Zuzana Chvátalová
email: chvatalova@fbm.vutbr.cz

Jiří Hřebíček

Oldřich Trenz
email: oldrich.trenz@mendelu.cz

Benchmarking Systems and Methods for Environmental Performance Models

Keywords: benchmark methodology, criteria, environmental performance, information system, environmental indicators, environmental performance evaluation, environmental reporting 1

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

Introduction

Benchmarking is the process of improving performance by identifying, understanding, adapting and implementing best practices and processes that are found inside and outside a company. It involves the creation of partnerships to exchange information on processes and measurements, resulting in the setting of realistic improvement goals. Effective benchmarking is a process of continuous improvement [START_REF] Andersen | The benchmaking handbook. Step-by-step instructions[END_REF].

Benchmarking is a framework within which performance indicators and the best practices are examined in order to determine areas where the company performance can be improved. Although most benchmarking initiatives concern financial and management issues, environmental benchmarking is becoming a major element in the environmental management of companies.

Environmental benchmarking is an environmental management tool that can provide a substantial contribution to the improvement of environmental performances by facilitating the identification of the gap between company performance and an optimal performance [START_REF] Ecosmes | Environmental benchmarking[END_REF]. It helps the company's management to find out how to continu-ously and exactly monitor the development of the company's environmental impacts in the chosen sector (economic activities connected with NACE -Statistical classification of economic activities [6]) and to find relationships between the environment, the economy and society and to transform them into Key Performance Indicators (KPIs) [START_REF] Hřebíček | Key Performance Indicators for Sustainable Reporting According to NACE[END_REF], [START_REF] Hermann | Assessing environmental performance by combining life cycle assessment, multi-criteria analysis and environmental performance indicators[END_REF], [START_REF] Hřebíček | Environmental Key Performance Indicators and Corporate Reporting[END_REF] for the measurement of environmental performance.

What is benchmarked in environmental benchmarking? The scope of environmental benchmarking should include all areas of the given company's activities, and not be restricted solely to those activities that have an obvious environmental impact. Therefore, it may include an assessment of Environmental Management Systems (EMS), management performance, Environmental Management Accounting (EMA), resource and waste management, product environmental quality, environmental education and training, customer relations and emergency response [START_REF] Bolli | Environmental benchmarking for local authorities: From concept to practice[END_REF].

Let us consider the environmental performance and the KPIs for the food processing sectors with NACE codes: C10 -Manufacture of food products and C11 -Manufacture of beverages in the section 2 of the paper. Here we have taken into account the Global Reporting Initiative (GRI), its G4 Guidelines [START_REF]G4 Sustainability Reporting Guidelines[END_REF] and the Food processing guideline of G4 Sector Disclosures [START_REF]G4 Sector Disclosures. Food processing[END_REF] and our past research [START_REF] Hřebíček | Sustainability Indicators: Development and Application for the Agriculture Sector[END_REF] to specify the KPIs. We have also analyzed the Sustainability Assessment of Food and Agriculture systems (SAFA) [START_REF] Safa | Sustainability Assessment of Food and Agriculture systems (SAFA)[END_REF] of the Food and Agriculture Organization of United Nations (FAO), its holistic global framework for the assessment of sustainability along the food and agriculture value chains, and this in order to optimize the environmental performance and the KPIs [START_REF] Hřebíček | Current Trends of Economic Modelling of Sustainable Corporate Performance and Reporting -Review and Research Agenda[END_REF]. Furthermore, we consider benchmarking as an ongoing process of actions, steps, functions and activities that aims to identify and adopt best practices for improving environmental performance specified by a given company's KPIs. A number of different methods for benchmarking have been developed [START_REF] Nerudová | Environmental Benchmarking Methodology for Identification of Key Environmental Aspects of Product[END_REF], [START_REF] Jónsdóttir | Enviromental Benchmarking a Tool for Continuous Environmental Improvements in the SME Sector[END_REF]. We have considered the process based on EEA methodology [START_REF] Bolli | Environmental benchmarking for local authorities: From concept to practice[END_REF] in the section 3 of the paper and we have applied this to chosen companies' food processing sector in the section 4 where we mention the architecture of the Web information system that has been developed as a part of our project [START_REF]Measuring Corporate Sustainability in Selected Sectors[END_REF].

Key Performance Indicators of the Food Processing Sector

The ISO 14031:2013 international standard [17] sets out Environmental Performance (EP) as measurable results of a company's management of its environmental aspects. The EPE process defined in ISO 14031:2013 and likewise in ISO 14031:1999 is too general including methods how to determine KPIs and choose appropriate EPIs and ECIs indicators. In addition, there are many international standards for implementing and certifying the sustainability pillars of environmental indicators, like for instance ISO 9000, ISO 14000, ISO 18000 [START_REF]Integrated Management System Documentation / Manuals for Integrated Certification[END_REF]; ISO 26000 [START_REF]Social responsibility[END_REF]; GRI [START_REF]G4 Sustainability Reporting Guidelines[END_REF], [START_REF]G4 Sector Disclosures. Food processing[END_REF]; SAFA [START_REF] Safa | Sustainability Assessment of Food and Agriculture systems (SAFA)[END_REF]; the Eco-Management and Audit Scheme [20] and the Organization for Economic Cooperation and Development (OECD) Guidelines for Multinational Enterprises [START_REF]OECD Guidelines for Multinational Enterprises[END_REF].

