A SOCIO-SEMANTIC APPROACH TO THE

CONCEPTUALISATION OF DOMAINS, PROCESSES AND

TASKS IN LARGE PROJECTS

Carla Pereira

1,2

, Cristóvão Sousa

Instituto de Engenharia de Sistemas e Computadores do Porto, Campus da FEUP

Rua Dr. Roberto Frias, 378, 4200 - 465 Porto, Portugal

Escola Superior de Tecnologia e Gestão de Felgueiras, Instituto Politécnico do Porto

Rua do Curral, Casa do Curral, Margaride, 4610-156, Felgueiras, Portugal

António Lucas Soares

Instituto de Engenharia de Sistemas e Computadores do Porto, Campus da FEUP

Rua Dr. Roberto Frias, 378, 4200 - 465 Porto, Portugal

Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias

4200-465, Porto, Portugal

Keywords: Domain conceptualisation, Social construction of meaning, Ontology development, Collaborative networks,

Conceptual blending.

Abstract: A case study involving a new method to support the collaborative construction of semantic artefacts in an

inter-organizational context is described. The method aims at being applied, in particular, in the early phases

of ontology development. We share the view that the development of semantic artefacts in collaborative

networks of organizations should be based on a continuous construction of meaning, rather than pursuing

the delivery of highly formalized accounts of domains. For that, our research is directed to the application of

cognitive semantics results, specifically by developing and extending the Conceptual Blending Theory to

cope with the socio-cognitive aspects of inter-organizational ontology development. An evaluation

experiment for this method is accomplished in the scope of a large European project in the area of industrial

engineering. The method evaluation and its results are described.

1 INTRODUCTION

This research work addresses the problems raised by

information and knowledge sharing in the context of

short life-cycle collaborative networks. Although

there is an increasing number of semantic tools and

resources available for the companies to use in

everyday business activities, problems in

establishing a common conceptualisation of a given

reality arise in two flavours: (i) notwithstanding the

evolution of semantic technologies, it is virtually

impossible to establish a priori comprehensive and

complete semantic artefacts that account for all the

possible variations in business situations and

contexts (which are more and more dynamic); (ii) in

spite of all the standardization efforts, there is a kind

of “social resistance” in accepting semantically

oriented standards (viewed as “grand narratives” of a

domain).

As clearly argued in (Cahier et al., 2005) about

the role of a “socio-semantic web”, we need to go

beyond of approaches that provide an high level of

“automation of the meaning” with formal ontologies

built by ontologists and processed by software

agents using automated inferences. Instead, we need

to address situations where human beings are highly

required to stay in the process, interacting during the

whole life-cycle of applications, for cognitive and

cooperative reasons (Cahier et al., 2005).

In the scientific context, research on ontology

engineering addressed poorly the above problems.

Current knowledge about the early phases of

ontology construction is insufficient to support

237

Pereira C., Sousa C. and Soares A. (2009).

A SOCIO-SEMANTIC APPROACH TO THE CONCEPTUALISATION OF DOMAINS, PROCESSES AND TASKS IN LARGE PROJECTS.

In Proceedings of the 11th International Conference on Enterprise Information Systems - Information Systems Analysis and Speciﬁcation, pages

237-242

DOI: 10.5220/0002009302370242

 SciTePress

methods and techniques for a collaborative

construction of a conceptualisation (Pereira and

Soares, 2008). However, the conceptualisation phase

is of utmost importance for the success of the

ontology. But it is in this phase that a social presence

is needed as it requires an actor to predict reliably

how other members of the community will interpret

the conceptual representation just based on its

limited description. By incorporating the notion of

semantics into the information architecture, we, thus

transform the users of the system themselves into a

critical part of the design.

Our view is that ontology engineering needs a

“socio-cognitive turn” in order to generate tools that

are really effective in copping with the complex,

unstructured, and highly situational contexts that

characterize a great deal of information and

knowledge sharing in businesses collaboration. Our

stance is thus a socio-semantic (Cahier et al., 2005)

one as we believe that the development of semantic

artifacts in collaborative networks of organizations

should be based on a continuous construction of

meaning, rather than pursuing the delivery of highly

formalized accounts of domains.

