Kairouan, Tunisia. {ing_mnasserhouda, maha_khemaja}@yahoo.fr ... to support the user travel planning; and section V presents our conclusions and future ...
A public transportation ontology to support user travel planning Mnasser Houda, Maha Khemaja
Kathia Oliveira, Mourad Abed
PRINCE Research Group, ISITC, Hammam Sousse, GP1 Hammam Sousse 4011 University of Sousse, Higher Institute of Computer Science and Management, ISIG Kairouan, Tunisia {ing_mnasserhouda, maha_khemaja}@yahoo.fr
Univ Lille Nord de France, F-59000 Lille, France UVHC, LAMIH, F-59313 Valenciennes, France CNRS, UMR 8530, F-59313 Valenciennes, France {kathia.oliveira, mourad.abed}@univ-valenciennes.fr
Abstract— Choose the best way to move from one place to another can involve different information: offers of different transport modes, their combination in the same journey and other information about services (such as restaurants, libraries, etc) that can be available in the route and useful for the passenger. Different approaches have been proposed to support the passenger's planning considering some part of this information. In this paper we present a public transportation domain ontology that considers different concepts related to the best and more relevant planning for the passenger. This ontology is formalized with OWL in Protégè tool. Using real instances and inferences, we show the ontology application, its relevance and consistency. Ontology, transportation.
I.
INTRODUCTION
A user from the transportation system is a passenger who seeks assistance about moving from one place to another. This simple daily activity deals with the complexity of multimodality of transportation, i.e., the possibility of using multiple modes of transport (bus, metro, etc) for a single journey between an origin and a final destination. Besides, for a better assistance to the passenger, it is also important to present all the possible services related to the journey, for example, information about restaurants and banks that he/she could have access in the way of his/her journey. All these information come from different systems and should be presented to the user in an integrated and organized view to make possible his choice and planning. To deal with this problem, different works have being proposed covering route planning [1] or transportation planning in general [2]. In this paper, we focus on the information required by the passenger to prepare a journey and to choose the best way to move from one point to the other using the same or several transport modes. To that end, we defined a public transportation ontology that represents this domain itself taking into account the transport multimodality and passenger’s interest. This paper is organized as follows: section II presents the related works using ontologies in this domain; section III describes our ontology from its definition to its validation;
section IV brings an illustrative scenario of use of this ontology to support the user travel planning; and section V presents our conclusions and future works. II.
RELATED WORKS
Ontology is a description of entities and their properties, relationships, and constraints [3] expressed by axioms. Domain ontologies [4] express conceptualizations that are specific for a particular domain (such as medicine or transportation). They put constraints on the structure and contents of domain knowledge (for example, in medical domain, it would describe the concept symptom and that symptom is a manifestation of a disease). Ontologies have been exploited in many domains and studies, thanks to their capacity to promote sharability of knowledge bases, knowledge organization, and interoperability among systems. Some studies can also be found in the domain of transportation with different goals. Becker and Smith [2], for instance, defined an ontology for multi-modal military transportation planning and scheduling. Their ontology focus on concepts about transport services, activities, resources (vehicles, crews, terminal facilities) and constraints that dictate how, when, by whom and where transport activities (deployment, evacuation, etc.) can be executed. This ontology considers different transport modes but its objectives are completely different from ours since it deals with military transportation activities and not with a travel planning in general. However, we consider Timph’s work [5] as closer to ours. In fact, he describes two ontologies of “wayfinding” with multiple transportation modes in an urban area based on two perspectives: the traveler and the public transportation system. His work consisted on identifying the concepts to define an ontology from the description of directions given verbally by five people. At the end, he obtained a list of concepts of both perspectives and showed that one is a subset of the other one. The research of seeking for concepts from the direction descriptions was very detailed, however, the list of concepts obtained are only a part of the ontology definition since proprieties, relations and axioms were not defined.
