Tools have already been developed that allow an OWL file to be generated from a table as input that contains the necessary information to build an ontology. However, conversion using these tools is time-consuming if the terms in the input file must be assigned to an existing IRI in an external ontology (rather than being assigned a new IRI) and manually assigned new IRIs. We developed OWLmaker to generate an RDF/XML format OWL file from tabular text, with the option of automating IRI assignment with reference to an existing ontology.
Part of our standard procedure for the EuPathDB project
[http://eupathdb.org/] is to create an RDF/XML format OWL file
for each study whose results we intend to incorporate, from a
spreadsheet of variables with extensive annotations used by data
providers. An OWL file may be built and edited one term at a time
using ontology development tools such as Stanford University’s
Protégé [
Even with these tools available, the overall process required in the conversion of tabular text to OWL can still be complex and timeconsuming to learn. A tool that provides similar functionality while also automating more of the conversion process would be preferable for the EuPathDB project. One such automating feature would be the ability to assign an existing IRI in a specified external ontology to a matching term in the input file based on the term’s label. The aforementioned tools also are more focused on axiom creation than annotation creation, even though the development of many ontologies, such as the EuPathDB ontology, involves generation of new terms with associated annotations (e.g. definition, definition source, term editor, etc.) OWLmaker was created to address this need and is available at [https://github.com/EuPath-ontology/OWLmaker].
OWLmaker is a JAR file that works with a tab-delimited setting file to convert the input table to RDF/XML format OWL. Before the user executes the application, adjustments may need to be made to both the input file and the setting file. The input file can be in either tab-delimited or csv format and should, for each term, have a row identifying the term’s label, parent IRI, and parent label to ensure the hierarchy is complete in the output OWL file. (The term IRI can be manually entered also, if required.) To attribute annotation properties to terms in the output file, the user first provides a column of values for each property that has the name of the property as the column header. Optional annotation values for each term also must be identified in its row to be added to the OWL file.
The setting file is arranged in tab-delimited format with two columns such that the left column names parameters used by the application and the right column contains the parameters’ values.
The values can be adjusted by the user and include the names of the input and output files, the ontology IRI, and the IRI prefix for new terms. The user also provides the number of the column for the term’s IRI, label, parent label, and parent IRI, as well as the name and IRI of each annotation property.
The setting, input, and output files of a simple example, shown in Figures 1-3, is available from the “test” directory in the project’s GitHub repository [https://github.com/EuPathontology/OWLmaker/tree/master/test]. Here a small OWL file based on the EuPath ontology is used as the external ontology. A URI for the external ontology is provided in this example, but a filename with file path can also be used. An input file and setting file are also provided so that, when OWLmaker is run, big_ontology.owl is created.
Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). IRI Label parentLabel parentIRI adecfainteitgioonrical measurement pqArPneCcsyRelonscteoomfatoidea by cmaeteagsourriecmalent datum hotrtgp/:o/b/po/uOrl.BoIb_o0l0ib0r0a9r3y.8 radbAeyancatcaaucyttmlreioeogsantotlhorataimisctmasasaleptymoepicedoiaelfyisaemuswreewarmashseedetnehtcteheractined EuPathDB
datum that specifies whether dprueosdeenncaeleofbyAnqcPyCloRstoma cmaeteagsourriecmalent datum hotrtgp/:o/b/po/uOrl.BoIb_o0l0ib0r0a9r3y.8 adpAeoncltcayeytmcleotgeesrotdaorisbmceyaalcahdmraueeioanadlsreteuinmraaecelmteioewnnatasssay EuPathDB
datum that specifies whether lpurmesberniccoeidoefsAbscyaqrPisCR cmaeteagsourriecmalent datum hotrtgp/:o/b/po/uOrl.BoIb_o0l0ib0r0a9r3y.8 apdAeoscltcayeatmcreitsgeerodlaurisbmceyablcarhmircaeoeianiadlsreteuismraewcemtaioesnntassay EuPathDB
datum that specifies whether /hottbpo:///EpUuPrAl.ToHbo_l0ib0r1a0r6y1.o1rg EprLeISsAence of Astrovirus by cmaeteagsourriecmalent datum hotrtgp/:o/b/po/uOrl.BoIb_o0l0ib0r0a9r3y.8 aaeAsnscstzarayotymevgiero-ulrsiincwkaeladmsidemeatmseuucrteneomdseobnrybtaennt EuPathDB
datum that specifies whether cpbmaryeetResagTes-nuoPrrciCeecRmaolfenAtstdraotvuirmus Y cmmaeeteaagssouurrrieecmmaleenntt ddaattuumm hotrtgp/:o/b/po/uOrl.BoIb_o0l0ib0r0a9r3y.8 rcAehsvaterinorsvreieruatrscatwniosancsraidpsetsitaoeynctpeodlybmyearase EuPathDB measurement datum data item iednanfttoiatrymiteamtion content icgenoenfntnoitetriymrniucaaatnlilotyndceopnetnednetnt ccgeooennntnittetiiynnriuucaaannlltty dependent ceonntittiynuant definition source The application has been shown to reliably output the desired OWL file from correctly populated input and setting files. The output file in Protégé displays the complete hierarchy correctly, and all annotations are properly attributed. OWLmaker fulfills its focus, which is the creation of annotated classes, rather than annotated individuals or properties.
Since tools are available to merge two OWL files into one, the output of OWLmaker can be used to add new terms into an existing ontology. Since a SPARQL query can generate a conversion file from an OWL file, having OWLMaker and software supporting SPARQL also allows an ontologist to keep an ontology in both tabular and OWL formats and convert between them easily. This way, an ontologist can submit an ontology as a CSV file to collaborators who can then easily populate a column with values to attribute a new annotation property to terms. The modified CSV can then be converted back to OWL with the new annotation values included.
Future work may include removing unnecessary warnings generated upon execution of the application. Generation of IDs could be improved as well: we could remove the seven-digit restriction of IDs and prevent the application from generating a new ID that was already assigned to a term in the external ontology. Future work could also allow the application to not only work with tab-delimited or comma-separated files as input, but also proprietary formats such as Excel files or Google Sheets.
OWLmaker does not need to be installed (although it requires Java) and requires access to only the websites specified in the setting file. Because a user of OWLmaker has both the options of having the application search an external ontology for IRIs for matching term labels and also having the application generate new IRIs as specified, a complete OWL file for an ontology can be generated in fewer steps compared to similar tools. For these reasons, we conclude that OWLmaker usefully supplements existing similiar tools to convert tabular text to OWL.
We thank Mark A. Miller for testing the software and providing valuable feedback. This work was supported by NIH HHSN272201400030C.
Jie Zheng, jiezheng@pennmedicine.upenn.edu 3. Xiang Z, Zheng J, Lin Y, He Y. Ontorat: automatic generation of new ontology terms, annotations, and axioms based on ontology design patterns: J Biomed Sem; 2015. 4. Tauber R, Balhoff JP, Douglass E, Mungall CJ, Overton JA. Standardizing Ontology Workflows Using ROBOT. CEUR Workshop Proc. 2018;2285.