=Paper=
{{Paper
|id=Vol-3235/paper21
|storemode=property
|title=Towards a Modular Ontology for Event-Based Data Sharing in the Logistics Domain
|pdfUrl=https://ceur-ws.org/Vol-3235/paper21.pdf
|volume=Vol-3235
|authors=Cornelis Bouter,Giulia Biagioni,Thom van Gessel,Wouter Korteling,Erik de Graaf,Wout Hofman
|dblpUrl=https://dblp.org/rec/conf/i-semantics/BouterBGKGH22
}}
==Towards a Modular Ontology for Event-Based Data Sharing in the Logistics Domain==
https://ceur-ws.org/Vol-3235/paper21.pdf
Towards a Modular Ontology for Event-Based Data
Sharing in the Logistics Domain
Cornelis Bouter1,∗ , Giulia Biagioni1 , Thom van Gessel1 , Wouter Korteling1 ,
Erik de Graaf1 and Wout Hofman1
1
TNO, Anna van Buerenplein 1, The Hague, The Netherlands
Abstract
We present ongoing work on developing a modular ontology to support event-sharing in the logistics
domain across modalities (e.g., road and rail) as envisioned by the Digital Transport and Logistics Forum
(DTLF). Our main contribution is an event module that describes a change in the state of logistics
activities. Additionally, we contribute a modularised ontology architecture to relate existing (semantic)
modelling efforts to the event module. All contributions are publicly available.
Keywords
Logistics, ontology development, interoperability, modularisation, data sharing, event, semantic technol-
ogy.
1. Introduction
The Digital Transport and Logistics Forum (DTLF), an expert group organised by the Directorate
General for Mobility and Transport of the European Commission, has adopted a proposed
solution for multi-modal (e.g., between rail, road, and air transport) decentralised data sharing
based on “events” [1]. Each future or current change in the state of logistics activities is
represented by an event.
For example, a load event establishes the association between a piece of equipment (e.g., a
container) and a transport means (e.g., a truck). An arrival event establishes the assignment
between a transport means and an infrastructural or geographical location. Each event also
has a counterpart that indicates the end of the assignment: a discharge and a departure event,
respectively. A complete collection of events encompasses the whole logistics process.
In this work we present the main modules of the FEDeRATED Semantic Model to show how
the DTLF principles can be adopted in the Connecting Europe Facility (CEF) FEDeRATED [2].
We show how the ontology modularisation can facilitate the process towards multi-modal
event-based data-sharing. We first describe the Semantic Web background. Then we give an
overview of the ontology through its functional requirements, modularisation, and a dedicated
look at the Event concept.
SEMANTICS 2022 EU: 18th International Conference on Semantic Systems, September 13-15, 2022, Vienna, Austria
Envelope-Open cornelis.bouter@tno.nl (C. Bouter); giulia.biagioni@tno.nl (G. Biagioni); thom.vangessel@tno.nl (T. v. Gessel);
wouter.korteling@tno.nl (W. Korteling); erik.degraaf@tno.nl (E. d. Graaf); wout.hofman@tno.nl (W. Hofman)
Orcid 0000−0002−5448−0543 (C. Bouter); 0000−0002−4686−0490 (T. v. Gessel); 0000−0001−8269−4402 (W. Korteling);
0000−0002−8615−6107 (W. Hofman)
© 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
Workshop
Proceedings
http://ceur-ws.org
ISSN 1613-0073
CEUR Workshop Proceedings (CEUR-WS.org)
2. Background
The Semantic Web is based on the principle of linking and reusing all relevant data sources [3].
This principle is supported by the process of modularisation, which is the practice of dividing on-
tologies into smaller parts that can be reused independently. This process additionally decreases
the complexity of the model and may increase understandability and query scalibility [4].
The principle of reusing existing models is relevant for logistics, because many standards and
ontologies have already been developed for the logistic modalities. Existing work is typically
concerned with modelling the entities and/or the documents involved in the logistics process.
