72
5 Applications of the Metadata Standards
Fig. 5.1 Part of the knowledge graph corresponding to a scenario describing a training event,
using the ontology OTRAS in combination with the Course Curriculum and Syllabus Ontology
(CCSO) [2], cf. Sect. 3.5. The elliptical vertices represent individuals, labels inside the ellipses
denote the concept instantiated by the respective individuals and labels in italics represent values
associated with the individuals by means of elementary datatype properties, while the arrows (edges)
represent relations between individuals and are labelled with the respective relation names
while the edge labelling function Λ e : E → 2
R assigns the corresponding relation
names
Λ e ((I, J )) = {R ∈ R | (I, R, J ) ∈ A r }
(5.3)
to an edge (I, J ) ∈ E.
An example is given in Fig. 5.1; this knowledge graph might be read as follows:
“There is a course labelled ‘CECAM SWiMM 2021’. This course has a syllabus,
in which information is given on an instructor who is labelled ‘Jean-Pierre’ and
‘Minier’. The course has a training unit labelled ‘Salome/YACS’ for which event
information is given,” etc. While this particular representation does not contain IRIs
of datatype properties (to match the definition of the knowledge graph given above),
it could easily be modified to incorporate this information as well, e.g. by using
property graphs following Abad Navarro et al. [1]. The individual name IRIs are not
shown in the figure to simplify the visualization; however, they are included in the
definition of the knowledge graph.
The technical implementation of semantic interoperability requires a syntactic
representation by which information can be extracted from (or ingested into) a digital
platform including a knowledge base; cf. Fig. 5.2 for a typical multi-tier design
approach. For this purpose, subject-predicate-object triples can be employed, e.g. in
TTL format (cf. Sect. 3.1), by which the scenario from Fig. 5.1 is rendered as follows:
@prefix ccso:.
@prefix ical:.
@prefix otras:.
@prefix swimm:.
5 Applications of the Metadata Standards
Fig. 5.1 Part of the knowledge graph corresponding to a scenario describing a training event,
using the ontology OTRAS in combination with the Course Curriculum and Syllabus Ontology
(CCSO) [2], cf. Sect. 3.5. The elliptical vertices represent individuals, labels inside the ellipses
denote the concept instantiated by the respective individuals and labels in italics represent values
associated with the individuals by means of elementary datatype properties, while the arrows (edges)
represent relations between individuals and are labelled with the respective relation names
while the edge labelling function Λ e : E → 2
R assigns the corresponding relation
names
Λ e ((I, J )) = {R ∈ R | (I, R, J ) ∈ A r }
(5.3)
to an edge (I, J ) ∈ E.
An example is given in Fig. 5.1; this knowledge graph might be read as follows:
“There is a course labelled ‘CECAM SWiMM 2021’. This course has a syllabus,
in which information is given on an instructor who is labelled ‘Jean-Pierre’ and
‘Minier’. The course has a training unit labelled ‘Salome/YACS’ for which event
information is given,” etc. While this particular representation does not contain IRIs
of datatype properties (to match the definition of the knowledge graph given above),
it could easily be modified to incorporate this information as well, e.g. by using
property graphs following Abad Navarro et al. [1]. The individual name IRIs are not
shown in the figure to simplify the visualization; however, they are included in the
definition of the knowledge graph.
The technical implementation of semantic interoperability requires a syntactic
representation by which information can be extracted from (or ingested into) a digital
platform including a knowledge base; cf. Fig. 5.2 for a typical multi-tier design
approach. For this purpose, subject-predicate-object triples can be employed, e.g. in
TTL format (cf. Sect. 3.1), by which the scenario from Fig. 5.1 is rendered as follows:
@prefix ccso:
@prefix ical:
@prefix otras:
@prefix swimm: