=Paper=
{{Paper
|id=Vol-1287/lanmr2014_paper_1
|storemode=property
|title=Knowledge Representation for Development of Collaborative Applications
|pdfUrl=https://ceur-ws.org/Vol-1287/lanmr2014_paper_1.pdf
|volume=Vol-1287
}}
==Knowledge Representation for Development of Collaborative Applications==
https://ceur-ws.org/Vol-1287/lanmr2014_paper_1.pdf
Knowledge Representation for the Development of
Collaborative Applications
Mario Anzures-García1, Luz A. Sánchez-Gálvez 1, Miguel J. Hornos2, and Patricia
Paderewski-Rodríguez2
1
Facultad de Ciencias de la Computación, Benemérita Universidad Autónoma de Puebla,
Avenida San Claudio y 14 Sur, Ciudad Universitaria. 72570 Puebla, México
2 Departamento de Lenguajes y Sistemas Informáticos, E.T.S.I. Informática y de
Telecomunicación, Universidad de Granada, C/ Periodista Saucedo Aranda, s/n,
18071 Granada, Spain.
Abstract. The workflow to develop collaborative applications should be highly
adaptable to frequent organizational changes. In order to increase the adaptability
of workflow, an ontology-based workflow model is proposed. This model
represents the set of steps —along with their order of execution— performed by
different entities for developing this kind of applications. Ontology is one of the
strategies for the structured representation of a chosen knowledge domain in a
formal way, helping to remove ambiguity and redundancy, detecting errors, and
allowing automated reasoning. In this work, the ontologies are considered as
models to represent knowledge. A case study is presented in order to show the
use of Knowledge-based Workflow Model for Collaborative Applications.
Palabras Clave: Ontology, Collaborative Application, Workflow Model,
Knowledge Representation, Knowledge-based Workflow Model.
1 Introduction
Ontology provides an ideal solution, for it represents the domain knowledge using
description logic symbols, which allows specifying it in a simple, readable way for both
humans and machines; as well as performing a much deeper reasoning by means of
machines. It facilitates a knowledge base to provide semantic, common understanding,
communication, and shared knowledge on the domain of interest, and a knowledge
reasoning carrying out an inference process to reach to conclusions on such a base, by
means of a reasoner, inference rules, and query languages.
Collaborative applications must provide an appropriate infrastructure to back up
group work and support the dynamic structure of the organizations in runtime. In such
a way that they can represent inherent knowledge in the applications that support groups
of people engaged in a common goal, and provide an interface for a shared
environment. This paper, tries to capture the resulting knowledge in the development
of such applications so, it proposes an ontology-based workflow model named
workflow ontology to develop collaborative applications. This workflow ontology
allows representing all the necessary symbols in order to specify the elements for
building this type of applications. These symbols make up a knowledge base, which
allows to reason and draw conclusions; to generate new knowledge in collaborative
domain, using reasoner, inference rules and query languages. The rest of the paper is
organized as follows: Section 2, describes briefly the ontology-based knowledge;
Section 3, explains the inherent knowledge in the collaborative applications; Section 4,
presents the workflow model for collaborative applications and a case study focused on
academic virtual space; Section 6, outlines the conclusions and future work.
2 Ontology-based knowledge
In recent years, the use of ontologies has extended in diverse areas such as medicine
[1]; bioinformatics [2]; groupware [3, 4]; mainly, because they allow a formal explicit
specification of a shared conceptualization of certain domain of interest.
Conceptualization refers to an abstract model of some knowledge in the world through
the identification of relevant concepts of this. Explicit specification, means that the type
of concepts used and the constraints on their use are explicitly defined. Formal, reflects
the fact that the ontology should be machine-readable. Shared, represents the notion
that an ontology captures consensual knowledge that is not reserved to some individual,
but it is accepted by a group. So, it is said that ontology establishes the vocabulary used
to describe and represent domain knowledge to facilitate machine reasoning. The
domain knowledge, describes the main static information and the objects of knowledge
[5]. According to Gruber [6], domain knowledge in ontologies can be formalized using
four kind of components: concepts, relations, axioms and instances.
