=Paper=
{{Paper
|id=Vol-2807/abstractZ
|storemode=property
|title=Expanding the eNanoMapper Ontology (short paper)
|pdfUrl=https://ceur-ws.org/Vol-2807/abstractZ.pdf
|volume=Vol-2807
|authors=Laurent A. Winckers,Egon L. Willighagen
|dblpUrl=https://dblp.org/rec/conf/icbo/WinckersW20
}}
==Expanding the eNanoMapper Ontology (short paper)==
https://ceur-ws.org/Vol-2807/abstractZ.pdf
Expanding the eNanoMapper Ontology
Laurent A. Winckersa and Egon L. Willighagena
a
Department of Bioinformatics – BiGCaT, NUTRIM School of Nutrition and
Translational Research in Metabolism, Maastricht University, Maastricht,
The Netherlands
Keywords. eNanoMapper, NanoCommons, EU NanoSafety Cluster, ontology,
nanomaterial, engineered nanomaterial, nanoinformatics
1. Introduction
The NanoSafety Cluster (NSC) is a cluster of projects funded by the European
Commission to assess the environmental health and safety of engineered nanomaterials
(NMs). Many (new) NMs are being developed for specific applications within multiple
fields such as healthcare/biomedical sciences and the industry. They are categorized
depending on their size, composition, shape and origin.
Matching the developmental rate of novel NMs with research and safety regulations is a
challenging task. Additionally, regulators have decided that the number of animals used
in research should be as low as possible. Whereas cytotoxicity testing from in vitro to in
vivo would take up too much time and resources, such as animals and money, to keep up
with the increasing prominence of NMs, the development and validation of in silico
toxicology and nanoinformatics are still at an early stage. To accelerate the transition to
in silico nanosafety, the NSC identified the need for an infrastructure for toxicological
data management and nanoinformatics, NanoCommons,
https://www.nanocommons.eu/nanocommons-knowedge-base/. An essential component
of nanoinformatics is an agreed ontology, and NanoCommons has continued to expand
and develop the eNanoMapper (ENM) ontology to aid toxicological data management
for NMs [1]. Ontological mapping facilitates the organisation, integration and reuse of
data which suits the premise of less usage of animals for research purposes.
Besides continuous collaboration with the NSC on the identification of missing terms
and additional existing ontologies to build upon, within NanoCommons we have
examined an approach to extend the current ontology with new properties. We used the
recently published ROBOT is an OBO Tool [2] to extend the ENM ontology with missing
annotation properties from, for example, the NanoParticle Ontology [3]. In addition, we
have used the OBO Dashboard to assess the quality and validate the ENM ontology to
assess the level of compliance with OBO Principles and best practises [3,4].
2. Methods
The latest release of the eNanoMapper ontology (ENM), version 4.0, was acquired via
Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
Zenodo, https://doi.org/10.5381/zenodo.260098.
The NanoParticle Ontology (NPO), https://bioportal.bioontology.org/ontologies/NPO,
was used to extract annotation properties which were not found in the ENM ontology.
ROBOT is an OBO Tool (ROBOT) was used as a command-line tool to work with the
ENM ontology. ROBOT was set up according to their instructions and was used in
Windows Command Prompt.
The OBO Dashboard, acquired from https://github.com/OBOFoundry/OBO-Dashboard,
was used to assess the quality and validate the ENM ontology.
3. Preliminary results
The ENM ontology could not directly be used in ROBOT as the OWL file uses
owl:imports of slimmed ontologies. This led to the recreation of the ENM ontology using
the MERGE command. The slimmed ontologies were merged and resulted in the
recreation of the eNanoMapper ontology as found on https://www.nanocommons.eu/.
Upon recreation of the ENM ontology, the resulting OWL file could be used for other
ROBOT commands. Additionally, we were able to extract annotation properties from
the NanoParticle Ontology such as npo:has_part, which were previously identified as
being absent from the ENM ontology, with the ROBOT’s EXTRACT command. We
were able to import these annotation properties into the ENM ontology. In addition, we
were able to use the OBO Dashboard to assess and validate the ENM ontology. The OBO
Dashboard prompted a report which assessed multiple aspects of the ontology and
provided errors if applicable. For example, missing ontology license and missing
definitions are common error messages.
4. Conclusion
A major improvement to the ENM ontology development is the extension with
annotation properties. ROBOT was found to be an easy-to-use and suitable tool to
achieve this. In addition, the OBO Dashboard was useful to assess and validate the ENM
ontology, which provides an improved workflow in which we will continue to develop
and maintain the eNanoMapper ontology as part of the NanoCommons research
infrastructure for nanosafety data management and nanoinformatics.
References
[1] Hastings J, Jeliazkova N, Owen G, Tsiliki G, Munteanu CR, Steinbeck C, Willighagen EL.
eNanoMapper: harnessing ontologies to enable data integration for nanomaterial risk assessment.
J Biomed Semantics. 2015;6:10. doi: 10.1186/s13326-015-0005-5
[2] Jackson, RC, Balhoff, JP, Douglass, E. et al. ROBOT: A Tool for Automating Ontology Workflows.
BMC Bioinformatics. 2019;20:407. doi: 10.1186/s12859-019-3002-3
[3] Thomas DG, Pappu RV, Baker NA. NanoParticle Ontology for Cancer Nanotechnology Research.
J Biomed Inform. 2011;44:1. doi: 10.1016/j.jbi.2010.03.001
[4] Smith B, et al. The OBO Foundry: coordinated evolution of ontologies to support biomedical data
integration. Nat Biotech 2007;25 doi: 10.1038/nbt1346.