Mauno Rönkkö
email: mauno.ronkko@uef.fi

Markus Stocker
email: markus.stocker@uef.fi

Markku Huttunen
email: markku.huttunen@vtt.fi

Ville Kotovirta
email: ville.kotovirta@vtt.fi

Mikko Kolehmainen
email: mikko.kolehmainen@uef.fi

TiTiMaKe: A Distributed Service Architecture for Security Applications

Keywords: Distributed Systems, Internet Computing, Service Networks, Safety and Security

In this article, we discuss integration of distributed information services, to support the implementation of applications for fields of safety and security. Although there are standard interfacing technologies, such as SOAP and REST, there is very little architectural support for the development of personalized and case specific applications, where the same data sources and computational services are integrated in different ways. As the main contribution, we present here a distributed service architecture, called TiTiMaKe, that supports the development of scenario based applications. We also illustrate TiTiMaKe by describing its use in applications in fields of surveillance and emergency rescue.

Introduction

In this article, we discuss information system solutions to crisis prevention and incident management. These phases appear in various models for crisis management, such as in the crisis management chain by Carter [START_REF] Carter | Disaster management: A disaster manager's handbook[END_REF] and in the relational model by Jaques [START_REF] Jaques | Issue management and crisis management: an integrated, non-linear, relational construct[END_REF]. In crisis prevention and incident management, enhanced perception by using state-of-the-art sensory technology coupled with computational methods can significantly improve situational awareness [START_REF] Salmon | What really is going on? Review, Critique and Extension of Situation Awareness Theory[END_REF], that is, the comprehension and projection capabilities for the actors involved in the action. Also, through specifically tailored systems architecture, the enhanced communication capabilities can significantly improve the shared situational picture, leading to faster and more accurate responses.

Applications for crisis prevention and incident management are classified as safety critical systems. According to Knight [4] "safety-critical systems are those systems whose failure could result in loss of life, significant property damage, or damage to the environment". Safety-critical systems require significant effort in specification, architecture design, implementation verification, and processing. In particular, reliability, efficiency, and resilience are key factors for the design. In this respect, Internet computing and cloud computing offer solutions for improving not only robustness and performance, but also extensibility and adaptation.

When developing service-based applications, however, there is virtually no support for features like adaptation, personalization, and automated reasoning at runtime. The same applies, if there is a need for data manipulation and transformation on-the-fly. Currently, the support is found at the technical level of integration. For instance, modern programming environments do support code generation for service integration, especially for standard interfacing techniques like SOAP and REST. Not surprisingly, some work on identifying integration patterns [START_REF] Hohpe | Enterprise Integration Patterns: Designing, Building, and Deploying Messaging Solutions[END_REF] has been done recently.

In this article, as the main contribution, we present an extensible, distributed service architecture, called TiTiMaKe, that supports the development of scenario based safety and security applications. The TiTiMaKe architecture is based on core logic design, where design patterns [START_REF] Gamma | Design Patterns: Elements of Reusable Object-Oriented Software[END_REF], such as factory, bridge, facade, chainof-responsibility, mediator, observer, thread pool, and messaging patterns, are applied. The architecture not only supports the integration of new data sources and computational services, but also their concurrent use in multiple scenarios. Concurrency issues are resolved with an internal event queue and attachable event listeners running in multiple threads. Because of this, the architecture supports also the reuse of components throughout different scenario implementations. This is also how the TiTiMaKe architecture differs from some existing architectures for safety and security applications, such as UHHA [START_REF] Molarius | UHHA -a framework for emergency management in chemical accidents[END_REF]. In this article, we also illustrate the use of the TiTiMaKe architecture in two scenarios that use the same sensor network as the data source, but integrate it with very different kinds of computational services. Both scenarios were implemented and tested for functioning.

The rest of the article is organized as follows. We start by briefly describing the used information services in Section 2. In Section 3, we describe the TiTi-MaKe architecture. In Section 4, we illustrate the use of TiTiMaKe in implementing two security applications. Finally, in Section 5, follows the conclusion.

Distributed Service Network

The service network considered in this article consists of multiple, heterogeneous services. These are the ToMoVaKe sensor network, Vehicle identification service, Dispersion modeling service, Reachability analysis service, and Spatio-temporal population modeling. We shall now briefly introduce each of these services.

The ToMoVaKe sensor network operated by Lappeenranta University of Technology, LUT Savo Laboratory of Green Chemistry, comprises of three zones: two control centers in two cities (Mikkeli and Kuopio) and an exercise field at the training site of Emergency Services College (PEO). There are many kinds of sensors at the field connected to the sensor network. The sensors include, among others, vibration sensors, acoustic sensors, weather stations, surveillance camera systems, and chemical detectors. The network supports versatile communication technologies, including wireless communications protocols, fiber optics, and Zigbee. The ToMoVaKe sensor network provides both an interface for accessing raw measurement data as well as a user interface framework for applications.

The University of Eastern Finland (UEF) and the VTT Technical Research Centre of Finland (VTT) have developed a non-intrusive vehicle classification service [START_REF] Stocker | Detection and classification of vehicles by measurement of road-pavement vibration and by means of supervised learning[END_REF] based on vibration measurements. The service is accessed on-line and it uses trained neural networks to classify vehicles based on preprocessed vibration measurement data. The service runs in real-time. It can be trained for different environmental conditions, including annual weather changes, temporal climate changes, and sustained changes in ambient noise.

Aalto University (Aalto) has developed an on-line reachability analysis service. It computes the reachability analysis for both on-road and off-road vehicles. Therefore, it uses not only road network data, but also forest and landscape vegetation data. It computes a reachability map based on location data and vehicle type classification. The map is provided as raster data.

The Finnish Meteorological Institute (FMI) has developed a on-line chemical dispersion modeling service, called ESCAPE [START_REF] Kukkonen | Modelling source terms for the atmospheric dispersion of hazardous substances[END_REF][START_REF] Riikonen | A validated assessment tool for consequence analysis of chemical emergencies -ESCAPE for Windows[END_REF]. It computes the dispersion forecast based on weather data, type of the chemical, and other properties, such as emission location and altitude. The computed dispersion map contains also estimated concentration values. The map is provided as vector data.

Aalto University (Aalto) has also developed an on-line spatio-temporal population modeling service [START_REF] Zhang | Virrantaus K: A spatio-temporal population model for alarming, situational picture and warning system[END_REF]. The service computes an estimation of inhabitants in a region at a given time of a day. The computation is, thus, dynamic taking into account variations in population dynamics during different times of the year and day. The estimation is based on building and road data. It differentiates between building types (e.g. office or residential). The service provides population estimation in XML format based on given location parameters.

TiTiMaKe Architecture

The TiTiMaKe architecture is depicted in Figure 1. It consists of the TiTiMaKe server, ToMoVaKe system, FMI server, Aalto server, and PEO sensor network. ToMoVaKe stores the measurements. It also provides messaging and query services that are used by the TiTiMaKe server to fetch the measurements. The TiTiMake server contains the core logic, which is responsible for running the application workflow. The core logic is used to detect anomalies in the measurements and to send alarms to ToMoVaKe through the Sensor ML interface. The core logic is also used to initiate relevant computations on FMI and Aalto servers over HTTP interfaces. The TiTiMaKe server relays computational results to ToMoVaKe for visualization. This logical decomposition is also depicted in Figure 1.

