Shun Shiramatsu
email: siramatu@nitech.ac.jp

Teemu Tossavainen
email: teemu.tossavainen@aalto.fi

Tadachika Ozono
email: ozono@nitech.ac.jp

Toramatsu Shintani

Towards Continuous Collaboration on Civic Tech Projects: Use Cases of a Goal Sharing System Based on Linked Open Data

Keywords: Linked open data, civic tech, hackathon, public collaboration, open innovation

Civic hackathon is a participatory event for prototyping of innovative services through collaboration between citizens and engineers towards addressing social issues. Although continuous contributions are needed for improving the prototypes and for applying them to social issues, participants frequently stop contributions after the hackathon due to their day job. To address this problem, we applied our Web system, called GoalShare, which gathers linked open data (LOD) of hierarchical goals to address social issues, to civic hackathons held in the city of Nagoya in Japan. We compared goal structures between two situations. The results showed that goal structures input by team members themselves with enough instruction time were relatively detailed but varied widely among teams, and those input by a single GoalShare user with limited time remained at a simple overview level but had uniform level of detail. A more user-friendly interface usable without instruction is required for real-world situations.

Introduction

Coverage of local government services in Japan is at risk of shrinking due to ongoing social issues that threaten the sustainability of regional societies, e.g., the aging population, disaster risks, and dilapidated infrastructure. In this context, public collaboration between broad citizens, local government officers, local companies, experts, and engineers has become more important to address social issues. Actual instances have arisen of addressing social issues by utilizing open data and mobile applications [START_REF] Sandoval-Almazan | Open government 2.0: Citizen empowerment through open data, web and mobile apps[END_REF] with smartphones, which are now widely used by citizens. Civic Tech refers to an activity for applying information technology to addressing social issues through collaboration between engineers, citizens, and local governments [START_REF] Pyrozhenko | Implementing open government: Exploring the ideological links between open government and the free and open source software movement[END_REF]. In Japan, the Civic Tech movement has been rapidly growing since around 2013.

Collaboration between a wide range of citizens is needed for addressing social issues using a civic-tech approach because engineers alone cannot design solutions without background context and because stakeholder citizens alone cannot utilize information technology. For example, local community managers and local IT companies are desired to participate in civic tech projects. Public outreach of contextual information on project activities is indispensable for getting a broad range of citizens to participate. The outreach of visions and approaches to addressing social issues facilitates collaboration with newly-arrived participants.

We have been developing a Web application called GoalShare for sharing such contextual information about collaborative activities by using linked open data (LOD) consisting of social issues and their solutions as goal hierarchies [START_REF] Shiramatsu | A Goal Matching Service for Facilitating Public Collaboration Using Linked Open Data[END_REF][START_REF] Tossavainen | Implementing a system enabling open innovation by sharing public goals based on linked open data[END_REF].In this paper, we describe our application of GoalShare to civic hackathons organized by civic tech communities. A hackathon, a coined term consisting of "hack" and "marathon," refers to a participatory event for prototyping services or applications in a short period such as over the weekend or for several hours. Civic hachathon [START_REF] Johnson | Civic Hackathons: Innovation, Procurement, or Civic Engagement?[END_REF] is a type of hackathon that is for prototyping civic tech applications. Figure 1 shows the typical flow of civic hackathons. Because outcomes of a civic hackathon in a short period tend to be an early prototype, continuous development is needed for applying the outcome to addressing real-world social issues. However, initial members frequently drop out of their project after a hackathon event due to the busyness of their day job. Contextual information on project activities needs to be disclosed and new participants need to be found to continue a project for improving the prototype as an outcome of a hackathon. Data on progress management and information sharing between project members should be reused for disclosing such contextual information to the public.

We applied GoalShare to two civic hackathons held in Nagoya city in Japan. This paper presents our qualitative analysis of difference in goal hierarchy data between a case of inputting by members of hackathon teams and a case of inputting by an audience who listens to the final presentation of hackathon teams. We seek improvement in GoalShare for collaborating on Civic Tech projects. Concretely, we consider a function for a tagging skill set to goal data and person data for matching a goal and a person.

Context of This Study

Civic Tech Organizations in Japan

Code for Japan1 , which is inspired by Code for America2 , was launched in 2013 [START_REF] Takagi | Research note: An introduction to the economic analysis of open data[END_REF]. Code for Japan collaborates with local organizations called "brigades" around the country. As of March 2015, 28 official brigades of Code for Japan have been registered. In this study, as we will describe later, GoalShare is used in civic hackathons organized by Code for Nagoya3 , which is one of the official brigades of Code for Japan. The Open Knowledge Foundation Japan4 and Open Street Map Foundation Japan5 are also active in Civic Tech in Japan.

On March 2015, Civic Tech Forum 20156 was held in Tokyo, and over 300 people participated. The invited speakers of the forum were from the brigades of Code for Japan, research institutes, local non-profit organizations, and local companies that are related to Civic Tech.

Systems for Sharing Issues and Ideas

Civic Tech Issue Finder7 is a system for sharing civic tech issues and for supporting collaboration provided by Code for America. Issues in this service are stored as GitHub Issues with the tag "Help Wanted." GitHub8 is a widely used Web repository for source code.

Knowledge Connector9 provided by the Ministry of Economy, Trade and Industry of Japan and LinkData [START_REF] Shimoyama | Linkdata.org synergistically associating rdf data repository and application repository stimulates positive feedback of mutual developing data applications[END_REF] is a Web platform for supporting commercialization of ideas that utilize open data [START_REF]METI: Supporting business creation with utilizing open data: Launch of "knowledge connector (β version)[END_REF]. It has a functionality for structuring events, organizations, ideas, datasets, issues, and subsidy programs.

Code for Kobe10 and Code for Japan are also planning to develop a Web system consisting of a "person finder" and "project finder" for Civic Tech activities in Japan.

Although the focus of this paper is close to the purpose of these systems, the originality of GoalShare is goal hierarchies as scenarios for addressing issues linked with existing SNSs and geographical datasets based on the LOD framework. The interoperability of the LOD framework can provide the possibility to link the dataset of GoalShare with those of the aforementioned systems in the future.

Our Previous Study: Data Model of Goal Hierarchy

We have developed a Web application called GoalShare 11 , which has a backend dataset based on the data model shown in Figure 2. The class socia:Issue represents the social issue, and socia:Goal represents the public goal as the solution of issues in this figure. The prefix "socia," which corresponds to the namespace http://data.open-opinion.org/socia-ns#, is prepared for the data model that we designed. This data model is designed to satisfy the following requirements.

Context of agents:

Represented by the link to people or organizations, e.g., those who wish for the goal or who participate in it. URIs of existing social networking services (SNSs), such as Facebook and Twitter, are used for linking to agents. The context of super/subgoals was represented by the property socia:subGoal enabling users to organize a goal hierarchy and to break down each goal into subgoals close to concrete actions. Concrete subgoals also enable citizens to consider which subgoal they can participate in or contribute to. Moreover, when concrete subgoals are not agreed on by multiple participants even if a final abstract goal is generally agreed on by them, visualizing their goal hierarchies has the potential to support building a consensus about their differences and to compromise on their collaboration. Furthermore, the properties socia:status and socia:completedDate for the context of progress enable users seamless reuse of data across managing progress and sharing the current status of the project with new participants or potential collaborators because the values of socia:status ("Not-Started," "InProgress," "Aborted," and "Completed") represented by colors of goal nodes can support grasping which subgoals are currently in progress, which ones are not started yet, and which ones are already completed. These features enable new participants to grasp a current context of projects easily.

Facilitating Collaboration on Civic Tech Project

There are two types of participation in Civic Tech: one is voluntary participation such as with aforementioned brigade organizations, and the other is participation with fellowship programs. The voluntary participants, in particular, sometimes drop out of their project due to the busyness of their day job. For continuous progress of civic tech projects based on voluntary participation, we need to open a gate for new participants with the transparency of contextual information about "what the project members are trying to do" and "which subgoals the new participant can contribute to." Such transparency enables new project members to make a match between themselves and partial subgoals of the project.

