A Dialogue Game Prototype for FCO-IM
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A Dialogue Game Prototype for FCO-IM
Stijn Hoppenbrouwers1, Albert Pratama Jemmi Oscar2,
Dimas Listianto Adisuryo2 and Jan Pieter Zwart2
1
Radboud University Nijmegen,
Institute for Computing and Information Sciences
P.O. Box 9010, 6500 GL, Nijmegen, the Netherlands
stijnh@cs.ru.nl
2
HAN University of Applied Sciences
Academy of Communication and Information Technology
Ruitenberglaan 26, 6826 CC, Arnhem, the Netherlands
albert.pratamajemmioscar@gmail.com
quatrosofia@yahoo.com
JanPieter.Zwart@han.nl
Abstract. We report on the development of a prototype dialogue game for
FCO-IM. Dialogue games are systems for executing controlled conversations.
As part of an ongoing effort to analyze and support collaborative modeling
processes by means of dialogue games, we created a dialogue game prototype
for essential parts of the FCO-IM modeling process. The project was
exploratory in nature, but results suggest that eventually it should be possible to
develop dialogue games that could effectively support fact-based conceptual
modeling efforts. In addition, work on such games enhances our insights in the
FCO-IM modeling process, and leads to improvements and extensions of its
operational guidelines.
Keywords: Fact Oriented Modeling, conceptual modeling, FCO-IM,
collaborative modeling, dialogue game, process of modeling
1 Introduction
Compared to mainstream conceptual modeling approaches like UML, the various
approaches to Fact Oriented Modeling (FOM) have always included a relatively well
defined process or procedure for executing their modeling practices. For example, in
ORM [1] this is known as the CSDP (Conceptual Schema Design Procedure). This
paper focuses on another flavor of FOM: FCO-IM [2], which includes an even more
elaborate modeling procedure.
In the past, initial steps have been taken to better understand, and ultimately better
support, the process of FOM [3-5]. A driver behind these efforts has been the
conviction that better support is needed for the process of conceiving and expressing
conceptual models beyond the use of diagram editors like NORMA, CaseTalk, or
Graphity. This actual process of modeling is at least as essential to the final product as
is the modeling language. Also, the practice of using FOM in system development
and business analysis processes would benefit from more accessible, easierprocedures requiring less training and experience for the production of good quality models [6]. This line of research now revisits FOM, from which it originated. It brings along accumulated knowledge from fields like Method Engineering [7], Collaborative Modeling [8] and Knowledge Engineering [9]. Chiefly, this paper reports on a Master’s Thesis project at HAN University of Applied Sciences, Arnhem, the Netherlands. Radboud University Nijmegen participated as problem owner and provided input and high level requirements for a prototype system embodying some key parts of the existing FCO-IM modeling procedure. This included an elaborate analysis of this procedure within the framework of ‘Dialogue Games’, as will be explained below, as well as ‘proof of concept’ design, implementation, and evaluation of the system. 2 Theoretical Retrospect: Modeling as a Dialogue Game Though the long term goal of the ‘methods as dialogue games’ line of research is to develop improved support systems for processes of system modeling, analysis, and development (within the Design Science paradigm), it also involves more fundamental work on what modeling is [10] (especially in a collaborative setting), what it is for, and what is asked of people when they model. From the outset, we have taken a communication perspective on these matters. Though the products (artifacts) resulting from modeling are firmly based on formalisms and formal representations (e.g. predicate logic, Petri nets), the activities of eliciting, conceptualizing, expressing, and discussing or even negotiating, and validating such artifacts constitute a step-by- step process that is rooted in human cognition, language, and social interaction. The challenge is to bring together the world of thinking using formal systems and the world of ‘regular’ human experience, thinking and communication [11]. This challenge is particularly hard (and interesting) if people are involved that have little or no training in thinking formally. The FOM tradition (contrary to many other approaches in conceptual modeling) has always included such considerations (for example, by using fact statements by domain experts as basis for further abstraction, and by deploying natural language verbalization mechanisms besides more technical diagrams), but has hardly considered them at a theoretical level focusing on thought processes of and interaction between individuals. We set out to remedy this. We initially aimed for understanding, capturing and providing strategies for modeling [4]. We found that to understand strategies, we first need to know what goals they work towards, in what situations and under which constraints. Also, the process of modeling cannot be fruitfully captured by a detailed step-by-step ‘recipe’, but rather concerns a set of goal-based constraints on expressions and interactions that allows for considerable freedom in the execution of a set of necessary steps. A declarative, rule-based way of describing goals and constraints proved better suited for capturing and guiding modeling processes than an imperative one using, for example, flow charts [6]. The next step was the realization that all this pointed towards the analysis and shaping of modeling processes as games, which are by nature interactive systems [7].