We have been developing specified KPIs for the food processing sector [START_REF] Hřebíček | Corporate Key Performance Indicators for Environmental Management and Reporting[END_REF], [START_REF] Hřebíček | Key Performance Indicators for Sustainable Reporting According to NACE[END_REF], [START_REF] Hřebíček | Environmental Key Performance Indicators and Corporate Reporting[END_REF], [START_REF] Hřebíček | Sustainability Indicators: Development and Application for the Agriculture Sector[END_REF] since 2007. We introduce the results of our research of KPIs' determinants in the food processing sector C10 and C11 in Table 1, where we follow the trends which brought the frameworks of the GRI and SAFA principles with our conclusions [START_REF] Hřebíček | Corporate Key Performance Indicators for Environmental Management and Reporting[END_REF], [START_REF] Hřebíček | Sustainability Indicators: Development and Application for the Agriculture Sector[END_REF], [START_REF] Hřebíček | Current Trends of Economic Modelling of Sustainable Corporate Performance and Reporting -Review and Research Agenda[END_REF], [START_REF] Hřebíček | Optimal set of agri-environmental indicators for the agricultural sector of Czech Republic[END_REF] and [START_REF] Kocmanová | Corporate performance measurement[END_REF].

Benchmarking Systems Methodology

The benchmarking process is a series of actions, steps, functions, or activities that bring about an end or a result: the identification and importance of best practices for the improvement of EP. There are dozens of sources which describe the benchmarking process. It is called by some "the nine-step benchmarking process", or by others "the four steps of benchmarking". The following description of phases is based on Andersen and Pettersen [START_REF] Andersen | The benchmaking handbook. Step-by-step instructions[END_REF], who call the process "the benchmarking wheel", in order to indicate that benchmarking is an ongoing process [START_REF] Kocmanová | Corporate performance measurement[END_REF]:

1. Plan: During the planning phase, the scope and type of environmental benchmarking are determined. The focus here lies in process benchmarking, because, through the analysis of best practices, it provides a basis for substantial improvements. The planning stage involves: selecting what is to be benchmarked; analysing the organization processes; establishing performance measures for the process; selecting benchmarking partners that will participate in the benchmarking process; and determining the data collection methods that will be employed. 2. Search: A primary task is to search for and identify suitable benchmarking partners in the investigated sector. This includes the following activities: to design a list of criteria which an ideal benchmarking partner should satisfy (e.g., geographical location, size, structure, products, technology, economic activity, and organisational climate); to search for potential benchmarking partners (i.e., companies that are better than oneself at the process in question); to compare the candidates and select the best-suited benchmarking partner(s) (it is recommended to select more than one possible benchmarking partner); to establish contact with the selected partner(s) and gain their acceptance for participation in the benchmarking study. The companies of the food processing sector (NACE codes C10, C11) were selected on the basis of the database of the Czech Environmental Information Agency of the Ministry of the Environment of the Czech Republic, which have enabled and certified their EMS with the ISO 14001 or EMAS standards in 2007 [START_REF] Kocmanová | Corporate performance measurement[END_REF].

Observe and collect data:

The steps of the observation phase are as follows: to assess the information needs (data and information should be collected on EP levels, which indicate how good the partner is compared to oneself; practices or methods which make it possible to achieve these EP levels, and enablers who make it possible to perform the process according to these practices or methods); select the method and tool for collecting the information and data; observe and debrief (it is important that after the visit a debriefing is conducted as soon as possible in order not to lose any details of the observation). We have combined the collection of data through the abovementioned Web Information System and also through personal visits of the investigated company's responsible environmentalists [START_REF] Jónsdóttir | Enviromental Benchmarking a Tool for Continuous Environmental Improvements in the SME Sector[END_REF]. The selected companies were further explored (we have used their annual reports, website, etc.) and submitted for evaluation according to additional criteria that were relevant to the selection of companies for our research [START_REF] Kocmanová | Corporate performance measurement[END_REF]. 4. Analyse: The descriptive statistics were made on the grounds that certain specifics of variables have an influence on the result of the methods and timing, and this can be seen in the descriptive statistics of the individual indicators. The average, standard deviation, variance and coefficient of variation were calculated. To determine the dominant factors which affect the company the method of the main components was used; the appropriateness of the data was tested using Bartlett's Test of Sphericity and the Kaiser-Meyer-Olkin Measure of Sampling Adequacy [START_REF] Kocmanová | Corporate performance measurement[END_REF]. The main purpose of this phase is to determine: the EP gaps between benchmarking partners; the causes of the gaps, such as the methods and practices that make it possible for partners to achieve higher performance levels; the factors that facilitate or hinder the adoption of best practices and methods. 5. Adapt: The main findings of the analysis phase are communicated and discussed with the benchmarking partners. The best practices identified during the benchmarking were adapted and improved by the companies and recommendations were developed for their implementation [START_REF] Kocmanová | Corporate performance measurement[END_REF]. 6. Continuous Improvement: Benchmarking should not be a one-time event but an interactive, continuous and dynamic process for improving a company's EP. This involves monitoring the process, introducing continuous learning and providing input for the company's continuous improvement. It could be done by means of the Web information system that has been developed.