Here, we deal with the possibility of match making between new participant a and a concrete goal g, where g is a partial subgoal of an abstract supergoal g 0 . In this situation, a and g could collaborate when they satisfy one or more of the following conditions. In this study, we developed a function for matching a and g based on (a) the similarity of goals [START_REF] Shiramatsu | A Goal Matching Service for Facilitating Public Collaboration Using Linked Open Data[END_REF]. Many prototypes implemented in civic hackathons could have slept without brushing up because many civic hackathons have been held since around 2013 in Japan. If such a situation is true, the matchmaking function based on (a) can enable hackathon participants to reorganize their team for continuous acitivity. Moreover, we need to consider the matchmaking function based on (b) the complementarity of resources that was not dealt with in this study. In particular, we will consider the complementarity of skill sets for civic tech in a later section.

Trial Use in Civic Hackathons

We tried to apply the GoalShare to two actual civic hackathons; the Hackathon on Barrier-free Underground Mall at Nagoya Station14 held at October 2014 and the Hackathon on International Open Data Day 2015 in Nagoya 15 . These hackathons were organized by the Code for Nagoya and the non-profit organization Lisra. Hereafter, the former one is called the barrier-free hackathon, and the latter one is called the ODD hackathon. The barrier-free hackathon was held on both days of a weekend. The goal hierarchies were input in a debate between members of each participating team themselves. On the other hand, the ODD hackathon was held on just one day. The goal hierarchies were input by a member of the audience for the final presentation of each team. These situations are summarized in Table 1.

Figures 4 and5 show goal hierarchies accumulated in each hackathon. The blue nodes represent ongoing goals, and the orange ones represent not-yet-started goals. Both of the goal hierarchies have top goals that correspond to a given theme of the hackathons and the direct subgoals of the top goals that correspond to the final goals participating teams in the hackathons.

Case of barrier-free hackathon

In the barrier-free hackathon, members of four participating teams input goal hierarchy data of each team by themselves. After idea generation and team building, team members first wrote their goals for development on sticky notes and organized them into a hierarchy on a paper. Figure 3 shows examples of goal hierarchies created through debate between team members participating in the barrier-free hackathon. After creating the goal hierarchies consisting of sticky notes, they input the data into GoalShare. With consideration for ensuring time for development, an organizer of the barrier-free hackathon announced that subgoals after the fourth layers of the goal hierarchies on a paper could be omitted when inputting the subgoals into GoalShare.

As shown in Figure 4, the minimum count of goal nodes for each team was one, and the maximum count was thirteen. Although this difference was affected by the context thats the team inputting minimum nodes consisted of foreign students and that the instruction about GoalShare was spoken in Japanese, this result indicates that data input by hackathon participants themselves tended not to be uniform in quality.

Case of Open Data Day hackathon

In the ODD hackathon, the time for instruction of GoalShare and for inputting of goal hierarchies was not provided to avoid reducing time for implementation. The reason was that the available time was less in the ODD hackathon than that in the barrier-free hackathon. As an alternative, one of the audience members for the final presentation given by seven participating teams input the goal hierarchies of each team. This goal inputter was proficient in the use of GoalShare.

The number of goal nodes for each team was about three or four because the presentation time for each team was short (about five minutes), with the exception of a team "Fat or Walk" in which the goal inputter participated. It is because the goal hierarchy of "Fat or Walk," the exceptional team, was cre-ated before the final presentation. Although the goal hierarchies of the other six teams were commonly abstract and their socia:wisher properties tended to be anonymous, such outline information can be used for considering the participation in the project by new candidate participants. Moreover, the blue nodes, which represent the ongoing subgoal with the property socia:state, in the ODD hackathon were more numerous than those in the barrier-free hackathon. This result indicates that data gathering from the final presentation of the hackathon by a proficient user can be the second best solution in cases where hackathon events cannot provide time for discussion and planning.

Discussion: Towards application to real-world situations

The aforementioned cases of trial use of the GoalShare indicate that a more user-friendly interface usable without instruction time is desired for real-world operations because organizing multiple days such a civic hackathon event is generally difficult. Because the main purpose of the civic hackathon is generally prototyping of an innovative service for social issues, the time for sharing goals should not interfere with the time needed for development more than necessary. We are currently implementing a more intuitive user interface, shown in Figure 6. This interface is designed using the metaphor of sticky notes, which is familiar to citizen participants in public workshops. This design of the user interface also considers remote and realtime co-authoring being implemented using the Google Hangout API.

Alternatively, a hybrid approach to inputting goal data through an interaction between team members and a proficient user in structuring goal hierarchies Fig. 6. The user interface designed using the metaphor of sticky notes after the presentation time can be considered for improving data quality. Although goal hierarchies input only by team members themselves are not uniform, the process for structuring goals by themselves is valuable for sharing detailed scenarios for addressing social issues. To attract new collaborators into a team after an event, concrete subgoal trees as a scenario to address a socia issue should be shared with potential collaborators. An interaction between team members and a proficient user in structuring goal hierarchies can improve the quality of goal hierarchies, and it does not disrupt development if the interaction is conducted after the final presentation. Moreover, a function for generating summary text of a goal hierarchy is desired to be provided to enable potential collaborators to understand the team's approach. Furthermore, recruiting new participants in the team building process (including after a hackathon event) needs complementarity of resources, e.g. a dataset or skill set, although we used GoalShare only just after team building in the aforementioned hackathon. We need to extend the data model shown in Figure 2 to enable us to describe a skill set as human resources. Figure 7 shows an extension of the properties connected to socia:Goal class and foaf:Agent class. The class socia:SkillTag represents the skill, and its super class socia:ResourceTag represents the general resource. The property dcterms:requires 16 connects with socia:Goal, and the aforementioned classes correponding to resources. Resources or skills owned by agents are represented by the property schema:owns 17 .

Figure 8 shows our extended Web interface of GoalShare to enable users to add skill tags to each goal node, and Table 2 shows an example of the inheritance relationship between skills. Such interface and data structure can be used for matchmaking algorithms if a skill ontology can be prepared. Therefore, we need to consider how to build a skill ontology. For example, we will consider a subgraph extraction from general-purpose ontologies such as DBpedia 18 to build a skill ontology.

Conclusion

We presented four requirements for designing a linked data model of goal hierarchies to facilitate collaboration in Civic Tech projects. We applied GoalShare to two actual civic hackathons held in Nagoya in Japan and qualitatively analyzed the differences in goal hierarchies between a case of inputting by members of hackathon teams and a case of inputting by an audience that listens to the final presentation of hackathon teams. These cases indicate that a more user-friendly interface usable without instruction time is desired for real-world situations. We presented a prototype of a more intuitive user interface designed using the metaphor of sticky notes, which are familiar to citizen participants in public workshops. Alternatively, to improve data quality, we considered a hybrid approach to inputting goal data through an interaction between team members 16 http://purl.org/dc/terms/requires 17 http://schema.org/owns 18 http://dbpedia.org/ and a proficient user in structuring goal hierarchies after the presentation time. Moreover, we considered an extension of our data model to deal with complementarity of skill sets that is important for Civic Tech, and we extended our Web interface for adding skill tags to each goal node.

In the future, we plan to integrate the similarity of goals and the complementarity of resources for improving the function to match citizens and Civic Tech projects. Moreover, we will apply a new intuitive user interface to goal input in the short final presentation of civic hackathons. The realtime co-authoring mechanism of the new user interface will be applied to an interaction between team members and a proficient user in structuring goal hierarchies after the presentation time.

Fig. 1 .

 1 Fig. 1. Typical flow of civic hackathon

Fig. 2 .

