=Paper=
{{Paper
|id=Vol-2919/paper24
|storemode=property
|title=On the Issue of Property Transitivity in RDF Datasets
|pdfUrl=https://ceur-ws.org/Vol-2919/paper24.pdf
|volume=Vol-2919
|authors=Tatiana Shulga,Alexander Sytnik,Ekaterina Panteleeva
}}
==On the Issue of Property Transitivity in RDF Datasets==
https://ceur-ws.org/Vol-2919/paper24.pdf
On the Issue of Property Transitivity in RDF Datasets
Tatiana Shulga [0000-0002-5521-5960], Alexander Sytnik [0000-0002-1256-7253],
Ekaterina Panteleeva [0000-0002-2693-937X]
Yuri Gagarin State Technical University of Saratov
77 Politechnicheskaya street, Saratov, Russia, 410054
taiss@yandex.ru
Abstract. As part of the development of the concept of the semantic web in re-
cent years have been created a large number of OWL ontologies and RDF da-
tasets based on them. However, in the design and using the properties of OWL
ontologies, is extremely important to correctly reflect real-world information,
because something that is totally logical in the world of abstract data may poor-
ly correlate with the expected behavior of web applications for the user. For ex-
ample, SPARQL queries that using the transitive properties of the OWL lan-
guage can create loops and return incorrect information. In this article we show
that in some cases it is preferable to abandon the use of transitivity of properties
in ontologies and describe an algorithm for traversing related entities, which al-
lows solving the problem of loops. As an example, illustrating this problem is
considered the web application "Linked Open Specialties" (LOS), which sends
SPARQL queries to the ontology "Specialties". The ontology “Specialties” rep-
resents the structure of official lists of specialties, bachelors and masters gradu-
ate programs and research specialties that were valid in recent years in Russian
Federation and allows us to establish their correspondence using the transitive
property “equalsTo”. Notably, that, although the developed algorithm is formu-
lated and used in terms of a specific subject area to solve the problem of a sepa-
rate application, it is quite universal and can be used to solve the transitivity
problem in RDF-datasets of other subject areas.
Keywords: Transitivity of OWL-properties, ontology, RDF, Semantic Web, re-
cursive algorithm, linked specialties
1. Introduction
The past two decades have been characterized by the rapid development of Seman-
tic Web technologies. [1]. Conceptually, semantic web is a stack (set) of web technol-
ogies that allow to store and link data from various sources (systems and documents)
in a manner that machine processing is applicable to them. One of the major technol-
ogies of this stack is the RDF language, which is used to recording statements about
any resources as triplets. This is a flexible data model, which is independent of sub-
ject area.
Copyright © 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0
International (CC BY 4.0).
Proceedings of the of the XXIII International Conference "Enterprise Engineering and Knowledge Management"
(EEKM 2020), Moscow, Russia, December 8-9, 2020.
However, the capabilities of the RDF language are limited by binary predicates and
efficient computer processing of data is possible only when semantics are added to
RDF data sets. In practice, for this purpose are developed RDF datasets based on
OWL ontologies. In accordance with the definition of the W3C consortium, ontology
is understood as a formal model of knowledge representation in a certain subject area
that describes types of objects (classes), interaction between them (properties), and
ways of joint use classes and properties (axioms) [2]. In recent years, a huge number
of RDF datasets based on OWL-ontologies have been developed, some of which are
provided in the Linked Open Data Cloud(LOD), and some are described in scientific
publications (for example, [3,4,5,6]).
The OWL language implements the basic requirements for ontology languages:
clearly defined syntax, formal semantics, sufficient power of expression, ease of ex-
pressing knowledge and effective support for logical inference. Support for logical
deduction allows to obtain new knowledge using existing knowledge and to detect
different kinds of contradictions in ontologies, for example, unforeseen relations be-
tween classes or individuals. This process is possible by the mechanism of axioms
(restrictions) - a kind of rules that operate in this ontology. Axioms of the OWL lan-
guage allow us to present “complex” knowledge, for example, to set restrictions of the
cardinality (there cannot be more than 20 students in a group), or characteristics of
properties, such as transitivity (if lecture1 is included in topic1, and topic1 is included
in section1, then this means that lecture 1 is included in section 1).
In this paper, we consider in detail an axiom of the OWL language such as the
transitivity of properties and the problem of using transitive properties in RDF da-
tasets. Queries that use transitive properties can create a kind of loops and return in-
correct information. In this paper, this problem is described and solved using a specif-
ic RDF-dataset as an example. The set is developed on the basis of the OWL-ontology
“Speciality”, which is for to present data of the lists of specialties, bachelors and mas-
ters graduate programs and research specialties ever operating in the Russian Federa-
tion. We propose a method for solving this problem by developing and implementing
an algorithm for traversing related entities.