The OWL representation [7] facilities are directly based on Description Logics [8].
This basis confers upon OWL a logical framework, including syntax and model-
theoretical semantics, allowing a knowledge representation language capable of
supporting a knowledge base, and a practical, effective reasoning. Protégé is used in
order to develop ontologies with OWL to provide graphical interfaces that facilitate the
knowledge representation and reasoning. Protégé is an engineering tool open source
ontology and a knowledge-based framework, which is widely used due to its scalability
and extensibility with lots of plugins; to facilitate inference knowledge through
reasoners, query languages, and rules. Therefore, it can be concluded that ontologies
are an ideal solution for knowledge representation and reasoning, since it provides a set
of symbols through a formal and structured vocabulary.
3 Knowledge in collaborative applications
A collaborative application focuses on supporting group work to achieve a common
goal by providing a shared workspace. For this reason, the knowledge is the result of a
group interaction and its adaptation on application, i.e. depends on:
Group, which carries out a set of tasks to achieve a common goal through a shared
environment. Consequently, the group should have a suitable Group
Organizational Structure (GOS). This is ruled by the Session Management
Policy —SMP— that establishes the same [9]. The SMP defines a hierarchical or
not-hierarchical GOS by means of Roles that users can play. These roles establish
the set of Rights/Obligations (R/O) and Status (St) within the group, as well as
the Tasks that can be carried out to accomplish a common goal. The Task is
composed of Activities, which use the prevailing shared Resources [10]. The GOS
specification provides the Knowledge about how the interaction among users is
carried out; what Roles are involved in the group; what Task is performed by each
Role, and what Resources are used to achieve a goal. This Knowledge facilitates
the basic elements of a collaborative application.
Interaction, requires: A session, shared workspace where a group will interact. A
notification process that provides the users with the necessary information to
support the group awareness,—users are aware of another member’s presence in
the session, and of the actions that each one of them is carrying out—; and supplies
a common context on which the activities of the group are performed, and where
the information of the shared resources is stored; thus, creating a group memory to
provide understanding and reasoning about the collaborative process. A
concurrency process that ensures the consistency of the data being shared;
providing collaborating users with dynamically-generated temporary access and
permissions, to reduce racing conditions, and to guarantee mutually exclusive
resource usage. These permissions depend on the GOS established and on the lock
mechanism. So, the interaction knowledge is supplied by concurrency, awareness,
and memory group, in such a way that the common context helps avoiding
surprises by reducing the probability of conflicts in the group established [11].
Application, presents the Views that are user interfaces allowing interaction
between the users and the application. There are three Views: Information View
(IV) which is related to individual information; the Participant View (PV) that is
associated with group awareness; and the Context View (CV) which is connected
to group memory. The application is made up into phases [12], where each phase
is defined as a global description of the tasks that are active. Therefore, the
knowledge is supplied via the IV, PV, and CV, allowing to show the interaction
between users and the application; as well as by means of phases which constrain
the users who can participate in accordance with the roles they are playing.
Adaptation [13]; adjusts the Views in accordance to changes triggered by
notification, in such a manner that the application shows the most recent updates
although preserving its functionality. Accordingly, it is necessary to monitor the
changes in the session using a detection process; in the case of an adaptable
process (when the adaptation is carried out by direct intervention of the user) in a
non-hierarchical GOS the pre-adaptation stage is performed. This process
accomplishes an agreement, where all users have to reach a consensus on whether
an adaptation process should be performed by means of a Voting Tool, which
offers several kinds of agreements such as the agreement based on the majority
vote, the one based on a maximum or minimum value, etc. In the case of an
adaptive process (when the adaptation is automatically performed) or the users
have agreed to make the adaptation, an adaptation flow process is performed.