Next, the combination of basic discourse theory and study of interactions during modeling sessions led to the development of the RIM (Rules, Interactions, Models) framework [12]. This takes the view that Models are sets of propositions put forward, evolved and selected in conversations by means of Interactions like ‘propose’, ‘agree’, ‘disagree’, ‘accept’, ‘reject’, which are governed and constrained by various types of Rules like grammar, content, interaction and procedure rules [8]. Many secondary aspects are integrated in the modeling process besides the core activity of ‘putting together the model’, including planning and even discussion of modeling concepts to be used (i.e. specifics of language and notation) [12]. The RIM framework and the game approach came together in the notion of dialog games: a theoretical concept from Argumentation Theory [13]. This theoretical notion was operationalized by Andrew Ravenscroft and his team, resulting in the InterLoc system for setting up and playing dialogue games for generic discussion [14]. It is the basic interface and interaction mechanisms of this system that inspired our prototype dialogue game for FCO-IM. The InterLoc approach includes the explicit structuring of “moves” in a discussion by making people choose moves like “asking”, “stating” and “refuting” in a chatbox- like environment. The main mechanism to operationalize this is the use of “openers”. During the chat dialogue, participants (or players) have to select an opener for each line they enter. For example, generic openers are “I’d like to state the following: …”, “I have a question about this: …”, or “That’s total rubbish, because …”. Setting such openers influences the possible structure and tone of the dialogue, and indicates to players what moves they can make. To extend this approach to a conceptual modeling context, the conceptual constraints associated with the use of a modeling language (syntax) had to be added. This was simply done by including such content into openers, e.g. “I propose the following fact type name: …”. The InterLoc approach also renders a log of all interactions that lead to a model. The model can be directly derived from the conversation (at every point in time) by means of gathering all accepted conclusions occurring in the log. In addition, it helps greatly if an up-to-date diagrammatic version is continuously shown to all players. We first successfully did this in the context of Group Model Building, a collaborative modeling discipline within Systems Dynamics modeling [15]. Based on these experiences, the current project was initiated: to apply a dialogue game approach to FCO-IM, in an explorative attempt to frame the FOM process as a dialogue game. We are aware that executing a conversation for modeling strictly through the mechanism of a structured textual chat can hardly be expected to be user friendly and efficient in a real modeling context. Therefore, we have from the beginning envisaged the augmentation of the deep interface (i.e. the chatbox and log) with a surface interface: a collection of form-like and graphical interfaces as well as visualizations providing efficient and user friendly short-cuts for entering the verbal dialogue. The projection of a current diagram is the most basic form of such a surface interface, but more advanced and more interactive mechanisms are expected to be of great benefit. Using such surface mechanisms will still result in the generation of deep interface log entries for the ongoing dialog, while also allowing for direct conversational entries in the log through the structured chat interface. In the next section, we present an outline of our prototype dialogue game for FCO-IM.
3 The prototype: Analysis, Design, Evaluation
The goal of our project was to create a prototype of a dialogue game for FCO-IM, or
at least for some essential parts of the procedure. Though dialogue games inherently
involve multi-player interactions, organizational and technical restrictions within the
project made it impossible to develop the prototype on a distributed architecture.
Instead, a single client was created that was used by all players taking turns. While
this is not a realistic solution for practice, it served well to explore and test the
principal interaction mechanisms.
The two usual roles in FCO-IM were discerned in the dialogue game: the domain
expert and the information analyst. In the initial dialogue game prototype created for
the Group Model Building approach (see Section 2), the role of facilitator was
explicitly used. For the FCO-IM game, this role was less prominently included as
‘Game Master’: the Game Master just controls the focus of conversation, switching
between a range of sub-games or ‘modes’ as required.
Three main parts in the FCO-IM modeling procedure were distinguished in the
prototype, in line with standard FCO-IM modeling:
1. Stating elementary facts [2, Ch. 2.3]: the basis of FCO-IM modeling;
2. Classification and Qualification [2, Ch. 2.4] of the facts given in 1;
3. Constraint determination applied to (populations of) the fact types created in 2.
Because of time restrictions of the project, only the assignment of uniqueness
constraints [2, Ch. 3.2] were covered by our prototype.
