common international ontology for v-con€¦ · web viewthe common international ontology has been...

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Bruno Fiès - CSTB Common Internationalontology for V-Con

Common International ontology for V-Con

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Table of ContentsCommon International ontology for V-Con.............................................................................................1

Change history..........................................................................................................................................2

Background...............................................................................................................................................2

General guidelines and sources for Common Int ontologies....................................................................3

The notion of upper ontology...................................................................................................................3

The context ontologies..............................................................................................................................5

The COMMON_INT.ttl ontology............................................................................................................7

Identification of potential shared concepts between DUL and Common_int V0.2..............................8

Similar entities (same “name”, similar semantic)............................................................................8

Equivalent entities (different “name”, similar semantic).................................................................9

Specific case of the common V-Con entities (Aligenment, etc.)...................................................10

Tools and language used.........................................................................................................................10

Ontology editing.................................................................................................................................10

Ontology alignment............................................................................................................................11

Testing the ontologies.............................................................................................................................11

Resulting structure..................................................................................................................................11

Recommendations for future work.........................................................................................................12

Annex......................................................................................................................................................13

Annex1 : The DUL – Event concept description...................................................................................13

Change historyDate Version Name Change

BackgroundThis document describes the work done within the V-Con project in order to create ttl ontologies to support the business use cases and test cases developed in the frame of the project. This document also, together with the ontology “COMMON_INT.TTL”, constitutes the international input for the V-Con deliverable D3.4.2.


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The need to propose a so called “international ontology” came from the project itself. Two different countries have defined their own use-cases and their corresponding ontologies in order to support the formal description of these use cases. Namely, Sweden and the Netherland have produced their V-CON national ontologies to cover each of their use cases. The reason for having a common part is multiple:

- It provides an upper ontology where national (supposedly more specific) ontologies can be attached.

- It provides a neutral place were to gather and factorize the common entities used in both places.

This document is a first draft version that will be developed further as work progresses. There is therefore no guarantee that it is complete or even correct on all aspects.

General guidelines and sources for Common Int ontologies

The Common international ontology has been developed taking into account the work done in the SE & NL ontologies. Therefore, it contain those concepts (classes, properties and relation types) that the Swedish and Dutch Common Ontologies for road authorities have in common and are worth sharing. This Common Ontology International has been developed also taking into account it has to contain high level entities covering the 5 following key notions:

- System Engineering- Process- Alignment- Infrastructure- Pavment

As already introduced in the Technical Specification - Phase 2document, this ontology should also be connected to some context ontologies (IFC4Road, Infra/CityGML, INSPIRE, ...) that are presented more in details later in this document.


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The notion of upper ontology

As the role of the Common int is to provide the upper & common entities in the V-CON environment, one approach in the elaboration methodology has been to consider exinsting so-called ”upper ontologies” as bootstrapping proposal providing a as neutral as possible structure where it will be then possible to develop/refine some parts in order to support all the V-CON notions.

In the litterature there are a lot of debates around the notion of ”Upper Ontology”. The Wikipedia page dedicated to the topic offers a good abstract about the difficulty to reach such paradigm and cites the most known candidates to play this role of ”Upper Ontology”.

It is define in this page that ”an upper ontology is an ontology which describes very general concepts that are the same across all knowledge domains. An important function of an upper ontology is to support broad semantic interoperability among a large number of domain-specific ontologies which are accessible ranking "under" this upper ontology”.

There have been many upper ontologies proposed and some of them are listed on this web page.

Among others, the DOLCE ontology and more specificaly the DUL ontology have been considered. DOLCE (for Descriptive Ontology for Linguistic and Cognitive Engineering) is an upper ontology aiming at capturing the ontological categories underlying natural language and human common sense. DOLCE intents to have just descriptive (vs prescriptive) notions. There has been some extensions of DOLCE and DnS (for Descriptions and Situations) is one of them. Both DOLCE and DnS are particularly devoted to the treatment of social entities, such as e.g. organizations, collectives, plans, norms, and information objects. A lighter version of DOLCE and DnS, with extensive inline comments is available and know as ”DOLCE+DnS-Ultralite” (abbreviated: DUL).


