Stavros Kolios
email: stavroskolios@kic.teiep.gr

Olga Maurodimou

Chrysostomos Stylios
email: stylios@teiep.gr

Integrated Large-Scale Environmental Information Systems: A Short Survey

Keywords:

The installation and operation of instrument/sensor networks has great importance in monitoring the physical environment from local to global scale. Nowadays, such networks comprise vital parts of integrated information systems that are called Environmental Information Systems (EIS). Such systems provide real time monitoring, forecasts and interesting conclusions extracted from the collected data sets that are stored in huge databases. These systems are used as the main source of data for model parameterization and as verification tools for accuracy assessment techniques. This paper comprises a short survey aiming to highlight the significant role of existing Environmental Information Systems (ELIS) consisted of instrument/sensor networks that are used for large-scale monitoring of environmental issues regarding atmospheric and marine environment. The operating principles of these systems, their usefulness, restrictions and their perspectives in the environmental sciences, are studied and described.

Introduction

The role of the Environmental Information Systems (EIS) is widely accepted and known. Although there are many different definitions about EIS [START_REF] Avouris | Environmental Informatics : Methodology and Applications of Environmental Information Processing[END_REF][START_REF] Checkland | Information, Systems and Information System -Making Sense of the Field[END_REF] all of them, share major common components in their architecture that include among others databases, monitoring modules, Geographical Information Systems (GIS) and the visualization of complex environmental data. In this study, we define as Environmental Information Systems (EIS) the integrated systems that use networks of instruments/sensors in order to collect and combine different kinds of data using automated procedures and providing high-quality products and services. These systems collect time-series of data and provide products at different spatial scales that are used to further monitor and forecast atmospheric, land and marine environment parameters as well as weather and climate changes. The most modern EIS uses indispensably, Environmental Sensor (or instrument) Networks (ESNs) as part of their structure because their installation and operation is proven fundamental for the monitoring of the physical environment. Thanks to recent technological advances in microelectronics, wireless communication technology and informatics, new advanced sensors have been emerged/evolved that are operating in clusters/arrays of devices utilizing wireless network. The development of sensor/instrumentation networks involves various research scientific fields, such as sensing, communication and computing areas (e.g. Chong and Kumar, 2009). These advances have led to the development of a huge number of networks at different spatial scales that measure, collect and store a wide range of environmental parameters. Nowadays, the modern ESNs are capable to record with high accuracy a wide variety of parameters in near real time and save the data for later recovery. There is a continuously increasing interest in ESNs establishment as modern networks have capabilities that geoscientists could hardly consider of twenty years ago. ESNs have been gradually evolved into integrated information systems that can be called EIS (according to the above mentioned definition) and provide real-time monitoring, forecasts and archive data of many different products and parameters from the initial collected data sets. The datasets of such systems are used as data sources to feed models with initial parameter values and as verification data pools for accuracy assessment of the satellite imagery. Another application area of EIS is in decision making, where along with other kinds of data (e.g. satellite data, socioeconomic parameters, census data) can provide an informational background in order to manage problems, suggest solutions and best practices for a sustainable management of the environment.

This work comprises a comparative study aiming to record and highlight the role of the existing EIS that use instrument/sensor networks along with other kinds of data for large-to-global scale monitoring of environmental issues of the atmospheric and the marine environment as well as weather and climate. There are examining characteristic examples of large scale instrument/sensor networks that are basic parts of EIS, where along with additional sources of data (like satellite datasets), are used as integrated information systems to measure, identify, monitor, analyse and forecast a vast series of atmospheric parameters (like CO 2 , O 3 , particle matter and solar irradiance), weather, climate and their impacts (e.g., cloud systems, lightning, rainfall, air and surface temperature, humidity, winds) and marine environment (salinity, water quality, sea surface temperature among others).