This line of research is thus directed towards the

application of cognitive semantics results in the

creation of artifacts acting as socio-technical devices

supporting the view that meaning socially

constructed through collaboration and negotiation.

The first line of this research work deals with the

application and extension of the Conceptual

Blending Theory (CBT) (Fauconnier and Turner,

1998) to the realm of collaborative semantic tools.

The practical application of our approach is to

support the co-construction of semantic artifacts by

groups of social actors placed in organizational

contexts interacting towards a set of common

objectives. Simple examples these artifacts are the

creation of a common taxonomy (or ontology) for

classifying and retrieving content from an inter-

organizational portal, the creation of specific

terminological accounts to serve as conceptual

references in project tasks, or the specification of

ontologies for systems interoperability.

2 THE CONCEPTUAL

BLENDING THEORY

The relation between cognitive semantics and

knowledge representation is better understood by

considering the four principles that collectively

characterize a cognitive semantics approach (Evans

and Green, 2006). According to this view, meaning

is constructed at the conceptual level: meaning

construction is equated with conceptualisation, a

dynamic process where linguistic units serve as

prompts for an array of conceptual operations and

the recruitment of background knowledge.

Our proposal to support a collaborative process

of conceptualisation of a given reality (e.g., a

domain in the context of a project) is founded on

cognitive semantics, specifically on the Conceptual

Blending Theory (Fauconnier and Turner, 1998).

CBT accounts for the emergence of meanings by

adopting the view that meaning construction

involves emergent structure, i.e., conceptual

integration is more than the sum of its component

parts. An integration network is thus a mechanism

for modeling how emergent meaning might come

about, accounting for the dynamic aspects of

meaning construction.

CBT representation gives rise to complex

networks by linking two (or more) input spaces by

means of a generic space. The generic space

provides information that is abstract enough to be

common to all the input spaces. Elements in the

generic space are mapped onto counterparts in each

of the input spaces, which motivate the identification

of cross-space counterparts in the input spaces. A

further space in this model of integration network is

the blended space or blend. This is the space that

contains new or emergent structure: information that

is not contained in either of the inputs. The blend

takes elements from both inputs, but goes further on

providing additional structure that distinguishes the

blend from either of its inputs. In CBT, there are

three component processes that produce an emergent

structure (Fauconnier and Turner, 1998):

composition; completion; and elaboration.

3 SUPPORTING THE

CONCEPTUALISATION

PROCESS

We recognize in the CBT a great potential as the

theoretical foundation of a method and associated

tools supporting collaborative conceptualisation

processes in inter-organizational settings. The

following is assumed as the initial state: (1) a

collaborative network has been formed and its goals

and mission are defined and understood by all

members (that we call "strategic frame"); (2) a

common ontology with certain goals and to be used

in a given time-frame has to be developed; (3) each

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238

organization has a representative in a “network

team” in charge of developing the ontology. (4) a

common conceptualisation (as the first step to the

ontology construction) is to be collaboratively

created through explanation, discussion and

negotiation. This approach is only feasible with the

support of a tool that facilitates and manages all the

process.

The proposed method establishes the following

steps (see figure 1): (1) each organization has

assigned one or more input spaces (only one input

space is considered here, for the sake of simplicity);

(2) each organization represents its conceptualisation

proposal through the input space; simultaneously,

the organization share the information and other

knowledge sources (e.g., URLs, documents and

other content) which allow for the correct

understanding of its conceptualisation proposal; in

the case study we are using conceptual maps as

knowledge representation technique; (3) by some

manual or automated (or something in between)

process, a generic conceptualisation is generated

(generic space); the common conceptual structure in

the generic space should be generic enough to be

accepted by all the team members with minimum

negotiation; (4) considering the “counterpart”

elements, the process of creating the blend space is

started using selective projection; based on the input

spaces, strategic frame, generic space and

documentation available in the input spaces, the

blend is “run” to obtain new conceptualisation

proposals; (5) new conceptual structures proposed in

the blend space are object of negotiation; the

concepts for which consensus exists are represented

in (“copied” to) the generic space; situations that

justify “backward projection” to the input spaces and

their modification are analyzed then the emergent

blend structure is validated (confirm or eliminate

new concepts that raise in the blend); (6) if input

spaces modification takes place, the method should

resume at step 4; however, is not necessary the

creation of a new blend space; (7) when all

participants manifest their agreement with the

conceptualisation represented in the generic space,

the method instance is finished.