2. Transitivity of properties in OWL
According to the OWL notation, property P is called transitive in the case from the
totality of facts that individuals A and B are connected by property P and individuals
B and C are connected by property P, it follows that individuals A and C are also
connected by property P.
Transitive properties are composite properties because they are created in a few
steps. For example, on the basis of the statements “Mari isDescendantOf Tom” and
“Tom isDescendantOf Mike”, it may be concluded that “Mari isDescendantOf
Mike”.
The fact that transitive properties are composite may be the source of some prob-
lems associated with the so-called “loops” which can occur unpredictably in the case
of sufficiently long transitive chains. This means that if the connection chain of this
property is nonlinear and represents some semblance of graph, then at the moment
there is no mechanism for specifying the order of its traversal or any restrictions on it,
therefore SPARQL queries to resources associated with this property can return re-
sults that do not meet expectations [7]. The situation is also complicated by the fact
that, although SPARQL query language has a filtering mechanism, it is applied direct-
ly to the query results and cannot affect the chain of logical inference during its exe-
cution. Since the results returned by the query are simple resources, it is impossible to
obtain any information about the transitive relation traversal order, which means that
it is also not possible to carry out any filtering from the outside.
More specifically, this problem can be illustrated by the example of the ontology
“Specialties”.
3. Ontology “Specialties”
The ontology “Specialties” [8] represents the structure of the official lists of spe-
cialties and areas of training bachelors and masters, operating in recent years in Rus-
sia, and a list of scientific specialties. The Ministry of Education and Science approve
such lists in the Russian Federation. In recent decades, the higher education system of
the Russian Federation has changed significantly. In particular, only from 2004 three
official lists of specialties and areas of training bachelors and masters was changed,
graduate school became an educational program and conformity of graduate school
areas with scientific specialties was established. The Ministry of Education and Sci-
ence publishes data about these changes on the Internet in the form of orders and in-
structions, but in practice their use by educational organizations and citizens cause’s
difficulties. This is due to the fact that this data are published in the form of pdf-
documents for which effective machine analysis is impossible Therefore, there is a
need to develop special web applications that would allow governing bodies, educa-
tional organizations and private citizens not only to have access to information, but
also to analyze it effectively. If such applications are developed on the basis of the
traditional approach — using relational databases, then many questions arise related
to data openness, their support, changing the structure of databases (after changing the
structure of lists), relationships with other educational resources. The solution to this
problem was the development of the OWL ontology "Specialties" and the correspond-
ing RDF data set. This set is developed based on official documents of the Ministry of
Education and Science of the Russian Federation, available in open access (for exam-
ple, [8]). It contains the output data of the lists such as the names and codes of spe-
cialties and educational programs combined in the UGSN from various lists and their
correspondence.
The ontology “Specialties” and RDF dataset were developed by a team of teachers
and students of Yuri Gagarin State Technical University of Saratov (SSTU) [9]. They
can be accessed in several ways: through the Web application Linked Open Special-
ties (LOS) [10], or through the SPARQL endpoint [11]. The described ontology is
also published in the cloud of open linked dictionaries (Linked Open Vocabulary)
[12] and can be used by any developers to create any web applications in the area of
higher education of the Russian Federation that require data on former or current lists
of specialties and educational programs.
Using the data of this ontology, it is possible by specialty in the diploma and the
year of its receipt to determine the relevant specialty or educational program currently
in force. That is, in particular, it associates the name and code of the specialty or edu-
cational program valid at one time with the name and code of the specialty or educa-
tional program valid at another time.
The class hierarchy of this ontology is presented in Figure 1.
Fig. 1. The structure of the ontology classes “Specialties"
Ontology object properties (properties that connect instances of two classes) are pre-
sented in Table 1.