Basic Operating Principles of Environmental Sensor Networks

The ESNs can be separated into three general categories relating to the spatial scale: local, regional and global [START_REF] Hart | Environmental Sensor Networks: A revolution in the earth system science?[END_REF]. The local scale networks tend to cover local and strictly defined regions, measuring specific parameters through a network of interconnected nodes, via like Radio Frequency (RF), internet or acoustic waves. The sensors are usually placed in space according to the scientific or operational needs. Any set of sensors• stand for a cluster that gathers measurements [START_REF] Chong | Sensor Networks: Evolution, Opportunities, and Challenges[END_REF] where the sensors of a cluster form a particular topology either "star" or "peer-topeer" [START_REF] Buratti | An Overview on Wireless Sensor Networks Technology and Evolution[END_REF]. The types of sensors can be passive (e.g. acoustic, seismic, IR, magnetic) or active (e.g. radars, lidars) [START_REF] Chong | Sensor Networks: Evolution, Opportunities, and Challenges[END_REF]. There are also many different types of sensors according to the parameters, they record. The sensors are also categorized, in relation to their size, shape and their mobility because they can be stationary (e.g. seismic sensors), mobile (e.g. on robot vehicles) [START_REF] Chong | Sensor Networks: Evolution, Opportunities, and Challenges[END_REF] and buoys (e.g. Forecast at sea, monitoring sea surface). Additionally, the communication among sensors can be wired, or wireless; using broadband or narrowband connectivity and the energy needed from each sensor is proportional to its size [START_REF] Chong | Sensor Networks: Evolution, Opportunities, and Challenges[END_REF]. In general, a cluster communicates with a server through a gateway, wireless or wired connection. The gateway is a network node equipped for interfacing with another network that uses different communication protocols. The way that information is transferred from the portal of the server differs, depending on the distance between them. When the distance is local, wired or wireless internet or RF signals for data transmission are used. If the distance gate to server is long enough, the transmission of information is achieved via satellite communication. The next "stop" of the information flow is the router. A router is a device that forwards data packets between computer networks, creating an overlay internetwork. The information comes out of the router and enters the server. In the most common use, a server is a physical computer (a computer hardware system) dedicated to run one or more services (as a host) and to serve the needs of the users of other computers on a network. The server then either sends the data collected from the sensors in a database that stores and keeps records for subsequent processes and investigations, or sends it to a user to further process them (Figure 1). There is an option to enter the data into a user interface for the information sent to the data station. User interfaces allow the users to handle the information of the system's database and visualize the selected data and products [graphical user interface (GUI)]. The last "stop" of the information flow in the network is a computer or a network of parallel-connected computers, which processes the total data available to the data station and those that might have been processed by the user or a user interface. The environmental sensor networks monitor phenomena in the atmosphere usually dealing with air quality and measure quantities of chemical compounds (organic and inorganic), greenhouse gases, dust and particle matters in the atmosphere. It is well known that the role of the atmosphere and the sun radiation is vital for the earth natural environment, the flora, the fauna and the human lives. Changes in the atmospheric components affect -among others -the incoming solar radiation, the upwelling radiation and finally the energy balance on the Earth with unpredictable consequences to weather, climate and sustainability of many species. Environmental Information Systems has been very important and can further improve our knowledge regarding the variations of atmospheric components at large up to global scale. Regarding the Table 1, the "EuNetAir" comprises a Cooperative network based on advanced chemical sensors and sensor-systems at low-cost, including functional materials and nanotechnologies for low-cost air-pollution monitoring through field studies and laboratory experiments, to transfer the results into preventive real-time control practices [START_REF] Penza | Overview oft he COST Action TD 1105 EuNetAir[END_REF]. The main scope of this network is a cleaner air in Europe with reduced negative effects; targeting to outdoor air pollution control and indoor energy efficiency in buildings. It fosters the technology of new sensing costeffective chemical sensors in the European countries [START_REF] Penza | Overview oft he COST Action TD 1105 EuNetAir[END_REF]. Another noteworthy system is the "EARLINET" (Table 1). This system is an aerosol lidar network, established in 2000, with the main goal to provide a comprehensive, quantitative, and statistically significant data base for the aerosol distribution on a European scale. Because of the unpropitious effects of aerosols on human life, it is important to achieve an advanced understanding of the processes that generate, redistribute, and remove aerosols in the atmosphere, through EARLINET system that has the capability for accurate and timely measurements and monitoring. The "GAPS" Network refers specifically to Persistent Organic Pollutants (POPs) in air (e.g. [START_REF] Breivik | Towards a global historical emission inventory for selected PCB congeners -a mass balance approach. I. Global production and consumption[END_REF]. Measurements of POPs are integrated with other to assess temporal trends and for investigating regional and long-range transport of POPs and other priority chemicals (e.g [START_REF] Breivik | Towards a global historical emission inventory for selected PCB congeners -a mass balance approach. I. Global production and consumption[END_REF]. The "GAPS" project initiated at 2004 in global-scale and it is operating currently at more than 50 sites around the world. Reliable scientific data and information on the chemical composition of the atmosphere and its natural and anthropogenic changes are measured and monitored through cooperation among institutions and organizations of many countries worldwide, within the "GAW" (Global Atmosphere Watch) program (e.g. Plass-Dülmer et al., 2002). To achieve the programme's goals, a network of hundreds of instruments and sensors are used all around Earth. It is mentioned that some of collected datasets of the "GAW" network are coupled with satellite measurements, which results in a more complete picture of atmospheric composition and processes on global scale that provides complimentary checks of instrument calibrations. Summarizing, "EARLINET" is a system focused on aerosols that are measured using a network of lidars. In opposite, the "EuNetAir" system uses many different types of sensors and networks, combining many different data and parameters of a wide variety of atmospheric components including aerosols. Another focused network in a specific category of components is the "GAPS" network that is referred as above mentioned to the POPs. Finally, the "GAW" programme can be included in the category of "system of systems" because uses many different data sets from many different systems worldwide, having as objective to collect data and products from many different sources for a better understanding and monitoring of the atmosphere and the marine environment.

Marine Environment

The EIS for the marine environment monitor and deal with a plethora of data and parameters that extends even in meteorology. The sensors of these systems are being designed to have the ability to measure physical, chemical and biological parameters that control the marine life. Phytoplankton, water temperature, optical depth, deposition of particle matter and chemical compounds, turbidity and height of waves are only just some of the parameters that these network systems monitor.

The "GOOS" is a collection of ocean observing and information delivery system ("system of systems") for observations, modeling and analysis of marine and ocean variables to support operational ocean services worldwide (e.g. [START_REF] Worth | Evolution of sustained ocean observing system[END_REF]. This system provides high-quality descriptions of the present state of the oceans, including living resources, continuous forecasts of the future conditions of the sea for as far ahead as possible, and the basis for forecasts of climate change. Satellite instruments, free floating buoys and profilers are used -among others -in order to measure parameters like sea surface temperature, salinity etc. The "IOCCP" comprises (e.g. Telszewski, 2012) a global network for the development of globally acceptable strategies, methodologies, practices and standards, homogenizing efforts of the research community as well as integrating ocean carbon programs and activities aiming at a sustained global observation network for marine biogeochemistry.

The "NOOS" system is aiming to develop and implement online operational marine data and information, to provide analysis, forecasts, and model-based products describing the marine conditions and to establish a marine database that proves time series and statistical analyses [START_REF] Holt | Towards NOOS-the EuroGoos new shelf task team 1996-2002[END_REF]. Main measured parameters include discharged loads, water level, waves and sea surface temperature. The forecasted parameters include total water net transports, seal level and wind currents.

Summarizing, the "GOOS" system is fully autonomous, having its own observation networks that provide a global view of the ocean system. It comprises a network system of sub-systems, each of which is working on different and complementary aspects of establishing an operational ocean observation capability. It is consisted of many different observation platforms that measure initial data in order to collect, monitor, describe and forecast the state of the oceans.

The "IOCCP" system on the other hand, has one clear objective, the ocean carbon observations. It's a global scale system that focuses on specific ocean parameters.

Finally, the "NOOS" system is a large scale system that covers the European North West Shelf (NWS), providing reliable descriptions of the actual marine conditions on the NWS area, through many different kinds of variables about the specific marine environment. The system has its own instrumentation network and its final scope is to develop and implement ocean observing and prediction services for the NWS area, by delivering real time operational data and products.

At this point, it is mentioned that there are some similar systems to "NOOS", like Baltic Operational Oceanographic System ("BOOS") and others that operate in regional scale and their data are used from broader scale systems such as GOOS that belongs to the category of "system of systems".