Environmental Benchmarking Information Tools

Some information and communication technology (ICT) tools are available for the purposes of environmental benchmarking. There exist both generic and specific ICT tools for environmental benchmarking [START_REF] Jónsdóttir | Enviromental Benchmarking a Tool for Continuous Environmental Improvements in the SME Sector[END_REF]. We mention several of them here:

• e-Bench [24] is a Web-enabled audit and simulation/modelling tool that is used to record systematically whatever energy or utilities an organization is consuming and to relate these to the core business activity. The system then benchmarks these input factors to identify how efficiently they are used with other users in the database. e-Bench has been successfully used in the USA, Australia and New Zealand. • The Global Environmental Management Initiative (GEMI) [25] is a coalition of large businesses aimed at providing strategies for businesses to achieve Environmental, Health and Safety (EHS) excellence, economic success, and corporate citizenship. The group introduced their primer for environmental benchmarking in 1994. The primer is not industry or sector-specific, and is accessible to everyone free of charge on the Internet. This ICT tool can be used as a framework for any kind of benchmarking, whether focusing on roles, strategic issues, processes or performance. • The Safety, Health and Environment Intra Industry Benchmarking Association (SHEIIBA) [START_REF]Health and Environmental Intra Industry Benchmarking Service[END_REF] was formed in 1996 in response to the recognition that many leading companies were eager to learn how others in different sectors managed EHS and to compare their accident performance. Corporate Benchmarking Ltd. (in SHEIIBA) has built and runs bespoke safety benchmarking programmes for industry sectors. Participating companies enter accident and ill-health data into an online form each month. The data is divided by cause and type and can by split into different employee groups. Data can be viewed in graphic or tabular format as fixed periods, rolling years or time spans (up to 12 quarters or years.) The system is currently in use in 14 United Kingdom water utilities.

• Environmental Management Assessment and Benchmarking (EMAB) [27] is a

Web application (portal) designed for the maturity assessment and benchmarking of corporate environmental management efforts [START_REF] Frehe | A Maturity Model and Web Application for Environmental Management Benchmarking[END_REF]. The portal enables the measuring of corporate environmental management efforts via a survey that is based on criteria pursuant to the ISO 14000 family [17] and the EMAS III [20] standards. In addition to the assessment, there is a benchmarking function that allows the comparison with other participating companies. Its development started in 2009 at the Ostnabrück University as part of the project IT-for-Green [29] and has been going since spring 2014. The portal is in both German and English and is open especially for German companies.

Our analysis of known environmental benchmarking ICT tools together with the evaluation [START_REF] Jónsdóttir | Enviromental Benchmarking a Tool for Continuous Environmental Improvements in the SME Sector[END_REF] show: an efficient ICT tool has to be based on reliable and purely scientific information of the main environmental impacts and aspects of companies of the given sector. Based on this the information environmental KPIs are worked out, and these are the foundations of a well-structured management benchmarking system. This system then has potential to be eco-efficient and easy to use [START_REF] Kocmanová | Corporate performance measurement[END_REF].

Web Information System

We have applied the abovementioned ideas of section 3.1 to companies in the food processing sector of the Czech Republic, where we have identified the environmental performance model based on the specific conditions of the EMS implementation [START_REF] Jónsdóttir | Enviromental Benchmarking a Tool for Continuous Environmental Improvements in the SME Sector[END_REF], [START_REF] Kocmanová | Corporate performance measurement[END_REF] and we have furthermore developed a Web Information System for the environmental benchmarking of companies in this sector, where we have also used our experiences with the development of the Web Information System for the corporate performance and reporting [START_REF] Hřebíček | Corporate Key Performance Indicators for Environmental Management and Reporting[END_REF], [START_REF] Hřebíček | Current Trends of Economic Modelling of Sustainable Corporate Performance and Reporting -Review and Research Agenda[END_REF], [START_REF] Kocmanová | Corporate performance measurement[END_REF], [START_REF] Hodinka | Business Intelligence in Environmental Reporting Powered by XBRL[END_REF].