978-1-4244-4840-1/10/$25.00 ©2010 IEEE
Another similar work [6] developed a system based on public transport ontology. Based on user inputs (origin, destination and the priorities), the software system searches for bus stops using a spatial radius search. The algorithm finds journeys based on origin and destination pairs by bus route identification utilizing a relation matrix between route and station. This work does not consider, therefore, neither the multimodality of transport nor the possible associated services that can be offered to the user. Finally, a recent work in this area is the research of Niaraki and Kim [1] that aims to determine an impedance model of road geographic information system and intelligent transportation system. The impedance is a model to compute the amount of cost or resistance, expected to pass through a link from its origin node to destination node. To that end they defined a road segment ontology based on the user preferences criteria and context (environmental) criteria, and from this ontology they defined an hierarchical structure divided into two branches: one related to the user criteria (such as information about tourist attractions and preferences) and the other to the context criteria (such as weather and safety). Using AHP (Analytical Hierarchical Process) they defined weighs to compute the impedance.
iii. How are the public transportation stop points organized? iv. Which are the associated services to a journey? v.
How is the public transport infrastructure?
vi. Which kinds of journeys can be offered to a passenger? To answer the first competency question (i.What is the transport multimodality?), four transport modes were selected from the literature[10]: metro, tram, train and bus. They are used by several transport lines from different operators of the transportation network [10]. A transport mode can have different types of vehicles with relevant properties for a journey planning (such as: number of seats). Figure 1 shows a diagram, using UML notation, of this part of the ontology related to the competency question i. For reasons of simplicity the concept properties were not shown.
In this paper we presented an approach which focus on the use of public transportation ontology to support passenger's planning from the different inferred options of a journey. III.
THE PUBLIC TRANSPORTATION ONTOLOGY DEFINITION
There are various methodologies to design an ontology (e.g [3][7][8]). All of them consider basically the following steps: definition of the ontology purpose, conceptualization, formalization, and validation. We defined our ontology using these steps. The purpose of this ontology is to facilitate information retrieval for user travel planning in a city or in a entire country, and, particularly, to help the passenger to decide which itinerary and what mode of transport is preferred to reach its intended destination. The conceptualization is the longest step and requires the definition of the ontology’s scope, definition of its concepts, relations and constraints, and a description of a glossary for all concepts and attributes specified. It represents the knowledge modeling itself. This step was based on a study of related works (see section II.) and mainly in the literature from transport system conceptual models [9][10]. The formalization consists of expressing the ontology in some language and code in a specific tool. This ontology was formalized with OWL 1.0, using Protégè. Those steps will be presented in this section. Finally the validation is done by instantiating the ontology with real instances examples about journeys. A. Conceptualization We start this step by defining the following competency questions, i.e., requirements in the form of questions that the ontology must answer [3]: i.
What is the transport multimodality?
ii.
How is a transportation journey characterized?
Figure 1. Part of the ontology related to transport multimodality
To answer the second competency question (ii. How is transportation journey characterized?), we found in literature that a transport line offers different journey patterns [10]. Each journey pattern is a collection of ordered stop points from an origin to a destination. A journey pattern is associated to a vehicle journey that defines the depart time based on a calendar that should consider a planning for each weekday and its particularities (such as festival days) From one stop point to another, a part of a vehicle journey describes the journey of a public service vehicle which is from one kind of transport mode. The price and duration of a journey depends, therefore, of the transport mode associated (for example, a bus journey may be cheaper but longer than a train journey by TGV). Figure 2 shows this part of the ontology.
The kind of a journey associated services (fourth competency question – iv. Which are the associated services to a journey? ) are presented as different geographic elements that are located in the connection stop point. We named geographic element any place, location, or site physically situated in the connection stop point. These geographic elements can provide services (geographic elements with services) that can be of interest to the user, since at those stop points, the user will change the vehicle and may spent some time there before taking the other vehicle. We included in the ontology the main geographic elements in this case. Another important aspect to consider is if the connection stop point provides some kind of protection for raining (platform or shelter). The geographic elements can also be organized in exchange poles with more than one service possibility. The kinds of geographic elements are disjoint. Figure 4 shows the diagram of the part of the ontology related to the competency question iv.