Conclusions

This study comprises a short review regarding the Environmental Information Systems that use indispensably instrumentation/sensor networks in order to collect environmental information. There are described the main basic operating principles and then it focuses on EIS for Atmosphere and Marine Environment; providing basic knowledge about the parameters that they record and the services that they provide. We present systems that operate in the large to global scale and we have mentioned that at global scale there is an approach to combine many systems that are established at regional and large scale. The combined use of regional and large scale systems and their recorded parameters can be further integrated into central databases that provide with the philosophy of a global information system, valuable information, products and services at global scale. The integration of information from many different regional/large systems to a central "global nature" system can define this, as "system of systems". Additionally, there is an increasing tendency to develop such systems by unifying smaller scale ones and creating global monitoring systems for a better understanding of Earth's environment.

The EIS uses instrumentation/sensor networks that record and process simultaneously vast types of parameters in large-to-global scale, associated with the atmosphere, the climate and the marine environment. The technological advances in many fields like sensing, telecommunications and computing can be integrated with the geosciences, resulting in fully automated systems that can record, collect and store a wide variety of parameters. The initially measured data and parameters can be further analyzed providing many valuable final products and services. The large scale monitoring systems can operate not only as databases but also as monitoring and forecasting systems, providing with this way plenty of services to the end users according to the goals and the needs for wide environmental issues. It is mentioned that EIS can provide a wealth of information not only to science but in public too, through data sending to decision making and risk management systems. This is another important contribution of such systems with beneficial effects to the sustainability of the environment as well as the quality of human lives, properties and their economic activities. We have also to mention, that such systems can help importantly to a sustainable and environmentally correct of the reindustrialization in local up to national and international level, through planning and management of air and water pollutants.

Fig. 1 .

 1 Fig. 1. A schematic flow chart of operation of environmental sensor networks

Table 1 .

 1 Examples of EIS that are referred to atmospheric parameters

	Name of the System	Parameters	Year
	Cost Action TD1105 -EuNetAir	CO 2 , H 2 O, NOx, SO 2 , H 2 S,	2011
		VOCs, PM, PAH, O 3 , etc.
	EARLINET	aerosols	2000
	GAPS (Global Atmospheric Passive Sampling	Persistent organic pollutants	2004
	Network)	(POPs)
	GAW -Global Atmosphere Watch	e.g. greenhouse gases (CO 2 ,
		chlorofluorocarbons, CH 4 , O 3 ,	2012
		N 2 O, CO, NO x , SO 2 , VOC),
		ozone, UV, aerosols

Table 2 .

 2 Examples of EIS regarding to the marine environment

	Name of the System	Parameter	Year
	GOOS -The Global Ocean	e.g. temperature, salinity,	1991
	GOOS -Global Ocean Observing	atmospheric pressure, oxygen, carbon
	System	dioxide (CO 2 )
	IOCCP -International Ocean	Dissolved organic carbon, alkalinity,	2005
	Carbon Coordination Project	pCO 2 , pH, particulate carbon
	NOOS -North West European	e.g. tides, storm surges, mean sea	2006
	Shelf Operational Oceanographic	level change, surface temperature,
	System	salinity, dissolved oxygen, nutrients,
		chlorophyll

Acknowledgements

This work was supported by the "Transnational enhancement of ECOPORT 8 network" (TEN ECOPORT) project with code SEE/D/ 0189/ 2.2/X. project co-financed by the European Union within the South East Europe Transnational Cooperation Program.


Luis M Camarinha-Matos
email: cam@uninova.pt

Collaborative Systems in Support

Keywords: Reindustrialization, Collaborative Networks, Sustainability

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

Introduction

The term reindustrialization has appeared to represent the economic, social, and political process of organizing resources for the purpose of re-establishing / revitalizing industries in order to reinvigorate the economy. After decades of industrial decline, due to deliberate policies that advocated an exclusive move towards a service-oriented society, while neglecting the production of tradable goods, many countries are struggling with hard public and private belt-tightening measures which only accelerate the crisis spiral. While the urgent need for growth and job creation are getting attention in the policy agendas, technical discussions more and more focus on new approaches for manufacturing, value creation, operational excellence in distributed contexts, agility, and collaborative networks.

Sustainability issues, considering the three pillars of environment protection, economic growth, and social progress, are clearly upfront in these trends. Any effective solution in the direction of sustainable industrial approaches imposes collaboration of multiple stakeholders organized in mixes of dynamic value chain networks. New collaborative systems need to be developed under a well-integrated socio-technical perspective.

This introductory chapter intends to briefly highlight the relevant contribution that collaborative networks can have in the development of a new generation of industrial systems able to address major societal challenges. For this purpose, a brief analysis of relevant literature and research roadmaps is made.

Some Literature Trends

The first wave of literature on reindustrialization appeared in the 1980s, particularly in Europe and the USA. In the case of Europe, most discussions were associated to the political changes in Central and East Europe and were focusing on the creation of new, innovative industries, activities and products, with high priority for environmental protection industry [START_REF] Horváth | Preliminary thoughts on the role of reindustrialisation and environmental protection in regional development[END_REF]. The transformation processes were associated to the crisis and decline of state-owned industries, leading to some deindustrialization [START_REF] Lux | The re-emerging role of industry in Central European economies[END_REF]. By the same time, considerable discussions on reindustrialization, productivity, and competitiveness were also taking place in the USA [START_REF] Bachelor | Reindustrialization in Detroit: Capital Mobility and Corporate Influence[END_REF], [START_REF] Norton | Reindustrialization and Economic Development Strategy[END_REF]. The need for collaborative strategies among various stakeholders for effective reversal of stagnant or declining economies was already recognized in this period [START_REF] Beauregard | ollaborative Strategies for Reindustrialization: Sheffield and Pittsburgh[END_REF].

More recently, in the sequel of the ongoing economic crisis, the subject became again on top of the political agenda. For instance, a manifesto for growth and employment in Europe [START_REF] Ce | Manifesto for growth and employment -Let´s reindustrialize Europe[END_REF] advocates the need: "To organize technological and industrial cooperation in all sectors and all regions: building new industries, European players of international dimensions, and creating ecosystems for innovation and investment call for sustainable partnerships".