Table 1. Object properties of the ontology “Specialties”
Object property Designation of property
dcterms:hasPart Property from the ontology "Dublin Core". Represents a resource
that is physically or logically included in the described resource.
dcterms:isPartOf Property from the ontology "Dublin Core". Represents a resource
in which the described resource is physically or logically includ-
ed in any resource.
partOf (included in) A property that indicates that a particular object is part of another
object. It is transitive and inverse to the “consistsOf” property
and is a subclass of a class dcterms: isPartOf.
isPartOfList (included Subproperty properties «PartOf», shows that certain UGSN
in the list) included in a certain list. Domain is UGSN, the range – is a list,
and it is the inverse of the property «listConsistsOf».
isPartOfUGSN (includ- Property that indicates that a certain specialty included in certain
ed in the UGSN) UGSN. Domain is a specialty, the range – is a UGSN, and it is
the inverse of the property «UGSNConsistsOf».
consistsOf (consists of) A property that indicates that a particular object has specific
components. It is transitive and inverse to the property
“isPartOf” , is a subclass of the class dcterms: hasPart class.
listConsistsOf (list The sub-property of the “consistsOf” property, showing that a
сonsists of) particular list has components (UGSN). Domain is the list, the
range – is a UGSN, and it is the inverse of the property
«isPartOfList».
ugsnConsistsOf (UGSN The sub-property of the “consistsOf” property, showing that a
сonsists of) certain UGSN has components (specialties). Domain is UGSN,
the range - is a specialty, and it is the inverse of the property
«isPartOfUGSN»,
hasLevelEducation (has Shows the level of training for a particular specialty. Domain is a
level education) specialty, and the range - is a level of education. Also is a
functional property.
owl:sameAs A property from the ontology "Web Ontology Language", show-
ing that two links actually refer to the same object, that is, the
objects are identical.
equalsTo (equals to) Property showing that one specialty from one list corresponds to
another specialty from another list. Domain and range - "Special-
ty". Is transitive and symmetric property, is a subclass of owl:
sameAs.
UGSNHasUDC A property indicating that a specific UGSN corresponds to a
specific UDC from the ontology "UDC-Scheme".
4. The problem of transitivity of the property “equalsTo”
From the object properties of the ontology “Specialties”, the most important in the
context of this work is the property equalsTo. It shows that one specialty from one list
corresponds to another specialty from another list. The domain and range of this
property is a specialty. It is transitive and symmetric property and is a subclass of a
class owl: sameAs.
The transitivity of this property is necessary in order to establish correspondence
through related lists, which is logical when establishing consistency between special-
ties.
However, the results of SPARQL queries directed at obtaining a list of equivalent
specialties did not meet the needs of the task, since they contained the full path of
property transitivity. Perhaps this is correct from the point of view of the abstract
application of this characteristic of the property, but it does not correspond to the
general logic of the LOS application, since it contains a kind of “cycle”. In this case,
“loop” means the non-linear course of transitivity in which the output chain returns to
the specialty from the same list as the initial specialty for which compliance is estab-
lishing. This leads to the fact that the user of the application often gets a result that
looks incorrect.
An example of such a result can be seen in Table 2. When requesting correspond-
ences for the specialty "Economics" from the list “OKSO” with the code "080100",
output contain such specialties as "Foreign regional studies", "Regional studies of
Russia", "Applied mathematics and computer science", which is not the expected
result for the user.
Table 2. Fragment of correspondences list for the specialty "Economics"
Educational pro- Code Level edu- UGSN List Period of
gram cation validity
Educational pro- Code Level edu- UGSN List Period of
gram cation validity
Foreign Regional 032000 Bachelor's Liberal arts 337 2011-2012
Studies degree
Regional Studies of 032200 Bachelor's Liberal arts 337 2011-2012
Russia degree
Regional Studies of 41.03.02 Bachelor's Political sciences 1061 2012-our
Russia degree and regional studies days
Foreign Regional 41.03.01 Bachelor's Political sciences 1061 2012-our
Studies degree and regional studies days
Applied Mathemat- 010400 Bachelor's Physics and Mathe- 337 2011-2012
ics and Computer degree matics sciences
Science
Applied Mathemat- 01.03.02 Bachelor's Mathematics and 1061 2012-our
ics and Computer degree Mechanics days
Science
Business Informatics 080500 Bachelor's Economics and 337 2011-2012
degree Management
Business Informatics 38.03.05 Bachelor's Economics and 1061 2012-our
degree Management days
Applied Computer 230700 Bachelor's Computer Science 337 2011-2012
Science degree and Computer Engi-
neering
Applied Computer 09.03.03 Bachelor's Computer Science 1061 2012-our
Science degree and Computer Engi- days
neering
It should be noted that in the above example already including the filtering by spe-
cialties, which belong to the same list as the initial specialty. However, as mentioned
above, the filters in the SPARQL-query works directly with its results and have no
influence on the inference process and the construction of the transitivity chain, there-
fore, they do not fulfill the required task.
5. A recursive traversal algorithm for related specialties
In order to solve the considered problem, we suggest removing the transitivity re-
striction on property equalsTo and using the following algorithm that obtains the list
of related specialty for a given specialty and returns values, which is the correct from
the user’s point of view.