 2 Fig. 2. Data model for public goal hirarchies as solutions of social issues

( a )

 a Similarity of goals Goals or issues focused on by agent a are similar to goal g. (b) Complementarity of resources Agent a can provide resources (including skills as human resources) required to archive g.

Fig. 3 .Fig. 4 .Fig. 5 .

 345 Fig. 3. Goal hierarchies written and structured by participants in the barrier-free hackathon

Fig. 7 .

 7 Fig. 7. Extension of data model to deal with skill set as human resources

Fig. 8 .

 8 Fig. 8. Web interface of GoalShare extended to append skill tags

Table 1 .

 1 Differences in situations between two hackathons

	Hackathon	Barrier-free hackathon	ODD hackathon
	Event period	Two days	One day
	Time for instructing	About 15 minutes	Cannot be ensured (0 minutes)
	usage
	Inputter	Team members themselves	A single participant trained in
			the usage of the GoalShare
	Way to structure	Structuring collaboratively be-	Structuring by a single inputter
	goal hierarchies	tween team members using	only with the GoalShare during
		sticky notes before inputting	five minutes of an outcome pre-
		data to GoalShare	sentation for each team
	Time for structuring	About 45 minutes	5 minutes (except for a team
	goal hierarchies		participated in by the inputter)
	Level of detail of goal	Relatively detailed but vary	Simple overview level but uni-
	hierarchies	widely among teams	form level of detail (expect for
			the inputter's team)
	Maximum and min-	Max: 13, Min: 1	Max: 4, Min: 2 (expect for the
	imum count of goal		inputter's team)
	nodes for each team

Table 2 .

 2 Examples of skill tag

	Tag	Super concept
	Android programming Programming
	GIS	Programming
	Google Maps	GIS
	Open Street Map GIS
	Sensor	Android Programming
	Acceleration sensor Sensor
	Geomagnetic sensor Sensor

http://code4japan.org/

http://www.codeforamerica.org/

https://www.facebook.com/code4nagoya and http://code4.nagoya/

http://okfn.jp/

http://www.osmf.jp/

http://wired.jp/special/ctf2015/

https://www.codeforamerica.org/geeks/civicissues

https://github.com/

http://idea.linkdata.org/

https://www.facebook.com/codeforkobe

http://geolod.ex.nii.ac.jp/

http://geonames.jp/

http://nagoya-bfree-hackathon.peatix.com/ (in Japanese)

Acknowledgments. This work was partially supported by a Grant-in-Aid for Young Scientists (B) (No. 25870321) from JSPS and a grant by the Nippon Foundation. We greatly appreciate the support by Prof. Nobuo Kawaguchi, Mr. Shinji Ichien, Mr. Takemi Nohara, partcipants in the hackathons, members of the NPO Lisra, and members of the Code for Nagoya.


Peter Parycek

Judith Schossböck

Bettina Rinnerbauer

Identification in E-Participation: Between Quality of Identification Data and Participation Threshold

Keywords: E-Participation, identification, authentication, data quality

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Whenever an e-participation process is designed, a decision about the modes of user identification is mandatory. For decision-makers and citizens who are initiating an eparticipation process (top-down and bottom-up setting) some guidance would be helpful. Such efforts are complicated by the complexity of e-participation processes and the large number of participation areas. [START_REF] Fraser | DEMO_net: Demo_net Deliverable 5.1: Report on current ICTs to enable participation[END_REF] As part of the nationally funded research project "E-Participationauthentication in democratic online participation", that aims at developing an e-participation ecosystem, questions like "Which levels of e-participation ask for what sort of identification method? How can the tension between the desired low participation threshold and the need for security be conceptualized?" arose. The model in this paper builds on the idea that a matching of the levels of e-participation with electronic identification methods can be a useful orientation for future initiators of e-participation processes and that the modelling of e-participation processes with a focus on identification options can be helpful for the scientific community.

In the following the levels of e-participation (chapter 2.1) and a selection of electronic identification methods (2.2), which the model is based on, are introduced. After describing the methodology (3.) and the relevant dimensions (4.1, 4.2), authors will present the model (5.) before describing limitations and suggestions on further research (6.).

2

Theoretical Framework

Levels of E-Participation: Definitions, State of the Art and Legal Aspects

When classifying e-participation processes, a useful framework, which is based on Glass' (1979) classification of the objectives of participation, was proposed by Phang/Kankanhalli [START_REF] Phang | J. Citizen participation in planning: The relationship between objectives and techniques[END_REF]. By distinguishing four objectives of e-participation and matching them with the process of policy making, Phang/Kankahalli map eparticipation as described in extracts as follows:

Fig. 1. Mapping of e-participation objectives with stages of policy making Another model includes performance indicators for each level [START_REF] Al-Dalou | E-Participation Levels and Technologies[END_REF]. Drawing on levels as presented by the Organization for Economic Cooperation and Development (OECD), Al-Dalou and Abu-Shanab emphasise that three basic levels (information provision, citizen-consultation and citizen active participation) would leave the final decision under the responsibility of the government [START_REF] Machintosh | Characterizing E-Participation in Policy-Making[END_REF][START_REF] Ahmed | An overview of e-participation models[END_REF]. However, they also mention "codetermination" as proposed by Medimorec et al. [START_REF] Medimorec | Vitalizing Democracy through E-Participation and Open Government: An Austrian and Eastern European Perspective[END_REF] as a new level. Another classification is described by Ergazakis et al. [START_REF] Ergazakis | A State-of-The-Art Review of Applied Forms and Areas, Tools and Technologies for e-Participation[END_REF], referring to the DEMO-net Excellence Network on e-Participation. They differ applied forms and areas of eparticipation: consultation is distinguished from deliberation, polling, voting, campaigning, electioneering, petitioning, decision making, service delivery, spatial planning, information provision, mediation and community building. [START_REF] Ergazakis | A State-of-The-Art Review of Applied Forms and Areas, Tools and Technologies for e-Participation[END_REF]. Further aspects relevant for examining participation threshold in e-participation processes are the role of mobile solutions as found in Wimmer et al. [START_REF] Wimmer | Mobile Participation: Exploring Mobile Tools in E-Participation in Wimmer/Tambouris/Macintosh[END_REF], and the effect of e-participation on the trust of citizens as examined by e.g. Kim et al [START_REF] Kim | E-Participation, Transparency, and Trust in Local Government[END_REF]. An Austrian model conceptualizing (e-)participation is the one proposed in the standards for public participation. This model distinguishes informative public participation, consultative public participation and cooperative public participation [START_REF] Arbter | Standards for public participation[END_REF] and was amended by the working group e-democracy of the Federal Chancellery [START_REF] Parycek | Positionspapier zu E-Democray und E-Participation in Österreich[END_REF] as follows: At the information level citizens are informed about a plan or decision without the opportunity to further influence it. Consultation refers to citizens stating their opinion. The third level is further divided into cooperation (3a), where citizens can influence the decision, and co-decision (3b), understood as a decision made commonly by participants and decision-makers.

Electronic Identification and Authentication

According to Art 3 paragraph 1 Regulation (EU) No 910/20141 , 'electronic identification' is defined as the process of using person identification data in electronic form uniquely representing either a natural or legal person, or a natural person representing a legal person. Art 3 paragraph 5 of the aforementioned regulation regulates authentication as an electronic process that enables the electronic identification of a natural or legal person, or the origin and integrity of data in electronic form to be confirmed. This understanding does not correspond with how identification and authentication are currently defined by the Austrian legal framework (for more detailed information see [START_REF] Böszörmenyi | Identitätsmanagement bei demokratischer Online-Beteiligung[END_REF]). As the project consortium consists of technical as well as legal experts and the technical understanding of those terms is not equal to the legal definitions, it has agreed on defining authentication and identification as is done by the Austrian E-Government-Act: Identification is understood as the process necessary to validate or recognize identity, while identity is the designation of a specific person by means of data which are particularly suitable to distinguish persons from each other, such as name, date of birth and place of birth. "Unique identity" enables the unmistakable distinction of one data subject from all other data subjects. 2 The process, which is necessary to validate or recognize authenticity is called authentication, while authenticity is understood as the genuine nature of a declaration of intent in the sense that the purported author of that declaration is in fact its actual author. 3 Unique identification in Austria is possible through the state-implemented citizencard or mobile-phone-signature: Independent of technology, the so-called "link to a person" assures unique identification of a natural person 4 by a derivation of the number assigned to a person within the central register of residents. Authentication of the declaration of intent is made possible through an electronic signature. 5 To summarize, unique electronic identification is the process equal to identification with an official document and the qualified electronic signature serves 6 as a means (of authentication) equal to a handwritten signature.