Figure 2. Part of the ontology related to journey pattern
To answer the third competency question (iii. How are the public transportation stop points organized?), two kind of stop points were identified: a stop point in a journey pattern, that represents a stop point where the passenger does not change the vehicle to arrive in the destination even if the vehicle stops; and a connection stop point, where the passenger needs to change the vehicle and, therefore, can also change the transport mode associated to it. A connection stop point is characterized by a connection link where the passenger has available vehicles of different transport modes. Different times may be necessary to cover this link, depending on the kind of passenger. It is defined, however, an average of the minutes to present the journey planning to the passenger. Figure 3 shows the part of the ontology related to the competency question ii.
Figure 4. Part of the ontology related to geographic elements
To answer the fifth competency question (v.How is the public transport infrastructure?), we found that the stop points are located in some infrastructure points: railway junction, wire junction and road junction. They are linked by infrastructure links. Each vehicle journey part describes the displacement in an infrastructure link (Figure 5). Based on the organization of transportation described, several kinds of journey patterns can be offered to the passenger for a better planning. We organized them in a taxonomy of journey patterns (Figure 6). In this way a journey pattern is classified as a direct journey pattern, when the journey pattern is composed only of stop points in journey pattern; or as an indirect journey pattern, when it has some connection stop points. Direct journey patterns were divided in two kinds: fast journey pattern, when the vehicle of a journey uses only wire and road elements; and non fast journey pattern when it uses only railway elements. For indirect journey pattern, we defined: •
Figure 3. Part of the ontology related to stop points
Service journey pattern, when in the associated connection stop point some banks or post offices are available.
To define this classification we considered basically the different kinds of geographic elements defined in the ontology and the interest of taking a journey of shorter duration. We note that although direct and indirect journey patterns are disjoint, the kinds of indirect journey patterns are not disjoint, that is a journey pattern can be classified as protected and also as leisure journey pattern. All the concepts and attributes were clearly defined in a glossary (see Table I for the most relevant concepts). Theses definition were based on [11][9]. Finally, other constraints (axioms) for the concepts and relations were set based on [10], such as:
Figure 5. Part of the ontology related to transport infrastructure
•
Interesting journey pattern, when in the associated connection stop point exchange pole is available.
•
Shopping journey pattern, when in the associated connection stop point some shopping mall is available.
•
Leisure journey pattern, when in the associated connection stop point some libraries or other leisure centers are available.
•
Journey pattern with little walking, when the walking distances associated to any stop point related to a journey pattern does not exceed 5 minutes.
•
Protected journey pattern, when in the associated connection stop point some shelter or platform is available.
•
All journey pattern are composed of stop points
•
Each connection link has at least one transport mode available to provide to the associated connection stop point.
•
Each exchange pole is composed of at least 2 geographic elements.
•
Each journey is defined by a vehicle journey with at least one transport mode.
•
Each vehicle journey is validated by at least one calendar.
•
Each vehicle type is associated to exactly one transport mode.
•
Each stop point is located exactly in one infrastructure point.
•
Each transport line is served by only one operator.
B. Formalization The ontology was formalized using OWL 1.0 and Protégé since OWL is considered a standard language to represent knowledge and facilitates exchanges and links between ontologies. Figure 7 shows the hierarchy defined in Protégé. To formalize in OWL the composition association (used in Network and Exchange Pole – Figure 1 and 4 respectively), we used the solution defined by [12]). Figure 8 shows the formalization in OWL of the part of the ontology related to transport multimodality where we use this kind of concept association. Some other formalization of the constraints is also presented. To formalize the association class in UML (Position and Journey presented in Figure 2) we used the pattern proposed by [13][14]. Using this pattern, new concepts are defined for each property of the concept that represents an association class. Figure 9 left-side shows, for instance, the concepts that were defined when the pattern was applied for the Journey concept and its formalization in OWL (right-side).