These three parts were chosen from the FCO-IM operational procedure [2] because
they cover the spectrum from exhaustively prescribed steps (for part 3, [2, 18]), via
partially prescribed steps (part 2) to only tentatively heuristically described steps (1).
The next step in the prototype development was to analyze the existing FCO-IM
procedure in terms of Focused Conceptualizations (or FoCons) [16]. The main thrust
of a FoCon analysis is to identify the various conceptual foci as they occur throughout
a modeling session. FoCons concern the operational focus in part of a conversation
for modeling, often rendering intermediate products. They are often sub-foci of those
directly related to the end product of the modeling effort (in our case, an FCO-IM
model). Though it is possible that such foci and their related game modes are applied
in a preset sequence, observations of collaborative modeling sessions of various types
have shown that foci are often switched reactively, in a more ad hoc fashion [12]. It
should therefore be possible to either apply foci in an orderly, systematic fashion, but
also to (re)visit some focus/mode unexpectedly, as required by the current dynamics
of conceptualization and discussion.
Below, we provide an overview of the FoCons identified, though lack of space
unfortunately prevents us from giving the full detail of the foci and the set question
types and answer types involved.
Stating Elementary Facts.
The sub game of ‘stating elementary facts’ concerns a highly creative activity that is
hard to cover by a fixed procedure. As a focused conceptualization, it requires the
domain expert to produce elementary fact statements (the ‘output’ of the FoCon)based on representative documentation (the ‘input’) reflecting actual communication
as takes place in the domain. In addition, all fact statements need to be structured in a
particular format: elementary facts. This FoCon has no sub-modes, i.e. is covered by
only one mode, with 7 openers (see section 2 for an explanation of ‘openers’).
Classification and Qualification.
This FoCon follows a more algorithm-like procedure than the previous one, which
provides its input: elementary fact statements. Its output is a set of ‘meaningful
classes of facts and objects’, with the structure restriction that the fact types thus
stated are correctly classified and qualified, i.e. are phrased in terms of correct object
types (with their proper identification) and/or label types. The FoCon is covered by
four separate conceptualization modes, with 10 to 15 openers; however, quite a few of
those openers (in particular the generic ones like “I agree, because …”) were used in
more than one, if not all, modes.
Assigning Uniqueness Constraints (UCs).
This third main FoCon involves a strict procedure which takes as input a fact type
expression (provided through the second main FoCon) as well as its population
(provided through the first main FoCon, but possibly also purpose-created). The
output is a set of ‘uniqueness constraints’ correctly assigned to the roles of the fact
type. The FoCon roughly involves presenting the domain expert with two fact
statements populating the same fact type and answering a question about this
configuration: “can these two fact statements hold (at the same time)?”. The actual
procedure is more complex, involving various iterations of the questions and covering
various sub-items within a fact type [18]. No fewer than eight different modes of
conceptualization were identified, with 2-9 openers.
Importantly, not only openers were provided but also rules (to be executed by the
game master) concerning when to switch from one mode to another. However, note
that such a switch can in principle be made at any point (possibly even at the initiative
of a player), though usually one will want to finish a single sub-activity in order to
avoid confusion and keep progress transparent.
Table 1. Some examples of openers used in various sub-modes of the ‘assign UC’ mode.
Role Interaction type Opener
Game master Directive Start mode for UC determination for fact type
Inf. analyst Proposition Consider the following fact statements: …
Inf. analyst Question Can these statements occur together?
Inf. analyst Proposition There is a UC on role(s) … of the fact statement
Domain exp. Answer No.
Domain exp. Answer Yes.
Game master, Question I have a question: …
Domain exp., (generic)
Inf. analyst
Domain exp. Disagreement I disagree, because …
Inf. analyst (generic)To keep a clear overview of openers to choose from at a certain point in the game,
but also to impose focus and maintain a certain level of control, openers available for
use at a certain moment are restricted by the role of the player who intends to make
the dialog move, and the mode that is currently active. As a limited example, Tab. 1
shows some typical openers from various phases of the ‘assign uniqueness
constraints’ FoCon, including the roles to use them and the interaction type they fall
under. The bottom two examples are generic, while the others are more specific for
one or more (UC related) modes.
Let us now turn to the way this design was implemented in a prototype dialog
game system. We will only consider the main functionality of the system here, i.e. the
actual dialog game. For reasons of space, we discard functionality concerning ‘project
and discussion management’ and ‘user and game role management’, which is fairly
straightforward.