System Requirements and Objectives

In our vision, we foresee two main objectives of the developed Web Environmental Benchmarking and Reporting Information System (WEBRIS) [START_REF] Hodinka | Business Intelligence in Environmental Reporting Powered by XBRL[END_REF]. A company may use such a system to create various reports and share its data with both its stakeholders and, in the future, with the state administrations concerned with regulatory demands and mandatory corporate reporting [23, p. 165-177].

The second objective of WEBRIS is the EPE performed by evaluating input KPIs (Tab. 1). This way, the company can share its EP with the public or check its EP development progress. EPE can be done through various reports as stated above or through custom dashboards [23, p. 223-228].

We define the following three main generic actors:

• Reporter -a person responsible for ensuring company mandatory environmental reporting (especially a company environmentalist) or reporting for stakeholders [23, p. 166]; this would typically be a member of the management team or a contractor.. • Evaluator -a person responsible for the EPE of a company [23, p. 212]; this role can be represented by a wide range of people starting from managers, auditors and various internal interested parties. The evaluator may also enter data into the information system, but it is not his/her primary task; typically, this would be the additional data required for the report generation, but not required as a part of mandatory reporting (e.g., company strategy, goals a targets, vision, etc.) • Administrator -the administrator of the information system responsible for defining the report templates and business rules used to generate reports [23, p. 212].

Basic high-level requirements for the Web information system are [START_REF] Kocmanová | Corporate performance measurement[END_REF][211][212][213][214][215][216][217]], [START_REF] Hodinka | Business Intelligence in Environmental Reporting Powered by XBRL[END_REF]:

• to store source company data; to evaluate KPIs according to the selected sector and methodology; • to generate environmental benchmarking reports in the selected format for offline storage, printing and archiving; • to import source company data from its company information system in the prescribed format; • to provide selected information in the form of reports accessible online to the general public or only to selected persons; • to provide selected information in the standardized XBRL (eXtensible Business Reporting Language) format for interchange with other systems [START_REF] Hodinka | Formalization of Business Rules and Methodology of their Implementation to the Information System[END_REF]; • to provide the possibility to evaluate the company EP anonymously;

• to provide the possibility to define report data and business logic;

• to dynamically generate the XBRL taxonomies for a given report [START_REF] Hodinka | Formalization of Business Rules and Methodology of their Implementation to the Information System[END_REF];

• to provide the possibility to customize standardized reports and to generate fully customized reports; • to provide the possibility to compare reports among the companies of the given sector.

WEBRIS Structure

The Fig. 1 shows an overview of WEBRIS architecture based on an XBRL database.

The main idea of this approach is a possibility of direct storing of XBRL data into an XML database that allows relational access to these data. The logical relational data model and the XBRL contents simplify the Business Intelligence integration [START_REF] Hodinka | Business Intelligence in Environmental Reporting Powered by XBRL[END_REF][START_REF]XBRL[END_REF][START_REF] Hodinka | Formalization of Business Rules and Methodology of their Implementation to the Information System[END_REF]. The architecture of WEBRIS is divided into application, processing and data layers.

The application layer accepts report submissions and provides the results of report queries. It is composed of various interfaces such as a web application user interface or some defined APIs. The application layer communicates with the storage layer via SQL queries or via the XQuery language. It defines the access tools and internet protocols used for the following purposes: SOAP, REST, JDBC or file access via Web-DAV.

The data layer is composed of both the RDB system and the XBRL database. The data layer exposes both the relational and the XML interface so that the data can be queried by both SQL and XQuery languages. The application layer provides a wide range of APIs to connect the database to various sources. This offers a high interoperability of the WEBRIS system. Alongside the application layer is the Business Intelligence engine [START_REF] Hodinka | Formalization of Business Rules and Methodology of their Implementation to the Information System[END_REF], which can benefit from direct access to the data layer. This will be possible if the data layer is self-containing, i.e., if it can provide an XBRL document with all the necessary taxonomies and templates.

WEBRIS Environmental Benchmarking Validation

The pilot implementation of WEBRIS has been performed in the set of twenty four SME breweries in the Czech Republic which belong to C11 -Manufacture of beverages NACE section and which have determined their KPIs according to Tab. 1. The benchmark values were calculated firstly as the mean of the KPIs of the registered companies and after further analysis as the optimum value" consulted with environmental experts. The choice was made vis á vis the availability of comprehensive data from the given market segment and the willingness of companies to develop further.