The Foundation Robert Schuman also points out the importance of cluster networks in the strategy to reduce disparities between regions and overcoming innovation gaps [START_REF] Lirzin | Reindustrialising Europe: the issues at stake in a European Innovation and Industrial Policy[END_REF]. At the European Commission level it is particularly relevant the new target for 2020 to counter the decline of Europe's industrial base and increase the share of manufacturing in EU's GDP to 20% [START_REF]Commission launches re-industrialisation drive[END_REF], [START_REF]Moving forward to an industrial renaissance to overcome economic crisis[END_REF]. Many discussions around reindustrialization and economic revitalization appear associated to transformations along the lines of a green economy.

A recent manufacturing outlook report by KPMG [START_REF] Kpmg | Global Manufacturing Outlook -Competitive advantage: enhancing supply chain networks for efficiency and innovation[END_REF] also highlights the importance of collaboration:

"While the lean manufacturing revolution was focused on getting businesses' own houses in order, the challenge now is to improve supply chain performance through genuinely closer working relationships and collaboration across the network".

Improved end-to-end visibility of the supply chain is also pointed out as key for optimization, which is synonymous of more effective collaboration. ICT collaboration platforms and tools are fundamental enablers in this process. According to the same report [START_REF] Kpmg | Global Manufacturing Outlook -Competitive advantage: enhancing supply chain networks for efficiency and innovation[END_REF], when asked "what are the major challenges your company faces in its ability to innovate?", manufacturing companies identified top 5 challenges:

1. Aligning innovation to company strategy; 2. Complexities in collaborating with suppliers and partners; 3. Executing innovation -on time and on budget; 4. Shortage of ideas to drive innovation; 5. Incomplete view of / difficulty understanding the needs of customers. Besides the second challenge, which clearly requires collaborative networks contribution, also concepts such as co-innovation, open innovation, or glocal enterprise, which are addressed in current research by the collaborative networks community, can bring significant inputs to challenges 4 and 5.

Industry-oriented Research Roadmaps

Realizing the importance of manufacturing in "growth and jobs", a prerequisite for societal sustainability, EFFRA has elaborated a multiannual roadmap [START_REF] Effra | Factories of the Future PPP -FoF 2020 Roadmap: Consultation document[END_REF] with research and innovation priorities for Factories of the Future under the Horizon 2020 program of the European Commission. The roadmap is designed with the aim of having a significant impact in the following major long-term objectives:

-Maintain and create new jobs in manufacturing.

-Increase value added by manufacturing.

-Address environmental concerns, by reducing emission of gases, energy consumption, waste generation, and consumption of materials. -Enhance attractiveness of jobs in manufacturing.

-Increase the number of manufacturing enterprises engaged in innovation and R&D. The roadmap identifies 6 main research and innovation priorities (Fig. 1). When observing the details of each priority and the proposed research actions, the role of collaborative networks becomes evident. This role is most obvious in the priority "Collaborative and mobile enterprise", in which the proposed actions are clearly aligned with research topics in collaborative networks. But relevant contributions of collaborative networks and collaborative systems are also identifiable in all the other priority domains, as summarized in Fig. 1.

Fig. 1. Role of collaborative systems in the FoF 2020 roadmap

A complementary roadmapping initiative is represented by the position paper towards Horizon 2020, elaborated by the FInES (Future Internet Enterprise Systems) cluster [START_REF] Fines | Embarking on New Research Orientations towards Horizon[END_REF]. This document is organized around 5 research priorities aimed at supporting Internet-based disruptive enterprise innovation towards competitive advantage development and sustainable growth.

As illustrated in Fig. 2, in all these priority areas collaborative networks is a major

Examples of Contributions from Collaborative Networks

The 2013 edition of PRO-VE was specifically focused on the contribution of collaborative systems for reindustrialization and, as such, it presents a good overview of current contributions [START_REF] Camarinha-Matos | Collaborative Systems for Reindustrialization[END_REF]. Furthermore, many other important contributions can also be found in other recent editions, with particular relevance to the ones devoted to sustainability [START_REF] Camarinha-Matos | Collaborative Networks for a Sustainable World[END_REF], value creation [START_REF] Camarinha-Matos | Adaptation and Value Creating Collaborative Networks[END_REF], and Internet of services [START_REF] Camarinha-Matos | Collaborative Networks in the Internet of Services[END_REF]. Fig. 3 gives an overview of the main areas covered by the selected papers. It shall be noted that some papers address more than one area. also known as product-service, represents the association of business services to the physical product, adding value to the product along its life-cycle through better satisfaction of customer needs. The term product-service system (PSS) is also used, including the product, the associated services, the involved enterprises network, and the needed infrastructure. Examples of significant research topics under this item:

-Notion of "servitization" and "service-dominant strategy" to represent a mindset shift from goods-dominant logic to service-dominant logic; -Role of service enhancement in sustainability and methods to assess that sustainability; -Organization of collaborative ecosystems to provide the services, introducing the perspectives of multi-stakeholders collaborative value creation and cocreation through the involvement of the customer; -Identification and characterization of the interplay among various collaborative networks along the product life-cycle such as product manufacturing network, service co-creation network, product servicing network, and the long-term ecosystem or manufacturers VBE; -The notion of glocal enterprise in the product-enhanced services, highlighting the role of the customer and its related "community" (local suppliers, regulators, other local stakeholders) and the interplay of this "community" with the manufacturers network; -Understanding and modeling the contribution of the various stakeholders in value proposition to form a PSS; -Identification of critical decision processes and decision centers in the transition to PSS; -Specification and configuration of customized complex products; -Assessment of (industrial) service procurement processes; -Value systems alignment in the creation of product servicing networks; -Cloud-based collaboration platforms and tools to support service-enhanced product ecosystems.

Focusing on co-innovation. The notion of co-innovation refers to a collaborative process involving not only industry stakeholders but also the customer in the design of new solutions. Examples of relevant research topics include: -Strategies and mechanisms to promote the creation of innovation networks; -Key roles and processes in co-creation of intellectual property; -Service co-creation networks and processes; -Mechanisms to assess knowledge circulation in co-innovation networks; -Co-creation support platforms and collaboration spaces.