The ERA Railway ontology [5], SmartRail1 , and the Rail Topology Ontology [6] model the domain
from the perspective of the entities it contains. In the airways modality the International Air
Traffic Association (IATA) OneRecord ontology takes a document centric view [7]. The Open
Trip Model2 (OTM), developed for the road modality, takes a combined view by modelling
events, documents, and entities.
Similarly, there are multiple efforts geared towards semantic modelling infrastructure and ge-
ography, consisting of, among others, the EU Knowledge Graph [8], Geonames 3 , GeoSPARQL4 ,
Kadaster KG [9]. These combined efforts provide dereferenceable URIs for every geographical
or infrastructural location across the globe.
3. Ontology overview
The FEDeRATED Semantic Model5 contributes to the existing literature by supporting the
capacity for event-based and multi-modal sharing of logistics data. The event-based contri-
bution lies in the domain-specific event module that we present, which conceptualises the
various activities of the logistics process (e.g. pick-up, arrival, and discharge). The multi-modal
contribution arises from the modularised ontology architecture that facilitates reuse of existing
models of the various modes of transport.
The functional requirements of the ontology are described in a set of competency questions
(CQs), derived by analysing the requirements set out in [1]. In Table 1 we highlight some
competency questions of the Event module ordered by complexity, including the SPARQL query
pattern to verify the CQ. The first questions therefore indicate the basic functionalities. The
last indicate emergent properties of a set of events: by combining events from multiple sources
in the semantic model, we can trace the unique identifier of a single entity (e.g., a container)
across modalities.
1
https://ontology.tno.nl/smart-rail/
2
https://otm5.opentripmodel.org/
3
http://www.geonames.org/
4
https://www.ogc.org/standards/geosparql
5
The current version of the FEDeRATED Semantic Model can be inspected on GitHub (https://github.com/
Federated-BDI/FEDeRATED-Semantic-Model and browsed in a VoCol viewer [10] (http://www.federatedplatforms.
eu/index.php/developer-portal).
Competency question Example answer SPARQL pattern
Which type of event is [this event]? Arrival $this a event:Event, ?additionalType .
Which digital twin(s) are involved in Vessel 𝑥 and container 𝑦 $ t h i s e v e n t : i n v o l v e s D i g i t a l T w i n ? d t .
[this event]?
At what time did or will [this event] 2022-06-01 at 08:31:06, $this event:hasTimestamp ?ts ;
take place? What is the qualifier of the actual time event:hasDateTimeType ?type .
timestamp?
Is the estimated time still before the Yes $reqEvent event:hasTimestamp ?reqTime .
required time of an event? $estEvent event:hasTimestamp ?estTime .
FILTER (?reqTime > ?estTime)
What is the planned route of [this Rotterdam, Antwerp, ?event event:involvesDigitalTwin $this ;
transport means]? Brussels, Luxembourg, a event:ArrivalEvent ;
Brussels, Antwerp, event:hasDateTimeType event:Planned ;
Rotterdam event:involvesPhysicalInfrastructure ?pi ;
event:hasTimestamp ?ts .
FILTER (?ts > ”2022-07-04T00:00:00”^^xsd:dateTime)
ORDER BY ?ts
Table 1
A subset of the Competency Questions. The SPARQL queries were developed to verify that the CQs
are modelled in the ontology. Dollar signs in the SPARQL queries indicate the CQ variables in square
brackets.
3.1. Modularisation
We identified six ontology modules based on the FEDeRATED architecture requirements: the
main Event module; Business Service describing enterprises and contracts, Digital Twin concern-
ing all physical objects in the logistics domain, ranging from transport means to equipment (e.g.,
containers) and goods; Classifications to reuse existing non-Linked Data code lists; Physical
Infrastructure for geographical and infrastructural objects; and Logistic Roles for a taxonomy of
roles.
The Event module takes a central place in the modularisation (Figure 1). The type of an event is
defined by its involved business transaction(s), physical object(s) and/or physical infrastructure
elements. These entities are respectively described in the Business Service, Digital Twin, and
Physical Infrastructure modules. The Logistics Roles module provides a taxonomy of roles that
an enterprise, part of the Business Service module, may play in the context of an event.
