO) was annotated with fungi, phenomics
and ascomycetes. The figure 1 shows a list of annotated ontologies
1 INTRODUCTION in AberOWL.
In recent years, several biological and biomedical ontology
repositories have been developed, such as BioPortal [5], Ontobee [7] 1.3 Ontology Browsing and Visualisation:
and the Ontology Lookup Service [2]. These provide web services We have improved the tools available for browsing and exploring
and front-end interfaces for users to query and explore the content ontologies. The class view in the ontology browser now shows the
of ontologies. AberOWL [3] is an ontology repository which utilises definition of the class in Manchester OWL Syntax. Additionally,
automated reasoning to allow users to access the semantic content the visualization module has been completely redesigned and we
of the ontologies. AberOWL provides both a web-based interface plan to further integrate a new library called Dagre [6], which
for the exploration and browsing of ontologies and a set of REST provides another way of representing ontologies by graphs instead
services which make the core functionality of AberOWL available of trees. Thus, while the current visualization module represents
using the JSON standard [1]. cycles as a repeated subtree, the new module can easily include
cycles without any repeated structure. Moreover, we plan to improve
1.1 Updates to AberOWL the performance of this module by transforming the ontologies into
Ontology Acquisition, Curation and Statistics: When AberOWL RDF graphs which will contain the inferred model of each ontology.
was originally presented in 2013, it contained 328 loadable Thus, we will be able to significantly reduce the delay involved in
ontologies. Since then, our repository has grown to a total of 522 subclass computation.
ontologies. The amount of ontologies in AberOWL has increased
due to the growing number of ontologies in the biological and REFERENCES
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