Figure 6. Part of the ontology related to kinds of journey pattern
TABLE I. Concepts Calendar Connection Link Connection Point Exchange Pole
Geographic Element Geographic Element with service Geographic Element without service Infrastructure link Journey Journey pattern Operator Railway Element Railway Junction Road Element
GLOSSARY OF CONCEPTS
Definition It allows the definition of a validity schedule period for a vehicle journey. The physical (spatial) possibility for a passenger to change from one public transport vehicle to another to continue the trip. A stop point where passengers change of vehicles from the same or different mode of transportation. It is a place that aims to facilitate intermodal practices between different modes of passenger transport. The interchanges are distinguished by the variety of modes of transport they gather in one place Location, place, position, site, corner, etc. Geographic element where different stores offer some service to the passenger or some physical structure of protection. Geographic element where the passenger waits for a public transport.
A type of infrastructure link used to describe a road network.
Stop Point
A point where passengers can board or alight from vehicles. A stop point where the passenger does not change of vehicle A group of journey patterns which is generally known to the public by a similar name or number. A characterization of the operation according to the means of transport. A set of transport line to ensure public transport.
Transportation network Vehicle Journey Vehicle Journey Part Vehicle type Wire Element Wire Junction
During ontology instantiation, we verified that all concepts were used and all the need information required to support the travel planning were represented.
A type of infrastructure point used to describe a railway network.
A type of infrastructure point used to describe a road network.
Transport Mode
C. Validation To validate the ontology, we create several instances based on real examples of journey patterns. Those examples were collected by querying the main french transportation system, concerning about Paris and surroundings1.
A supertype including all infrastructure points of the physical network A trip from an origin place to a destination place using a specific transport mode. An ordered list of stop points defining one single path through the road (or rail) network. Institutions that offers the public transport. A type of infrastructure link used to describe a railway network.
Road Junction
Stop point in journey pattern Transport line
library named f (CONNECTION_POINT(?z) ∧ LIBRARY(?f) ∧ is_encercled_by(?z, ?f) ). In those rules, the concepts are written with uppercase letters and the relations between concepts with lowercase letters.
The planned movement of a public transport vehicle on a weekday from the start point to the end point of a journey pattern on a specified infrastructure. A part of a vehicle journey created according to a specific functional purpose A classification of public transport vehicles according to the vehicle scheduling requirements in mode and capacity (e.g. standard bus, double-deck). A type of infrastructure link used to describe a wire network. A type of infrastructure point used to describe a wire network.
Formal expressions in SWRL (Semantic Web Rule Language) were also defined to classify each kind of journey pattern presented in the Figure 6 (see the SWRL expressions in Figure 10). Those rules are defined by expressing how to infer that a specific journey pattern is considered of a specific type. For example, rule 3 in Figure 10 states that a journey pattern named v (JOURNEY_PATTERN(?v)), is classified as a leisure journey pattern (LEISURE_JOURNEY_PATTERN(?v)) since it has a connection point named (CONNECTION_POINT(?z) ∧POSITION_RELATIONSHIP(?b) ∧ is_designated(?z, ?b) ∧ Journey_Pattern_Position(?b, ?v)) that is encircled by a
Figure 7. Ontology hierarchy in Protege
1
http://www.transilien.com
Formalization of the composition association
1 0
Formalization of the constraint between Operator and Transport Line
Formalization of Transport Mode type and the constraint that it is disjoint from the other types
......
