=Paper=
{{Paper
|id=Vol-3262/paper6
|storemode=property
|title=Analysing and promoting ontology interoperability in Wikibase
|pdfUrl=https://ceur-ws.org/Vol-3262/paper6.pdf
|volume=Vol-3262
|authors=Daniil Dobriy,Axel Polleres
|dblpUrl=https://dblp.org/rec/conf/semweb/DobriyP22
}}
==Analysing and promoting ontology interoperability in Wikibase==
https://ceur-ws.org/Vol-3262/paper6.pdf
Analysing and promoting ontology interoperability in
Wikibase
Daniil Dobriy, Axel Polleres
Vienna University of Economics and Business, Vienna, AT
Abstract
Wikibase, the open-source software behind Wikidata, increasingly gains popularity among third-party
Linked Data publishers. However, the platform’s unique data model decreases the degree of inter-
operability with existing Semantic Web standards and tools that underlie Linked Data as codified by
Linked Data principles. In particular, this unique data model of Wikibase also undermines the direct
reuse of ontologies and vocabularies, in a manner compliant with Semantic Web standards and Linked
Data principles. To this end, firstly, we compare the Wikibase data model to the established RDF data
model. Secondly, we enumerate a series of challenges for importing existing ontologies into Wikibase.
Thirdly, we present practical solutions to these challenges and introduce a tool for importing and re-using
ontologies within Wikibase. Thus, the paper aims to promote ontology interoperability in Wikibase and
by doing so hopes to contribute to higher degree of inter-linkage of Wikibase instances with Linked
Open Data.
1. Introduction
Many openly published datasets that conform to the Linked Data principles are collected in
the manually curated LOD Cloud (Linked Open Data Cloud) [1]. However, studies analysing
Linked Data have shown that in reality Linked Data datasets have significant availability issues
[2]. Furthermore, in previous studies we found that links between datasets in the LOD Cloud
are very sparse on the level of individuals and although ontology reuse was common, many
links on the level of ontologies were broken [3, 4]. In particular, in our previous work we have
also shown that ontology links are very sparse in Wikidata [5].
Herein, we would like to argue that the differences between Wikidata’s (and fundamentally
Wikibase’s) data model and plain RDF are a major factor in this mismatch and non-reuse
of vocabularies and ontologies: although Wikibase (WB), the open-source software behind
Wikidata, is intended to and is increasingly used by third parties to manage more specialized
Knowledge Graphs outside of scope of Wikidata (WD), it lacks built-in functionality to import
RDF vocabularies1 which makes ontology re-use nontrivial. Generally, the standardized nature
of RDF, the ability to conveniently join RDF datasets and the usage of URIs as global identifiers
for both properties and classes promote ontology re-use in Linked Data. However, the WB
data model is unique and quite distinct from plain RDF in a number of ways (discussed in
Section 2) and can merely be mapped to RDF for the purpose of querying the data of an instance
Wikidata’22: Wikidata workshop at ISWC 2022
Envelope-Open daniil.dobriy@wu.ac.at (D. Dobriy); axel.polleres@wu.ac.at (A. Polleres)
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CEUR
Workshop
Proceedings CEUR Workshop Proceedings (CEUR-WS.org)
http://ceur-ws.org
ISSN 1613-0073
1
further referred to as ontologies
Figure 1: An exemplary fragment of the FOAF ontology.
with SPARQL or publishing it as an RDF dump. With the aim of appropriately representing
ontologies in Wikibase and therefore allowing their reuse through facilitating their import,
management and export in Wikibase, this paper poses the following research questions:
R1 Which features distinguish the WB and plain RDF data models?
R2 How can RDF ontologies be represented in the WB data model?
R3 How can ontologies be imported, managed and exported in WB?
The next three sections sequentially discuss each of the posed research questions and the
final two sections discuss related works and draw conclusions. A fragment of the FOAF
ontology2 is used to exemplify the approach presented in the paper. Figure 1 illustrates the
mentioned fragment that includes a definition of the class foaf:Person and of two properties:
the foaf:topic_interest (of type owl:ObjectProperty ) and the foaf:myersBriggs (of type
owl:DatatypeProperty ).
2. Data model comparison
The RDF data model [6] describes factual knowledge through subject-predicate-object Triples.
IRIs or Blank Nodes take the position of subjects representing described things and concepts,
IRIs take the predicate position representing relations, whereas objects can be IRIs, Blank Nodes,
or (Typed) Literals.
2
see https://xmlns.com/foaf/spec/|
The current realization of WB’s data model is documented in [7]. ”Technical Support” is one
of the design goals of the data model and posits that the WB data model should allow adequate
representation of data in existing data formats like RDF/OWL. The basic structure to describe
factual knowledge in Wikibase is, similarly to RDF, by subject-predicate-object statements
or Snaks. These statements may have additional qualifying property-value pairs that further
describe the underlying Snak (Qualifiers), a ReferenceList that indicates sources for the overall
content of the structure and a Rank for various presentation and administration purposes.