Summarizing, at the end of the process the

generic space contains the collective

conceptualisation, the blend was used during the

negotiation process with the goal to improve, enrich

and mainly helping in obtaining consensus. This

method may also be used by each organization to

support the creation of its input space, which can

result in the presence of multiple blendings.

Figure 1: Method to support collaborative

conceptualisation process.

4 EMPIRICAL EVALUATION

4.1 Context and Experiment Setup

Several real world experiments were planned aiming

to empirically validate and fine-tune the approach.

The one described here was carried out within a

trans-national (european) project in the area of

industrial (automotive) engineering. In this project, a

consortium of major European car manufacturers,

suppliers, and research institutes develop the

“dynamic supply chain collaboration" concept that

changes the conventional automotive terms of

delivery to a highly reactive “5-Day-capable”

system that radically cuts down inventories in the

supply network. This is a big and complex project,

as it involves 19 partners, from 7 countries and 9

tasks grouped in 3 work packages. One of the work

packages aims at building an ontology to be used in

several tasks of the project. The general goal of the

AC+DC Ontology is to facilitate a common and

precise understanding of the concepts used by all

partners in the several project activities. The

ontology development task started initially without a

supporting methodology or even a clear vision of the

ontology goals and scope. Within this context, we

took the opportunity to set-up an action-research

project aiming at, from the one side, to help the

project to develop its ontology and, from the other

side, to create knowledge about the collaborative

construction of ontologies by designing and

undertaking a set of experiments. From the

preliminary analysis of the problem, jointly with the

project team, the following general requirements

were derived: (1) the goals and scope of the

ontology should be clearly stated, even if not

completely detailed; this is of utmost importance to

guide the conceptualisation process; (2) there is a

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239

clear need for a method and tools supporting the

conceptualisation process; only with such a support

a collaborative process is feasible.

The first step was to look for existing ontologies

in the supply chain management area in order to

reuse them. There are some specialized ontologies

such as (Ureten and Ilter, 2006) and (Fayez et al.,

2005) that present a models based on the SCOR

model; (Maier et al. 2003) that study the information

integration inside an enterprise and not between

supply chain members; and The United Nations

Standard Products and Services Code (UNSPSC)

provides an open, global multi-sector standard for

efficient, accurate classification of products and

services. These ontologies cover very specific sub-

domains being hard to reuse. There are also several

upper-level ontologies which are too abstract to be

applied in particular situations. Since collaboration

concepts behind supply chains and their

requirements could be fundamentally different, there

is no standard ontology, which would be detailed

enough to be applicable in every practical case.

In this experimental phase two tools are used to

support all the process. For the joint construction of

a conceptual representation, Concept Maps

supported by CmapTools

(http://CMAP.ihmc.us/conceptmap.html) were used.

With CmapTools it is possible to endow the

conceptual representation with some collaborative

mechanisms which support a partial implementation

of the method. CmapTools has a client-server

architecture allowing users to build their own

personal CMAPS and publishing them, later on for

discussion in the form of "claims". To support the

blend space creation, together with CmapTools

features, the text mining tool, TermExtractor

(http://lcl2.uniroma1.it/TermExtractor), capable to

extract relevant terms in the interest domain, by

submitting an archive of domain-related documents

in any format was used.

The experiment context was the following: Four

teams from four different organizations

(geographically dispersed) participated in the

domain conceptualisation. Two of those teams

(Team1 and Team2), from two different

organizations (Org1 and Org2), were domain experts

from academic and professional areas respectively;

another team (Team3) from another organization

(Org3) were experts in information and knowledge

management and in collaborative networks; the

fourth team (Team4) from another organization

(Org4), beyond their academic expertise in the

specific domain, they have a reasonable

understanding about ontologies.