Methodology

Our central goal was to examine the appropriateness of e-ID options at the different levels of e-participation processes and how these can be mapped in a model based on already existing classifications and expert opinions. A qualitative approach was pursued: After a desk research, focus groups were held both with interested citizens (external focus group 1, November 2014) and experts (internal focus group 2, March 2015). As a part of the requirement analysis for the e-participation ecosystem to be developed, 10 expert interviews were held until March 2015.

The first focus group was a one hour moderated discussion starting with the clarification of basic definitions of identification and authentication, with around 20 participants (practitioners and activists with an interest in ICT and governance) in Vienna in November 2014. The goal of this focus group was to access the user perspective and to define areas of conflict and high interest.

Guided expert interviews with open questions [START_REF] Atteslander | Methoden der empirischen Sozialforschung[END_REF] have been conducted with 10 experts in e-participation, e-governance and e-voting in Austria and the EU. Experts were defined as those with knowledge in the field of e-participation due to their profession [START_REF] Gläser | Experteninterviews und qualitative Inhaltsanalyse[END_REF], i.e. whose research interests were relevant for the topic or who had been running projects of this sort. The role of the expert interviews was to evaluate and further elaborate the findings from desk research for the requirement analysis of the project. Interview guidelines were set up in accordance with the project consortium. The interviews lasted from 40 to 60 minutes and were done in person (3), in written form [START_REF] Phang | J. Citizen participation in planning: The relationship between objectives and techniques[END_REF] or by Skype recording [START_REF] Ahmed | An overview of e-participation models[END_REF]. Interviewees are quoted anonymously (as interviewee A -J).

Focus group 2 consisted of the interdisciplinary scientific partners of the consortium with a strong legal and technical specialization, as well as three representatives of the Austrian Ministry of the Interior (e.g. the leader of the Austrian Election Commission). The results of this focus group lead to a depiction of relating six selected identification methods to seven forms of e-participation. Therefore, the dimensions risk/security and practicability/reasonability/low participation threshold were suggested in a first attempt. In a second step, these were amended to the following subquestions:

 How strong is the link to a specific person? The quality of identity data is considered higher if an authority validated the identification data.  How low-levelled or high-levelled can the electronic identification method possibly be without forming a too high participation threshold with regard to a particular form of participation?

Results

Citizen Perspective

With view to the citizen perspective, in focus group 1, it became clear that the topic e-IDs in e-participation is controversial and often polarizing. Two major areas of con-flict could be identified: Firstly, in order to reach a big and diverse amount of participants, access to an e-participation process should be as low as possible (low participation threshold). Secondly, the level of risk resp. security often seems to contradict high participation rates from a user perspective. These dimensions are also reflected in the two perspectives of the model. The focus group showed that high quality ID are perceived as a hurdle for participation, and e-ID management can reduce manipulation, but could also be used to control citizens' activities. Compared to offline participation, there is a lack of trust in e-ID providers or organizations that run eparticipation projects. Anonymous e-participation is not seen as a solution; however specific user groups are very critical regarding data security standards. The potentials of a comprehensive e-ID management are seen in the increasing reliability of results and the possibility to lower participation threshold by using different e-ID solutions. This was also reflected in the interviews, which point towards the importance of user empowerment by offering transparent processes (e.g. regarding data collection) and different e-ID options (cp. Interviewees F, D, B, J).

In the following, we describe the analytical dimensions used to create a twodimensional model and how they were selected, based on desk research, interviews and focus groups.

Vertical Dimension: Levels of E-Participation

The levels of e-participation express the intensity of the influence of citizens during a participation process, based on the distinction proposed by Arbter [START_REF] Arbter | Standards for public participation[END_REF] and amended by Parycek [START_REF] Parycek | Positionspapier zu E-Democray und E-Participation in Österreich[END_REF]. At the third level, Parycek distinguishes cooperation from codecision. These levels of e-participation were amended and further divided into subcategories reflecting more concrete e-participation processes:

 The first step is information, meaning the provision of information to be accessed by participants.  Participants are provided with more influence at the second step, consultation, divided into three subcategories: the statement of ideas, the addition of content and opinions (one-way-communication), annotation/commenting/discussion (two-waycommunication) and the evaluation of content (e.g. to "like").  Cooperation, defined as a collaborative preparation of results, builds the third step.  Co-decision is understood as a possibility to vote on results or implementations.  Decision is defined as a legally binding decision made solely by the participants.

Horizontal Dimension: Identification Methods

On this axis we focused on the following selected e-IDs relevant for Austrian citizens and according to technical requirements:

1. Unique identifications provided by the state (unmistakable distinction of citizens); 2. Application specific user management (like LDAP, Active Directory etc. used, f.i. in an enterprise for the identification of employees);

3. The number of an official document (e.g. passport), which is saved in a register; (A link to the corresponding register would not enable verification of the user, but at least verify if there is a document with this number at all.) 4. A reputation based processes of identification (a login with e.g. username and password and a confirmation of other users in the sense, that the user's real identity is equal to the one used in the participation process); similarly to a Social media login, this is risky due to the lack of verification of the identity data. 5. "Social IDs"; this category summarizes identification methods like OpenID, Facebook Connect, Google Connect, Twitter, Amazon, LinkedIn etc. (username and password) 6. No identification Regarding the quality of identification data, interviewees point towards the bindingness of a decision as a main factor speaking for high quality of identification data. For some e-participation cases, e.g. youth participation, some experts are in favour of a lower participation threshold at the cost of security standards to ensure participation (I, J). Youth also seems to be more prepared to use real names for political participation (I). The integration of target group specific IDs plays a big role in e-participation. In particular practitioners emphasize a multidimensional solution on most eparticipation levels to empower citizens (B, J), which is also reflected in the description of minimum standards in our model. In particular youth and citizens living abroad can be reached well through e-participation (I). Independent from target groups, it is almost impossible to separate the bindingness of a process from secure identification tools (B, D, E, J, K.). If decision making relies on an output based on participant numbers, the importance of the quality of identification data is increased.

Context of E-Participation

As it is difficult to detach e-participation from its context, we address the aspects eparticipation is embedded in.