When an adaptation flow cannot be completed, a reparation process is invoked,
—which returns each component to its previous state— then, users are notified that
this adaptation process cannot be achieved. Knowledge is related to modifying
one or several application components, in order to change exclusively that part of
the application which did not fit the features of the new scenario.
The aforementioned is derived from the architectural model (see Figure 1) presented
in [10] that is the result of the study and review of several tools or frameworks (such as
Groupkit [14], ANTS [15], and SAGA [16]), architectures (e.g., Clock [17], and Clover
[18]), and methodologies (AMENITIES [19], ClAM [3], and TOUCHE [4]). Where
the different concepts and terms above mentioned (such as group, role, task, activity,
resource, session, notification, concurrency, shared user interface, phase, adaptation,
etc.), have been applied to design and develop collaborative applications. All these
concepts and terms will be used as symbols, which are part of workflow ontology for
the development of collaborative applications.
Pre-Adaptation Votation Adaptation Stage
ADAPTATION Stage Tool Reparation
LEVEL
Adaptation
Detection Agreement Flow
APPLICATION Participant Context
Information
LEVEL Phase
View View View
INTERACTION Session Concurrence
LEVEL Notification
Group
Organizational User Resource
GROUP Structure Task
LEVEL
Policy Role
Activity
Right/
Status Obligation
Figure 1. Layered architectural model for building groupware
4 A workflow model for collaborative applications
The development of collaborative applications needs to perform a group of coordinated
steps which can be accomplished by means of a workflow. The term workflow typically
refers to coordinated execution of multiple tasks or operations [20]. However,
workflows lack the expressive power to represent the domain knowledge and the
sequence of operations. On the other hand, ontology describes knowledge domain
through concepts, relations, axioms and instances, although ontology does not specify
how these entities should be used and combined.
Special attention has recently been paid to the development of workflow ontologies,
as the workflow can be built on the ontology. The former defines how the tasks or
operations should be used and combined, and once that it has been represented, it may
be considered a static structure. The latter can symbolize this structure due to its
expressive power. So the ontology is an ideal solution for the workflow representation.
There are several examples of workflow ontologies: it presents a collaborative
workflow for terminology extraction and collaborative modeling of formal ontologies
using two tools Protege and OntoLancs [21]; it allows the development of cooperative
and distributed ontologies, based on dependencies management between ontologies
modules [22]; it shows an ontology-based workflows for ontology collaborative
development in Protégé [23],it presents the combination of workflows with ontologies
to design way formal protocols for laboratories [24], it proposes a workflow ontology
for the preservation of digital material produced by an organization or a file system
[25]. All these works are focused on building workflow ontologies to represent
collaborative work in different areas, however, this paper presents a workflow ontology
to develop collaborative application (see Figure 2) using the architectural model
elements as the ontology vocabulary.
The Table 1 shows the concepts, relations and axioms of the Workflow Ontology,
which establishes; first, the Application is described; second, the SMP name is stated;
third, the GOS together with all the elements that contain it are defined; fourth, the
Tasks that are part of the Phase and the View are specified; fifth, the Resources that
will be presented on the View; sixth, the IV, PV, and CV that will have the View;
seventh, the Change produced by Activity; eighth, the Notification and Concurrency
(Cc) triggered by Change; ninth, the Resource locked by means of the Cc; tenth, the
Adaptation (Ad) generated through Notification; eleventh, the Adaptation is showed
on View (IV, PV, and CV); twelfth, it outlines both Views and Phases that are part of
the Session, and finally the Sessions that comprise the Application.
Table 1. Workflow Ontology components.