TiTiMaKe uses design patterns [START_REF] Gamma | Design Patterns: Elements of Reusable Object-Oriented Software[END_REF], such as factory, bridge, facade, chain-ofresponsibility, mediator, observer, thread pool, and messaging. The architecture supports the integration of new data sources and computational services, as well as their concurrent use in multiple scenarios. Concurrency issues are resolved with an internal event queue and attachable event listeners running in multiple threads. Because of this, the architecture supports also the reuse of components throughout different scenario implementations.

Figures 2 and3 represent the domain view and the dynamic view of the TiTiMaKe core logic, respectively. The core logic has monitors, each of which executes a single scenario. A monitor has an associated listener that implements the scenario by orchestrating calls to distributed modeling services, integrating their results, and communicating with ToMoVaKe to present the modeling results. Listeners use detectors to detect certain events that are produced by sensors. For instance, a sensor could be collecting classified vehicle observations to a queue accessed by a detector. If the observations in the queue correspond to messages of interest, the detector forwards the observations to the listener. Note that the implementation of listeners, detectors, and sensors are specific to each scenario. We present now two scenarios that were implemented using the TiTiMaKe architecture: "Unauthorized driving on a private road", and "Fire at an industrial site with chemicals".

Unauthorized driving on a private road

The scenario starts with vibration sensors detecting a vehicle on a private road.

The system alerts about this by flashing a red icon on top of map on screen. At the same time, the system initiates a reachability computation, to find out how far the vehicle could drive within the next few minutes. Once the reachability computation is completed, the results are shown on the map. The person on duty can also bring up pictures of the vehicle as taken by the surveillance camera. The pictures are fetched when the person on duty clicks the flashing red icon. Based on the images of the vehicle, and the reachability results, the person on duty can either identify the vehicle or raise an alarm, if vehicle cannot be identified. Figure 4 depicts this scenario. The implementation of the scenario is depicted in Figure 5 as a sequence diagram. The communication logic of the sequence diagram was implemented as sensor, detector, and listener components in the TiTiMaKe architecture.

Fire at an industrial site with chemicals

This is a simulated scenario. The scenario starts when a fire in a factory causes an automatic fire alarm. The system fetches data about the factory and informs the person on duty and firemen about a danger of a chemical hazard. Upon an arrival, the firemen inform the control center about toxic smoke, whereby the system informs about potential toxins and visualizes a computed estimate of dispersion. Based on this, the control center starts to plan the need for additional resources and procedures. Based on a continuous on-site measurement activity, the system alerts the control center about how toxic the smoke is and computes using weather data an estimated dispersion and concentration on the map. Next, the system fetches population data within the concentration area and computes an estimate for the number of affected people and for potential risk groups. Then, the system produces an evacuation and alert message for the interest groups. The scenario is depicted in Figure 6.

As this scenario included externalities, such as an industrial site, chemical containers, and firemen, the implementation of the scenario was limited to its core functionality. The implementation is depicted in Figure 7 as a sequence diagram. In particular, the implementation focused on the interaction between the TiTiMaKe server and the computational services, namely dispersion modeling computed by the FMI server and dynamic population modeling computed by the Aalto server. The logic of the sequence diagram in Figure 7 was implemented as sensor, detector, and listener components in the TiTiMaKe architecture.

Conclusion

In this article, we discussed the integration of distributed information services to support the implementation of applications for the fields of safety and security. To support the development of such applications, and as the main contribution, we presented here the TiTiMaKe architecture. We used the architecture to implement two scenario based applications: "Unauthorized driving on a private road", and "Fire at an industrial site with chemicals".

The implementation of both scenarios confirmed that the TiTiMaKe architecture does indeed support the development of scenario based applications by using a distributed service network. The tests, however, revealed how sensitive such a system is to defects, if robustness and resilience are not considered in the communication logic. To overcome such defects, central services of the system need to be duplicated or communication with minimal information has to be guaranteed some other way, for instance by providing alternative communication media. The TiTiMaKe architecture supports both of these measures.

One clear topic for future research is to integrate more services to the TiTi-MaKe architecture and thereby to implement different kinds of scenario based applications. In this way, the core logic of the architecture becomes more versatile, thus supporting the development of more advanced safety-critical applications.

Another topic for future development has to do with the centralized aspect of the TiTiMaKe architecture. In current form, the core logic has a central supervisor. Although parts of the logic can be distributed, the supervisory logic must reside in a central server. This raises the issue of resilience, if the central server becomes unaccessible. An alternative is to investigate cooperative decision making by implementing loosely coupled autonomous servers that cooperate by communication. Such an arrangement would facilitate not only better robustness and resilience, but also better performance scaling when the number of concurrent applications increases.

Fig. 1 .

 1 Fig. 1. TiTiMaKe architecture and logical decomposition.

Fig. 2 .

 2 Fig. 2. Domain view of the TiTiMaKe core logic.

Fig. 3 .

 3 Fig. 3. Dynamic view of the TiTiMaKe core logic.

Fig. 4 .

 4 Fig. 4. Unauthorized driving on a private road.

Fig. 5 .

 5 Fig. 5. Implementation of the scenario "Unauthorized driving on a private road" depicted as a sequence diagram.

Fig. 6 .

 6 Fig. 6. Fire at an industrial site with chemicals.

Fig. 7 .

 7 Fig. 7. Implementation of the scenario "Fire at an industrial site with chemicals" depicted as a sequence diagram.

Acknowledgements

We wish to thank the Finnish Funding Agency for Technology and Innovation (TEKES) and the industrial partners (APL Systems Oy, Control Express Finland Oy, Environics Oy, Finnish Defence Forces Research Centre, and Symo Oy) for funding this research. We also wish to thank all our academic partners (Aalto University, Emergency Services College, and Finnish Meteorological Institute) for excellent work and support during the project. Mauno Rönkkö and Mikko Kolehmainen would also like to thank European Regional Development Fund and TEKES for support to continue research in cooperation with Amphion Loudspeakers Oy, Genelec Oy, Mediatuotanto Mindcom Oy, Observis Oy, and Defence Forces Technical Research Centre. Last but not least, we wish to thank Heikki Isotalus and Jarmo Kastinen for technical support.


Petr Šauer
email: sauer@vse.cz

Petr Fiala
email: pfiala@vse.cz

Antonín Dvořák

Modelling of Environmental Risk Management under Information Asymmetry

Keywords: environmental risk, management, pollution, combinatorial auctions, environmental subsidy, economic laboratory experiments

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

Introduction

Reducing environmental risks in a cost-effective way is an important issue in environmental economics and policy. Three kinds of environmental policy instruments are able to achieve this solution: tradable pollution rights (permits), environmental charges/taxes and financial supports. This paper presents a relatively new approach to environmental risk management. It is a negotiation between polluters and authorities (mostly government in practice) where economic instruments of environmental policies in the form of financial support are applied and where there is an information asymmetry between the authority and the polluters. The authority distributes financial resources in a one-round auction. The polluters know their individual abatement costs and try to maximize their surplus, which they can get if they apply for and negotiate higher support from the authority than the minimum they need, so their project is efficient for them. They are also allowed to establish coalitions to achieve goals in environmental risk reduction. After negotiating with the coalition partner(s), they apply for financial support to the coalition project(s) together with their individual projects.