Anonymous Participation and No Identification

Anonymity and pseudonymity play a big role as a general option for users, in particular for a more critical target group (cp. interviewees I, B, F). Interviewee A points to the fact that identical solutions can be linked to different participation thresholds in different countries, depending on cultural factors, marketing and the recognition value of a solution. Often, there is a difference between the anonymity experienced by users and the technical possibilities. An advantage of anonymity might be that the content is more focused and personalization becomes less relevant. On the contrary, anonymity may lead to lower inhibition by users up to aggressive tones of a discussion. Nagiller [START_REF] Nagiller | Das deliberative Potenzial von Online-Diskussionen auf Nachrichtenportalen[END_REF] investigated news portals with comment functions, showing a high amount of abusive postings. She concludes that the use of real names results in less offences. The working group E-E-emocracy of the Austrian Federal Chancellery mentioned the danger of "flamewars" because of the perceived distance between users in an anonymous setting [START_REF] Parycek | Positionspapier zu E-Democray und E-Participation in Österreich[END_REF]. However, the thesis that the use of real names automatically mini-mizes offensive comments could not be proved either. In contrast, interviewees state that offensive behavior plays a minimal role in official e-participation projects (B, I, J). Another advantage of anonymity is that peer pressure might become less relevant in online communication [START_REF] Parycek | Positionspapier zu E-Democray und E-Participation in Österreich[END_REF]. Interviewees emphasized the importance of anonymity, if a project allows for that option (D, F, I, J). A study conducted by Bernstein et al. [START_REF] Bernstein | 4chan and/b: An Analysis of Anonymity and Ephemerality in a Large Online Community[END_REF] outlines that a large majority of users (over 90% of posts were anonymous) tend to choose anonymity if they have the choice to either enter no name, use any name or use a cryptographic identity mechanism on a discussion board. The question whether a huge amount of participants shall be reached is crucial (J, F). In any case, the declaration of a name and registration processes will form a participation hurdle. Technical advancements are often in favor of user privacy, although they have to be both known and implemented and usually lead to a more complicated process. Recent research on identity management has, for instance, concentrated on protecting user data [START_REF] Stein | Implementing the ECI: Challenges for the Member States[END_REF]. Generally, anonymization and pseudonymization are complex categories. When speaking of anonymity, it should be clarified whether this refers to identification towards a system or the participants.

Strategies to Lower Participation Threshold

As strategies to lower participation threshold for users, the use of solutions that are known from e-business cases as well as the use of widely accepted e-IDs were mentioned. Drawing on existing e-business cases might decrease participation threshold for particular IDs (cp. interviewee A), as users are already used to that sort of online identity management and tend to trust those things they already know. The implementation of basic e-government technologies like IDs guaranteed by the state into the corporate sector can lead to more acceptance of such technologies [START_REF] Stranach | Bürgerkarte und Handy-Signatur in der Privatwirtschaft[END_REF]. Increasing availability of such technologies in the private sector (like electronic signatures, online registration based on secure identity data or electronic RSa-delivery) could encourage citizens to also use those for e-government services. One example would be the transnational online opening of an account as implemented in the EU large scale pilot project STORK 2.0.7 In particular experts from the practitioner domain were very open towards integrating Social IDs in e-participation processes. Offering such IDs in addition to other e-ID options was seen as a valid option that empowers users by providing them with alternative solutions (B, I, J). However, if many levels of the e-participation process are reflected in a particular solution (multi-level approach), due to the complexity of the system, one e-ID for all processes might be more applicable (B). Nevertheless, there seems to be a big potential for multi-level, flexible e-participation processes with voting options (in particular for a tech-savvy and politically interested target group) that can be used by smaller administrative communities or communes. Germany builds on such models in close cooperation with associations and the lessons learned from such projects should be further considered in the Austrian, but also European context (B, D).

Legal Framework vs. sSandards

Identification methods have to meet legal requirements, e.g. those of data protection law. There is a tendency against more legal regulations regarding the implementation of e-participation processes (cp. interviewees F, I, D, E, H), however, a better standardization in the e-participation field is seen as advantage (F). Other experts criticize the lack of a unified access to e-government services for the general public (one-stop-shop) as well as a lack of a legal framework for e-participation [START_REF] Ringler | Internet und Demokratie in Österreich. Grundlagenstudie[END_REF]. EU Regulation No 211/20118 e.g. regulates the European Citizens' Initiative (ECI) and has been critically reviewed by Stein/Wenda [START_REF] Stein | Reviewing the Regulation: The Future of European Citizens' Initiatives[END_REF].

Model

The following model originates from two tables created within the internal focus group. It is an attempt to conceptualise the use of e-IDs along the two perspectives quality of identification data and participation threshold and shall serve as a basis for further defining use cases, best practices and recommendations: Which e-ID options can or cannot be recommended as a minimum standard on a specific level of participation? Not all all aspects of online identification and e-participation shall be comprehensively captured in one model, but this depiction shall be used as a basis for further verification by experts and the scientific community. The internal focus group discussed the model along the following two questions: Is the quality of the investigated identification data good enough to be used for a particular level of participation? How high-levelled can the e-ID possibly be without being regarded as a too high participation threshold for a particular form of e-participation? Fig. 2. Matching of quality of identification data and participation threshold 9As mentioned, the model describes minimum requirements on the ID level. In favour of a wide distribution of e-identification methods, it is not advised against the use of eID methods with higher quality of identification data in general, in order to include users who prefer using these forms of e-ID over of methods with lower quality of identification data. Those e-ID methods can often be technically included, depending on their availability and dissemination. In the following we summarize experts' opinion and reasoning that lead to the depicted model.

For accessing information all identification methods would possibly prevent citizens from participating. Therefore it is recommended to design the participation process without the need of any identification of participants. However, the possibility to identify themselves can be provided to participants. The same applies to the step of consultation seen as an option to state ideas and add content in a one-waycommunication-process.

For an interactive discussion process in the form of a two-way communication, it is recommended to use a form of identification, as the counterpart of a discussion is of interest. At this point the model shows a breaking point, from that it is recommended to make use of an identification method. It will depend on the individual case whether social IDs, a number of an official document saved in a register or an application specific user management will be the appropriate method of identification in such processes. This will further depend on the topic as well as the necessity to identify participants. In this process, the possibility of owning more than one social media account has to be taken into account, as well as the fact that the real identity of the user and his/her social ID do not necessarily have to correspond. There is no possibility of a secure verification in this case. A reputation based process of identification contains the additional component of other participants confirming that the identity of the user corresponds with the identity he or she participates with. On the level of consultation as a discussion, it is recommended to use reputation based processes of identification. If the use of a number of an official document saved in a register or an application specific user management is seen as more complex than other identification options, the decision should be made individually according to each case. The voluntary use of an electronic identification method implemented by the state should be possible.

The use of identification methods implemented by the state could hold back participants from participating in a discussion or evaluating content. Moreover, a unique identification is not necessary in a consultation. Therefore there is no need to only use identification methods implemented by the state on this level. Due to the insecurity of social IDs, which also applies to other levels of participation, their use is not recommended in general, but seen as a possibility on the steps of consultation in a discussion, for evaluation and on the level of cooperation, especially with regard to specific target groups. The use of a number of an official document saved in a register as well the identification method on the corresponding level of e-participation depends on the individual case and cannot be unconditionally recommended; dark grey: the use of this identification method on the corresponding level isas a tendencyseen as resulting in a too high participation-threshold (H) or the quality of identification data is regarded as too low (L) as the use of identification methods implemented by the state is considered as a potential participation hurdle. To keep participation threshold as low as possible, the mandatory use of such systems is not recommended on the level evaluation. It is recommended to use application specific user management or reputation based processes of identification as they provide a higher probability that the alleged author of a statement is the actual author.

On the level of cooperation, which basically means a collaborative elaboration of content or solutions, it may be appropriate to make use of e-ID methods that identify participants uniquely. Social IDs may be appropriate for decision makers not considering unique identification as greatly important, but preferring a high participation rate. Dependent on the requirements of the initiator of the cooperation, it is recommended to either use application-specific user management, a number of an official document saved in a register or reputation based processes of identification.

At the step of co-decision (and above all at the decision-level), it will most likely not suffice to aim for a high participation rate without knowing the identity of participants. Thus, for the processes co-decision and decision, not implementing an identification method or using social IDs is not advisable. Apart from this, all identification methods are seen as appropriate.

On the decision level, participants are provided with the most influence. Therefore, the use of secure identification methods providing a unique identification method is highly recommended. Application-specific user management is also an appropriate solution. The use of a number of an official document saved in a register or reputation based processes of identification can be appropriate, dependent on the individual case, and is thus not excluded.