Another direction of the software implementation will be connected with improving the user-friendliness (in accord with feedback) and the integration of complementary methods for measuring company performance, together with an extension into other market segments. Every user of WEBRIS, after completing the registration of his company, can input their KPIs (see Tab. 1) and thereupon the output benchmark will be determined. Based on the input KPIs, the benchmark will be shown. This means that the company EPE is performed based on the assessment of the KPIs that have been entered. The individual criteria are displayed in a ray chart (Fig. 2). The closer the partial value to the outer edge, the closer it is to the maximum evaluation level of the given segment (company benchmark). Emphasis in assessment is placed on sustainability. One part of benchmarking are recommendations useable for the further development of the company. Fig. 2. Rating of the best company of the breweries that have been examined

Conclusion

Our research [START_REF] Hřebíček | Corporate Key Performance Indicators for Environmental Management and Reporting[END_REF][START_REF] Hřebíček | Key Performance Indicators for Sustainable Reporting According to NACE[END_REF], [START_REF] Hřebíček | Environmental Key Performance Indicators and Corporate Reporting[END_REF], [START_REF]Measuring Corporate Sustainability in Selected Sectors[END_REF][START_REF] Hřebíček | Current Trends of Economic Modelling of Sustainable Corporate Performance and Reporting -Review and Research Agenda[END_REF], [START_REF] Kocmanová | Corporate performance measurement[END_REF], [START_REF] Hodinka | Business Intelligence in Environmental Reporting Powered by XBRL[END_REF][START_REF] Hodinka | Formalization of Business Rules and Methodology of their Implementation to the Information System[END_REF] has focused the possibility of the utilization of ICT and XBRL taxonomy for environmental benchmarking and reporting of food processing organizations. We have suggested the formalization of this system on the basis of the universal XML markup language by means of the use of the XBRL [START_REF] Hodinka | Business Intelligence in Environmental Reporting Powered by XBRL[END_REF][START_REF] Hodinka | Formalization of Business Rules and Methodology of their Implementation to the Information System[END_REF] and we have developed WEBRIS based on KPIs. We have assumed that it will minimize the main barriers that prevent the tested organizations (C10 and C11 NACE codes) from supporting environmental reporting. Some of their objections have been for example:

• Collecting and managing environmental data is expensive, technical issues with data collection are also a problem. • Determining a set of appropriate KPIs to monitor and measure EP is difficult.

• Disclosure can create business risks which competitors and regulators may seize upon. • Environmental reporting is seen as a superfluous and burdening activity.

The core of these barriers is the time-demanding nature of creating the breweries' data-processing reports, and the absence of positive feedback of their managers.

By using WEBRIS, the given brewery gains a whole set of advantages. The administration and editing of KPIs is much easier and much more effective for EPE. The benchmark methodology in WEBRIS makes it possible to assess the given brewery's environmental impacts (caused by its activity) by means of objective considerations; to conduct the comparison of different breweries and evaluate whether their activities correspond to the principles of sustainable development.

Fig. 1 .

 1 Fig.1. WEBRIS architecture[START_REF] Hodinka | Business Intelligence in Environmental Reporting Powered by XBRL[END_REF]

Table 1 .

 1 List of KPI Indicators[START_REF] Kocmanová | Corporate performance measurement[END_REF]

	Area	Indicator Title	Unit
	Investment	EN1 EN2	Investments into environmental protection The cost of investment into environmental protection	Czech crown Czech crown
	Emission	EN3 EN4	Total air-emissions (at least SO2, NOx, CO, VOC, NH3 and PM20,.50,.10) Total greenhouse gas emissions (CO2, CH4, N2O, HFCs, PFCs and SF6)	Ton kg of CO2-eq
		EN5	Total annual energy consumption	MWh
	Resource consumption	EN6 EN7 EN8	Total consumption of renewable energy Material use (except water and energy) Recyclable input material use	% Ton %
		EN9	Total annual water consumption	m 3
	Waste	EN10 EN11	Total annual waste production Total annual production of hazardous waste	Ton Ton


Ludek Matyska
email: ludek@ics.muni.cz

The Czech e-Infrastructure and the European Grid Infrastructure Perspective

Keywords: e-Infrastructures, high throughput computing, compute and storage resources, weather forecast and modelling

National e-Infrastructures are playing an increasingly important role in the support of complex computational and data requirements from all scientific disciplines, environmental informatics not excepting. Since 1996, such an e-Infrastructure is developed and operated in the Czech Republic, with its emphasis shifting from a shared uniform distributed infrastructure to a more usertailored environment. Its development relates (and in some cases precedes) the evolution of European Grid Infrastructure (EGI), with its current vision of an Open Science Commons concept. While the current e-Infrastructure concept and its implementation is of a very generic nature, it can be tailored to specifically cover different needs of environmental applications. This paper gives an overview of the Czech national e-Infrastructure, its connection to EGI and a number of applications from environmental science domains.

Introduction

Nowadays, high quality research and education is practically impossible without an extensive information and communication technology support. As there is an ever increasing request for more resources, it is necessary to combine compute and storage resources from different sites leading to the development of a concept of an e-Infrastructure (known also as Cyberinfrastructure in the USA). The e-Infrastructure is a distributed system that could span an institution, country or even a continent, combining resources sufficient for even the most demanding needs.