The research questions were as follows: (i) to what extent can the negotiated result be close to the computed optimum solution, (ii) what is the role of the financial pressure on the subjects and pay-offs, and (iii) how do the coalition subjects distribute the "extra cake" from getting higher support than the minimum?

Economic laboratory experiments were used as the method to answer the research questions. It is possible to observe increasing use of economic laboratory experiments in research. Supporters of these experiments argue that the experiments can serve well in fundamental research for (pre)testing theoretical hypotheses and continuing to build theories. In applied research, the experiments serve testing various institutional settings that are considered for introduction in policy practice. For the use of economic laboratory experiments for research purposes and its advantages and disadvantages, see for instance [START_REF] Davis | Experimental Economics[END_REF][START_REF] Smith | Experimental Economics: Induced Value Theory[END_REF][START_REF] Walker | Economic Instruction: Experimental Economics in the Classroom[END_REF][START_REF] Roth | Introduction to Experimental Economics[END_REF][START_REF] Sauer | A Procedure for Negotiating Pollution Reduction under Information Asymmetry[END_REF][START_REF] Levitt | What Do Laboratory Experiments Measuring Social Preferences Reveal about the Real World?[END_REF][START_REF] Falk | Lab Experiments are a Major Source of Knowledge in the Social Sciences[END_REF].

The paper is structured as follows: The general model of combinatorial auctions is presented first. Theoretical optimum results for a case with 10 polluters computed with the use of the CRAB software are compared with experimental results, where financial pressure and pay-offs were not introduced. A new series of laboratory experiments where financial pressure and pay-offs are introduced is described and the results are presented in the last part.

Combinatorial auctions -general model

Combinatorial auctions serve as a theoretical framework for the approach presented in the paper. Auctions are important market mechanisms for the allocation of goods and services. Auctions have emerged as a particularly interesting tool for negotiations. An auction provides a mechanism for negotiation between buyers and sellers. Combinatorial auctions [START_REF]Combinatorial Auctions[END_REF][START_REF] De Vries | Combinatorial auctions: A survey[END_REF] are those auctions in which bidders can place bids on combinations of items, so-called bundles. The advantage of combinatorial auctions is that the bidder can express his preferences more fully. This is particularly important when the items are complements. The auction designer also derives value from combinatorial auctions. Allowing bidders to express preferences more fully often leads to improved economic efficiency and greater auction revenues. It is possible to formulate singlesided combinatorial auctions, forward auctions and reverse auctions. In forward auctions, a single seller sells resources to multiple buyers. In reverse auctions, a single buyer attempts to source resources from multiple suppliers, as is common in procurement.

The problem, called the winner determination problem, has received considerable attention in the literature. The problem is formulated as follows: Given a set of bids in a combinatorial auction, find an allocation of items to bidders that maximize the seller's revenue. Many important ideas are introduced, such as the mathematical programming formulation of the winner determination problem, the connection between the winner determination problem and the set packing problem, as well as the issue of complexity.

Many types of combinatorial auctions can be formulated as mathematical programming problems. Among the different types of combinatorial auctions, we present the reverse auction of indivisible items with one buyer and several sellers. This type of auction is important for the supplier selection problem. This type of auctioning serves as the theoretical basis for our case, where the polluters sell their contributions to environmental risk reduction when investing in pollution reduction projects.

Let us suppose that m potential sellers S1, S2, ..., Sm offer a set R of r items, j = 1, 2, …, r, to one buyer B (see Fig. 1).

Fig. 1. Reverse auction

A bid b h made by the seller S h , h = 1, 2, …, m, is defined as b h = {C, c h (C)}, (1)
where C ⊆ R, is a combination of items, ch(C), is the offered price by seller Sh for the combination of items C. The objective is to minimize the buyer's cost given the bids made by sellers. Constraints establish that the procurement provides at least a set of all items.

Bivalent variables are introduced for model formulation:

y h (C) is a bivalent variable specifying whether the combination C is bought from the seller S h (y h (C) = 1).
The reverse combinatorial auction can be formulated as follows

1 m h  CR   c h (C) y h (C)  min (2) subject to 1 m h  CR   y h (C)  1,  j ∊ R, (3)
B S 1 S 2 S m y h (C) ∊ {0, 1},  C ⊆ R,  h, h = 1, 2, …, m. (4)
The objective function expresses the cost. The constraints ensure that the procurement provides at least a set of all items.

The CRAB (CombinatoRial Auction Body) software system was proposed [START_REF] Fiala | CRAB-CombinatoRial Auction Body Software System[END_REF]. The CRAB is a non-commercial software system for generating, solving, and testing of combinatorial auction problems. The system solves problems using Balas' method or the primal-dual algorithm.

Base experimental case

An ideal model territory was created for the laboratory experiment. There were 10 polluters in 5 groups specified as A, B, C, D and E. This group also shows where it makes sense (from the economic point of view) to think about coalition projects (see Fig. 2).

Fig. 2. Polluters in the region

Information about 10 individual projects (A1, A2, A3; B1, B2; C1, C2, C3; D; E1) and for 9 coalition projects (A1-A2, A1-A3, A2-A3, A1-A2-A3; B1-B2; C1-C2, C1-C3, C2-C3, C1-C2-C3) was prepared. The environmental effects were expressed as emission reduction (as an easy-to-understand indicator), but environmental risk reduction could also be applied. The following indicators were prepared for each of the projects: Pollution reduction dEi, i = 1, 2, …, 19, Minimum financial support Pmini, i = 1, 2, …, 19, needed from an external source, so the projects are economically efficient for the subject. The minimum financial support was based on the idea of so-called net abatement costs [START_REF] Šauer | Negotiation between authority and polluters: A model for the support of decision-making in ecological policy (in Czech)[END_REF].

A table with all the experimental data can be found in [START_REF] Fiala | Application of Combinatorial Auctions on Allocation of Public Financial Support in the Area of Environmental Protection: Economic Laboratory Experiment (in Czech)[END_REF]. The subjects playing the role of the managers were asked to reduce the pollution by a given amount for each of the groups. They could apply for support for individual projects and/or negotiate within the group for support for coalition projects. Students of the University of Economics played the role of the polluters. Teachers -authors of the paper -played

A A1 A2 A3 B B1 B2 E E1 C C1 C2 C3 D D1
the role of the authority. A cost-effective solution was computed with the CRAB software. The results of 8 experiments (E1 … E8) were compared to this first best solution.

The main goal of these economic laboratory experiments was to test whether and to what extent it is possible to establish coalitions that will solve the problem of pollution reduction with the lowest costs. The experiment was already complex enough, so it would be difficult to stimulate the subjects to reduce their bids. It would be possible via introducing multi-round negotiations. For more details about this experiment, see [START_REF] Fiala | Application of Combinatorial Auctions on Allocation of Public Financial Support in the Area of Environmental Protection: Economic Laboratory Experiment (in Czech)[END_REF]. Most of the experiments achieved close to the optimum (first best) solution in terms of the structure of selected projects (i.e. the "right" coalitions were found). It can be seen in Table 1 that without the application of multi-round negotiations or/and a financial pressure on the subjects, the negotiated financial support is very high.

Partially detailed experiments -design and results

Two experiments were prepared. The case for them was derived from the base experiment mentioned in Section 3, including the data where also the first best solution was computed. The first experiment was designed for groups of two subjects. The second experiment was elaborated for groups of three subjects.