The experiment was setup firstly by establishing

the roles of each actor: 1) Contributor: all team

members should play this role contributing for the

improvement and enlargement of the current version

of the AC+DC conceptualisation. The contributor

responsibilities are to make inputs to the shared

conceptualisation by proposing and discussing

concepts and relationships (claims); 2) Facilitator:

responsible by facilitating the discussion/negotiation

around the conceptualisation and by maintaining the

CMAPS updated and consistent. Teams 2, 3 and 4

where assigned the role of contributor; team 1 was

assigned the role of facilitator.

4.2 Experiment Procedure

As mentioned before, the use of CmapTools would

allow untrained users, that cannot be expected to

conform to the constraints of a formal semantics, to

concentrate on the task at hand in an unrestrictive

environment. Our goal is to allow users could start

informally, without having to translate their know-

how into any knowledge representation (heavy)

formalism (Eskridge et al., 2006).

The first step, the strategic frame definition,

helped to define the context, goal and mission of the

ontology development task, as well as, the scope and

boundaries of the conceptualisation. With the main

focus in the dynamic supply chain collaboration

concept, more precisely in the Dynamic Supply

Loops (DSL) concepts, the team created an initial

shared conceptualisation guided by the following

focus question: "what processes, activities and

information are involved in the DSL network

planning model, allowing collaboration in entire

supply chain in feedback loops?" The resulting

conceptualisation was presented in a concept map,

defining the scope and boundaries of the

conceptualisation process, i.e., this result together

with the goals initially defined for the ontology

constituted the "strategic frame". Afterwards, the

conceptualisation of the several process and

activities was initiated, which means detailing the

DSL.

After the construction of the first CMAP, a

"knowledge soup" (Canas et al., 2004) object was

created in order to aggregate ideas and propositions

about the Production Planning Process. The input

spaces, by their turn, were connected to the

"knowledge soup", contributing for the

implementation of the blend space. Thus, all the

teams in the project were able to extend the first

shared domain conceptualisation about the DSL,

contributing with their own claims - changes that

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were made in the input spaces and which were

published in the server. All members could see the

other member’s claims. Claims come from each

team's domain expertise, from the results of the

TermExtractor tool document analysis, other

documents produced by the several project

workpackages, the logistics area of SAP dictionary

(http://help.sap.com/saphelp_46c/helpdata/En/35/2c

d77bd7705394e10000009b387c12/frameset.htm),

the terms and glossary about supply chain

management proposed by (Vitasek, 2008) and the

most important of all, by the conceptual structures

identification in the experts mind when they interact

with the other member’s claims.

Negotiation is initiated, supported by discussion

threads over each claim. Following the end of a

discussion, the approved (consensual) claims, can be

imported directly to the CmapTools Client instance

of each organization, updating the personal map in

focus. This last step is the “Backward Projection” of

the method. Technically, all this process is supported

by the CmapTools "knowledge soups" feature,

which aggregates in the server all the claims from all

input spaces, therefore users are able to see the

claims and who published them. Accordingly,

knowledge soups jointly with discussion threads

contribute to shape the blend space in the

CmapServer. With TermExtractor the enrichment of

the current conceptualisation by the discovery of

new terms and the supported validation of the

existing ones was achieved. All the input spaces

have the same conceptual structure and the person in

charge for coordinating the process perform the

upload of the final (consensual) map into the server.

The CMAPS present in the CmapServer, comprise

the generic space.

4.3 Analysis of the Results

This experiment dealt fundamentally with the first

three steps of our method, i.e., the creation of the

strategic frame, input spaces and the generic space

of departure. Consequently, the focus was directed

to empirically understand how the inter-

organizational team uses and appropriates the visual

concept map building tool and it interacts and

organizes the work.