The modules directly surrounding the Event module are intended as “interfaces” to align
with and between external standards. In Section 2, we already identified several models for the
various logistic modalities that can be aligned with Digital Twin, of which we implemented an
alignment to the ERA ontology. The PhysicalInfrastructure module also facilitates the reuse of
external vocabularies, namely Geonames, Place from Schema.org, and Geo (WGS84). In the
Classifications we provide an RDF implementation of several commonly used codelists to reuse
Classifications
Geonames
Digital Twin WSG 84
Physical
event:involves Infrastructure
event:involves
Geo-SPARQL
ERA Ontology Event
EU KG
event:involves
Business
Service
Logistic Roles
Figure 1: Modularisation of the FEDeRATED Semantic Model. The Event Module is dark blue, other
modules are blue, and external ontologies are light blue.
existing attributes about physical entities or business transactions.
3.1.1. Event module
The properties that link the Event (Figure 2) to the other modules indicate that the Event has an
association to those elements. The milestone of an event indicates whether the association is
established (“Start”) or removed (“End”). The type of event is defined by its associations. For
example, a load event is the establishment of an association between a transport means and a
container. A discharge event would constitute the end of that association. If an event has an
association to another event we call it a complex event. This way we create a composite event.
For example, a pickup event consists of an arrival event, some load events, and a departure
event. Otherwise, we call it an atomic event. Additionally, each event has a qualifier on its
timestamp: actual, expected, estimated, planned or requested. Taken altogether, Figure 3 shows
an example event in Turtle syntax.
4. Discussion
In this work we have presented a modularised ontology consisting of a main Event module and
complementary extensions to support multi-modal event-based data sharing in the logistics
domain [2, 1]. Our main ongoing work is the integration of the semantic model with the proposed
data sharing architecture [11], validating the model in ongoing usecases, the transformation
of various data sources (e.g., OTM or enterprise data) using an RML-based mapper [12], and
supporting the alignment of additional standards with the FEDeRATED Semantic Model.
hasDateTimeType hasMilestone
DateTimeType Event Milestone
rdf:type
rdf:type
involvesEvent
Actual Expected
End Start
Estimated Planned
Requested CallEvent
AtomicEvent ComplexEvent
MilkRun
DepartureEvent ArrivalEvent ... DropOffEvent DischargeEvent
Figure 2: High level diagram of the Event module. For conciseness, the diagram leaves out the relation
depicted in the modularisation and the full AtomicEvent taxonomy. Legend: Rectangles represent
classes, with the main class in yellow, the first degree of the event taxonomy in green, the second
degree of the event taxonomy in white, and other classes in orange; parallelograms (purple) represent
enumerated individuals; arrows with white tips represent rdfs:subclassOf relations; and other arrows
represent the indicated relations.
@prefix event: .
@prefix dt: .
@prefix bs: .
@prefix data: .
@prefix lsp: .
data:event_1 rdf:type event:Event, event:ArrivalEvent ;
rdfs:label ”Example arrival event” ;
event:hasDateTimeType event:Planned ;
event:hasMilestone event:Start ;
event:hasTimestamp ”2022-01-19T14:04:00.9”^^xsd:dateTime ;
event:involvesDigitalTwin lsp:transportMeans_1 ;
event:involvesPhysicalInfrastructure ;
event:involvesBusinessService data:thisCompany .
lsp:transportMeans_1 rdf:type dt:Truck ;
dt:hasLicensePlateNumber ”00-BBB-1” .
data:thisCompany rdf:type bs:Enterprise ;
bs:actorName ”someCompany”^^xsd:string .
Figure 3: Example planned arrival event
Acknowledgments
This work is based on developments in the CEF FEDeRATED Action and the Digital Transport
and Logistics Forum. This work is partly supported by the Horizon 2020 Magpie project under
grant agreement 101036594.
The presented work is not adopted by EC DG Move as eFTI Implementing Act and is solely
the proposal of the authors, based on concepts, principles, and architecture developed by the
Connecting European Facility (CEF) FEDeRATED Action and adopted by the DTLF.
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