Experiment design

Experiment design for groups of two subjects (A and B). Sixteen students of the University of Economics, Prague (8 in international trade major and 8 in theory of decision making major) and sixteen students of the College of Polytechnics Jihlava (management of tourism major) were subjects in the experiments. They played the roles of managers applying for the financial support from the authority. The role of the authority was played by the teacher (the same person in all the experiments).

Pollution
The subjects in the role of managers were given the following materials (see attachment for more details):

 The situation (case) description  Training (non-confidential) data for better understanding the experiment  Confidential data for the experiment(s)  Application form for financial support from the authority.

The subject playing the role of the authority had the same materials as the students plus a description of details of the experimental process to keep the same conditions in all the repetitions of the experiments.

The subject playing the role of the authority distributed the materials, made a picture of the situation on the blackboard and explained the case, demonstrated the managers' decision making process on the training data, and collected the filled-in application forms for financial support from the subjects at the end of the experiments. He also informed the subjects that there is one round of application possible, that the financial resources for financial support are limited (i.e., not all applications can be supported) and that the subject will be financially rewarded after the experiments (CZK 30 for showing up + part of the surplus they will negotiate in the experiment).

4.2

Experiment results for groups of two subjects (Table 2)

Solution for individual groups.

The first-best solution for groups of two subjects (A, B) is to establish the coalition AB with a total pollution reduction of 70 units and a minimum support of 50 monetary units. All these groups established coalitions with minimum requested support of 72.5 monetary units on average in the University of Economics experiments (71.4 monetary units in the Polytechnics Jihlava experiments). In the base experiment (see Section 3) without pressure, the requested support was 85 monetary units on average.

Solution for the whole region.

If we presume pollution reduction in the whole region by 60%, the total pollution reduction would be 336 units (0.6*8*70 = 336). By solving the combinatorial reverse auction problem (see Section 2), we get a solution of selected coalitions: 1AB, 4A, 5AB, 6AB, 7AB, 8A; the minimum support would be 323.6 monetary units in the University of Economics experiments (1A, 4AB, 5AB, 6AB, 7A, 8AB); the minimum support would be 316 monetary units in the Polytechnics Jihlava experiments). The solutions are not trivial; they are combinations of one-and two-element coalitions.

Distribution of surplus.

The total surplus in the experiments under pressure is lower than in the experiments without pressure. The distribution of surplus in negotiations between the subjects A and B is 9.9 : 12.6 average in the University of Economics experiments (9.4 : 12 in the Polytechnics Jihlava experiments).

4.3

Experiment results for groups of three subjects (Table 3)

Solution for individual groups.

The first-best solution for groups of three subjects (A, B, C) is to establish the big coalition ABC (total pollution reduction of 230 units) with a minimum support of 60 monetary units.

Six groups of three subjects (1-6) established the big coalition with a minimum requested support of 94 on average. Group no. 7 proposed the best solution by establishing the coalition AB (requested support 45) and C (requested support 50), totalling 95 monetary units. The requested support for the big coalition was 99 monetary units. In the base experiment (see Section 3) without pressure, the requested support was 133.125 on average, which is almost 50% more.

Solution for the whole region.

If we presume pollution reduction in the whole region by 60%, the total pollution reduction would be 966 units (0.6*7*230 = 966). By solving the combinatorial reverse auction problem (see Section 2), we get a solution of selected coalitions: 1AB, 2ABC, 4ABC, 5AB, 6AB, 7AB; the minimum support would be 359 monetary units. The solution is not trivial; it is a combination of two-and three-element coalitions.

Distribution of surplus.

The total surplus in the experiments under pressure with three subjects is lower than in the experiments without pressure. The distribution of surplus in negotiations among the subjects A, B and C is 10.7 : 10.4 : 13.6 on average.¨

Concluding remarks

Modelling of environmental risk management under information asymmetry seems to be a very promising area of research. The aim of this paper was to contribute to a theoretical framework and compare the computed theoretical first-best solution with experimental results. Models of combinatorial auctions were selected as the theoretical framework. A base experimental case and partially detailed experiments were created and used for testing the basic research questions in the paper, which were as follows: (i) to what extent can the negotiated results be close to the computed optimal solution, (ii) what is the role of financial pressure on the subjects and pay-offs, and (iii) how do the coalition subjects distribute the "extra cake" from getting higher support than the minimum?

The experiments showed that the experimental results were close to theoretical results mainly in the structure of the solution, i.e., the structure of selected coalitions to the structure of the first best solution. The required supports are significantly closer to the theoretical minimum supports in the experiments under financial pressure than in the situations without the pressure, i.e., in the situations where all the subjects get the supports and there is no pay-off for the subjects in the experiments. The negotiated distributions of the surplus among the subjects are, on average, fairly balanced. Small differences are caused by the position of the subject in establishing coalitions. An interesting observation is the finding that the results are very similar for groups of students (experimental subjects) from different universities.

The results in the paper inspire us to continue experiments for a richer structure of coalitions with multi-round negotiations under pressure and with the introduction of multi-criteria evaluation of environmental and other effects performed by the authorities. These more general cases promise to bring new interesting findings. The EU Operational Programme Environment (OPE) support for water management infrastructure and the reduction of flood risks is a typical field of application for establishing joint (coalition) projects supported from public funds. We believe that it also makes sense to develop one-round models. This procedure is typical for various support programmes, such as the grants provided from the OPE for reducing industrial pollution and environmental risks.

  reduction by individual projects: dPA, dPB Pollution reduction by a joint project: dPAB = dPA + dPB Costs of individual projects: CA, CB Costs of joint (coalition) project: CAB Experiment design for groups of three subjects (A, B and C). Pollution reduction by individual projects: dPA, dPB, dPC Pollution reduction by joint projects: dPAB = dPA + dPB; dPAC = dPA + dPC; dPBC = dPB + dPC; dPABC = dPA + dPB + dPC Costs of individual projects: CA, CB, CC Costs of joint (coalition) projects: CAB, CAC, CBC, CABC

Table 1 .

 1 Comparing computed and experimental results

	Computed optimum solution								270
	Experiment no.	E1	E2	E3	E4	E5	E6	E7	E8
	Negotiated financial support 520 348 470 417 521 370 500	510
	Minimum support	340 280 270 310 315 270 300	290

Table 2 .

 2 Results of the experiment for groups of two subjects

	Project	Pollution	Univ. of Economics, Prague		Polytechnics Jihlava
		reduction	Required	Surplus	Surplus	Required	Surplus	Surplus
			support	A	B	support	A	B
	1A	30	30	10	-	25	5	-
	1B	40	78	-	18	70	-	10
	1AB	70	70*	9	11	70*	10	10
	2A	30	35	15	-	50	30	-
	2B	40	95	-	35	90	-	30
	2AB	70	80*	10	20	80*	15	15
	3A	30	30	10	-	30	10	-
	3B	40	70	-	10	75	-	15
	3AB	70	75*	15	10	75*	15	10
	4A	30	27	7	-	32	12	-
	4B	40	70	-	10	75	-	15
	4AB	70	80*	10	20	72*	10	12
	5A	30	23.5	3.5	-	30	10	-
	5B	40	80	-	20	68	-	8
	5AB	70	70*	8	12	64*	6	8
	6A	30	30	10	-	30	10	-
	6B	40	80	-	20	75	-	15
	6AB	70	70*	10	10	70*	5	15
	7A	30	35	15	-	25	5	-
	7B	40	65	-	5	90	-	30
	7AB	70	65*	7	8	80*	10	20
	8A	30	21.6	1.6	-	30	10	-
	8B	40	70	-	10	70	-	10
	8AB	70	70*	10	10	60*	4	6

Table 3 .