The prototype was developed using two components: Microsoft SQL Server 2008
as database management system, and Microsoft Visual Studio with the visual basic
dot net (VB.Net) language to develop the windows application. The connection
between the windows application and the database was done by using an ODBC
connection.
Figure 1. UC determination Deep Interface, the main window of the prototype.
The dialogue game deep interface consists of three forms, one for each main
FoCon or sub-game in the FCO-IM procedure. Each form consists of two parts. The
left part is used to enter the conversation (for each user, switching between them).
The right part is used to show the conversation log of the game. Fig. 1 shows the deep
interface (see section 2) of a UC determination dialogue game; the ‘surface interface’,
introducing more advanced and efficient interaction and visualisation, was not
included in this prototype.The left part of the form consists of the population of User Name, Mode Number
(named Phase Number in the screenshot), Mode Description, Interaction Type, and
Opener. Mode Number is used to filter what interaction types and openers are
available for the current mode in the discussion. For each user name and its related
discussion role, there can be a unique interaction type on different mode numbers.
The mode number can only be changed by the game master since she is the one who
guides the discussion and determines its focus. However, if required, the filter can be
temporarily removed, allowing players to use all openers of all modes in the game.
For each FoCon, there are several groups of openers which require different types
of input fields used to insert the free text part(s) following the openers. These free text
parts are used to show known elements of the model (or derivatives thereof) required
in some specific statements and questions. For example, they hold two fact statements
that are to be compared. In the prototype, the elements have to be entered manually;
in future versions, such elements could be imported straight from a model repository.
If there is one free text part, one input field is enabled; if there are two free text parts,
two input fields are enabled, and so on.
All inserted conversations are logged (showing a timestamp and the user entering
the entry) and can be viewed through the data grid on the left side of the form. In
Table 2, a short but representative part of a test dialogue for ‘UC Determination for
fact type’ is shown.
Table 2. A part of the log for a session in the UC Determination mode
2010-09-13 Information Analyst [Question] Can these statements occur UC-D-FactType
23:53:29.563 together?
[First Statement: Student Peter Johnson
lives in New York];
[Second Statement: Student John Peterson
lives in New York]
2010-09-13 Domain Expert [Answer] Yes UC-D-FactType
23:53:40.633
2010-09-13 Information Analyst [Decision] There is no UC on role 2 UC-D-FactType
23:54:00.947
2010-09-13 Information Analyst [Question] Can these statements occur UC-D-FactType
23:54:32.667 together?
[First Statement: Student Peter Johnson
lives in New York];
[Second Statement: Student Peter Johnson
lives in Houston]
2010-09-13 Domain Expert [Answer] No, because one only can live in UC-D-FactType
23:55:01.990 one city
2010-09-13 Information Analyst [Decision] There is a UC on role 1 UC-D-FactType
23:55:17.980
2010-09-13 Game Master [Directive] The session for UC UC-D-FactType
23:55:29.443 determination for this fact type is finished
Following its initial implementation, the prototype was tested in an elaborate
session with three students (not otherwise involved in the project but familiar withFCO-IM) who took turns in playing the ‘information analyst’ and ‘domain expert’
(switching roles after each main FoCon ended). One of the researchers acted as ‘game
master’. After the test, improvements were carried through. Next, the system was
tested one final time in another, more limited session not involving ‘external’ people.
The initial, elaborate game session in particular aimed to capture the response of
the participants when they played the dialogue game for FCO-IM, and also to get
some feedback from the participants in order to refine the dialogue game system as
such. The complete session took two hours in total. It led to the following relevant
improvements of the system (we disregard technical problems and debugging):
1. The openers were refined by replacing the initial ‘dotted blanks’ in statements
(as still shown in Table 1) with more explicit indications: [Expression 1], [Expression
2], etc. This improved clarity for players.
2. The users had no trouble using the openers in the Fact Statement and UC
Determination modes. However, the Classification and Qualification modes were
problematic in their current form. Questions that can be asked by the information
analyst are more open than in the other phases. The modeller could use several
openers provided in the prototype in common cases of classification and qualification.
However, if a special case was encountered, such as semantic equivalence, the
questions to be asked by the modeler are highly dependent on the context of the case
itself. We conclude that this mode needs to be reconsidered and redesigned.
3. Various terms used in openers (even quite basic ones like “class”,
“classification”, and “qualification”) were too difficult for the players to be
understandable and usable in the game. It seems recommendable to either rephrase
them in more accessible language or form, or alternatively to much more elaborately
instruct the players (probably in advance). We lean towards the first option.