Figure 8. OWL code for the part of the ontology presented in Figure 1
Figure 9. OWL code for the formalization of the Journey part of the ontology presented in Figure 2
1)
ROAD_ELEMENT(?x) ∧ ROAD_JUNCTION(?a) ∧ ROAD_JUNCTION(?b) ∧ is_started_with(?x, ?a) ∧ is_ended_with(?x, ?b) ∧ STOP_POINT_IN_JOURNEY_PATTERN(?t) ∧ defines(?a, ?t) ∧ POSITION_RELATIONSHIP(?k) ∧ is_designated(?t, ?k) ∧ JOURNEY_PATTERN(?p) ∧ Journey_Pattern_Position(?k, ?p) ∧ STOP_POINT_IN_JOURNEY_PATTERN(?e) ∧ defines(?b, ?e) ∧ POSITION_RELATIONSHIP(?m) ∧ is_designated(?e, ?m) ∧ Journey_Pattern_Position(?m, ?p) → FAST_JOURNEY_PATTERN(?p).
2)
RAILWAY_ELEMENT(?y) ∧ RAILWAY_JUNCTION(?g) ∧ RAILWAY_JUNCTION(?h) ∧ is_started_with(?y, ?g) ∧ is_ended_with(?y, ?h) ∧ STOP_POINT_IN_JOURNEY_PATTERN(?s) ∧ defines(?g, ?s) ∧ POSITION_RELATIONSHIP(?f) ∧ is_designated(?s, ?f) ∧ JOURNEY_PATTERN(?p) ∧ Journey_Pattern_Position(?f, ?p) ∧ STOP_POINT_IN_JOURNEY_PATTERN(?v) ∧ defines(?h, ?v) ∧ POSITION_RELATIONSHIP(?n) ∧ is_designated(?v, ?n) ∧ Journey_Pattern_Position(?n, ?p) → NON_FAST_JOURNEY_PATTERN(?p).
3)
CONNECTION_POINT(?z) ∧ LIBRARY(?f) ∧ is_encercled_by(?z, ?f) ∧ POSITION_RELATIONSHIP(?b) ∧ is_designated(?z, ?b) ∧ JOURNEY_PATTERN(?v) ∧ Journey_Pattern_Position(?b, ?v) → LEISURE_JOURNEY_PATTERN(?v).
4)
CONNECTION_POINT(?x) ∧ LEISURE(?e) ∧ is_encercled_by(?x, ?e) ∧ POSITION_RELATIONSHIP(?a) ∧ is_designated(?x, ?a) ∧ JOURNEY_PATTERN(?p) ∧ Journey_Pattern_Position(?a, ?p) → LEISURE_JOURNEY_PATTERN(?p).
5)
WALKING(?x) ∧ walking_duration(?x, ?d) ∧ swrlb:lessThan(?d, 5) ∧ CONNECTION_LINK(?y) ∧ is_relative(?x, ?y) ∧ CONNECTION_POINT(?m) ∧ is_started_with(?y, ?m) ∧ CONNECTION_POINT(?k) ∧ is_ended_with(?y, ?k) ∧ POSITION_RELATIONSHIP(?r) ∧ is_designated(?m, ?r) ∧ POSITION_RELATIONSHIP(?h) ∧ is_designated(?k, ?h) ∧ JOURNEY_PATTERN(?p) ∧ Journey_Pattern_Position(?r, ?p) ∧ Journey_Pattern_Position(?h, ?p) → LITTLE_WALKING_JOURNEY_PATTERN(?p).
6)
EXCHANGE_POLE(?e) ∧ GEOGRAPHIC_ELEMENT(?a) ∧ is_composed_of(?e, ?a) ∧ CONNECTION_POINT(?c) ∧ corresponds(?a, ?c) ∧ POSITION_RELATIONSHIP(?m) ∧ is_designated(?c, ?m) ∧ JOURNEY_PATTERN(?f) ∧ Journey_Pattern_Position(?m, ?f) → INTERESTING_JOURNEY_PATTERN(?f).
7)
CONNECTION_POINT(?d) ∧ SHELTER(?a) ∧ is_encercled_by(?d, ?a) ∧ POSITION_RELATIONSHIP(?e) ∧ is_designated(?d, ?e) ∧ JOURNEY_PATTERN(?p) ∧ Journey_Pattern_Position(?e, ?p) → PROTECTED_JOURNEY_PATTERN(?p).