Items, Properties or Datatypes, jointly referred to as Entities, take the position of subjects in a
Snak, Properties take the position of predicates and Entities as well as DataValues take up the
position of objects. Entities are identified by IRIs which most notably follow the IRI schemas
https://www.wikidata.org/entity/Qnnn and https://www.wikidata.org/entity/Pnnn
for Items and Properties, resp. Datatypes and their IRIs are pre-defined by the Wikibase
software. Each Property has an allowed Datatype, and although data model does not require
strict typing for Properties, the Wikibase UI and API nevertheless only permit this required
Datatype in the object position. Basic lexical information about Items, Properties and Datatypes
as their Labels, Descriptions and Aliases is treated specially by the data model and defined as
EntityDescriptions rather than as DataValues objects of Snaks.
Indeed, the two data models have key similarities. Snaks representing factual data resemble
plain Triples in RDF, things, concepts and possible relation types are uniquely identified by IRIs,
DataValues used in object position of Snaks resemble Typed Literals in object position of plain
RDF Triples.
However, the WB data model also shows key restrictions that do not allow direct translation
of data from plain RDF data model into the WB data model:
• Wheres WB only allows Entities identified by IRIs to be subjects, RDF also permits Blank
Nodes which stand as placeholders for things and concepts: WB does not have Blank
Nodes.
• WB makes an additional distinction between Items and Properties (and Datatypes) identi-
fied by IRIs and prohibits Items to be used in predicate position whereas RDF allows any
IRI to be reused in any Triple position.
• The UI and API of WB imposes a de-facto strict typing of Properties on data entry which
in contrast with RDF requires the definition of Property Datatypes and objects used in
Snaks with there Properties to be of the expected Datatype.
3. Ontology Representation Requirements
When considering importing existing RDF ontologies in WB we define the following require-
ments:
• imported classes (e.g. foaf:Person ) and properties (e.g. foaf:topic_interest ) should
be usable inside WB as Items and Properties;
• the imported ontology should be editable in WB with minimal restrictions;
• roundtripping: an (edited) ontology from WB should be exportable in the same form as it
was imported;
In order to achieve the roundtripping requierement, we need to define a meta-ontology
within WD to identify Snaks related to imported/edited ontologies and distinguish them
from ”regular” Snaks in order to be able to export ontologies or include new items into them.
Such a meta-ontology is defined in RDF and then represented in WD according to the rep-
resentation rules applicable to any ontology and discussed in the next section. The meta-
ontology is accessible at and defines its classes and properties in the following namespace:
https://data.wu.ac.at/ns/o2wb# .
Therefore, an ontology representation must sufficiently represent the features of the RDF
data model not to lose any information necessary for ontology export but must ideally not
introduce any excessive modeling components that could be ambiguously translated back on
ontology export. Every RDF ontology is fully represented by the set of its Triples (all vertices in
Figure 1). Since both data models rely on s-p-o representation of factual statements and factual
statements are represented in Snaks in WB, our approach is based on faithful recreation of
every ontology Triple as a Snak in WD.
IRIs in the subject position of a Triple are represented as Items or Properties. Since the RDF
data model does not impose restrictions as Item/Property distinction and strict typing, the
faithful representation of IRIs would allow them to be used in any capacity in accordance to the
second requirement of allowing ontology management with minimal restrictions. In order to
allow the same ”freedom” within WB, any given RDF IRI has to be defined both as an Item and
as (multiple) Properties (spanning every possible WB Datatype). Although the representation
of an IRI as multiple Properties spanning every Datatype in WB would effectively already be
sufficient for it to be used in any statement position (subject, predicate, object as it is possible
in the RDF data model) thus rendering representation of an IRI as an Item unnecessary, the
over-use of Properties in subject position of Snaks might lead to confusion as Items would
normally be expected in this position and therefore we choose to also represent IRIs as Items.
The foaf:Person IRI would be represented as a Item with a distinct Q-ID and a multiple of
Properties with different P-IDs and Datatypes (e.g. String, Monolingual Text, Item etc.3 )
It is important to note that the Datatypes used in WB do not directly or approximately
correspond to (e.g. XSD) datatypes commonly used in Typed Literals, since they represent
more complex data structures (e.g. geographical shapes or coordinates). Literals in plain RDF
consist of a Unicode string, datatype IRI and (only if the datatype IRI is rdf:langString ) a
non-empty language tag [8]. We propose mapping RDF Literals occurring in Triples to WB data
model by representing their Turtle serialization [9] as String Datatype of WB. Although this
approach simplifies the variety of possible mappings of various datatype IRIs to WB Datatypes,
it proposes a unified procedure that guarantees full freedom to modify Literal values represented
in WB data model as they could be modified in the RDF data model. Further work may focus
on establishing a more fine-grained mapping approach.