Algorithm to obtain the list of related specialties
This algorithm allows getting the set of all equivalent specialties from other lists by
the code of a given specialty.
Input data: code of the specialty s;
Output data: set of specialties A corresponding to the specialty s filed by the input.
The steps of the algorithm:
1. Get the list code p, to which specialty s belongs;
2. Get a list of specialties B, associated with s by property equalsTo;
3. Remove specialty s from list B, if B is contained s;
4. For each specialty si from list B do the following steps:
4.1. Get the code of list pi that contain specialty si;
4.2. If pi corresponds with p, break the current iteration of the loop and go
to specialty si+1;
4.3. If the set of specialties A, contains si, break the current iteration of the
loop and go to specialty si+1;
4.4. Add specialty si to the set of specialties A;
4.5. Do steps 2-4 for specialty si.
For ease of developing and testing this algorithm, on the base of the ontology
“Specialties” a small ontology “Test” was developed and filled with data. It is an
abstraction of that part of the original ontology, which will interact directly mecha-
nism for establishing correspondences.
The class hierarchy of the developed ontology is presented in Figure 2 and includes
only two classes: EducationalProgramm - the specialty of education, and List - a list
that contains specialties.
Fig. 2. The structure of the ontology classes “Test”
The object properties hierarchy of the ontology «Test» is presented in Figure 3.
The main properties in it are the following properties: equalsTo - establishes the cor-
respondence between specialties from various lists, isPartOfList - shows that the spe-
cialty is part of the list, listConsistOf - shows that the list consists of components -
specialties.
Fig. 3. The structure of the ontology object properties “Test”
The resulting ontology was filled with data about individuals - specialties, and for
the convenience of testing the name of each contains names of those specialties with
which it is directly related by the property equalsTo. An example of a description of
such specialty is presented in Figure 4.
Fig. 4. Description of the specialty а11а01а21а22
The next step was the development of a console application that implements this
algorithm in Java. The main reason for choosing this programming language was the
fact that LOS application is written in this language and thus further integration of the
developed mechanism would be the most simple.
The following classes were created during application development:
App, directly responsible for the logic of establishing correspondence be-
tween specialties and the formation of the required result;
SparqlQuery containing the texts of all used SPARQL-queries;
QueryService, necessary for substitution of variable values and correct
formation of SPARQL queries before sending to the server;
Util, responsible for connecting to a SPARQL-endpoint, sending
SPARQL-queries and receiving their results.
The App class requires special attention, since the algorithm for obtaining the list
of correspondences for the specialty is implemented precisely in it. The main function
in it is recursiveTraversal, a recursive function to bypass the list of specialties related
by property equalsTo, its code is shown in Figure 5.
Fig. 5. Function recursiveTraversal
The result of work of the application for the specialty "a11a01a21a22" is presented
in Figure 6. All necessary correspondences were obtained, including those whose
connection by the property equalsTo with this individual was not setup directly, but
was obtained as a result of a recursive traversal of related specialties.
Fig. 6. The result of work of the application
The integration of this algorithm in the LOS application will provide correct results
when performing a request to search for specialties that correspond to the specialty
"Economics" from the list “OKSO” with the code "080100" (Fig. 8.)
Table 3. Correspondences list for the specialty "Economics"
Educational Code Level edu- UGSN List Period of
program cation validity
Economics 521600 Bachelor's Liberal arts and so- The 2001-2004
degree cio-economic science List
Economics 080100 Bachelor's Economy and Man- 337 2011-2012
degree agement
Economics 032200 Bachelor's Economy and Man- 1061 2012-our
degree agement days
6. Conclusion
Thus, we investigated the problem of property transitivity in RDF-datasets using a
specific example. To do this, we analyzed the work of the LOS application that per-
forms SPARQL queries to the RDF-dataset, which was based on the ontology "Spe-
cialty". As a result, a problem was revealed in constructing the output chain of the
transitive property equalsTo: queries using this property returned an incorrect result
containing "loops". A recursive traversal algorithm for related specialties, described in
this article is correct and can be successfully implemented in the application “Special-
ties of higher education of the Russian Federation” to solve the problem of transitivity
of the property equalsTo.
In the future, the re-engineering of the application “Specialties of higher education
of the Russian Federation” will be held using this algorithm, for which the developed
Java application that implements this algorithm will be useful.
Notably, that, although the developed algorithm is formulated and used in terms of
a specific subject area to solve the problem of a separate application, it is quite uni-
versal and can be used to solve the transitivity problem in RDF-datasets of other sub-
ject areas.
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