2

The Czech e-Infrastructure

Brief History

The history of a modern complex e-Infrastructure in the Czech Republic dates back to 1996, when Masaryk University through its Supercomputing Centre Brno coordinated the first project to build a distributed shared computing infrastructure known as "Met-aCentrum" [START_REF] Matyska | MetaCenter-Building a Virtual Supercomputer[END_REF]. In 1998, the MetaCentrum coordination was transferred to CESNET, the Czech National Research and Educational Network provider (NREN). The Meta-Centrum evolved gradually into the Czech National Grid Initiative. The primary goal of the MetaCentrum was to build a distributed computing environment that exposed a uniform interface to its users; the emphasis was on uniformity, hiding the complexity of the used technology, but in the same time forcing users to adapt to the environment which MetaCentrum provided. MetaCentrum created a true grid -a combination of resources provided by different resource providers (public universities and institutes of Academy of Science) that together created a uniform compute and storage infrastructure. Recently, CESNET complemented the computing resources (clusters) with a distributed infrastructure of large scale hierarchical storage systems to cover also needs for big data storage and processing (the dawn of big data analytics).

MetaCentrum connects some 10 000 cores at 6 major and several more minor locations. The largest is at CERIT-SC. All the cores use x86_64 architecture, some nodes are also equipped with NVidia graphics. The total storage capacity are near 30 PB at four major installations throughout the country.

The SCB at Masaryk University, while offloading the responsibility for the management of the large scale distributed e-infrastructure to CESNET, continued to develop new concepts for the e-Infrastructure. In 2011, it started a transformation into the center CERIT Scientific Cloud, a highly flexible computing and data center focusing on user-tailored e-Infrastructure development and operation. CERIT-SC provides some 4500 cores and additional 4 PB of storage capacity; among the resources is also a SGI Ultraviolet 2 system with 6 TB of RAM shared among its 284 cores (a slightly larger system is expected to be delivered in the mid of November 2014).

Approximately at the same time, Technical University of Ostrava started its "IT4Innovations" project, to build a full scale national supercomputing center. In October 2014, SGI won a tender on the national supercomputer with its ICE X system that will include almost 600 basic nodes with nearly 900 Xeon Phi multicore processors-this will be the largest Xeon Phi installation in Europe.

Currently, the national e-Infrastructure landscape of the Czech Republic is composed of these three centers: CESNET with its MetaCentrum and extensive storage capacities, IT4Innovations supercomputing center and CERIT-SC as the grid and cloud center for collaborative research. All these centers are connected through the high speed network backbone provided by CESNET. The network provides capacity of ten of gigabits per second (with the main trunks recently upgraded to 100 Gbps lines). The network connects all the university cities and has sufficient capacity to support even the most demanding data transfers within the country.

Technology and Access

The basic distributed e-Infrastructure provided currently by MetaCentrum and CERIT-SC is based on a lightweight model of shared resources offered through a scheduling system (i.e., targeting a job submission mechanism). The system, built around the Torque schedulers [START_REF] Toth | Practical Experiences with Torque Meta-Scheduling in the Czech National Grid[END_REF], offers several queues that differ in their priority, the maximum time each job is allowed to run, and the queue capacity (how many jobs an individual user can submit simultaneously). When submitting a job, users must select the appropriate queue and could annotate their job with additional information like number of cores needed, amount of needed disk space or extent of RAM needed for successful job completion. To support complex requirements, a specific web service is provided that can be used to check whether the used combination could be actually fulfilled by the e-Infrastructure, which combination of resources could serve the job with the given annotation (and how many such combinations exists). This service helps users to optimize their job descriptions to best meet their needs while taking into account the limits of the e-Infrastructure and its capacity.

Practically the whole computing infrastructure is virtualized, with part accessible through standard cloud interface as provided by OpenNebula [START_REF] Sotomayor | Virtual Infrastructure management in private and hybrid clouds[END_REF]. This gives the system higher flexibility, as users are not restricted to the "standard" environment (operating system-in this case Debian-set of defined libraries plus an extensible set of applications), but they could submit whole virtual machines (either from a pre-defined pool or their own) with their own specific environment (including a completely different operating system like MS Windows).

With the virtualized nodes and the cloud interface, users are able to ask also for interactive access to the individual nodes or their sets. MetaCentrum provides even full virtual clusters [START_REF] Antos | Metacenter Virtual Networks[END_REF][START_REF] Antos | VirtCloud: Virtualizing Network for Grid Environments-First Experience[END_REF], where a set of nodes could be connected through a virtualized private network and used as a whole. Use of network virtualization guarantees separation from other users, creating thus a secured (encapsulated) environment that is accessible through specified interfaces only (or not at all).

2.3

Scheduling and Fairshare

The whole e-Infrastructure is available free of charge to all bona-fide scientists and academicians in the Czech Republic (this includes also all university students). Users can just register with MetaCentrum and are immediately given access to the resources. With its near 900 users the demands of the e-Infrastructure exceed its capacity; therefore some scheduling is needed. The Czech national e-Infrastructure uses a specific fairshare mechanism [START_REF] Isard | Quincy: Fair scheduling for distributed computing clusters[END_REF] that dynamically adjust individual user's priorities with respect to the extent of past computations. When a user joins MetaCentrum, he is given some basic priority. The priority is automatically decreased when he uses the e-Infrastructure above average use; and it is increased when the usage is low. This means all users get a "fair" access to the e-Infrastructure. To support excellent research, user's priority can be (permanently) increased if a result (usually a publication) is registered with MetaCentrum. This priority increase is immediately taken into account by the fairshare scheduler, giving such users better access to the resources. Users with high (and high quality) research output are thus visibly prioritized without any unnecessary bureaucracy (i.e. this system does not need to evaluate any a-priori user's proposals for the use of e-Infrastructure while guaranteeing to highly productive users that they will have access regardless of the number of average users).