Next, Blank Nodes do not exist in the data model of WB and therefore have to be represented
as skolemized IRIs with the same representation in WB as previously discussed IRIs. They are
not representing any original IRIs (are therefore not used with o2wb:representsIRI relation) and
for clarity are instances of class o2wb:BlankNode.
Finally, since the original IRIs (and skolemized Blank Node IRIs) are replaced by different Item
3
for all WB Datatypes see: https://www.wikidata.org/wiki/Help:Data_type|
and Property Q-ID and P-ID IRIs within WB, in order to maintain ontological interoperability,
equivalence to the original IRIs has to be established again for every representation of an IRI
in WB. The meta-ontology therefore defines the o2wb:representsIRI property that is used
to relate the IRI representations in WB to the original IRIs. In the data model of WB a Snak
is created relating the Entity representing the IRI through the o2wb:representsIRI Property
with Datatype String to the String representing the original IRI.
Additional meta-ontological concepts that have to be defined are the o2wb:Ontology class
whose representation in WB is used to indicate that a specified Item represents an imported
ontology and o2wb:memberOfAnOntology represented as Property with Datatype Item and used
in a qualifier to indicate that a given Snak is a representation of a Triple from a given ontology.
For each ontology import, an ontology individual of class o2wb:Ontology has to be established
and represented in WD for all the related Snaks to be set in o2wb:memberOfAnOntology relation
with it.
Finally, Triples are represented as Snaks. IRIs or Blank Nodes in subject position of a Triple
are represented as the corresponding equivalent WB (o2wb:representsIRI ) Items in subject
position of a Snak. IRIs in predicate position of a Triple are represented as Properties with
either Datatype Item or String in predicate position of a Snak depending on whether the object
of a Triple is either an IRI/Blank Node, or a Literal. IRIs or Blank Nodes in object position of a
Triple are represented as Items and Literals are represented as DataValues with Datatype String
in the object position of a Snak.
Practically, the triple foaf:Person rdfs:subClassOf foaf:Agent . would be translated
into a Snak that has the Item representing foaf:Person in its subject position, the Property with
Datatype Item representing rdfs:subClassOf in predicate position and the Item representing
foaf:Agent in object position. The triple foaf:myersBriggs vs:term_status "testing" .
would be translated into a Snak that has the Item representing foaf:myersBriggs , the Property
with Datatype String representing vs:term_status and a String ”testing” for the Literal.
4. Ontology import, management, export
We propose o2wb, a novel tool that enables ontology import into WB by consequently im-
plementing the approach described in the previous sections. For each ontology to be im-
ported, o2wb creates an Item in WB representing the ontology and iterates over each Triple
of an ontology creating, if they do not exist yet, appropriate representations of encountered
IRIs, Blank Nodes and Literals, instantiating Snaks that correspond to the Triples using the
newly created representations with correct Datatypes and including qualifiers to indicate that
the Snaks belongs to the imported ontology. The tool is available under the following link:
https://git.ai.wu.ac.at/dobriy/o2wb .
Importing ontologies with the help of this approach ensures that the ontology can be effec-
tively edited though the WB UI and extracted back. The edit history is then preserved as page
edit logs for respective Entities. However, representing IRIs and Blank Nodes through multiple
Entities in the WB data model creates a challenge for exporting when a given representation
is changed through WB UI. There is a number of solutions to this obstacle: changes can be
implemented to all equivalent representations through bots whenever there is a change to one,
user could be asked to indicate the changes that should be exported back or users could be
notified of the inconsistency and asked to consequently solve it. This considerations are subject
of future work which includes enhancing the tool to be able to export ontologies back.
5. Related works
Although some work has described importing various data into a Wikibase instance [10]
[11] [12] , we are unaware of any work specifically targeting ontology import in order to
systematically increase ontology interoperability in the Wikibase ecosystem. Similar tools
have been developed [13] for Semantic MediaWiki. However, the design choices are strongly
dependent on the underlying data model of the system and we are unaware of any work
discussing the differences and translation of WB data model and RDF.
6. Conclusion
It is possible to faithfully import and maintain an ontology in Wikibase in a way that will also
allow its export at a later stage. Wikibase data model possesses a number of unique features
(effectively strict property typing and hard distinction between Items and Properties) that
decrease its ontological interoperability. To ensure a faithful representation of ontologies in
the Wikibase data model, IRIs are represented as both Items and multiple Properties spanning
all Datatypes, Blank Nodes are skolemized before being represented as IRIs and a supporting
ontology is established to identify ontology contents during its editing in Wikibase. Finally, the
o2wb tool is introduced as an implementation of the discussed approach to reusing ontologies
in Wikibase.
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