8)
CONNECTION_POINT(?e) ∧ PLATFORM(?b) ∧ is_encercled_by(?e, ?b) ∧ POSITION_RELATIONSHIP(?a) ∧ is_designated(?e, ?a) ∧ JOURNEY_PATTERN(?q) ∧ Journey_Pattern_Position(?a, ?q) → PROTECTED_JOURNEY_PATTERN(?q).
9)
CONNECTION_POINT(?j) ∧ BANK(?k) ∧ is_encercled_by(?j, ?k) ∧ POSITION_RELATIONSHIP(?d) ∧ is_designated(?j, ?d) ∧ JOURNEY_PATTERN(?e) ∧ Journey_Pattern_Position(?d, ?e) → SERVICE_JOURNEY_PATTERN(?e).
10)
CONNECTION_POINT(?i) ∧ POST(?s) ∧ is_encercled_by(?i, ?s) ∧ POSITION_RELATIONSHIP(?q) ∧ is_designated(?i, ?q) ∧ JOURNEY_PATTERN(?b) ∧ Journey_Pattern_Position(?q, ?b) → SERVICE_JOURNEY_PATTERN(?b).
11)
CONNECTION_POINT(?m) ∧ SHOPPING_MALL(?a) ∧ is_encercled_by(?m, ?a) ∧ POSITION_RELATIONSHIP(?k) ∧ is_designated(?m, ?k) ∧ JOURNEY_PATTERN(?g) ∧ Journey_Pattern_Position(?k, ?g) → SHOPPING_JOURNEY_PATTERN(?g).
Figure 10. SWRL expressions
Figure 11- Using the ontology for passenger’s planning
IV. PLANNING A JOURNEY : A SCENARIO A typical scenario of use for the public transportation ontology is supporting the user travel planning. In this scenario the user defines the origin and final destination of his/her trip. With this information, a query system supported by the public transportation ontology defined in this paper uses the internet to look for all possibilities of journey patterns in the different operators’ databases. Besides, the relevant information about geographic elements that are close to the connection stop points is also collected. All this information is used to create several instances in the public ontology. Thus, the system runs some inference engine from Protégè. As a result the inferred journey patterns are proposed to the user for his/her planning. Figure 11 illustrates this typical use of the ontology. Let us suppose that a user needs to go from “Roissy Charles de Gaulle Airport (Tremblay-en-France)” to “Orly Ouest Airport”. We searched in some internet sites from transport operators (particularly, SNCF and RATP, in France) possible journey patterns. We defined some geographic elements associated to some connection stop points identified in those journey patterns as presented in Table II. We used this information to instantiate the ontology in Protege tool. TABLE II. Journey pattern Journey pattern 1 Journey pattern 2 Journey pattern 3
ASSOCIATED ELEMENTS Associated elements Geographic elements: Platform B, library, flower shop, and Restaurant Walking: < 5min ---- with not connection stop point Geographic elements: Restaurant, Shelter A, Post office, Supermarket and Bank
Using Jess engine2, all axioms and SWRL rules defined in our ontology was executed (the result is presented in Figure 12). Jess is a rule engine that can be integrated in Protégé. It runs the rules written in SWRL integrated with all the ontology 2
http://herzberg.ca.sandia.gov/jess/
definition in Protege. The proposed journey patterns were classified as follows: a)
Journey pattern 1 was classified as protected journey pattern and leisure (with restaurant and library) as the result of rules 3, 4 and 8 (Figure 10) and of all axioms defined to represent the ontology.
b) Journey pattern 2 was classified as a direct journey pattern since there is no connection stop point. c)
Journey pattern 3 was classified as a Protected and Interesting journey pattern with services (bank and post office), shopping (supermarket) and leisure (restaurant) as the result of rules 4, 9, 7, 10 and 11 (Figure 10) and of all axioms defined to represent the ontology.
