Adding nanomaterial data to an eNanoMapper instance can be done in many different ways, as one would expect in a open platform. Data can be entered using the JRC spreadsheet formats, using R code and the eNanoMapper application programming interface (API), and, as done in this tutorial in the Resource Description Framework (RDF) format, using a schema based on various ontologies.
This tutorial expects some basic knowledge about RDF, particularly, the concept of IRIs and triples. The examples used will illustrate a lot, but does not replace reading up on RDF literature. If new to this, and if something in not clear when you go through the tutorial below, you consider reading RDF 1.1 Turtle - Terse RDF Triple Language.
Furthermore, because RDF is a semantic format, it will rely on the eNanoMapper ontology. At various places it will link to the EMBL-EBI Ontology Lookup Service (OLS) to show a term. Besides the OLS BioPortal can be used to browse the ontology too. The reader may be interested in the Browsing the eNanoMapper ontology with BioPortal, AberOWL and Protégé tutorial.
To shorten the RDF statements in this tutorial, it will depend on the use of namespace. The following
two documents are identical, using the @prefix
command to define the namespaces:
<https://nanocommons.github.io/tutorials/demo/owner/NT18-DS> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://rdfs.org/ns/void#Dataset> .
and
@prefix owner: <https://nanocommons.github.io/tutorials/demo/owner/> .
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix void: <http://rdfs.org/ns/void#> .
@prefix dcterms: <http://purl.org/dc/terms/> .
owner:NT18-DS rdf:type void:Dataset .
Because rdf:type
is frequently used, the Turtle standard allows it to be shortened to a mere a
, so that
the triple can be further shortened to (just the triple, so ommiting the namespace declarations):
owner:NT18-DS a void:Dataset .
Because using namespaces makes the RDF more readable, this tutorial uses the following namespaces:
@prefix bao: <http://www.bioassayontology.org/bao#> .
@prefix cito: <http://purl.org/net/cito/> .
@prefix dc: <http://purl.org/dc/elements/1.1/> .
@prefix dcterms: <http://purl.org/dc/terms/> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
@prefix npo: <http://purl.bioontology.org/ontology/npo#> .
@prefix obo: <http://purl.obolibrary.org/obo/> .
@prefix owner: <https://nanocommons.github.io/tutorials/demo/owner/> .
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix sio: <http://semanticscience.org/resource/> .
@prefix void: <http://rdfs.org/ns/void#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
The first thing to do is define a dataset. The eNanoMapper software will read this as a bundle
.
Each dataset has license statement, the name of the distributor (which is often different from the
copyright owner), a description (the @en
annotation indicated the language), and a title. For example:
owner:NT18-DS
a void:Dataset ;
dcterms:license <https://creativecommons.org/publicdomain/zero/1.0/> ;
dcterms:publisher "Egon Willighagen"@en ;
dcterms:description "Nanomaterials I am excited about."@en ;
dcterms:title "Exciting nanomaterials"@en .
Possible license IRIs include:
But at this moment, the dataset is still empty. We did not add nanomaterials to it.
The very minimal amount of information is that the nanomaterial is a chemical substance,
and for that we will use the chemical substance
term from the eNanoMapper ontology
(CHEBI_59999).
Furthermore, we will give the material a name and a ontology annotation, for which we also use the
eNanoMapper ontology (here, a
NPO_1542):
owner:NT18-S1
a obo:CHEBI_59999 ;
rdfs:label "zinc oxide" ;
dcterms:source owner:NT18-DS ;
dcterms:type npo:NPO_1542 .
This example is taken from a recent paper by the HINAMOX project (doi:10.3390/ijms19010246).
To figure out what type of nanomaterial you have, you can browse the eNanoMapper ontology (see the aforementioned tutorial). If you are using any of the OECD or JRC nanomaterials, you are lucky and can also use one of these two guidance documents:
The above information does not sounds like a lot yet, but can still be useful. Say you have some data collection online, with one web page for each material, and you want the eNanoMapper database to link to that. The above would be enough, except that we would need to add the link to that web page. That can be done with the FOAF ontology:
owner:NT18-S1 foaf:page <http://www.mdpi.com/1422-0067/19/1/246/htm>
For the running example, the page linked to is not specifically about that nanomaterial, but the page of the full article.
There is plenty of room at the bottom, and that applies to this story too. The above basically only covers the name of the compound, along with some metadata. Let’s describe next what we know about the chemical content of the material.
First, the full composition is modelled after the NPO ontology and each nanoparticle has parts, so
if we want to define a core part, we create a new resource for that, with out unique IRI, and link
that to the nanoparticle with npo:has_part
.
Let’s first define the core of that nanomaterial. For this we define a new resource, for the core, and type it as a core using a term from the NPO ontology NPO
owner:NT18-S1_core a npo:NPO_1597 ;
sio:CHEMINF_000200 owner:NT18-S1_core_smiles .
owner:NT18-S1_core_smiles
a sio:CHEMINF_000018 ;
rdfs:label "zinc oxide" ;
sio:SIO_000300 "ZnO" .
In the above example, we used the NPO_1597
term for fiat material part
.