Improving processes and agility. Various research activities continue focused on the improvement of distributed business processes, redesign of processes towards more optimized operation, and configuration and reconfiguration of networks. Examples include:

-Incentives, sanction mechanisms, and fair distribution of benefits; -Transportation logistics optimization; -Sensor networks in large-scale monitoring; -Collaborative cyber-physical systems in process monitoring;

-Identification and characterization of collaborative processes; -Context-aware process modeling methods; -Representation of behavior related processes; -Consortia formation and reconfiguration of collaborative networks to support better coordination and control.

Focusing on service design and provision.

The growing importance of (business) services and the need to better "engineer" them led to the emergence of new research streams such as services science and services design. Services science is a movement trying to clarify the notion of service in all its dimensions and provide a sound conceptual framework for the area. Service design aims at providing effective approaches and tools for service design, addressing the functionality and form of the services. In particular, it aims to ensure that service interfaces are useful, usable, and desirable from the client's perspective, while being also effective, efficient, and distinctive from the supplier's perspective. Examples of relevant research topics:

-Modeling services life-cycle; -Methods for services discovery and selection based on non-functional properties: -Role of mobile and location-based services in dynamic value chains; -Dynamic negotiation and contracting of services to support agile manufacturing networks; -Handling uncertainties associated with partnerships in provision of sustainable services, e.g. dealing with variability of governance structures, climate of relationships, behavioral uncertainty, performance variations, etc.; -Methods to support service co-design, with particular focus on visual thinking approaches; -Cost prediction for service systems, namely in co-creation contexts; -Approaches to "industrialize" the service design and service innovation processes; -Interaction patterns in NFC interfaces for services; -Service level agreements in cloud-based environments; -Adaptation of service design tools to different industries; -Identification and characterization of services in fashionable products; -Development of energy-control services for smart homes based on multistakeholders collaboration; -Collaboration in effective service recovery in incidents management.

Stimulating collaborative strategies.

A substantial group of diversified contributions are focusing on strategic and managerial approaches to promote collaboration.

Examples of addressed topics include:

-Trends in global economy and facilitators for intercontinental collaboration; -Dynamic networks and employment structure; -Approaches to enhance collaboration strategies and anything relationships management; -Legal and regulatory frameworks to promote enterprise networks; -Collaborative approaches in revitalizing rural communities; -Promotion of public-private collaboration; -Evolution of business models in networks; -Collaboration forms in the tourism and healthcare sectors; -Risk analysis and trust promotion methods; -Exploiting the value of social networks, namely in terms of information fusion and knowledge extraction.

Addressing sustainability in its various perspectives. The role of collaborative networks in sustainability has deserved considerable attention in the last years [START_REF] Camarinha-Matos | Collaborative Networks for a Sustainable World[END_REF] and is likely to continue a major topic of research. Examples of current issues include:

-Models to promote sustainable packaging and transportation logistics, aiming at reducing environmental impacts; -Collaborative networks in reverse logistics and end-of-life manufacturing challenges; -Enterprise networking in support of remanufacturing and recycling; -Role of intangible assets in business sustainability; -Power distribution and sustainability of the networks; -Sustainability issues in networked mass customization, namely addressing variability rationalization.

Developing infrastructures and tools. In addition to the various technological components and systems included in previous sections, the developments of collaboration platforms and generic collaboration support tools offers important enablers for the actual establishment of collaborative networks. Examples of developments include:

-Collaboration spaces -models and support functionalities; -Knowledge-based architectures to support co-creation; -Collaboration platforms for learning environments; -Cloud-based collaboration platforms; -Collaborative planning support tools; -Event-driven architectures and event marketplaces; -Support for dynamic composition of processes.

The above examples do not constitute an exhaustive representation of research in this domain but provide a comprehensive set of examples of issues being tackled by a large variety of research groups [START_REF] Camarinha-Matos | Collaborative Systems for Reindustrialization[END_REF], and which are likely to contribute to effective reindustrialization.

Concluding Remarks

The perspective of collaboration and enterprise networks has become a central issue in the ongoing policy agendas and initiatives to revitalize industry. As such, collaborative networks play a relevant enabling role in the reindustrialization processes. This is well recognized in recent literature and strategic research roadmaps for future manufacturing and enterprise systems. A survey of current research in the collaborative networks area, as represented by the contributions to recent PRO-VE conferences, illustrates well how collaborative systems and models are being developed and evaluated in support of a new industrial landscape.

Fig. 2 .

 2 Fig. 2. Role of collaborative systems in the FInES position paper towards Horizon 2020

Fig. 3 .

 3 Fig. 3. Main covered areas in PRO-VE'13

Factories of the Future 2020 Roadmap contributing

			…
			Novel supply chain approaches for innovative products
	Cloud-based Manufacturing Business Web for Supply Network		… Embedded cognitive functions for supporting the use of machinery and robot systems in changing shop floor
	Collaboration		environments
	End-of-Life (EoL) applications in a network of remanufacturing stakeholders Mobile store and applications for	Advanced manufacturing processes Research priorities	Symbiotic Safe and Productive human robot interaction, professional Service Robots and Multimodal Human-Machine-Robot Collaboration Mechatronics and new machine architectures for adaptive and evolving Factories
	an agile and open supply network Connected objects for assets and	Adaptive and smart manufacturing systems	…
	enterprises in the supply networks Complex Event Processing (CEP)	Collaborative and mobile enterprises Digital, virtual and resource-efficient factories	Integrated factory models for evolvable manufacturing systems System-oriented quality control strategies in multi-stage manufacturing
	for state detection and analytics in supply networks Collaborative Demand and Supply Planning, Traceability, and Execution	Customer-focused manufacturing Human-centred manufacturing	… New ways of interaction and collaboration between workers and other resources in manufacturing systems Linking organisational knowledge in connected enterprises
	Digital Rights Management (DRM)		…
	of products and code in enterprise		Collaborative product-service systems design environments
	supply networks Multi-Enterprise Role-Based Access Control (mRBAC) in manufacturing enterprises		for SME involvement Crowd sourcing for highly personalized & innovative product design Product-Service Simulation for Sustainability Impact Mobile servicing cockpit for extended business offerings
			On-demand manufacturing of customer-centric products
			Customer focused products quality assessment standards &
			tools
			Implementation of creativity and user-driven innovation
			through flexible design and manufacturing processes

discipline.