Let us suppose that the user needs to pay some bills and that he/she would also like to eat something. With this in mind and the options offered by the system, event that the journey pattern 2 could be faster since it does not need any connection, the user selects the journey pattern 3. IV.
CONCLUSIONS AND FUTURE WORK
This paper presented a transportation ontology defined from the analysis of the main concepts of the public transportation domain considering some transport system conceptual models [9][10]. We aim at using this ontology to assist the user to choose the best way to go from one point to another. The main contribution of this paper is the detailed description of the definition process of a public transportation ontology, from the definition of the concepts till the specification and formalization of axioms related to the domain. We describe also how this ontology can be used to support user travel planning by the inference of the axioms defined in the ontology. We recognized that collecting the instances of the concepts from operators and geographic information databases is not trivial, but we consider important to provide to the user all necessary information for a travel planning in a unified and integrated way.
Figure 12. Inferred journey patterns using Jess engine
We are now working on developing a query system that automatically captures the instances from different operators to analyze the different possibilities of inferences we can get using this ontology. Future works include also evolve the ontology with other kind of transportation mode (boats, plane, etc.) provided by different kind of operators, other kinds of geographic elements and services that can be of interest to the passenger (such as different kind of geographic elements that offers leisure services) and also real time data (e.g. real time data provided for buses, trains, etc.) .
[6] [7]
[8]
[9]
REFERENCES [1]
[2]
[3]
[4] [5]
A.S. Niaraki, K. Kim, “Ontology based personalized route planning system using a multi-criteria decision making approach”, Expert Systems with Applications 36, pp. 2250–2259, 2009. Becker M., Smith S. F., “An Ontology for Multi-Modal Transportation Planning and Scheduling. Technical Report CMU-RI-TR-98-15, Robotics Institute, Carnegie Mellon University, Pittsburgh, USA, 1997. M. Grüninger, M.S. Fox, “Methodology for the Design and Evaluation of Ontologies”, Technical Report, University of Toronto, Toronto, Canada, 1995. N. Guarino (ed.), “Formal Ontology in Information Systems”. Proceedings of FOIS’98, Trento, Italy, 6-8 June 1998 S. Timpf, “Ontologies of Wayfinding: a Traveler’s Perspective” Networks and Spatial Economics, 2, pp. 9–33, 2002.
[10] [11] [12]
[13]
[14]
J. Wang, Z. Ding, C. Jiang, “An Ontology-based Public Trasnport Query System”, First International Conference on semantincs and Grid,2005. M. F. Lopez, A. Gomez-perez, J. Sierra j. P, “Building a chemical ontology using methontology and the ontology design environment”, IEEE intelligent systems & their applications vol. 14, no1, pp. 37-45, 1999. N.F. Noy, D. L. McGuinness. “Ontology Development 101: A Guide to Creating Your First Ontology''. Stanford Knowledge Systems Laboratory Technical Report KSL-01-05 and Stanford Medical Informatics Technical Report SMI-2001-0880, March 2001. First Ontology « Quelles données échanger avec l’application CHOUETTE ? Une implémentation des spécifications TRIDENT Projet – Profil d’échange – Concepts et contexte normatif. » Ministère de l’écologie, du Développement, et de L’Aménagement durables, 2008. Guide d’apprentissage de Transmodel. http://www.predim.org/spip.php?article2688. (last access 20/11/2009) Transmodel – Englisg and French Definitions for trasnportation. http://www.predim.org/spip.php?article2502. (last access 20/11/2009) G. Antoniou, and F. van Harmelen, Web Ontology Language: OWL, Handbook on Ontologies, (Staab and Studer, eds.), Springer-Verlag, 2004. R. Hoekstra, “Ontology Representation-Design Patterns and Ontologies that Make Sense”, http://dare.uva.nl/document/144859 (last acess 25/11/2009) W3C, “Defining N-ary Relations on the Semantic Web”, W3C Working Group Note 12 April 2006 (http://www.w3.org/TR/swbp-naryRelations/) (last acess 25/11/2009)