 3 Results of the experiment for groups of three subjects

	Project Pollution Reduction Required support Surplus A Surplus B Surplus C
	1A	90	35	5	-	-
	1B	40	65	-	35	-
	1C	100	75	-	-	25
	1AB	130	50	7	8	-
	1AC	190	100	10	-	20
	1BC	140	90	-	15	15
	1ABC	230	90	10	10	10
	2A	90	41	11	-	-
	2B	40	45	-	15	-
	2C	100	66	-	-	16
	2AB	130	55	10	10	-
	2AC	190	88	8	-	10
	2BC	140	78	-	9	9
	2ABC	230	84	8	7	9
	3A	90	50	20	-	-
	3B	40	40	-	10	-
	3C	100	85	-	-	35
	3AB	130	55	15	5	-
	3AC	190	100	10	-	20
	3BC	140	80	-	5	15
	3ABC	230	90	5	5	20
	4A	90	55	25	-	-
	4B	40	40	-	10	-
	4C	100	60	-	-	10
	4AB	130	50	10	5	-
	4AC	190	85	5	-	10
	4BC	140	70	-	5	5
	4ABC	230	80	5	5	10
	5A	90	40	10	-	-
	5B	40	35	-	5	-
	5C	100	75	-	-	25
	5AB	130	45	5	5	-
	5AC	190	90	10	-	10
	5BC	140	90	-	15	15
	5ABC	230	100	14	13	13
	6A	90	40	10	-	-
	6B	40	45	-	15	-
	6C	100	60	-	-	10
	6AB	130	55	10	10	-
	6AC	190	100	15	-	15
	6BC	140	90	-	15	15
	6ABC	230	120	20	20	20
	7A	90	40	10	-	-
	7B	40	40	-	10	-
	7C	100	50	-	-	0
	7AB	130	45	3	7	-
	7AC	190	85	8	-	7
	7BC	140	70	-	4	6
	7ABC	230	99	13	13	13

Acknowledgement. The paper was developed with the support of the Czech Science Foundation, grant no.13-07036S "Modelling of Negotiations in Environmental Policy under Information Asymmetry".

Annex -Text distributed to the subjects (Polluter A as an example; case of the groups of three subjects).

Case situation.

In the region in which your Firm [ A ] is located, there are several sources of environmental pollution. It is important to reduce this pollution due to fulfilment of an international agreement in the field of environmental risk reduction. Each of the polluters has four potential projects for reducing the pollution in the region. The individual project is one of the options. Joint (coalition) projects with the other firms [ B, C ] is the other option. Each of the projects (i.e., individual or coalition ones) offers some pollution reduction (dP), requires some costs (C) and needs some minimum external financial support (Smin). The firms and/or their coalitions apply for this financial support at the authority. The application procedure has one round. In the application forms, you are supposed to fill in: a) Pollution reduction offered (see dP in the Confidential data …) and b) Required amount of financial support; its amount is based on your negotiation strategy; you must not request less than the shown minimum amount (Smin in the Confidential data …).

The financial resources for the support are limited. The support will be distributed to the most efficient projects, i.e., not all projects can be supported. If you succeed in getting higher support than the minimum you need (Smin), you get a surplus. The whole surplus belongs to you in the case your individual project is supported. In case a coalition project is supported, you share the surplus with the other firms in the coalition. The shares in the surplus are negotiated with the other firms before the application is submitted.

You will be rewarded for your participation in the experiment. The remuneration will consist of a show-up fee of CZK 30 and the amount derived from the amount of surplus you get.

Training data (non-confidential data for better understanding the experiment by the subjects; case of the group of two subjects):


Thorsten Hell
email: thorsten.hell@cismet.de

Eckhard Kohlhas
email: eckhard.kohlhas@lung.mv-regierung.de

Sascha Schlobinski
email: sascha.schlobinski@cismet.de

Ralf Denzer
email: ralf.denzer@enviromatics.org

Reiner Güttler
email: reiner.guettler@enviromatics.net

An Information System Supporting WFD Reporting

Keywords: Water Framework Directive, WFD, water reporting, environmental information system, EIS

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

1

Software support in the context of the EU WFD

The EU Water Framework Directive1 (WFD, [1]) requires the EU Member States to provide reports on the biological and chemical status of ground and surface water, to plan and execute programs for improvement and to report about plans, measures and results as well. In Germany these reporting requirements are managed by the federal states and the national government. The reporting is carried out through a formalized data model in order to harmonize data across Europe. Reported information is available in the Water Information System for Europe (WISE) [START_REF]Water Information System for Europe (WISE)[END_REF].

In the German state Mecklenburg-Vorpommern, the WFD reporting is carried out in the context of the FIS Water MV (Water Information System of Mecklenburg-Vorpommern), which aims at providing an integrated water information base for all water-related management and reporting activities in the state. Besides water information, data from sources like general statistics, agriculture, land use, nature protection and bio diversity etc. are relevant for the assessment of water body quality.

The diverse water-related data and processes (like runoff, drainage, gages, flood forecasts, maintenance plans etc.) require the same baseline and common base geometries. For this reason, the WFD reporting cannot be regarded as an isolated activity that happens once a year.

The FIS Water MV ( Fig. 1) is operated by the "Landesamt für Umwelt, Naturschutz und Geologie Mecklenburg-Vorpommern" (LUNG), the state agency for environment, nature protection and geology. The different systems are at different stages of realisation.

While the FIS WRRL (WFD Reporting) is productive, other components are under development or only at a conceptual stage. E.g. the FIS for flood risk management is currently under implementation and the information system for water use and wastewater will be upgraded from 2014 on.

Fig. 1. Overview of FIS Water MV

All systems operate on catchments and water bodies regardless of political boundaries. They use a common water network with unified numbering and stationing, the same references for coastal zones, the same geometry and referencing for still waters and a common spatial reference system. This paper gives an overview of the FIS WRRL (Information System for WFD Reporting).

Users, requirements and functional architecture

The FIS WRRL must support users from several organisations involved in WFD activities that have a variety of different requirements (Fig. 2). The organisatons are:

 the LUNG as the responsible organisation,  subsidiary water administrations, namely 4 state agencies for agriculture and environment who are responsible for the management of 4 territories (shortly called "state agencies" in this paper),  subsidiary lower water administrations,  water and soil management associations who are not direct subsidiaries and  external users like contractors.

Fig. 2. Users of the FIS WRRL

Some of these users operate on the scale of the whole state, others (like lower water administrations, regions and cities) only within their territories. Also, some users work on information beyond WFD data and may need to connect their concepts and data with data in the WFD reporting system.