Limitations and Further Research

On the basis of these results, we conclude that the integration of target-group specific e-IDs, the creation of exciting and motivating use cases for existing e-ID models as well as building on already well received and known solutions can significantly lower participation threshold. However, the right method mix in e-participation will always depend on the scope of the project and the specific target group. Emphasis of further research will be on the development of use-cases, additional options for different e-participation levels (new forms of online identification may arise or gain more popularity) and on digital inclusion, on further evaluation and review of the model proposed through expert opinions. A workshop at the International Conference for E-Democracy and Open Government 2015 was held in May 2015. A quantitative survey is planned. Limitations of the model can be seen in its dedicated focus on top-down processes. Some relevant and promising e-participation models like the supranational European Citizens' Initiative [START_REF] Stein | Implementing the ECI: Challenges for the Member States[END_REF], despite some issues regarding stochastic elements and certification [START_REF] Müller-Török | The European Citizens' Initiative -A Supranational Approach towards eParticipation[END_REF], work well on the basis of just mentioning a passport number without further validation of the identity document, are not mentioned separately. User assessment and usability testing are still necessary once specific projects are put into prac-tice. The model proposed shall be seen as a first expert based depiction for categorizing and choosing e-ID options for specific e-participation processes.

Regulation of the European Parliament and of the Council of

July 2014, published in OJ L 257/73 on 28 August 2014; this regulation shall apply from 1 July 2016 (Art 52 describes the entry into force further). 2 These definitions are regulated in § 2 Nr. 4 (identification), Nr. 1 (identity) and Nr. 2 (unique identity) of the Austrian Federal Act on Provisions Facilitating Electronic Communications with Public Bodies (E-Government-Act), Austrian Federal Law Gazette (BGBl), part I, Nr. 2004/10, version BGBl I 2013/83; a former version is accessible in English https://www.digitales.oesterreich.gv.at/DocView.axd?CobId=19380. 3 § 2 Nr. 5 and Nr. 6 E-Government-Act, Austrian Federal Law Gazette (BGBl), part I, Nr. 2004/10, version BGBl I 2013/83. 4 § 4 Nr. 2 E-Government-Act, Austrian Federal Law Gazette (BGBl), part I, Nr. 10/2004, version BGBl I 2013/83. 5 Other means, which can guarantee authentication are e.g. log files or a mobile TAN. The latter serves as a second factor of authentication through the Austrian mobile-phonesignature. 6 apart from certain exceptions, see § 4 Federal act on Electronic Signatures, Austrian Federal Law Gazette (BGBl) I Nr. 1999/190 BGBl. I Nr. 2010/75.

https://www.eid-stork2.eu/ (accessed 31 March 2015).

Regulation (EU) No 211/2011 of the European Parliament and of the Council of 16 February 2011, published in OJ L 65/2 on 11 March 2011.

[START_REF] Kim | E-Participation, Transparency, and Trust in Local Government[END_REF] Colour code: white: the quality of the identification data and the e-identification method are considered as appropriate for its use on the corresponding step of participation; light grey:

Acknowledgement

The project "E-Partizipation" ("E-Participation") is funded by the Austrian security research programme KIRAS of the Federal Ministry for Transport, Innovation and Technology (bmvit). We would like to thank our project partners: the Austrian Institute of Technology, the Austrian State Printing House, the Centre for Computers and Law (University of Vienna), the Federal Ministry of the Interior and Rubicon.


Aron Larsson

Osama Ibrahim

Modeling for Policy Formulation: Causal Mapping, Scenario Generation, and Decision Evaluation

Keywords: Causal Mapping, Scenario Generation, and Decision Evaluation Policy Analysis, Impact assessment, Policy Modelling, Problem Structuring, Dynamic Simulation, Causal Mapping, Scenario Planning, Decision Analysis

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

A large body of public policy analysis is devoted to retrospective analysis (evaluation), which tries to understand the causes and consequences of policies after they have been implemented (Tsoukias et al. 2013). Equally important in policy analysis is the role of ex ante evaluations, i.e. prescriptive analysis involving impact assessment carried out at the early stages of policy development, cf., e.g., [START_REF] Turnpenny | The policy and politics of policy appraisal: emerging trends and new directions[END_REF]). Ex ante evaluation encompasses forecasting of consequences if policies were to be implemented and prescriptions about which policies should be implemented. One important aim of ex ante decision support within the context of policy making therefore involve developing ways of facilitating for policy-makers to create policies that is consistent with their preferences while at the same time being accepted by other stakeholders, cf. [START_REF] Bryson | What to do when stakeholders matter[END_REF]). However, there is a lack of operational approaches for addressing the cognitive activity of designing or finding policy options. The long term implications of policy making imply the need to consider a vast range of possible futures, often characterized by the presence of multiple stakeholders and sometimes characterized by large uncertainties as well.

Problem structuring are now widely acknowledged as an important feature of strategic decision support tools and there is a growing but still small body of research and practice on how to integrate such methods with other formal and/or quantitative methods for decision evaluation, see [START_REF] Tsoukiàs | Policy analytics: an agenda for research and practice[END_REF]. The aim of this paper is therefore to provide a basis for the selection and use of modeling and decision support tools from the operational research field in a common toolkit for ex ante policy analysis, such that there is a logical relationship between the tool used to the stage and sub-stage of the policy making process and how the modeling tools provide decision value in the policy making process.

Policy Making Process and Policy Formulation

Herein public policy is defined as a purposeful, goal-oriented action that is taken by government to deal with societal problems or to improve societal conditions for the wellbeing of its population. Decision making is the cognitive process of selecting a course of action from many possible ones which might be initially known or not known.

According to [START_REF] Bero | How consumers and policymakers can use systematic reviews for decision making[END_REF], policy making has some distinguishing features having an impact on the decision process: (i) A population level decision making context;

(ii) Explicit justification is required, as policies are formally and informally evaluated by government agencies, by outside consultants, by interest groups, by the mass media, and by the public; (iii) Effect of the existing political ideology and governance; and (iv) Evidence of systematic reviews on public policy decisions is hard to come by.

We relate to three-stage process model for policy-making conforming to the wellestablished policy cycle models of [START_REF] Lindblom | The Policy-making Process[END_REF] and [START_REF] Howlett | Studying Public Policy: Policy Cycles & Sybsystems[END_REF]. The process model includes the following steps; i) problem identification stage, ii) policy formulation stage, and iii) policy implementation stage, see Fig. 1. This process model acknowledges that policy-making is an ongoing, continuous process that requires continuous assessment, evaluation, and reaction. Each stage has a set of activities according to Table 1

Policy Implementation

Legitimizing and implementing a public policy: Policy is legitimized as a result of the public statements or actions of government officials at all levels. This includes: executive orders, rules, regulations, laws, budgets, appropriations, decisions and interpretations that have the effect of setting policy direction.

Policy is implemented through the activities of public bureaucracies and the expenditure of public funds.

Monitoring & Evaluation: Record and control of the implementation. Analysis, evaluation and feedback of the results of implementation.

Hence, a large part of the activities occurring within a policy cycle is about understanding, formulating and structuring "problems", see also [START_REF] Mingers | Problem structuring methods in action[END_REF][START_REF] Tsoukiàs | On the concept of decision aiding process: an operational perspective[END_REF]). Thus, problem structuring is a key element of the public policy making process and in particular for the policy formulation stage. Modeling for problem structuring in order to find feasible policy options and decision evaluation of these options is of prime concern in the policy formulation stage, since in this stage "policy makers must ensure that there is a meaningful definition of the problem" and "need a comprehensive understanding of the problem" in order to identify different policy options [START_REF] Hamilton | Policy formulationcritique, analysis and strategic implications, in New Voices: Essays on the Policy Process[END_REF]. Having this said, in the next section we focus on operational research and the decision sciences within the context of supporting policy formulation and a selection of methods for an integrated modeling approach to policy formulation decision support is suggested.