We can further annotate the material part, by adding a triple to indicate the part is actually a core with NPO_1617:
owner:NT18-S1_core a npo:NPO_1617 .
Alternative ontology annotations for cores from the eNanoMapper ontology (inherited from the NanoPartical Ontology) include:
See the full hierarchy for more possible annotation.
A coating is added as fiat material part
too, and follows the same approach as the core.
We can also add physical-chemical properties to the data, further characterizing the nanomaterial. For both physical-chemical and biological properties, the data model is reused introduced in the PubChem RDF (see also doi:10.1186/s13321-015-0084-4) and using various ontologies:
has measure group
(BAO_0000209) a measure group
(BAO_0000040)participates in
(BFO_0000056) a measure group
has specified output
(OBI_0000299) a endpoint
(BAO_0000179)Here are two examples of physical chemical endpoints. In fact, we can use physical property endpoint
(BAO_0002128) instead of endpoint
of
which it is a subclass.
For example, for a particle size (NPO_1694), we get the following set up:
owner:NFYS16-M12
obo:BFO_0000056 owner:NFYS16-M12_sizemg .
owner:NFYS16-sizeAssay1
a npo:NPO_1694 , bao:BAO_0000015 ;
dc:title "Particle Size" ;
bao:BAO_0000209 owner:NFYS16-M12_sizemg .
owner:NFYS16-M12_sizemg a obo:BAO_0000040 ;
obo:OBI_0000299 owner:NFYS16-M12_size .
owner:NFYS16-M12_size a bao:BAO_0002128 ;
rdfs:label "primary particle size" ;
sio:has-unit "nm" ;
sio:has-value "13.6" .
Note: the above is ontologically not entirely correct, as NPO_1694 is not actually an assay type, but a quality.
A citation to the article which describes the physicochemical properties can be added to the endpoint, which would make the last block look like:
owner:NFYS16-M12_size a bao:BAO_0002128 ;
rdfs:label "primary particle size" ;
sio:has-unit "nm" ;
sio:has-value "13.6" ;
cito:usesDataFrom <https://doi.org/10.1021/es900754q> .
Similarly, for a zeta potential
owner:NFYS16-M12
obo:BFO_0000056 owner:NFYS16-M12_zpmg .
owner:NFYS16-sizeAssay2
a npo:NPO_1302 , bao:BAO_0000015 ;
dc:title "Zeta Potential" ;
bao:BAO_0000209 ex:NFYS16-M12_zpmg .
owner:NFYS16-M12_zpmg a obo:BAO_0000040 ;
obo:OBI_0000299 owner:NFYS16-M12_zp .
owner:NFYS16-M12_zp a bao:BAO_0002128 ;
rdfs:label "ZETA POTENTIAL" ;
obo:STATO_0000035 "-53.5 ± 10.6"^^xsd:string ;
sio:has-unit "mV" .
The above two examples indicated two different ways to provide the measured value of the end point. In both cases there was a single value, but one had an indication of the measurement error. The system supports currently the following patterns.
First, a single value:
owner:NFYS16-M12_zp a bao:BAO_0000179 ;
sio:has-value "13.6"^^xsd:double .
Secondly, a single value with error indication, using a predicate from the STATO:
owner:NFYS16-M12_zp a bao:BAO_0000179 ;
obo:STATO_0000035 "-53.5 ± 10.6"^^xsd:string .
The third option is to define a minimum and maximum:
owner:NFYS16-M12_zp a bao:BAO_0000179 ;
obo:STATO_0000035 "1-10"^^xsd:string ; .
A biological endpoints is modelled similarly to a physical-chemical endpoint. But currently, the ontological type of quality measured is given on the endpoint, not on the assay. For example,
owner:m134_noecMeasurementGroup533
a bao:BAO_0000040 ;
obo:OBI_0000299 owner:m134_noecMeasurementGroup533_noecEndpoint .
owner:m134_noecMeasurementGroup533_noecEndpoint
a enm:ENM_0000060 ;
rdfs:label "NOEC" ;
obo:IAO_0000136 etox:m134 ;
sio:has-unit "µg/L" ;
sio:has-value "15"^^xsd:double .
In this tutorial we will use a test server with the eNanoMapper server provided by IDEAConsult Ltd., where we can upload any test data: https://apps.ideaconsult.net/enmtest/.
The September 2018 version of the eNanoMapper database software contains a dedicated upload page for the here introduced Turtle:
With the “Choose File” button, you can select your newly created Turtle file, followed by clicking the Submit button.
The next page will show information of the running task, reflecting the reading of the data. If your Turtle validated (see the previous step), you should not get an error message. If all indeed loaded well, you will get a link to one of the materials loaded.
However, to see the full collection, we can better go to the Bundles page, which should list your new bundle too. If there are many bundles listed, you can search your bundle using the title you provided:
If you click the folder icon in the first column, in the row for your bundle, you will get a link to a list with all Substances. That way you can verify that all your materials were read in properly.
This tutorial was written as part of the NanoCommons project. NanoCommons (Grant Agreement 731032) is a project funded by the European Commission within Horizon2020 Programme