The following fundamental goals were defined before the FIS WRRL was developed. To:  enable on-the-fly reporting (push-button-reporting) at any time,  support those workflows in the LUNG which are required for WFD reporting,  provide current and historic data on a day-to-day basis,  hold the WFD-related data in a central common data repository in the LUNG,  enable decentralized data input and maintenance, also by external users, while avoiding redundancies  enable the integration of data from other data holders  ensure that the solution is scalable,  ensure that the solution is extendable towardsother components of the FIS Water MV and beyond,  use open standards and to avoid licensing costs. Some of these requirements lead directly to a service-based approach, based on open source / open standards software. A critical issue was to provide a fine grain security and access control framework as users from different administrative bodies interact with the system. Fig. 3 shows an overview of the functional architecture. At the core is a WFD data repository which serves to store all WFD-related data, including photo documentation and related features. Beyond the data as such, information regarding management strategies, ongoing and past projects, project monitoring and cost is also included in this core repository. Water body network data can be imported from external sources. The actual WFD reporting is based on WFD Reporting Templates which are used to configure the reports to the BFG (Bundesanstalt für Gewässerkunde) 2 . The current format for reports to the BFG is the Shape-File format3 . Additionally the system allows service-based access to reports.

3

Software stack for the solution

The solution has been implemented with a stack of freely available open source software. The core of the solution is the CIDS product suite of CISMET GmbH. This product consists of a set of software components, application programming interfaces (APIs), management and development tools, services and applications, with a special focus on interactive solutions which need to integrate geo-spatial systems with databases, sensor networks, document-oriented systems, unstructured information sources and numerical models. CIDS is particularly suited for solutions which have to be built across existing heterogeneous information systems, which may be under control of different organisations. CIDS uses freely available open source software exclusively, is itself freely available as open source software, distributed as Github 4 projects, and is compliant with all major OGC services. CIDS has been used in numerous projects since 1999 [START_REF] Güttler | An EIS Called WuNDa[END_REF]. For recent projects see [START_REF] Denzer | An Environmental Decision Support System for Water Issues in the Oil Industry[END_REF][START_REF] Schlobinski | Vision and Requirements of Scenario-Driven Environmental Decision Support Systems Supporting Automation for End Users[END_REF]. The CIDS Kernel consists of one or more Integration Base(s), which are connected to a network of services. One Integration Base represents one CIDS Domain. Domains are used to organise thematic application areas within larger solutions. Domains in a large municipality can for instance be "traffic", "noise", "water bodies", "land register", "street light inventory" or "waste water". In cross-governmental applications, domains can also be organised as "City of X", "City of Y", "Water Supplier of City of Y", "Region Z". The domain concept includes fine grain control of access rights and access policies even across domains.

The Integration Base consists of a standard relational Database Management System (DBMS) augmented by meta-information that facilitates integration tasks. It is the basis for a concrete CIDS solution and is able to model arbitrary objects (realworld objects, services, models, geographical features, other information systems, etc.), their attributes (e.g. data types, geographic location) and relationships. The Integration Base also models users, user groups, navigational structures for users, permissions, and many other properties

The Integration Base is protected through Access Control mechanisms. Moreover, the CIDS Kernel consists of a Server Actions module that can be used to run procedures on the integration base, for instance for aggregation or statistics.

The concrete data of a CIDS solution can reside in external systems, or within the Integration Base, or both. For each individual attribute, CIDS can be the "leading system" or the "following system", and there are diverse mechanisms for synchronisation and mapping of data structures in both directions (from or to an external system). As an example, in a waste water taxation application, the user interacts with a "land parcel", which in physical terms consists of geo-data coming from external WMS/WFS services, geo-data stored in the Integration Base itself (individual parcels within the premise, which are only needed in this application), ownership information from a database and documents from a standard document management system. Three types of services constitute a CIDS Service Network:  A Domain Service publishes one Integration Base.  A Broker Service acts as proxy hiding details of distributed access from client applications.  A Registry Service is responsible for service name resolution, rights management, parallelised distributed search as well as core infrastructure functionalities such as service infrastructure monitoring.

A complex system can contain any number of Integration Bases and can be scaled in any direction using an appropriate number of Integration Bases and services. The physical design of this network is adapted to the organisational and computational setup of a concrete customer. A minimal system consists of one software bundle which publishes one Integration Base, and which integrates no external data sources at all (similar to operating one standard RDBMS server and using a dedicated database client software).

A CIDS Service Network is configured and developed with an interactive development and configuration environment (CIDS-IDE), which consists of the configuration and development tool ABF and the ETL tool JPresso for synchronisation with external systems. The Server Console is a management interface to the CIDS services.

Fig. 5. CIDS ABF

As open source software the CIDS platform uses many open source tools to provide its functionality. Among the most prominent are: Netbeans RCP 5 and PostGres/PostGis6 .

End user view of a highly integrated interactive application

End users interact with the CIDS solution through customized interactive applications. At the core of most developments is the CIDS Navigator. The Navigator offers different metaphors to interact with the system. The Inventory at the left (in Fig. 6) is a customized poly-hierarchical view over user interests and serves for "browsing" and "search". Entries in the inventory are often data objects that represent arbitrary data sets ("water bodies" as top level of a water domain), but can also be information like organisational processes ("maintenance", "people", "billing") or interactions with and results of numerical models ("runoff model", "model configuration", "model run"). The Inventory can be customized for user groups and individual users.

Fig. 6. CIDS Navigator

In the case of the WFD reporting system described in this paper, the inventory contains the following themes: chemical monitoring sites, biological monitoring sites, rivers, still waters, ground water bodies, coastal water bodies, buildings, projects, drainage pipes, routes, catchments, photo documentation, land use, protected areas, hydrology and several waterway maintenance themes.

For spatial information, the map component Cismap is provided. This component is a map application specialized to access OGC compliant services like WFS and WMS for information from internal and external geospatial data sets. The individual layers being visualized can be either layers generated by CIDS or external layers as required.

The third way to interact with the system are "data pages", which can be relatively simple views but also full blown applications (Thematic Apps), customized to the user's view on the data provided. Data pages can include visualization and interaction with time series data, photo documentation, document views, spatial previews and many more types of information; data pages can be configured to allow for editing of the data contained as required.

An outstanding feature of the Navigator is the fact that users can search, browse and interact seamlessly across these different metaphors. For instance data objects can be dragged on to the map, and polygons on the map can be used to query data themes in the service network, including all connected external systems. The software of the Navigator includes extension points for interactive editors and renderers which can be included in map views and data pages respectively. There is also an extension point for information aggregation over a set of objects. Customization: linear referencing

The CIDS system provides a powerful framework to build geo-spatial information systems. However, in every project customizations are necessary particularly at the graphical user interface to support end users in an optimal fashion. An example of such a customization is the Linear Referencing implemented as part of the FIS WRRL implementation.

Fig. 9. Linear referencing

In a river network, the so-called route is an important concept. A route defines one river with a name and a unique number. The river is represented in the system by a polyline "M" which contains measurement information. Every location along a river can be referenced along the route by the distance to the estuary. This reference is called linear reference. Linear references are used throughout waterway management and are a central concept to connect information to a location (which is along a river). Because this concept is so central, it was essential that end users be supported in stationing (locating) arbitrary objects interactively along a route, and to enable them to create station segments which are for instance used for waterway maintenance projects.

Through a custom extension point of CIDS an interactive editor for CISMAP was implemented to support the stationing of objects ( Fig. 9). With this, users are enabled to position objects along rivers and to create segments.