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The context ontologies

As seen in the introduction the notion of ”Alignment” and ”Infrastructure” are crucial for V-CON and are already supported and formaly described by some so-called ”context ontologies”. Namely, the IFC ontology (IFC4Road) and the INFRAGML model contain the corresponding entities.

- IFC (Industry Foundation Classes): The IFC specification is developed and maintained by buildingSMART International as its “Data standard”. Since IFC4 it is accepted as ISO 16739 standard.

- InfraGML: It is an evolution of LandXML. InfraGML is a modular conceptual model correcting LandXML weakness and easing to setup gateways with other languages (including other OGC standards, buildingSmart standards, etc…).

Thanks to the common approach followed by OGC and BSi resulting in a common data model, it is obvious to identify what are in both domains (IFC and InfraGML) the entities corresponding to the common notions. This parallel is illustrated by the figure above. In V-CON, it has been decided to integrate in the Common int the latest elements (Positioning Element & Alignment). It will be enough to then establish the needed correspondences with the context ontologies.

The notion of Alignment covers:- Ability to exchange alignment information from planning to design, to construction, and

finally to asset management phase- Ability to link alignment information to other project information such as cross sections and

full 3D geometry of construction elements (realized by upcoming IFC-Bridge and IFC-Road projects)

- Ability to query alignment information providing data such as linear referencing for positioning

- Ability to allow open data access of alignment information from asset management databases


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Alignment

horizontal alignment vertical alignment

3D Alignment

horizontal alignment segment

vertical alignment segment

associated requirement definitions

Figure 1: General decomposition of alignment information

The following principles have governed the development of the conceptual schema: Alignment is seen as “a reference system associated to linear constructions, such as roads, rails,

bridges, used to position elements, such as road, rail or bridge elements or other feature elements, positioned along an alignment”;

A single alignment is defined as a non-branching, continuous, single alternative, single location alignment. Multiple alternatives of one alignment are multiple alignments with a different label. A single linear construction facility may have zero, one or more alignment with discriminating labels (for purposes, alternative, others);

A single alignment can be represented as:A horizontal, a vertical and a resulting 3D alignment,A horizontal and a vertical alignment,Only a horizontal alignment,Only a 3D alignment (e.g. from surveying).

Multiple vertical alignments can be defined using the same horizontal alignment. Future versions of the alignment conceptual schema will add support for offsets and other relationships between horizontal and vertical alignments;

Alignment segment geometry includes curve types used for road constructions and a generic template for additional spirals for alignment segments used in rail constructions;

Tangential continuity between alignment segments is not enforced per se by the alignment conceptual schema. It can be enforced individually by a Boolean setting. This allows using the alignment definition also for other infrastructure works, such a power lines.

The COMMON_INT.ttl ontology


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As already briefly explained in the introduction, the elaboration of this ontology has followed a mix between a bottom up approach (by mixing in the “Common_Int.ttl”) the entities coming from the two national ontologies. This has led us to produce a first “common” version (called “COMMON_INT V0.2”) which can be described by the following figures:

- Composed of 159 different concepts- Sharing

o 30 concepts with Common_SEo 75 concepts with Common_NL

- Containing 66 concepts that are not reused either by COMMON_NL or COMMON_SE

One of the difficulties encountered by proceeding in that way was to mix different approaches (as both national ontologies were also based on the compilation / multi import of parts of existing specialized ontologies). The resulting structure was containing some inconsistences.

At this point, it has been decided to introduce an upper ontology playing the role of a neutral high level backbone where to attach our more specialized concepts. DUL has been used in that way and the resulting ontology is illustrated below.

Identification of potential shared concepts between DUL and Common_int V0.3.

Similar entities (same “name”, similar semantic)

12 entities have been identified as bellowing to this category. They are listed along with their respective definitions in the table below.

Shared Concepts

DUL Ontology

Concept definition (rdfs:comment)

COMMON_INT V0.3 ontology –Concept definition

Collection Any container for entities that share one or more common properties. E.g. "stone objects", "the nurses", "the Louvre Aegyptian collection", all the elections for the Italian President of the Republic.

