Introduction and definition

The English sayings “two heads are better than one” and “too many cooks spoil the broth” give an idea of the expectations that arise from a collaboration of people. On the one hand, one would expect that a group of people is able to better observe and perceive situations as well as to make better decisions than a single person would be able to. On the other hand, it is also common knowledge that the collaboration of several people entails the problem of group coordination, which, if disregarded, can make group work inefficient, compared to the work of a single person.

There are three kinds of problems that are typically approached by groups:

1. cognition problems, problems with a definite solution or a set of solutions that are certainly better than others;
2. coordination problems, problems that require the group to figure out how to coordinate the behaviour of its members;
3. cooperation problems, problems which feature the involvement of several self-interested, distrustful people who have to work together.

Collaborative modelling refers to a process where a number of people actively contribute to the creation of a model. The weakest form of involvement is feedback to the session facilitator, similar to the conventional way of modelling. Stronger forms are proposals for changes or (partial) model proposals. In this particular approach the modelling process should be supported by a combination of narrative scenarios, modelling rules, and e-Participation tools (all integrated via an ICT e-Governance platform): so the policy model for a given domain can be created iteratively using cooperation of several stakeholder groups (decision makers, analysts, companies, civic society, and the general public).

As a matter of fact groups require rules (or cultural norms) to maintain order and coherence, as well as diversity and independence of its group members in order to create a kind of a collective intelligence. Bringing together people with diverse perspectives and backgrounds for working together in multi-disciplinary teams is expected to improve the overall group performance, so the first issue on which the collaborative process should be based is the definition of a shared modelling rules framework (the social norms), guiding the modelling team in determining whether a proposal is accepted or rejected. Two usually adopted types of rules are:

1. Rules of majority, where a certain number of group members had to support or oppose a proposal in order for the whole group to accept or reject it (e.g., more than half). A tie-break rule was sometimes specified (e.g., for the case of an equal number of supporters and opponents). The tie-break could involve seniority issues.
2. Rules of seniority, where the weight of a group member’s support or opposition was related to his or her status within the group. This status could be acquired (e.g., by experience) or associated with a position to which the member was appointed. A frequent example of this was the case of a more experienced modeller who was considered as the leader by the group and took decisions on their behalf. The other members filled the role of consultants in such a case.

These rules were sometimes set up explicitly before the group began their work, or in an early phase of this work. But in most cases they rather emerged as the result of each member’s behaviour. Individuals making regular contributions of high quality were likely to acquire seniority. In homogeneous teams majority rules were used more often.

Why it matters in governance

From a very high level of abstraction, collaborative modelling itself can be seen as a social interaction between several people, while these people who together perform the modelling process form a social entity. Thus, the process of collaboratively defining and implementing a model, with a particular reference to the public policy modelling, is strictly connected with the public aspect of every citizen’s life, starting from the communities bridged by the decision makers that collaboratively define some policies, to an average citizen which interacts with other citizens within the rules framework defined by the policies themselves.

Starting from the needs perceived by the citizens, the limitations of existing modelling techniques adopted in policy making include the following issues:

1. Changing models is too time-intensive and integrating to other diagrams is difficult. Also there are version control problems.
2. It is not possible for more than one person to work on the same diagram at the same time.
3. Modelling has to be done at the specific location where the modeller is present.
4. Contribution to the model comes from those interviewed or at a group meeting, limiting the potential contribution from a larger group.
5. Low model acceptance: the model resulting from the modelling session is not supported by some of the stakeholders.
6. Participants feel misunderstood: as a consequence of bad elicitation or a wrong understanding of the model.
7. Low perceived model quality and limited model comprehension: Individuals do not fully understand the model or do not agree with it.

Reasons that argue for conducting policy modelling in a collaborative manner are:

1. No person typically understands all requirements and understanding tends to be distributed across a number of individuals.
2. A group is better capable of pointing out shortcomings than an individual.
3. Individuals who participate during analysis and design are more likely to cooperate during implementation.

Collaborative modelling calls for the definition of the citizen’s role in the public policy modelling process (e.g.: the mass participation issues and processes have been already researched in depth by the e-Participation research programs). In order to guarantee participation there are some prerequisites that should be fulfilled:

1. all citizens who access ICT services in order to participate should represent the views of communities affected by the given policy;
2. all citizens are able to take part in the modelling process via intuitive IT systems that enable them an effective and efficient contribution;
3. all citizens possess proper skills (or are assisted) to purposely follow a process of group model-building in order to avoid/abate wrong mental models and thus ultimately reach a shared vision of the problem. 