Focusing on service-enhanced products.

  The notion of service-enhanced product,

	Future

Internet PPP Web Entrepreneurship Sensing Enterprise Digital Enterprise Collective Awareness Platforms Research priorities FInES Position Paper Towards Horizon 2020

		…
	… Leveraging the emerging "network effect" by combining open social media, distributed knowledge creation and data from real environments Collaborative Awareness Platform as a socio-technical artefact capable of openly link (smart) objects, people and knowledge for the benefit of the enterprise Embrace the wider ecosystem of enterprises and society Co-existence of Digital Business Innovation and Social Innovation	Decentralised intelligence and fusion between the physical world and the virtual world Decentralised intelligence on a massive scale (Smart) objects capable of making autonomous decisions People and objects will become collaborating and possibly competing partners in an enterprise environment Investigate governance of smart objects including their cyber identities in the context of business operations and enterprise networks
	… Involving, interacting and engaging a new ecosystem of physical and virtual stakeholders Wisdom of the crowds and business awareness Effectively harnessing internal and external knowledge, resources and capabilities Provide innovation-oriented enterprise …. collaboration platforms Supporting extended, virtual or agile enterprises in the Future Internet.	… Business ecosystems based on collaborating as well as competing service platforms Governance models of multi-sided platforms ecosystems Facilitate a permanent SME/micro-enterprise/start-up ecosystem that co-exists and influence the FI long-term evolution Perform R&D on effective value network modelling, value network monitoring & analysis, business modelling tools
	… Crowdsourcing of "Problems to be solved" Open innovation Supporting innovation serendipity	Promote R&D social business networking and knowledge management technologies for SMEs and Entrepreneurs Perform R&D in technologies and methodologies to nurture and manage
		business innovation networks of enterprises

Acknowledgements. This work was funded in part by the European Commission through the GloNet project (FP7 programme).


Maiara Heil Cancian
email: maiara@das.ufsc.br

Ricardo J Rabelo
email: rabelo@das.ufsc.br

Christiane Von Wangenheim

Christiane G Von Wangenheim

Supporting Processes for Collaborative SaaS

Keywords: Collaboration, Business Process, Software-as-a-Service

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

Introduction

The adoption of strategic alliances focused on highly intense collaboration has been seen as a sustainable alternative to increase enterprise competitiveness through innovation and productivity [START_REF] Gulati | Strategic Networks, Strategische Unternehmungsplanung -Strategische Unternehmungsführung[END_REF]. Collaborative Networks (CN) has emerged as a prominent paradigm allowing companies to keep focused on their skills and to aggregate competencies with other companies in order to offer products with higher value to meet businesses [START_REF] Rabelo | Smart Configuration of Dynamic Virtual EnterprisesVirtual Enterprises and Collaborative Networks[END_REF]. CN can provide the basis for capacity elasticity and workload allocation flexibility in dynamic and adaptive value chain networks.

ICT represents one of the most important sectors in the nowadays knowledge and increasingly service-oriented economy, and has become vital to leverage enterprises competitiveness [START_REF] Kourtesis | Discovery and Selection of Certified Web Services Through Registry-Based Testing and Verification[END_REF]. However, it is important to consider the typical profile of ICT companies. In Europe, for instance, there are more than fifty thousand SMEs within the ICT sector [START_REF] Office | [END_REF]. It is well known that SMEs have many limitations, such as in terms of human and financial resources, marketing, scalability, time-to-market, best practices and innovation. Therefore, it is crucial to develop sustainable models for ICT companies that are aligned to that reality.

Within this context, cloud computing and Service Oriented Architecture (SOA) paradigms have introduced a new outlook on systems design, development, integration and servitization [START_REF] Papazoglou | Web Services & SOA, Principles and Technology[END_REF]. Following this trend, a number of architectural and supporting business models start to be widely adopted, such as SaaS (Software-asa-Service) [START_REF] Jiehui | Research on Key Technology in SaaS[END_REF]. SaaS is an architectural and availability model of software that is accessed on demand via Internet and that is paid per use. In this model companies no longer buy traditional software packages' licenses but remotely invoke ('rent') specific software services from providers instead. Although not mandatorily, in order to take more advantages of the software features provided by SOA, several SaaS solutions are developed under this paradigm, where a SaaS solution is then composed of a set of (decoupled) software services [START_REF] Laplante | What's in a Name? Distinguishing between SaaS and SOA[END_REF].

Regarding the ICT companies that have been investing in SOA and SaaS-based solutions, on one hand the adoption of these models can open new business opportunities. On the other hand this does not solve those limitations by itself as companies usually remain working alone, developing services by their own and for their use only, keeping them deployed at their local silos [START_REF] Perin-Souza | Services Discovery as a Mean to Enhance Software Resources Sharing in Collaborative Networks, in Adaptation and Value Creating Collaborative Networks[END_REF]. The underlying motivation of this paper is to explore the premise that ICT SMEs sustainability can be highly enhanced if they collaborate more with other companies -even being competitors -in the form of sharing services and business strategies with the aim of composing and offering more value-added services-based solutions to the market.

CN appears as an adequate scientific foundation to pave a collaborative work among ICT SMEs in that perspective. In this paper, the envisaged business scenario refers to making such companies sharing their individual (interoperable) services in order to compose more flexible SaaS solutions to better cope with market needs. This scenario has been called as "Collaborative SaaS" [START_REF] Cancian | What Is Collaboration? An Analytical Cut from the Business Processes and SaaS Perspectives[END_REF]. In the light of CN paradigm, this means creating a Virtual Organization (VO) to attend to a concrete demand for or to prospectively develop a new SaaS solution, where the VO members are the ICT companies which own the involved services of that solution.

A number of works in the literature use to generally state about the importance of ICT companies to more intensely work in a collaborative way. However, no one say how to do that in a precise and comprehensively way. Even larger companies that do that use to make it in an ad-hoc manner and very much focused on their reality regarding their long-term and know partners. The fact is that working collaboratively -and even more in such Collaborative SaaS scenario -is not a mere wish. There are many organizational, legal, financial, technological among other issues to cope with to approach this problem. This is especially difficult considering that companies are naturally heterogeneous and that their independence and autonomy must be kept along the collaboration.