A collection is not a logical class: a collection is a first-order entity, while a class is second-order.

is a concept which members have a plurality that is not by definition one. Typically the plurality of the members is bigger than one. It is a number of things. Those things may be individuals, classes, relations or combinations of them.A grouping of some variable number of objects that have some shared significance.

InformationObject

A piece of information, such as a musical composition, a text, a word, a picture, independently from how it is concretely realized.

is an object that is an individual set of data with its own identity. For example: document, database data, email message (with attachments), (case) file, Internet site (or any part thereof), photo / image, sound recording, wiki, blog etc.


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Amount A quantity, independently from how it is measured, computed, etc.

-None-

Event Any physical, social, or mental process, event, or state.... (Very long description – see annex)

a thing that happens or takes place and marks the beginning or ending of an activity.

Method A method is a Description that defines or uses concepts in order to guide carrying out actions aimed at a solution with respect to a problem.

It is different from a Plan, because plans could be carried out in order to follow a method, but a method can be followed by executing alternative plans.

is a systematic procedure for accomplishing or approaching something.

Process This is a placeholder for events that are considered in their evolution, or anyway not strictly dependent on agents, tasks, and plans.

See Event class for some thoughts on classifying events. See also 'Transition'.

is one or more activities that deliver a changed state to objects that are used as input.

Project A Plan that defines Role(s), Task(s), and a specific structure for tasks to be executed in relation to goals to be achieved, in order to achieve the main goal of the project. In other words, a project is a plan with a subgoal structure and multiple roles and tasks.

is a temporary organization that is created for the purpose of delivering one or more business products according to an agreed Business Case.

PhysicalObject

Any Object that has a proper space region. The prototypical physical object has also an associated mass, but the nature of its mass can greatly vary based on the epistemological status of the object (scientifically measured, subjectively possible, imaginary).

Thing that exists in space and time.

Description A Description is a SocialObject that represents a conceptualization.

It can be thought also as a 'descriptive context' that uses or defines concepts in order to create a view on a 'relational context' (cf. Situation) out of a set of data or observations.

For example, a Plan is a Description of some actions to be executed by agents in a certain way, with certain parameters; a Diagnosis is a Description that provides an interpretation for a set of observed entities, etc.

is an information representation that describes a thing.

Contract (The content of) an agreement between at least two agents that play a Party Role, about some contract object (a Task to be executed).

The binding document or agreement to create one or more legal obligations.

Person Persons in commonsense intuition, which does not apparently distinguish between either natural or social persons.

-None -

Role A Concept that classifies an Object is a function assumed by a thing in a particular situation.


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Equivalent entities (different “name”, similar semantic)

<TBC>

Specific case of the common V-Con entities (Aligenment, etc.)

<TBC>

Tools and language used

Ontology editingFor developing this ontology, the Protégé (version 5.0.0 béta 17) editor has been used. It is worth noticing that the Swedish and the Dutch ontologies were developed in parallel using TopBraid Composer. The file format chosen among us was Turtle (producing *.ttl files).

The IFC4Road context ontology is in fact composed of 3 different files:

- IFC4Road.ttl- IFCAlignment.ttl- IFC4Add1.owl

The “Ifc4Road.ttl” is importing the “IfcAlignment.ttl” which is importing the “IFC4Add1.owl” file as represented by the figure below. The imported “Ifc4add1.owl” file is the reference BSi ontology available at the BSi server.


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Ontology alignment

There are various tools available online to compare ontologies. In order to establish links between the two national ontologies and between Common_Int V0.2 and DUL, the alignment server from INRIA has been used. This alignment has nothing to do with the alignment of roads described earlier in the document. It is a matching service that is comparing two ontologies and finds common entities.


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Testing the ontologiesA methodology has been defined to test the ontology produced. The guidelines have been published.

Resulting structureThe resulting ontologies may be downloaded from http://www.modelservers.org/public/ontologies/vcon/

The exact structure, regarding ontologies and versions is still to be determined.