Assessment and conclusions

The FIS WRRL has been in operation since 2011 and has supported WFD reporting since. The FIS Water MV is currently being extended with additional systems in order to provide an integrated water information framework for the state. The choice of open software has proven to be important for long-term protection of investments into the water information infrastructure of the state. With the realisation of the FIS-WRRL, the state Mecklenburg-Vorpommern has made an important step towards co-ordinated water information management. All WFD-related information can now be managed in a coherent way at a central location while data maintenance is performed in a decentralized fashion by the LUNG, the 4 state agencies and other organisations in a federated fashion based on geographical and organisational access rights. Now the reports required for EU WFD reporting can be generated in an on-the-fly procedure based on actual daily data.

At the same time, the kernel of an integrated water information system has been developed which serves administration, policy and experts in their daily work.

The system has been in productive operation in the state agencies for two years, has operated without problems and has become an important information asset for the daily work of experts. Since one year, water management agencies and soil management agencies use the system. In total, 300 users are registered and daily logins are around 70 (May 2013). The users can access a total of 204 information themes supplied by the water management agencies. These themes are structured according to the needs of the WFD. Users generate approximately 15000 map access interactions each day.

The supported functionalities of the system are also extended. Since 2011 a business process supporting the mapping of morphological features of the waterbodies (FGSK -Fließgewässerstrukturgütekartierung) is integrated. Since then, contractors of the 4 state agencies, typically engineering companies, can directly maintain results of the FGSK mapping from their sites. Both contractors and water management agencies thus operate on a highly actual information base.

Currently (June 2013) a solution for river maintenance planning is in the test installation while a project has been started to build an information management application for the inventories of watercourses, profiles and technical plants maintained by the water and soil associations.

The technical solution is fully compliant with OGC standards7 and additional information sources complying with these standards can be accessed on-the-fly by end users. Most of these geographical data sources are maps and aerial photos provided by the "Landesamt für innere Verwaltung (LAIV-MV)". Access to mapping services of the neighbouring states Brandenburg, Niedersachsen und Schleswig-Holstein make sure that the view is not restricted at the state borders.

Fig. 3 .

 3 Fig. 3. Overview of functional architecture

Fig. 4 .

 4 Fig. 4. Overview of CIDS product suite

Fig. 7 .Fig. 8 .

 78 Fig. 7. Geographic interaction with Cismap

5

 5

http://ec.europa.eu/environment/water/water-framework/

http://www.bafg.de

http://www.esri.com/library/whitepapers/pdfs/shapefile.pdf

https://github.com/cismet

http://netbeans.org/features/platform

http://www.postgresql.org

http://www.opengeospatial.org


Katharina Schleidt
email: katharina.schleidt@umweltbundesamt.at

INSPIREd Air Quality Reporting European Air Quality e-Reporting Based on INSPIRE

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

Introduction

The For this purpose, the requirements ensuing from the AQD must be analysed and the appropriate classes from the INSPIRE data specifications that can serve as base classes for AQD e-Reporting must be identified. These INSPIRE base classes must then be extended as required to fulfil all requirements ensuing from the AQD. In addition, mandatory attributes stemming from the INSPIRE data specifications must be integrated with the existing reporting requirements from the AQD.

In this paper, we provide both information on the legal background pertaining to the AQD and INSPIRE, as well as detailing the process required for the extension of the existing INSPIRE based classes to the requirements of e-Reporting under the AQD. The annexes of the IPR also provide information on data processing and encoding, mandatory thresholds such as limit and target values, aggregates and statistics to be provided as well as the units of measurement to be used for the provision of data.

Background

INSPIRE and AQD Data Models

The INSPIRE is based on the infrastructures for spatial information that are created by the MS and that are made compatible with common implementing rules and are supplemented with measures at Community level. These measures should ensure that the infrastructures for spatial information created by the MS are compatible and usable in a Community and trans-boundary context.

The INSPIRE Directive states that infrastructures for spatial information in the MS should be designed to ensure that spatial data are stored, made available and maintained at the most appropriate level; that it is possible to combine spatial data from different sources across the Community in a consistent way and share them between several users and applications. Since the wide diversity of formats and structures in which spatial data are organised and accessed in the Community hampers the efficient formulation, implementation, monitoring and evaluation of Community legislation that directly or indirectly affect the environment, implementing measures should be provided for in order to facilitate the use of spatial data from different sources across the MS. Network services are necessary for sharing spatial data between the various levels of public authority in the Community. Those network services should make it possible to discover, transform, view and download spatial data and to invoke spatial data and e-commerce services.

INSPIRE and Reporting.

While the basic INSPIRE data specifications consciously do not take reporting requirements into account, they are built in such a manner as to allow for extension for reporting purposes. Various environmental reporting obligations were provided as Use Cases to the Thematic Working Groups, and taken into consideration in the definition of the INSPIRE data specifications for relevant themes.

Annex F of the INSPIRE Generic Conceptual Model describes how the INSPIRE data specifications can be extended in order to support other purposes while maintaining the INSPIRE requirements. Thus, data provided using an INSPIRE based extended data specification can be used to fulfil obligations stemming from both INSPIRE as well as a thematic reporting requirement, thus reducing the burden on MS data providers.

However, the inclusion of the explicit reporting concepts directly into the INSPIRE Data Specifications would not be beneficial, as this would increase the legislative burden each time thematic reporting requirements were adjusted. In addition to the necessary modifications of the thematic legislation, changes to the INSPIRE Data Specifications would also be required. Thus, the INSPIRE Data Specifications have been designed in such a manner to provide the core thematic framework, which can then then be extended to also support the additional requirements stemming from reporting requirements.

AQD Data Model.

The AQD e-Reporting data model has been designed based on the INSPIRE data specifications. The UML data models created by the INSPIRE Thematic Working Groups (TWG) have been extended to support all requirements stemming from the IPR; these data models have then been used to generate the AQD e-Reporting schemata. The INSPIRE Annex III data specifications, that are of specific relevance to the provision of air quality data under the AQD, are in the process of finalisation.

At the present time, information on the INSPIRE based AQD e-reporting data model is available only from the EEA Air Quality (AQ) Portal. This information includes UML diagrams, presentations on the data model, a mapping file showing the correspondence between the individual elements of data flows B-G to the data model as well as preliminary XSD schema files.

Further background information is also available from the INSPIRE data specification on Environmental Monitoring Facilities which provides the basis for the AQD ereporting data model as well as the Guidelines for the use of Observations & Measurements (O&M) and Sensor Web Enablement-related standards in INSPIRE Annex II and III data specification development. While these documents do not specifically cover the AQD e-reporting data model, they provide valuable background information and insights to this specification.

3

Definition of the AQD e-Reporting Data Model

Data Model Definition Process

In order to achieve full synergies between INSPIRE and the newly defined AQD e-Reporting, it is necessary to define an INSPIRE based data model fulfilling all requirements ensuing from the AQD. The air quality reporting concepts have been harmonized within Annex II of the Implementing Provisions (2011/850/EU) of the AQD and described as discrete data flows. Data flows B-G are of relevance to INSPIRE, as the data to be provided under these data flows corresponds directly to INSPIRE Themes. The information to be provided under data flows H-K pertain to air quality Plans and Programmes; while the data models for these data flows are also modelled in accordance with all specifications and requirements from the INSPIRE Directive for simplicity of reporting, there is no direct connection between these data flows and INSPIRE data types. Thus, data flows H-K will not be further discussed in this paper. In addition, in ANNEX II the section (A) Common Data types provides common data types that are referenced and reused by the data flows B-K.