Flexibility and CERIT-SC

The center CERIT-SC has a specific position in the national landscape. It is not only the largest individual resource provider in the Czech Republic, but the center focuses on collaborative research with other user communities and also on further development of the e-Infrastructure itself. The center promotes the wide adoption of cloud technologies to provide highly flexible and adaptable compute and storage environment. The center works closely with its partners from other research fields to analyze the problem and to find out the most efficient ways of the use of the e-infrastructure, At the same time, it supports extensive modifications and adaptation to the e-Infrastructure itself to support its most innovative use.

The basic mode of work is the establishment of joint research teams together with users. Computer Science experts contributed by the center complement domain scientists from the application area; such interdisciplinary teams are best prepared to maximize the potential offered by the e-Infrastructure. These teams usually involve also bachelor, master and especially PhD students (both from the Computer Science and the particular research discipline) that are thus given an opportunity to directly participate in high quality research. See [START_REF][END_REF] for examples of successful collaborations.

European Grid I

The Czech e-Infrastructure is a part of the European Grid Infrastructure (EGI) [8]. The current EGI infrastructure is a result of 15 years of development. It currently connects 347 data centers in 57 participating countries (not all of them in Europe, one is even in Australia) and it provides 487,600 CPU cores, 286 PB disk and 118 PB tape storage. Its measured reliability is above 99.6 % and it runs around 1.5 million jobs each day (this is equivalent of almost 5 million core-hours per day). Since 2011, more than 2000 publications with EGI acknowledgment have been produced in almost all scientific disciplines in more than 200 projects. Since the initial EU activities in the DataGrid project in late nineties, CESNET has been a strong partner in all major activities related to the European grid infrastructure. CESNET was a coordinator of the EGI Design Study project that led to the proposal EGI and its first consolidated project, EGI InSPIRE.

More recently, CESNET together with CERIT-SC are major players in the Federated Cloud activity that allows multiple IaaS cloud providers to become visible to the user as a single system that scales to user needs, providers resilience, prevents provider/vendor lock-in and could be targeted towards the research community. The Federated Cloud infrastructure currently includes resources from 12 countries; the Czech partners provide not only necessary resources but also play a strong role in the development of individual software components-the major contribution lies in the development of the rOCCI implementation to guarantee standards compliance of the federated Cloud approaches [START_REF] Rochwerger | The reservoir model and architecture for open federated cloud computing[END_REF].

CESNET and CERIT-SC are also working together in the area of AAI and Identity management, especially through a joint development of the Perun system. Perun serves as an extensive identity management and consolidation system supporting also authorization through VO and group concept, both at the national and also at international levels [START_REF] Prochazka | Perun-Modern Approach for user and Service Management[END_REF].

EGI Vision

As the primary grid (i.e., batch processing oriented) the EGI infrastructure is considered too static and inflexible by an increasing number of research communities: Therefore a new EGI vision has been developed and presented recently.

The vision states:

Researchers from all disciplines have easy and open access to the digital services, data, knowledge and expertise they need to collaborate and perform excellent research.

This vision found its expression through Open Science Commons, a concept based on three complementary pillars: e-Infrastructure Commons: a flexible and dynamic ecosystem providing integrated services through interoperable infrastructures;

Open Data Commons: Observations, results, applications of scientific activities available for anyone to use and reuse;

Open Knowledge Commons: Easy access to knowledge and expertise to address challenges in education and research.

EGI positions itself to be the key provider of open access to compute, storage, data, knowledge and expertise complementing the community specific capabilities (the EGI Mission).

This mission is currently being implemented through a portfolio of platforms based on a middleware agnostic infrastructure. It covers and integrates all previous approaches like desktop grids, high throughput and high performance computing systems and is primary based on the cloud Infrastructure as a Service (IaaS) concept.

Environmental Applications

While the original grid-based e-Infrastructure provided a rather uniform environment that forced its users to adapt their applications to the environment, the recent trends are much more user-friendly. Using techniques of virtualization of all e-Infrastructure component, smart scheduling and cloud access policies, it is the e-Infrastructure that is adapted and tailored to best fit the applications, data manipulation, and workflows. Such user orientation is naturally beneficial for the environmental sciences, with their complex workflows, whose elements have extremely different requirements on the einfrastructure.

