POLICY SIMULATION AND E-GOVERNANCE Peter SONNTAGBAUER cellent AG Lassallestraße 7b, A-1020 Vienna, Austria Artis AIZSTRAUTS, Egils GINTERS, Dace AIZSTRAUTA Vidzeme University of Applied Sciences Cesu street 4, Valmiera, LV4200 Latvija ABSTRACT The paper describes the FUPOL project (www.fupol.eu), an Integrated Program (IP) selected under objective 5.6. ICT solutions for governance and policy modelling in the 7th call FP7 program. (ICT for Health, Ageing Well, Inclusion and Governance). The project duration is four years (October 2011 October 2015). It proposes a comprehensive new governance model to support the design of complex policies and their implementation. The project has currently limited its scope on urban policies, however the approach itself is generic and can be applied to the lifecycle of any policy. The proposed policy design and implementation model has a specific focus on the use of agent based simulations in the deliberative process of urban policies. KEYWORDS E-governance, policy modelling, E-participation, agent based modelling, social media analysis, urban policy 1. INTRODUCTION In 2010 the Major Cities of Europe Association (MCE) conducted a study on the "Citizen Web Empowerment in a network of European Municipalities: "value for citizens" in Web 2.0 projects [L.Buccoliero, 2010]. It studies the growing demand of citizen empowerment and benchmarks the degree of citizen empowerment across the network of European municipalities in four areas e- information, Web 2.0, e-consultation and e-decision. The major outcome is that e-information is sufficiently addressed, while Web 2.0, e-consultation and e-decision is not developed yet. Likewise the European Commission has conducted several studies and added a specific action to developed advanced ICT tools for policy modelling, prediction of policy impacts, development of new governance models and collaborative solving of complex societal problems. [EC Workprogram 2011] Based on the above the FUPOL consortium has elaborated a comprehensive approach to further advance the research and development in simulation, urban policy process modelling, semantic analysis, visualization and integration of those technologies. The approach developed seeks the active involvement of all stakeholders including policy makers, civil servants, citizens and companies in the urban policy making process. The proposal has been funded under the 7th framework program of the European Commission and will be implemented 2011 2015.
The FUPOL consortium consists of 17 partners from Europe and China. It has a good balance of research partners, IT-industry, local governments and political cluster organizations capable to ensure wide-spread dissemination and exploitation. The current political focus is urban e-governance, which is deemed important on a worldwide scale since the majority of the world s population is living in urban areas. In Europe currently more than 79 % of the population are urbanized and it is expected that it will further increase and reach 85 % by 2030. 2. FUPOL GOVERNANCE MODEL The FUPOL governance model (see Figure 1) is based on the integration of the following major components: 2.1. Automatic "Hot Topic" Sensing The political blogosphere is searched to find-out current "hot" political topics within a predefined scope (regional, national, EU) and weigh them according in a subsequent analysis. The information is harvested with a web-crawler, which starts with a list of predefined URLs to visit (seeds). As the crawler visits these URLs, it identifies all the hyperlinks in the page and adds them to the list of URLs to visit, called the crawl frontier. URLs from the frontier are recursively visited according to a set of policies. Hot political topics are extracted from the raw text data and clustered. A key feature is that the analysis will be based upon latent Dirichlet allocation (LDA), [Blei, 2003] and therefore relatively language independent to take into account cross border and European context. 2.2. Deliberation and Stakeholder Involvement After a hot political topic has been identified a deliberation on a possible new policy is initiated using multichannel social computing. This refers to an environment in which the various social Web 2.0 channels are Figure 1: FUPOL Governance Model integrated into a single social computing environment in order to reduce the workload of continuous interaction with large number of people. The contributions are aggregated and summarized by the FUPOL software. This data aggregation step is crucial for e-governance since it expresses the voice of the citizen. A feature called opinion summarization aims at giving the overall sentiment of a large number of opinion resources at various granularities. The presentation and visualization is still to a large extent unexplored and a new research field. Results of the opinion extraction as well as the underlying raw data will be classified and linked with the topic, so users can drill down at any time to see the single stakeholder opinion. Likewise they will be linked with related results of a classical survey (if available).