Current Practice and Inspiring cases

In current practice, collaborative modelling is mainly performed offline; still the rules and guidelines for session processes are not yet sufficiently widespread. In fact, the abatement of wrong mental models and the creation of knowledge from information usually imply the dialogue of people with different views of the problem as well as the need for critical skills. Further to that, the information that occurred in a discussion has to be grounded and definitively transferred to the formal model. Thus, e-Participation might be of help in achieving a critical mass of data and information exchange online but in itself does not solve the problem of mass cooperation and collaboration in a formal modelling process. Even more, the participation in this process entails, at present, a thorough knowledge on modelling processes or tools that an average citizen does not have. Therefore, there is an urgent need for Intuitive Interfaces, Modelling Wizards and guided simplified approaches to modelling. Starting from the relevance of collaborative modelling in policy making, as a very former inspiring case Maarten Sierhuis and Albert M. Selvin, working at NYNEX Science & Technology Inc in New York, presented in 1996 an applied research report on “Towards a Framework for Collaborative Modelling and Simulation”, describing methodologies for modelling and simulation in a collaborative analysis or design project, and describing a case study in which Conversational Modelling, a software-supported technique for collaborative modelling, enabled participants to construct static knowledge models in collaborative sessions. The sessions described in the report resulted in the identification of 207 queries. Of these, 24 were chosen for detailed modelling. As a result of the modelling, 44 resources, 29 knowledge items, 58 data items, and 8 organizational issues were identified. The response from participants was positive. Many stated that they had learned more about each others’ work in the conversational modelling sessions then they had been able to in the course of their normal work activities. The development organization has been able to use the output of the sessions to generate design requirements. A picture of the interface (figure 6) used during the sessions follows.

Figure 5: Conversational Modelling Interface

As more recent inspiring case, one can refer to the results of the FP7 projects OCPOMO2 or PADGETS3. This last one, PADGETS, aims at bringing together two well established domains, the mashup architectural approach of web 2.0 for creating web applications (gadgets) and the methodology of system dynamics in analyzing complex system behaviour. The objective is to design, develop and deploy a prototype toolset that will allow policy makers to graphically create web applications that will be deployed in the environment of underlying knowledge in Web 2.0 media. The project introduces the concept of Policy Gadget (PADGET) – similarly to the approach of gadget applications in web 2.0 – to represent a micro web application that combines a policy message with underlying group knowledge in social media (in the form of content and user activities) and interacts with end users in popular locations (such as social networks, blogs, forums, news sites, etc) in order to get and convey their input to policy makers.

Figure 6: the PADGET Framework

A PADGET is composed of four main components:

1. A message, that is a policy in any of its stages and forms
2. A set of interaction services, that allows users to interact with the policy gadget (find it, access its content, comment its content, share it etc.). These interfaces may be provided by either the underlying social media platforms in which the PADGET Campaign is launched or by the PADGET itself when it takes the form of a micro application (i.e. in the case of the iGoogle gadget).
3. The social context, that is the framework describing the social activity and content relating with the policy gadget in each individual social media platform where the policy gadget is present.
4. The decision services, which are offered by two modules. The PADGETS analytics and the PADGETS simulation model. The decision services component is responsible for the generation of the information outputs to be presented to the PADGET initiator (usually a policy maker).

PADGETS will use publicly available APIs for interconnecting, publishing and retrieving content from underlying social media platforms. The collected information and user activities that policy gadgets invoke in the media platforms will be categorized using semantic tags as to their relation to the policies in order to help the policy maker form an opinion about what the users think about relevant issues and policies.

Available Tools

Research about collaborative software has been conducted since the mid 1980's, when computer-human interaction, office automation, and support for group work became the focus of research projects. The term computer-supported cooperative work (CSCW) was first used in 1984 and focused on the support of small groups of people. Other terms are used as synonyms for CSCW, especially: collaborative computing, computer mediated communication, and group decision support systems. CSCW is defined as a “computer-assisted coordinated activity such as communication and problem solving carried out by a group of collaborating individuals" or as a system, which “looks at how groups work and seeks to discover how technology (especially computers) can help them work". The term groupware also stems from the 1980's and is defined as “computer-based systems that support groups of people engaged in a common task (or goal) and that provide an interface to a shared environment". Interestingly, some authors see groupware as advanced software that has to provide awareness support, while other authors also understand code management or emailing as groupware systems. In contrast to groupware, CSCW does not only comprise technological aspects of collaboration, but also incorporates psychological, social, and organizational effects.

Collaborative technologies, especially in the field of groupware and CSCW, are typically classified using the time-space taxonomy which distinguishes between communication that occurs at the same space or concurrently at different spaces, and communication that occurs in the same time (synchronously) or in different times (asynchronously). This view was established in 1988 by R. Johansen (“GroupWare: Computer Support for Business Teams”, The Free Press, New York) and taken on in various related publications. The following figure depicts the typical time-space matrix as presented in these publications.