Relation Domain Range Constrain
(Concept) (Concept)
establishies inverse: isEstablished Application GOS max cardinality=1
contains inverse: IsContained GOS User min cardinality=2
isGoverned inverse: governs GOS Policy max cardinality=1
determines inverse: isDetermined Policy Role min cardinality=1
indicate inverse: isIndicated Role Status max cardinality=1
designates inverse: isDesignated Status R/O min cardinality=1
signpost inverse: isSignposted R/O Task min cardinality=1
isFormed inverse: formed Task Activity min cardinality=1
uses inverse: isUsed Activity Resource min cardinality=1
has inverse: isHave Phase Task min cardinality=1
isDisplayed inverse: display Task View min cardinality=1
exhibits inverse: isExhibited View Resource min cardinality=1
is IV/PV/CV View min cardinality=1
produces inverse: is Produced Activity Change min cardinality=0
triggers inverse: isTriggered Change Notification min cardinality=0
triggers inverse: isTriggered Change Concurrency min cardinality=0
locks inverse: isLocked Concurrency Resource min cardinality=1
generates inverse: isGenerated Notification Adaptation min cardinality=1
shows inverse: isShowed View Adaptation min cardinality=1
is_part_of View Session min cardinality=1
is_part_of Phase Session min cardinality=1
composite Application Session min cardinality=1
A case study is an Academic Virtual Space (AVS) which provides the students with a
shared workspace to simplify their access to the course material previously loaded by
the professor. The AVS includes two roles: 1) The professor can register himself, create
groups, upload and download files both his and those of the students, publish and
respond to those made by others; and 2) The students, can register themselves in the
shared space and access courses, load and unload files (homework and course materials
that have been uploaded by the teacher), make publications and to reply to them. Thus,
in order to create this workspace only the workflow ontology instances should be
defined (see Table 2). The instances are defined in according to the established steps in
the workflow ontology. These constitute the knowledge base for developing
collaborative applications. Therefore, first, the described Application is AVS; second,
the stated SMP is SMP-AVS; third, the defined GOS is GOS-AVS and the elements
play
indicate
contains designates
determines
isGoverned
establishes signpost
has isFormed
designates
composites
isDisplayed produces uses
designates
locks
triggers
presents
exhibits
generates
is is_showed
Figure 2. Workflow Ontology to develop groupware.
that contain the GOS-AVS are showed in the Table 2; the fourth, two phases are
specified along with their tasks that are part of the Phase, as well as the Views are
designated; fifth, the Resources on each View are presented; sixth, the IV, PV, and CV
that will have the View are showed; seventh, the produced Change by Activity are
revealed in the Notification Colum of the Table 2; eighth, the triggered Cc by Change
is indicated by Yes in the Cc column (Y); ninth, the Cc column presents Y, when a
Resource is locked; tenth, the generated Adaptation is displayed in the Ad column;
eleventh, the showed Adaptation on View is specified with Y in IV, PV, and CV;
twelfth, the Views and Phases of the Session are exhibited, and finally the Sessions
that comprise the Application. When Table 2 is constructed, and the GOS elements are
already defined, it is possible infer, for example: The tasks of each phase and view; the
presented resources in each view, the produced changes by each activity, the activated
concurrency by change, etc. This inference is very important when a collaborative
application has been developed. Furthermore, the AVS knowledge base can be used in
another applications, which focus in academic environment and requires two roles
(Teacher and Student). In this a manner, it will be possible to reduce time and costs in
the development of collaborative applications.
5 Conclusions and Future Work
This paper has presented a workflow model for developing collaborative applications
using the inherent knowledge of the integrated elements —group, interaction,
application and adaptation— necessary to build this applications. These elements are
the ontology concepts, and present a set of constrains, that guide and facilitate the
development of this applications. Developing a formal and structured knowledge base,
which allows building any collaborative application, defining its instances on ontology.
Furthermore, in order to simplify and facilitate an ontology description, a specification
table is proposed, in such a manner that any individual may be able to develop a
collaborative application by means on this table.
The future work will aim to specify a methodology to develop collaborative
application, starting with the workflow ontology described in this article.
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