The ontologies may also be viewed over the web by accessing http://vcon.tno.nl:8080/webprotege/#List:coll=Home;

Recommendations for future work


http://vcon.tno.nl:8080/webprotege/#List:coll=Home

http://www.modelservers.org/public/ontologies/vcon/

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Annex

Annex1 : The DUL – Event concept description

(from rdfs:comment)

Any physical, social, or mental process, event, or state.

More theoretically, events can be classified in different ways, possibly based on 'aspect' (e.g. stative, continuous, accomplishement, achievement, etc.), on 'agentivity' (e.g. intentional, natural, etc.), or on 'typical participants' (e.g. human, physical, abstract, food, etc.).

Here no special direction is taken, and the following explains why: events are related to observable situations, and they can have different views at a same time.

If a position has to be suggested here anyway, the participant-based classification of events seems the most stable and appropriate for many modelling problems.

(1) Alternative aspectual views

Consider a same event 'rock erosion in the Sinni valley': it can be conceptualized as an accomplishment (what has brought a certain state to occur), as an achievement (the state resulting from a previous accomplishment), as a punctual event (if we collapse the time interval of the erosion into a time point), or as a transition (something that has changed a state to a different one).

In the erosion case, we could therefore have good motivations to shift from one aspect to another: a) causation focus, b) effectual focus, c) historical condensation d) transition (causality).

The different views refer to the same event, but are still different: how to live with this seeming paradox?

A typical solution e.g. in linguistics (cf. Levin's aspectual classes) and in DOLCE Full (cf. WonderWeb D18 axiomatization) is to classify events based on aspectual differences. But this solution would create different identities for a same event, where the difference is only based on the modeller's attitude.

An alternative solution is applied here, and exploits the notion of (observable) Situation; a Situation is a view, consistent with a Description, which can be observed of a set of entities. It can also be seen as a 'relational context' created by an observer on the basis of a 'frame'. Therefore, a Situation allows to create a context where each particular view can have a proper identity, while the Event preserves its own identity.


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For example, ErosionAsAccomplishment is a Situation where rock erosion is observed as a process leading to a certain achievement: the conditions (roles, parameters) that suggest such view are stated in a Description, which acts as a 'theory of accomplishments'. Similarly, ErosionAsTransition is a Situation where rock erosion is observed as an event that has changed a state to another: the conditions for such interpretation are stated in a different Description, which acts as a 'theory of state transitions'.

Consider that in no case the Event is changed or enriched in parts by the aspectual view.

(2) Alternative intentionality views

Similarly to aspectual views, several intentionality views can be provided for a same Event. For example, one can investigate if an avalanche has been caused by immediate natural forces, or if there is any hint of an intentional effort to activate those natural forces.

Also in this case, the Event as such has not different identities, while the causal analysis generates situations with different identities, according to what Description is taken for interpreting the Event.

On the other hand, if the possible actions of an Agent causing the starting of an avalanche are taken as parts of the Event, then this makes its identity change, because we are adding a part to it.

Therefore, if intentionality is a criterion to classify events or not depends on if an ontology designer wants to consider causality as a relevant dimension for events' identity.

(3) Alternative participant views

A slightly different case is when we consider the basic participants to an Event. In this case, the identity of the Event is affected by the participating objects, because it depends on them.

For example, if snow, mountain slopes, wind, waves, etc. are considered as an avalanche basic participants, or if we also want to add water, human agents, etc., makes the identity of an avalanche change.

Anyway, this approach to event classification is based on the designer's choices, and more accurately mirrors lexical or commonsense classifications (see. e.g. WordNet 'supersenses' for verb synsets).

Ultimately, this discussion has no end, because realists will keep defending the idea that events in reality are not changed by the way we describe them, while constructivists will keep defending the idea that, whatever 'true reality' is about, it can't be modelled without the theoretical burden of how we observe and describe it.

Both positions are in principle valid, but, if taken too radically, they focus on issues that are only partly relevant to the aim of computational ontologies, which only attempt to assist domain experts in representing what they want to conceptualize about a certain portion of reality according to their own ideas.


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For this reason, in this ontology both events and situations are allowed, together with descriptions, in order to encode the modelling needs independently from the position (if any) chosen by the designer.


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