An example is the SDI4Apps project (Uptake of open geographic information through innovative services based on linked data; http://sdi4apps.eu/, co-funded by the EU). Its main objectives are to integrate a new generation of spatial data infrastructure (SDI) based on user participation and social validation, support easy discovery and accessibility of spatial data for everybody, and link spatial and non-spatial data using the Linked Open Data principles. To actually implement these objectives, the SDI4Apps rely extensively on a scalable cloud infrastructure, whose architecture is developed and continuously updated with the input from six pilot applications. These applications focus on easy access to data, tourism, sensor network, land use mapping, education and ecosystem services evaluation. The projects is trying to bridge the 1) top-down managed word of INSPIRE, Copernicus and GEOSS initiatives with 2) the bottom-up mobile world of voluntary initiatives and thousands of micro SMEs and individuals developing ad ho applications based on geospatial information. CERIT-SC is responsible for the architecture, development, and operation of the cloud infrastructure for SDI4Apps, making it a natural part of the national e-Infrastructure landscape. The experience built through the development for Federated Cloud infrastructure is directly used by the SDI4Apps, while the know-how achieved through this project implementation is transferred to other areas and disciplines, esp. in the area of storage and processing of geospatial data in a federated cloud environment.

The Platform for the provision of specialized meteo-predictions for power plants, a project funded by the Technology Agency of the Czech Republic, targets the development and implementation of a modular software system for prediction of electricity production from solar and wind power plants. It combines numerical models of weather forecast, whose outputs are among other intensity fields of global microwave radiation, cloudiness, air humidity, wind and temperature. The individual models are cross-correlated and the forecast values are used to remove errors and improve precision of the inputs into the model of power prediction [START_REF] Stepanek | Experiences with data quality control and homogenization of daily records of various meteorological elements in the Czech Republic in the period 1961-2010[END_REF]. The reliability and universality of the power production prediction is increased through "real-time" verification, using both the real-time weather and power production data to modify the forecast. The resulting highly reliable, modular and at the same time flexible system can be used by wide range of power generating plants. The development of this system extensively relies on the national e-Infrastructure that supports fast combination of different models, collection of data from real-time sensors and on demand processing in a virtualized environment.

The national e-Infrastructure is used to support reconstruction of 3D models of forest covers from full-waveform LiDAR and multispectral scans. This ultimate goal of such a reconstruction is to increase prediction precision for ecological models that simulate processes in natural and also human controlled ecosystems, to analyze the photosynthetic activity in the large vegetation covers etc. The precise 3D models of studied ecosystems play essential role in the prediction. These 3D models could be created from a combination of data provided through different techniques of surface and air scans (full-waveform LiDAR, hyperspectral scans, thermal scans etc.), eventually combined with "in-situ" measurements. Again, the target is to combine all the available data and improve thus analysis of independent individual data sets. The collaboration between experts in both environmental prediction and computer science already lead to the development of highly optimized 3D reconstruction algorithms of individual trees that are two orders of magnitude faster than other currently available methods [START_REF] Sloup | Automatic reconstruction of Norway spruce tree models from LiDAR data[END_REF].

The Atmospheric processes and modelling group, part of the Research Center for Toxic Compounds in the Environment (Recetox), studies processes which influence concentration of persistent organic pollutants in the atmosphere and other parts of the environment. The group aims to understand the processes important for the geographical distribution of pollutant and study time trends of their concentration. The studies use complex atmospheric models, e.g. to study air quality in Europe between 2009 and 2010 with hourly temporal resolution, space resolution 12x12 km and 28 vertical layers. The study uses the chemical transport model CMAQ (Community Multiscale Air Quality Model), the weather is forecast using the WRF (Weather Research and Forecasting Model). The WRF produces meteorological input fields for the CMAQ model which then performs modelling of advection, diffusion and chemistry of gas phase, aerosols and clouds [7:2011-2012].

All these examples of successful collaboration between domain science (in this case environment sciences) and e-Infrastructure experts demonstrate the validity and strength of the most recent evolution in the e-Infrastructures, namely their increased ability to support large scale data collections combined with extensive simulations on a tailored e-Infrastructure.

Conclusion

e-Infrastructures are becoming an indispensable tool for environmental sciences. The previous phase of the e-Infrastructure development required massive adaptation of applications and workflows to fit the provided e-Infrastructure; this lead to rather disappointing experience that resulted in rather reluctant uptake of the large scale e-Infrastructures. Recently, with the shift to more user-tailored and user-friendly e-Infrastructures, using the most advanced techniques of virtualization and clouds to provide highly flexible and adaptable environments, the environmental sciences widely benefit from the existence of large scale e-Infrastructures. The Open Science Commons concept defines a novel way for the joint development of the e-Infrastructure and the ways it is used. At the Czech national level, CERIT-SC is the forerunner of such activities, through extensive collaboration with research communities and focusing on mutual co-development of both the e-infrastructure and the applications that are expected to run on it.

adfa, p. 1, 2011. © Springer-Verlag Berlin Heidelberg 2011