In this sense, this work provides a comprehensive list of the business processes that SaaS providers should deal with along a collaboration towards having a SaaS solution. In a previous work [START_REF] Cancian | What Is Collaboration? An Analytical Cut from the Business Processes and SaaS Perspectives[END_REF] authors provided a preliminary list of collaborative processes for Collaborative SaaS. This article now presents the consolidated and formalized version of this list, the processes' related practices and the positioning of each process within each phase of the VO life cycle. A list like that is an important instrument offering a more solid basis to SaaS providers about the impact of these processes on their current practice. As such, they can be better prepared for supporting the processes, for better managing resources and efforts in each VO / collaboration phase as well as for implementing processes' related practices.

This article is organized as follows: section 2 depicts the essentials of research methodology applied in this work as well as of the literature review. Section 3 presents the list of collaborative processes and example of practices. Section 4 discusses about the main findings of this research.

Basic Research Methodology and Literature Review

This research corresponds to a qualitative and applied work, strongly grounded on revision of literature. The literature review was mostly conducted applying the SLR methodology [START_REF] Fraser | Managing product development collaborations-a process maturity approach[END_REF] over IEEExplore, ACM Digital Library, Compendex/Engineering Village and ScienceDirect scientific databases collecting papers published in journals and conference proceedings between Sept 2000 and Sept 2012. This was complemented with ad-hoc searches, also looking at works developed in the software industry. From an initial and rigorously filtered list of 278 works that were found out, 11 works were taken as the core theoretical referential source of collaborative processes [START_REF] Rabelo | Advanced Collaborative Business ICT Infrastructures[END_REF][START_REF] Alonso | Enterprise Collaboration Maturity Model (ECMM): Preliminary Definition and Future Challenges[END_REF][START_REF] Soria | Developing an Enterprise Collaboration Maturity Model: Research Challenges and Future Directions[END_REF] [ [START_REF] Santanen | The Collaboration Engineering Maturity Model[END_REF][START_REF] Fraser | Managing product development collaborations-a process maturity approach[END_REF][START_REF] Fraser | A maturity grid approach to the assessment of product development collaborations[END_REF][START_REF] Magdaleno | Designing Collaborative Processes[END_REF][START_REF] Thomson | Collaboration Processes: Inside the Black Box[END_REF][START_REF] Romero | VO breeding environments value systems, business models and governance rules[END_REF], regarding their scope and depth in the processes description.

An inductive method was applied as the research strategy aiming at creating a generalized but preliminary list of collaborative processes from particular instances (related works) and from empirical evidences.

It could be observed that Collaborative SaaS is a new area and no very directed related works were found out. Therefore, that list had to be compiled and adapted to that as well as fit in along the VO life cycle. It is important to clarify that reference models as CMMI or ISO/IEC 15504 [10] are devoted to software improvement processes and for the acquisition model, and not to collaborative processes and service-oriented model. On the other hand, being very consolidated models, they were used as the basis for the elaboration of the processes' base practices.

A selected international working group composed of 24 experts on the areas of collaborative processes/systems and services was formed to refine and evaluate the compiled processes list. This was carried out along three rounds of interactions via a web site created for that. Intermediate and final refinements were conducted by the authors, also based on their experience in the involved areas. This has also involved a final consolidation of the resulting list in order to check redundancies (i.e. different processes' purposes dealing with equivalent concepts), synonyms (i.e. different words but with the same meaning) and semantics misleading (i.e. definitions of processes that were in fact more related to other process' definition). A number of supporting books were also taken into account for that 'normalization', [START_REF] Camarinha-Matos | Methods and Tools for Collaborative Networked Organizations[END_REF] in more particular.

Collaborative Processes

With the processes compiled with 'normalized' names and purposes, they were analyzed and categorized within and according to the phases of the VO life cycle reference model [START_REF] Camarinha-Matos | Methods and Tools for Collaborative Networked Organizations[END_REF]: creation, operation, evolution and dissolution. Due to the more amplitude, the processes within Operation and Evolution phases were organized into subcategories, regarding their more intrinsic nature. They were also prioritized in terms of which ones have to be primary supported. The prioritization (P) level was divided into 5 categories: essential [START_REF] Papazoglou | Web Services & SOA, Principles and Technology[END_REF], very important (4), important (3), low important (3) and likely unnecessary [START_REF] Gulati | Strategic Networks, Strategische Unternehmungsplanung -Strategische Unternehmungsführung[END_REF] to be supported only if they are indeed necessary for the particular case. Table 1 resumes the consolidated list of 42 processes required to support Collaborative SaaS. The prioritization was built based on experts' opinions. This prioritization should be seen as a reference and, as any qualitative classification, has some degree of subjectivity. Depending on local conditions and culture, strategic planning, working methods, among other aspects, this can change and so can be deployed differently. It might be said that this corresponds to the 'why', 'what' and 'when' to do the collaboration.

Selection of performance indicators

Performance indicators to be used in the monitoring must to be defined by the SaaS collaboration group.

4 Partner Search Identification of potential partners, and their assessment and selection to be a SaaS provider.

Partner Selection

Setting up SaaS partner's section criteria and selection supporting method.

Negotiation & Risk Analysis

Activities and supporting tools to assist partners during the negotiation processes and risk analysis assessment towards the SaaS collaboration.

E-Contracting

Final formulation of contracts and agreements as well as the contract signing process itself, before the SaaS collaboration can effectively be launched.

4

Collaboration Planning Determination of a rough structure of the potential SaaS collaboration, identifying the required competencies and capacities, structure of the task to be performed as well.

Operation & Evolution

QoS Management Processes 4 Trust Management Promotion the establishment of trust relationships and levels among SaaS participants.

Governance Management

Management activities and supporting tools for the SaaS collaboration policy management, operational rules and bylaws, regulation, and control of the network structure.

3

Measurement and analysis

Developing and sustaining a measurement and analysis capability of the SaaS collaboration that is used to support management information needs.

3

Decision Support Management Management activities and supporting tools for decision support, using KPIs in the SaaS collaboration.