3

Modeling for Policy Formulation

Problem Analysis

Problem analysis calls for problem structuring methods (PSM) which aim to enable a better understanding of unstructured problems characterized by the existence of multiple actors, multiple perspectives, incommensurable and/or conflicting interests, intangibles and key uncertainties. The methods rely heavily on engaging with policy makers, adopting a facilitative mode of engagement, and simple, often qualitative, models [START_REF] Franco | Facilitated modelling in operational research[END_REF]. See (Mingers and Rosenhead 2001) for an overview of the characteristics of a wide range of PSM's. The use of cognitive maps is among the early approaches to enable for problem understanding, originally intended for representing social science knowledge, see (Axelrod 1976). A cognitive map is a directed graph where nodes represents societal concepts or variables (such as subsidy size, traffic intensity, CO2 emission rates) and links represent causal connections between these concepts. With respect to the simple example, two nodes "car traffic" and "emissions" and a link from the former to the latter would then mean that the former causally has an impact on the latter, negative or positive.

Multiple perspectives of the problem from different actors can be represented and debated for improving the policy-makers' understanding of the problem situation and sharing it with associates. Several "dialects" of cognitive maps have emerged, which share focus on the qualitative aspects of problem structuring, see, e.g., [START_REF] Acar | Endowing cognitive mapping with computational properties for strategic analysis[END_REF].

Although a cognitive map serves its purpose as a problem structuring method, its content is too informal to be used as an underlying model for simulation of how changes in one node affects other nodes through causal relations. A causal map in the sense of [START_REF] Acar | Toward a theory of problem formulation and the planning of change: causal mapping and dialectical debate in situation formulation[END_REF] is a diagram that maps problem variables, or factors, and defines their interdependencies in a quantitative manner. Goals for different actors of the problem can be defined to facilitate group decision making and negotiation analysis. The primitive elements used in the causal mapping method are: Independent variables (sources of change), dependent variables (intermediate and outcome/goal variables), change transmission channels, change transfer coefficients, time lags, minimum thresholds (minimum change to be transferred), status-quo level of the map (the initial state of the system, considering 0% relative change), and goal vector representing the targeted changes in goal variables relative to status-quo values. Fig. 2. Causal map model of bus ticket price subsidy policy problem with four actors, three controlling resources on the left hand side and one actor having an interest in the town commerce factor. The goal vector consists of that the three controlling actors want to reduce CO2 emissions by 20% while the third actor wants to increase town commerce with 5%. Each link has a change transfer coefficient and a time lag. For instance, the link from "Subsidy bus tickets" into "Car traffic" has a coefficient of -0.2 and a time lag of 1 month.

As a simple example, consider a local government wanting to reduce CO2 emissions in order to contribute to climate targets and improve central town air quality. The upfront objectives are focused on the environmental issue. One policy option is to increase the subsidy of bus tickets, where the underlying hypothesis in terms of causality is that higher subsidies (lower ticket prices) will cause more people to take the bus instead of cars when going into town, thereby reducing emissions also enabling for more citizens to access the central town area increasing town commerce, which is the main concern of an influential stakeholder group. However, there is also a positive causal relationship between car traffic and town commerce, increasing the complexity of the policy option making. In the problem analysis, it becomes clear that for many citizens it is not the bus ticket price that cause them to avoid taking the bus, but rather the frequency of buses. Further, reducing emissions can also be done by increasing the proportion of gas driven buses. A causal map of the policy problem can then be illustrated in Fig. 2 above.

The richer computational semantics of the causal mapping approach support simulation in ways that other varieties of cognitive mapping and causal mapping do not, see [START_REF] Druckenmiller | An agent-based collaborative approach to graphing causal maps for situation formulation[END_REF]. The method includes indications not only of the signs of the presumed causal influences, but also of their intensities, minimum threshold values and the time lags. Still, it is possible to utilize the non-quantitative elements of the map analogously to how cognitive maps are employed. Three classes of analyses are supported, see [START_REF] Acar | Toward a theory of problem formulation and the planning of change: causal mapping and dialectical debate in situation formulation[END_REF]) for detailed description:

1-Backward analysis: Clarifying, testing and reassessing assumptions about the cause-effect relationships of the situation. It can be divided into:

(a) Major assumptional analysis (validity of the major aspects of the graph elements and relationships); and (b) Minor assumptional analysis (validity of detailed qualifications and quantifications of the graph).

2-Structural analysis:

It includes: Graph scope, connectivity analysis, reachability analysis and goal comparative analysis (qualitative and quantitative).

3-Forward analysis:

Implications of a "change scenario" through simulating the transfer of change, includes:

(a) Scenario simulation: running change scenarios on the graphsimulating transfer of change over time from origins throughout the map. (b) Goal negotiation analysis: Goal feasibility and compatibility of goals, identify scenarios realizing a goal or goals jointly). Effectiveness or efficiencyexpression of outcomes in comparison with objectives and relative to change needed at origins. Within policy formulation, a policy option would be represented by a change scenario. Feasible scenarios would be the ones who satisfy the actors by reaching their goals in different ways, and in this way scenarios can be generated/discovered [START_REF] Bryant | Thinking inside the box: a participatory, computerassisted approach to scenario discovery[END_REF]. The method cannot capture all the intricacies of a situation to its minutest details, but can sufficiently map out its principal elements and their relationships.

Design and Generation of Policy Options

The identification and creation of new alternatives is one of the most important aspects of any decision support. If the decision alternatives under consideration are weak, it will lead to a poor choice (Brown 2005). Thus, support in the generation of feasible options is important for policy formulation. A policy option is represented by a scenario of change from the status-quo level of the causal map. A base line scenario is defined with initial values for the problem's key variables with zero initial relative changes. The desired state of the system is represented by a goal vector (targeted relative changes in outcome variables compared to the base line scenario). The causal map allows triggering change transfer by a 'Pure scenario', a single change at one source, or a 'Mixed scenario', change in several sources all at once or with a time lag.

Graph change analysis allows us to investigate the dynamic consequences of entering a change in one of the graph origins, thus simulating the propagation of change throughout the causal map. Several decision analytic concepts are readily usable for scenario generation:

 "Optimality", relating scenarios to the level or degree to which the goal vector is realised.  "Dominance", reducing the number of scenarios by discarding dominated  "Resource constraint", cost of input triggers of certain magnitude at a node.

Triggering a scenario may impose on the controlling actor the supply of funds and resources.  "Goal compatibility", goal vectors of different actors is compatible if a scenario can be found to realize them jointly. tor or being dominated are filtered out, while scenarios deemed efficient and "interesting" according to some predefined decision rule based upon resource constraints and goal compatibility concepts mentioned above are suggested as policy options for further evaluation.

Evaluation of Policy Options

Arriving at a set of feasible options which are non-dominated, further discrimination between them will call for taking preference information into account. Although, the scenario-based dynamic simulation allows decision makers to identify alternative policy options and verify their effects over time, it does not provide the explicit decision evaluation of policy options. Multi-criteria decision analysis (MCDA) has been extensively used to support a wide variety of complex decision problems as a tool for evaluating options where decisions involve the achievement of multiple objectives and considering multiple decision makers and stakeholders, see, e.g., [START_REF] Zavadskas | State of art surveys of overviews on MCDM/MADM methods[END_REF].

MCDA typically distinguish between a decision maker which has control of some decision variable, and stakeholders, which are affected by the consequences of a decision. This distinction is straightforwardly analogous to the actor representations of the causal map. Applying MCDA should thus provide the relative global performance of each alternative, and is particularly useful when selecting one out of a finite set of feasible alternatives.

When evaluation of policy options is guided by a decision analysis approach, a relevant MCDA model is required equipped with preference elicitation methods for capturing policy makers' and stakeholders' preferences. Given that we have identified feasible policy options from scenario generation, there are two main tasks remaining in structuring MCDA evaluation models; i) representation of objectives in a structure, commonly a value tree, and ii) the definition of attributes to measure the achievement of objectives (Franco and Montibeller 2011).