In the table below, a mapping to the INSPIRE Themes identified as relevant to serve as base classes for the implementation of these data flows is provided:

Extension Examples

The relevant classes from the INSPIRE data specifications must be identified, and the required reporting concepts mapped to these classes. Where necessary, the base classes provided by INSPIRE must be extended with Air Quality reporting specific concepts. This mapping and extension process pertains not only to the spatial information, such as station and zone geometry and metadata; it also covers both primary and aggregated data available for both the station and zone levels, utilizing the Observations and Measurements Standard (ISO 19156) for the provision of measurement data. In other cases, the documentation of reporting relevant concepts must be extended in order to fulfill INSPIRE requirements in addition to those ensuing from the AQD.

In the following sections, we will illustrate this extension process

  new Air Quality Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008 on ambient air quality and cleaner air for Europe (AQD) foresees the provision of air quality reporting data utilizing the data specifications and services specified by the INSPIRE Directive (2007/2/EC). E-Reporting under the AQD is foreseen to begin with the reporting cycle starting in 2014.

  Parliament and of the Council as regards the reciprocal exchange of information and reporting on ambient air quality (IPR). The following data flows have been defined to cover the requirements of 2008/50/EC: (B) Information on zones and agglomerations (Article 6); (C) Information on the assessment regime (Article 7); (D) Information on the assessment methods (Articles 8 and 9); (E) Information on primary validated assessment data and primary up-to-date assessment data (Article 10); (F) Information on generated aggregated data (Article 11); (G) Information on the attainment of environmental objectives (Article 12); (H) Information on air quality plans (Article 13); (I) Information on source apportionment (Article 13); (J) Information on the scenario for the attainment year (Article 13); (K) Information on measures (Articles 13 and 14);

Fig. 1 .Fig. 2 .Fig. 3 .Fig. 4 .

 1234 Fig. 1. INSPIRE Class and IPR Requirements

2.1 Air Quality Directive and Reporting 2008/50/EC on ambient air quality and cleaner air for Europe.

  The Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008 on ambient air quality and cleaner air for Europe entered into force on 11 June 2008. This Directive merges most of existing air quality legislation into a single directive (except for the fourth daughter directive) with no change to existing air quality objectives, repealing the Directives 96/62/EC, 1999/30/EC, 2000/69/EC and 2002/3/EC as well as Decision 97/101/EC.In the process of defining Directive 2008/50/EC the previous air quality directives where reviewed and streamlined with the following goals:

	to
	all other information flows;
	 Eliminate any double reporting;
	 Reduce administrative burden of Member States (MS), the Commission and Euro-
	pean Environment Agency (EEA) by automating tools for checking report consis-
	tency etc. (applies to all data-flows);
	 Enable faster availability of basic assessment information (provisional monitoring
	data) at a European scale, even in near real time; information will not be used for
	compliance purposes, but will enable further and cost-effective public dissemina-
	tion and provide input to European models supporting national and local assess-
	ment and forecasting;
	 Replace provisional monthly summer ozone reporting and notifications of alert
	threshold situations by automated near-real time exchange
	For provision of data stipulated by Directive 2008/50/EC, the provisions laid down in
	Directive 2007/2/EC (INSPIRE) shall be taken into account.

 Simplify/replace specific reporting obligations on exceedances of information and alert thresholds by a semi-automated exchange based on established near-real-time data exchange mechanism;  Update and optimize exchange of monitoring data and metadata (current exchange of information under 97/101/EC EoI) to minimize administrative burden by providing data exchange tools; these should enable semi-automated aggregation/cascading and through further Quality Control (QC) provisions and availability of metadata minimize further need for interaction between supplier and user;  Update and optimize provisions on reporting assessment information (current 2004/461/EC questionnaire) that will enable semi-automated aggregation/cascading of the assessment information regardless of its origin (monitoring, modelling), enabling spatial presentation of assessment and unambiguous links

2004/107/EC relating to arsenic, cadmium, mercury, nickel and polycyclic aro- matic hydrocarbons in ambient air.

  The Commission shall also identify ways of streamlining the way data are reported and the reciprocal exchange of information and data from networks and individual stations measuring ambient air pollution within the MS.This task has been realised in the form of the Commission Implementing Decision of 12 December 2011 laying down rules for Directives 2004/107/EC and 2008/50/EC of the European

	Directive 2004/107/EC is the 4th daughter directive passed under the previous air
	quality framework directive (96/62/EC) on ambient air quality assessment and man-
	agement, and the only daughter directive not repealed by 2008/50/EC. The directive
	sets target values for all the pollutants except mercury, complementing the environ-
	mental objectives harmonised in 2008/50/EC.
	2011/850/EU Implementing Decision .
	As stated in Article 28(2) of Directive 2008/50/EC, the Commission shall determine
	the additional information to be made available by MS as well as the timescales in
	which such information is to be communicated.

  The following steps have been identified as necessary for the extension of INSPIRE Data Specifications to reporting requirements:

	 Analyze reporting concepts from legal requirements
	 Identify relevant INSPIRE Themes
	 Identify relevant INSPIRE Feature Types
	 Map reporting concepts to INSPIRE Feature Types
	─ Direct mapping to attributes possible
	─ Direct mapping to associations possible
	─ Additional attributes necessary  derive class from INSPIRE
	─ If required, define additional classes
	─ INSPIRE requires additional attributes  add to reporting guidelines
	 Provide Mapping from reporting concepts to (extended) INSPIRE classes

Table 1 .

 1 Mapping of IPR Data Flows to INSPIRE Themes

	AQD e-Reporting Data Flow	INSPIRE Theme
	(A)	Common Data types	INSPIRE Base, GML
	(B)	Information on zones and agglomera-	III.11.	Area	manage-
		tions	ment/restriction/regulation zones
			and reporting units
	(C)	Information on the assessment regime
	(D)	Information on the assessment methods III.7. Environmental monitoring
			facilities
			O&M in INSPIRE
	(E)	Information on primary validated as-	III.7. Environmental monitoring
		sessment data and primary up-to-date	facilities
		assessment data	O&M in INSPIRE
	(F)	Information on generated aggregated	III.7. Environmental monitoring
		data	facilities
			O&M in INSPIRE
	(G)	Information on the attainment of envi-	I.4. Administrative units
		ronmental objectives
	(H)	Information on the air quality plan(s)
	(I)	Quantitative source apportionment
	(J)	Evaluation -Baseline and projection
	(K)	Documentation of measures
	In addition, the following INSPIRE themes are of relevance, as the data specifications
	either link to elements provided by other institutions under these themes or in turn
	provide input to them:
	I.4. Administrative units
	III.5. Human health and safety
	III.10. Population distribution -demography
	Links to and from the relevant AQD e-Reporting classes must be provided within
	the data model.

A new class AQD_Station must be defined extending the base INSPIRE EnvironmentalMonitoringFacility class as follows: Through the use of INSPIRE data specifications as a basis for the AQD e-Reporting, great synergies can be attained. Member States only need to set up one INSPIRE service providing relevant Air Quality Features and Data to cover both their INSPIRE obligations as well as their legal reporting obligations pertaining to Air Quality. Air quality data, including both measurement metadata as well as real-time measurement data flows, will be made widely available in a standardized manner allowing for reuse beyond European Reporting obligations.