There was a high receptiveness of the concept maps

as visual representation technique. This experience

showed that conceptual maps are a suitable tool to

be used during the collaborative conceptualisation

process, because in this phase "completeness is more

important neatness and rigor" (Kremer, 1994). We

can conclude that this approach is a good way to

overcome the problem that untrained users cannot be

expected to conform to the constraints of a formal

semantics, for they can become frustrated and

distracted if they must change their thinking to

conform to the structures of a formal system

(Eskridge et al., 2006). From our observation and

from the interviews we concluded that by discussing

the problem using a domain-specific vocabulary

supported by a visually oriented, easy to use,

informal tool, effective results are achieved in a

relatively short time.

Our goal is to allow that the users could start

informally, the construction of a (non-

computational) "knowledge base" without having to

commit to a particular knowledge representation,

and without having to translate their know-how into

any particular knowledge representation format.

After the informal knowledge is built up, its

structure may become more obvious. Then, users

could then begin to gradually coerce the concept

maps to conform to the formal semantic system.

In the following paragraph we share some

lessons learnt with this experiment.

1. Appropriate definition of the strategic frame and

road map: The starting point of this case study

shows clearly the importance of these tasks. After

the initial definition of the strategic frame and road

map, is equally important that in the previous

specified time periods, go backwards and review the

following questions: What do we have? What do we

want? and How to get there? These questions allow

the team to evaluate the forces and weaknesses of

current situation. 2. Rules to organise the process

and motivate the participation: The evaluation

showed that the majority of users were passive in

their participation. Automatic notifications of all

teams whenever changes exist, version control and

definition of a time frame in which the proposals can

be discussed are fundamental to better organise the

process, and motivate the participants. Therefore, if

no one present suggestions during the time period

defined, it means that agreement exists. Every time

there's a change in any discussion item within the

process, users should be informed and invited to

comment the new proposals. The collaborative

process of conceptualisation is really complex

because of the high number of areas, processes and

activities, among others. One way to deal with this is

to follow some rules such as (Gómez-Gauchía et al.,

2004a): to create many small CMAPS with few

concepts and relations in each; to organize them in

an orthogonal manner: horizontally by levels of

abstraction and vertically by sub areas of the

ontology; and use a code based on colours. 3. Project

A SOCIO-SEMANTIC APPROACH TO THE CONCEPTUALISATION OF DOMAINS, PROCESSES AND TASKS IN

LARGE PROJECTS

241

generated documentation as an enabler: The

continuous production of project documentation is a

way to validate and improve the conceptualisation.

On the other hand, the consensual conceptual

structure, agreed so far, should be used in the

production of new deliverables in order to

standardize the contents of each deliverable. By this

reason it's easy to share and understand the meaning

of the concepts in the domain. 4. First version of the

conceptualisation: Somehow in contradiction with

3., the need to anticipate as much as possible the

first version of the conceptualisation was identified.

The existence of a blend space provided more

reliability, collaboration and agility to the process of

conceptualisation. This was due to the fact that the

inputs for blend were based on project produced

documentation, as well as other important resources

selected by the domain experts. This resulted in an

high level of acceptance of the proposals. However,

it would be advantageous if the conceptualisation

was created even before the elaboration of the first

deliverable. Equally, the blend should be created

based on resources other than those produced within

the project. A good example is the use of the SAP

dictionary and ILIPT project documentation. 5.

Carefully selection of the information resources used

as inputs in the blend space: The results obtained in

the blend depend directly on the information sources

used. The blend results can be accepted with more or

less support, according to the provided inputs during

its creation.

5 CONCLUSIONS

The results presented and discussed here allowed us

to identify some of the weaknesses of the adopted

procedure as well as the foremost drives for the

improvement of the method and supporting tools.

During this experiment, some of the method steps

were well covered by the existing tools while others

were partial or not covered at all. Nonetheless we

were able to represent all steps outputs using

CmapTools. The blend creation became an

important mechanism within our case study,

increasing trust during the conceptualisation process.

However, considering the knowledge acquired

during the experiment, we are convinced that the

support of a semantic wiki enabling versioning

besides the discussion on the visual conceptual

structures will be very advantageous.

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