Traditionally in MCDA, the decision process starts by structuring the problem as an attribute tree hierarchically ordering the decision makers' aims at different abstraction levels, from fundamental objectives (such as "improved environment") to lower level attributes (such as "NOx reduction") where the latter contributes to the former in a hierarchical value tree. It is generally assumes that each criterion can be operationalized by a set of measurable attributes allowing for assessing the consequences arising from the implementation of any particular alternative. In the next step preferential information is elicited. The relative importance of criteria is captured in weights for each criterion at each abstraction level. At the lowest level of the value tree these objectives are translated into attributes, with each one of them evaluating a given characteristic of the decision options (for example, an objective 'efficiency' may be measured by the attribute 'operating cost'). The performance of each decision option against each attribute is determined and weights reflecting acceptable trade-offs of performance among objectives are elicited from the decision-makers. Given the presence of many decision makers or stakeholders, for a group decision a decision has to be made and there might be disagreement with respect to what the best option is, but the group choice still has sufficient support from the group, i.e. there is a way of representing the collective pref-erences of the group. This differs from negotiation in that in such as process each stakeholder might simply abandon the decision process and there is no decision at all, see, e.g., [START_REF] Kilgour | Multiple criteria approaches to group decision and negotiation[END_REF].

There is no universal way of applying MCDA to group decision and negotiation processes, but the underlying use of a causal map and scenarios generated leads to that the features of interest are preference elicitation and preference aggregation. With respect to integrating multi-criteria decision analysis with causal maps and simulation of scenarios, [START_REF] Comes | Decision maps: a framework for multi-criteria decision support under se-vere uncertainty[END_REF] presents the concept of "decision maps", integrating problem structuring and scenario planning using causal maps with multi-criteria decision analysis, but keeps the focus on operational decision making and to a lesser extent on policy making. However, the structure and content of the map informs the building of the value tree, in an ad hoc translation, in which, the causal map can be used to elicit preferences, cf. [START_REF] Comes | Decision maps: a framework for multi-criteria decision support under se-vere uncertainty[END_REF]). For a simple example of this, see Fig. 5 showing a value tree model based upon the causal map of Fig. 4. [START_REF] Montibeller | Causal maps and the evaluation of decision options a review[END_REF] investigate various ways to use causal maps as the underlying problem structuring tool and extending it with decision evaluation features and/or using the map to effectively inform the decision analysis model in the form of a multi attribute value tree. where multiple stakeholders are present. Elicitation or anticipation of stakeholder preferences is done or assessed in the form of utility statements for each stakeholder or stakeholder group regarding each specific policy option and criteria weights. Stakeholders give the different outcomes a ranking order if they are unsure of their preferred choice and methods for computational decision analysis with imprecise information is promoted in order to support such statements, see [START_REF] Larsson | Decision analysis with multiple objectives in a framework for evaluating imprecision[END_REF][START_REF] Danielson | Using a software tool for public decision analysis: the case of Nacka municipality[END_REF]). The result is a preference assessment for each decision maker and/or stakeholder and the value tree is constructed with stakeholders as the lowest level of the tree, see Fig. 4 for the value tree corresponding to the causal map of Fig. 3 where each decision maker has a trade-off expressed as criteria weights between cost and their benefits of concern. With respect to the model in Fig. 4, we can consider the following simple preference scheme using value functions V(S) of the scenarios for each criterion delimiting the decision evaluation to the status-quo scenario called S0 and the generated scenario shown in Fig. 3

Decision maker CO2 emissions Cost

V(S0) V(S1) V(S0) V(S1) DM Subsidy 0 1 1 0 DM Bus frequency 0 1 1 0 DM Gas driven buses 0 1 1 0

Stakeholder Town commerce V(S0) V(S1) ST Town commerce 0 1

Decision evaluation is then done stakeholder-wise. Each decision maker or stakeholder will receive a utility value for each scenario and the choice of selecting or discarding one scenario will be based upon its total utility through aggregating the stakeholders' utility values (see Fig. 5) together with group decision admissibility concepts such as maximum disagreement thresholds or minimum consensus thresholds [START_REF] Fasth | Admissibility concepts for group portfolio decision analysis[END_REF].

Concluding Remarks

In this paper we have outlined the linkages between the policy formulation stage of the policy making process model and contemporary decision analytic support methodologies and based upon that discussed an integrated modeling framework for computer assisted policy formulation. The approach suggested combines causal mapping for problem structuring and simulation of consequences together with identifying scenarios deemed feasible for further investigation in a multi-criteria decision evaluation. This sequence follows a logical work process conforming to the activities of the policy formulation process.

Scenario generation helps policy-makers in identifying feasible options from a possibly vast space of possible ones reaching stipulated targets, while the decision evaluation can supports an in-depth performance evaluation of policy proposals taking the preferences of stakeholders into account. The resulting integrated model for the policy problem situation can improve the process of reaching well-accepted scenarios and a transparent design of policy options while taking into account costs, benefits, resource constraints, different perspectives, and multiple objectives. In the context of policymaking the decision makers are often confronted with large and complex amounts of information, not seldom of a conflicting nature and reflect multiple interests. Problem structuring and decision analysis allows policy-makers to judge the performance of alternative policy options and from stakeholders' different points of view of what represents a positive or negative policy impact. Hence, policy impact assessment frameworks and tools have much to gain from implementing decision analytic support methodologies.

Fig. 1 .

 1 Fig. 1. Policy-making process model.

Fig. 3 .

 3 Fig.3. Example of a generated scenario reaching both the emission and the town commerce target. The scenario consists of increasing the subsidy with 15% at the initial timestep, increasing bus frequencies at the sixth, and increasing the proportion of gas driven buses at timestep 12.The simulation is run upon the causal map modeled, whereas the set of objectives and their target values are used for identifying feasible scenarios. Based on the simulation results of an initially large sample of scenarios generated by, e.g., full factorial design or Latin hypercube sampling, unsatisfactory scenarios not realizing the goal vec-

Fig. 4 .

 4 Fig. 4. Value tree counterpart of causal map in Fig. 3 in accordance to the SEMPAI framework. In this example, DM Subsidy's weight for CO2 emissions is 40% so for simplicity precise numerical weights are used here. For simulation, in the SEMPAI 1 framework reported in Hansson et al. (2011), simulation results of flooding models are combined with multi-criteria decision analysis

Fig. 5 .

 5 Fig. 5. Comparison of scenarios generated by adding part-worth utilities for each stakeholder.There is disagreement since DM Subsidy and DM Gas driven buses consider S1 to be inferior to S0 while the other actors have differing preferences.

Table 1 .

 1 below. Stages and sub-stages of the policy-making process model.

	Stage	Activity
	1. Problem Identification	Recognition and diagnosis:
		Decision makers become aware of the fact that there
		is a problem and diagnosis is required to order and
		combine the information related to that problem.
		Agenda Setting:
		Focusing attention, involving interest groups, setting
		targets, defining and documenting the long view
		and/or the short view of the policy.
	2. Policy Formulation	Problem analysis:
		Identify elements of policy problem: actors, stake-
		holders, decision variables, parameters, links, goals,
		risks, limitations and associated technologies.
		Identify problem environment: conflicting goals, in-
		ter-and intra-group negotiations. Specify decision
		dynamics: interrupts, feedback loops, delays, and
		speedups.
		Design and generation of policy options:
		Formulate policy proposals through political chan-
		nels by policy planning organisations, interest groups
		and government bureaucracies. Identify the feasible
		options that will or might lead to desired policy con-
		sequences, conduct impact assessments of different
		policy options.
		Evaluation of policy options/alternatives:
		Compare the feasible options, considering that con-
		flicting goals are likely to exist as well as differing
		acceptance levels for different stakeholders.
		Policy Decision:
		Decide upon policy after evaluation of the options
		encompassing different viewpoints and perspectives,
		multiple objectives, and multiple stakeholders using
		integrated assessments.

Table 2 .

 2 called S1. Preference schema.

Simulation and Evaluation with Multiple Perspectives and Agents Integrated