During the policy lifecycle, the e-citizen feedback is crucial, but cannot be reduced to a single voting system where policymakers propose scenarios and users give their preferences in an online system. The FUPOL vision is to enable the e-citizen to participate to the policy management from the beginning (proposing ideas) to the end (giving feedback about the success or the failure of the policy). Since it is difficult to give a formal language in which ideas and feedback should be sent, we allow opinions to be expressed in free text (i.e. in natural language), possibly enhanced with a voting scheme to identify interesting content through crowd-sourcing. This type of system is called an Idea Management System (IMS) and is currently an active research area in Computer-Human Interaction. 2.3. Simulation The deliberation loop contains a component to simulate the potential impact of a new policy. The result of the simulation is visualized and provided as a feedback to stakeholder. The scenarios and their potential impact over a timeline are simulated using available data and eventually data from other public administration obtained through data import facilities. For this purpose the integrated toolbox will also contain a repository, where public data from other governments can be found for certain policy domains as well as an input facility to retrieve those following the W3C recommendations on "Publishing Open Government Data". The methodology of simulation allows an organization to analyse the behaviour of complex systems in a flexible and detailed manner, and often in real-time. Simulation also allows for a quick implementation of adjustments in the modelled policy system, making it possible to analyse different alternative solutions in a relatively short time. It is intended to use agent based simulation (ABM) as the method of choice for the simulation component. It is therefore discussed in more detail in the following chapter. 3. AGENT BASED SIMULATION 3.1. Definition Agent-based modelling is a type of simulation, which allows a researcher to create, analyze, and experiment with agents that interact within an environment. Agents are typically components of the software representing social actors such as people of a certain group, political parties, companies or governments. They interact in an environment in various ways and it is exactly this feature, which makes agentbased modelling very suitable for political and social processes. It means that agents can transfer information to each other and their future behaviour is based on this information. Transfer of information is understood in a broad sense and encompasses for example a message or observing the behaviour of other agents. 3.2. Advantages In classical science the impact of changes on a system is explored with experiments. An experiment is defined as applying some treatment to an isolated system and observing the impact. The isolated system is compared with another system without or with another treatment. In social and political sciences, conducting experiments is normally impossible or undesirable. The reasons are as follows: a) creating two isolated systems is typically very difficult or impossible b) treating one system while not treating the control is often ethically undesirable.
Therefore classical experiments in political and social science are rare. Agent based modelling offers a convenient way out since the ethical problems of experimentation are not present. Moreover the experiment can be repeated many times to achieve optimized results. 3.3. Implementation The simulation model is implemented as a software program. A well-known computer game which comes close to agent based simulation is SIMS. The agents and interactions in the simulation model program itself represents the processes that are thought to exist in the real social world [Macy & Willer, 2002]. It means the agents must be programmed with rules to react in the simulation environment as in the real world. Typically it is not a challenge to program the agents, the real challenge is to determine the rules and their properties. The environment in which the agents interact can be more or less neutral (e.g. a lattice) or it can have specific properties itself. It is expected that in FUPOL the environment should be spatially explicit, which means it should represent the geographical space in a GIS based format. The reason is that such an environment representation comes closer to reality of the urban challenges to be simulated. 3.4. Challenges It is not sure, whether agent based simulation alone will be sufficient to model reality. It might be necessary to use different simulation technologies and mostly non-compatible set of simulation tools [Gilbert and Troitzsch, 2006]. Moreover most of the platforms cannot be used for policy decision makers due to complexity, heavy architecture and special knowledge on of programming and mathematics. In order to solve the shortcomings above the FUPOL consortium intends to elaborate a new policy simulator (see Figure 2) and to design a pilot solution of an integrated software environment. It will be accessible for the persons without specific knowledge in Figure 2: FUPOL simulator cell programming. This architecture will allow architecture the integration of several simulation types, if required. 4. CONCLUSION The FUPOL project proposes a comprehensive new e-governance model to support the whole policy design and implementation lifecycle, which is based on Web 2.0 technologies and simulation techniques. The advantages of the proposed model is that it will provide a better and more comprehensive understanding of citizen needs and as well as better forecasting to understand future trends. The use of agent based modelling to simulate polices offers a convenient way to experiment with policy alternatives. A possible limitation is that some of the real policies to be modelled are found too complex for computer simulation.
Currently the governance model and simulation will be tested in cities with urban policies. The future application of the model and its ICT components can be further expanded to national and regional policy issues. Research results will be published on the FUPOL website (www.fupol.eu). REFERENCES Blei, David M.; Ng, Andrew Y.; Jordan, Michael I, January 2003, Lafferty, John. ed. "Latent Dirichlet allocation". Journal of Machine Learning Research 3 (4 5): pp. 993 1022. doi:10.1162/jmlr.2003.3.4-5.993. Buccoliero, L. and E. Bellio (2010). "Citizens Web Empowerment in European Municipalities." Journal of E- Governance 33(4): 11. 2: 1347-1351. David Osimo et al. 2010, Project Crossroads, Deliverable D4.1 Roadmap European Commission, 2010, Workprogram Cooperation Theme 3 ICT Information and Communication Technologies, page 72 Gilbert, Nigel, and Troitzsch, Klaus G. (2006). Simulation for the Social Scientist. Second Edition. ISBN 139780335221493, Open University Press. Macy. M., Willer R. (2002) From factors to actors: Computational sociology and agent based modelling, Annual review of sociology 28, 143-166