Figure 7: the Time-Space Matrix

The matrix divides collaborative technologies into four possible constellations, while each of these constellations can be supported better or worse by different communication media.

By the way the architecture of a collaborative modelling tool, i.e., a system that supports a group in developing models, is still under investigation. Some authors have suggested groupware systems that help teams in collective sense-making which is an important part of the modelling process. Conklin, Selvin, Buckingham and Sierhuis in “Facilitated Hypertext for Collective Sensemaking: 15 Years on from gIBIS”, a paper presented in 2003 during the 8th International Working Conference on the Language-Action Perspective on Communication Modelling (Tilburg, The Netherlands), reports on an approach, Compendium, that is the result of 15 years of experience. Compendium combines three different areas: meeting facilitation, graphical hypertext and conceptual frameworks. To make them work, facilitation is viewed as essential to remove the cognitive overhead for the group members. As groupware systems address the important issue of collective sense-making they can be used as the core of a collaborative modelling tool. So far these systems are typically tailored for specific modelling languages though. For a collaborative modelling tool they need to be more modular so that any modelling language can be “plugged in” (e.g., other enterprise or information systems modelling languages). In addition, there is also the need for a negotiation component that facilitates structured arguments and decisions regarding modelling choices. Based on this reflections and issues, recently two tools are emerging:

The COllaborative Modelling Architecture, COMA4, allows group modelling. Any group member can work on the models whenever it suits them. Any participant can contribute in the way they can: by just looking at proposals and commenting them, by making minor changes to them or maybe even by making their own proposals. The facilitator can see the status of the modelling process at any time and can decide whether a certain proposal should be adopted or needs improvement based on the comments by the other group members and his own judgment.

Figure 8: COMA, COllaborative Modelling Architecture

COMA's design has been inspired by theoretical insights from organizational semiotics and driven by observations of group modelling behavior. The tool is implemented in Visual C++ 2005 on Windows based on the UML Pad and with the wxWidgets GUI library5.

The OCOPOMO eParticipation platforms, deployed by Open Collaboration for Policy Modelling FP7 project, that will end in December 2012.

Figure 9: OCOPOMO eParticipation Platform

The platform is a suite of ICT tools for:

1. Iterative development of policies in a form of narrative scenarios;
2. Policy modelling, creation of agent-based formal policy models;
3. Open and transparent collaboration in the process of policy development;
4. Seamless, goal-oriented information exchange between all the stakeholders (policy analysts, operators, decision makers, wider interest groups, general public, etc.);
5. Simulation and visualisation of policy alternatives and their consequences;

A First prototype was released in autumn 2011 and tested on a 1st round of pilot applications started on winter 2011. 2nd pilot applications and evaluation will start in autumn 2012, and the platform will definitely released in December 2012.

Key challenges and gaps

This research challenge is connected to the research on Web 2.0 and the next generation web. As far as the Policy Modelling in Governance is concerned, this research challenge bridges the gap between citizens and decision makers. It permits an early stage evaluation of the decision maker mental models by opening a dialogue with citizens and allows for an exchange of perspectives. It finally enables the collaboration in the public policy modelling process with the use of a rigorous and formal scientific process.

Current research

According to current research, the following issues are being explored:

1. Group model building and systems thinking, focusing on models when tackling a mix of interrelated strategic problems to enhance team learning, foster consensus, and create commitment; although people have different views of the situation and define problems differently, this current field of research shows that this can be very productive if and when people learn from each other in order to build a shared perspective.
2. Web 2.0 tools for collaboration, as recently pointed out in the FP7 project OCOPOMO (Open Collaboration in Policy Modelling), which aim to implement collaborative scenario building and policy modelling via an integrated ICT toolbox. OCOPOMO provides an innovative "off the mainstream" bottom-up approach to policy development, combined with advanced ICT tools and techniques supporting open collaboration. The project is developing an ICT-based environment integrating lessons and practical techniques from complexity science, agent based social simulation, foresight scenario analysis and stakeholder participation in order to formulate and monitor social policies to be adopted at several levels. The project is co-funded by the European Commission under the 7th Framework Program, Theme 7.3 (ICT for Governance and Policy Modelling).

Future research

Future research should therefore focus on:

1. Collaborative Internet-based modelling tools, allowing more than one modeller to cooperate, at the same time, on a single model.
2. Definition of frameworks allowing even “low-skilled” citizens to provide their contribution (even if in a discursive way) to the modelling process.
3. Design of more intuitive and accessible Human-Computer Interfaces.