4. The users found it difficult to follow the flow of the game (switching between
modes), since users (in particular when acting as ‘information analyst’) were
insufficiently familiar with the dialogue game modes and their underlying procedures.
A possible solution might be for the game master to more actively engage in
facilitating the process (not unlike in the GMB dialog game; in fact, perhaps the roles
of information analyst and game master could be merged). However, simplifying the
game is another viable option (in line with 3. above). Even more than in the case of 3.,
very elaborate instruction of the players seems undesirable, since the game is intended
to, eventually, support the modelling process, not vice versa.
4 Conclusions and Further Research
We are quite aware that in its current form, the prototype comes nowhere near
providing realistic support for FCO-IM modeling. In fact, we did not expect it would.
We are merely exploring principles of shaping and structuring the act of modeling.
However, we managed to take a first, substantial step in taking the existing FCO-IM
modeling procedure and transforming it into something that is the basis for a
‘collaborative system’ in the sense of [17]. Expected advantages of such an approach
(when successful) are:1. Complete records of the conceptualization of the model, including rejected
options and modifications, and also (importantly) all communication about the
model (including rationales for modeling decisions). This is useful for later
reference, but also for systematic analysis of the interactive process of modeling
in view of improvement of the process. In this sense, dialog games as discussed
here are perhaps mostly a means for developing more evolved approaches rather
than a definite solution.
2. The use of foci or ‘modes’ in a framework for enactment of conceptualization
reflects the natural way of thinking (not just ‘model editing’) that occurs in most
if not all collaborative conceptual modeling efforts. The way the modes are
managed and deployed makes it possible to strike a balance between providing
structure and allowing for a degree of freedom (ad hoc initiative and liberal
iteration), as required by the nature of collaborative modeling.
3. The dialog frame can in principle be used as a basis for much more advanced
interactive systems, combining accumulated findings of various experimental
games into a generic, deep interface system that can be parameterized, and
augmented with elaborate surface interface functionality. Importantly, the deep
structure interface can thus be combined with existing surface structure
functionalities like advanced editors, verbalizations, user friendly forms, etc.
Looking at our first prototype, we conclude that simplification is the main goal for
improvement. Usage of specialized FCO-IM terms in focus questions (and set
answers) should be minimized. Some parts of the FCO-IM modeling practice might
be simplified, not just by reducing the use of specialized terms involved, but also by
defining even smaller, more understandable and focused steps and providing clear-cut
and ‘natural’ examples during the game. Other parts might be supplemented with
hints, heuristics or more detailed guidelines. The current prototype was only a first
attempt to capture the existing FCO-IM procedure in a dialogue game. Simplification
certainly is a challenge, which does not so much concern the general setup of the
dialog game system with its modes and openers, but the FCO-IM modeling procedure
as such. Indeed, we intend the dialog game framework to be a platform for studying
and improving procedures for conceptual modeling.
This is not to say that the general setup should not also be improved. Main
limitations of the prototype (and directions for improvement) include the following:
• The system is not actively and automatically linked with a real model repository.
Doing so would greatly improve the functionality and efficiency of the game.
• In the InterLoc system, a threading mechanism is available, providing very
helpful additional structure in the dialog log and greatly aiding navigation and
analysis. Since it has been observed that players indeed like to refer back to
previous statements whilst playing the game, threading and other navigation aids
would be a substantial improvement.
• Obviously, it is desirable to generate verbalizations and visualizations based on
the model elements gathered in the repository. However, such items should be
made available only if they are really helpful. For example, overly complex
diagrams should not be shown to players who have no grasp of them, since this
would only confuse them and create information overload. Focus remains
important.• Even more obviously, any realistic version of the dialog game requires a
distributed, multi-client implementation – as is already present in the InterLoc
system.
• Currently, the game master has to know everything about the modes and their
required succession. Intelligent aids (based on formalized and decidable rules)
may help a game master to master the game, lowering expertise needed to
facilitate a game session.
Given various non-trivial aspects of the conceptualization of properly formalized
models, there will doubtlessly be limits to making such a process accessible and
‘disintermediated’. Nevertheless, we do believe that considerable progress can be
made in this respect. Clear and effective interplay between the differentiated roles
involved, and adjusting the games to the skills and knowledge of typical people
playing these roles, may seriously improve the effective organization of interaction
between participants in FCO-IM and other conceptual modeling sessions.
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