Process and Product Assurance

Provides appropriate conformance guidance and objectively reviews the activities and SaaS work products of work efforts within the collaboration to ensure.

Strategic collaborative processes 5 Strategic Management

Formulating, and evaluating functional decisions that will enable a collaboration to achieve its objectives.

3

Customer Relationship Management Managing the interaction with SaaS customers with the collaboration, using enterprises data and information.

Organizational Innovation

Selection and deployment of innovative and measurably improvements of the SaaS collaboration's processes

Collaborative Strategy

Investment in strategies to improve the SaaS collaboration, to develop provider competence and to improve the general network.

Reconciling Individual and Collective Interests

Achieving trade-off between individual partners' missions and collective interest.

3 Simulation Generation of scenarios about implementation decisions evolving SaaS and collaboration.

process outcomes (PO) and base practices (BP). BPs contains the list of indicators that should be used to achieve process' purpose, including some optional notes. POs can be seen as the checklist to evaluate if BPs were properly implemented.

A PRM and related BPs should be seen as a referential basis and so they should be expressed at a relatively abstract level allowing a further particularization for collaborative companies. ISO/IEC 15504 was also used as a basis for the BPs and then adapted to the Collaborative SaaS scenario. Table 2 shows a PRM of one of the 42 elicited collaborative processes. It refers to the process 'collaborative strategy', which is performed in the operation ('OPE') phase of the VO/collaboration life cycle, it is the first ('.1') process in this phase, and that has seven BPs. The complete list of PRM for all processes can be found at: http://www.das.ufsc.br/~maiara/Collab_SaaS_MM.pdf.

Discussion and Conclusions

This article has presented a comprehensive list of the collaborative processes that are generally required when groups of SaaS providers decide to work collaboratively aiming at providing a given SaaS solution as a Virtual Organization. Processes are detailed and formalized in way to help companies in their implementation and management along the VO / collaboration life cycle. This list should be taken as complementary to the traditional transaction-based business processes that companies use to execute in their daily business life.

One of the most important usages of that list is to give awareness to SaaS providers about what, how and when to do in a collaboration. As such, they can help companies in making less difficult the 'shifting process' of transforming collaboration as a process routine and value adding instead of an exception and sporadic action, as usually happens in the companies, SMEs in particular.

Although comprehensive and it had been validated by a group of international experts, the processes list cannot be seen as definitive. A number of works in the literature has brought up valuable outcomes on collaboration among companies but essentially focused on more consolidated sectors, as manufacturing, and sometimes targeting to specific problems. Collaborative SaaS, on the contrary, is a new scenario, having a number of open points and challenges. As such, it is natural that the list evolves as long as such form of gets more mature and companies start using them more intensely as a basis for continuous process improvement. Therefore, this list should be seen as an initial contribution, as a starting point. Even though, it should be adapted to the current or envisaged SaaS digital business ecosystem, considering aspects as business strategy and local conditions, capacity and maturity models, organizational change management, trust building, companies' performance evaluation and reputation management, financial impact, selection and use of proper implementation ICTs, interoperability, security, SLA management and services deployment, among many other. All this costs and takes time to be implemented and to evolve.

It is important to highlight that the processes list and related PRM does not cover other macro phases of a SaaS life cycle. It assumes that a sort of services are registered and made available in a proper and standard-based way so diverse composite SaaS solutions can be assembled on top of this. The provided list copes with the processes involved in this 'assembly' and basic provision. Other phases, as services conception, design, implementation, fully provision and maintenance, are not supported as they were out of the scope of this specific research.

Next main steps of this research refer to its expansion in general. Firstly but gradually, to enlarge that list in order to also comprise those mentioned SaaS macro phases. Secondly, to evaluate at which extent companies can enhance their organization for more efficient creation and provision of SaaS solutions if they become members of long-term alliance, as VBE -Virtual organization Breeding Environment [START_REF] Camarinha-Matos | Methods and Tools for Collaborative Networked Organizations[END_REF]) and Federation [START_REF] Rabelo | The Ecolead Collaborative Business Infrastructure for Networked Organizations[END_REF].

Table 1 .

 1 Consolidated list of Processes for Collaborative SaaS.

	Phase	P	Processes	Purpose
		4	Business Opportunity characterization	Involves the identification and characterization of a new collaboration opportunity of a new SaaS collaboration.
	Creation

Table 2 .

 2 Process, Purpose, Outcomes and Base Practices.

	Process ID OPE.1
	Name Collaborative Strategy
	Process	The purpose of Collaborative Strategy is to select and deploy improvements
	Purpose	to the SaaS Solution.
	Process	As a result of successful implementation of this process:
	Outcomes	1) Improvements to SaaS Solutions known;
		2) Improvements analyzed;
		3) Goals, strategies and plan defined;
		4) Goals, strategies and plan implemented.
	Base	OPE.1.BP1: Research and identify possible improvements to deploy in the
	Practices	SaaS Solution. [Outcome 1]
		OPE.1.BP2: Analyze if the are aligned with the business
		strategy. [Outcome 2]
		OPE.1.BP3: Analyze how the proposed change generates value for the
		customer. [Outcome 2]
		OPE.1.BP4: Analyze what investment is required and if the needed
		investment will generate an acceptable return. [Outcome 2]
		OPE.1.BP5: Analyze what would be the impact of the improvement on the
		current business. [Outcome 2]
		OPE.1.BP6: Implement activities for improvement.[Outcome 4]
		NOTE 1: When the improvement involves innovation, it is strongly
		recommended to use a Model of Innovation Management.
	Sources [21] [22] [16]

Acknowledgements

This work was supported by CNPq and Capes Brazilian research funding agencies.

Operation & Evolution

Project Processes

Collaborative Project Management

Establishment and managing Collaborative SaaS projects and the involvement of the relevant stakeholders.

Requirements Management

Managing the requirements of the SaaS project's products and to identify inconsistencies between those requirements and the project's plans and work products.

Requirements Development

Producing and analyzing customer, product and product component requirements.

Risk Management

Identify potential problems so that risk-handling can be planned and invoked as needed along the collaboration.

Support Institutions Management

Management activities for identifying and integrating Support Institutions into the SaaS collaboration.

Performance Management

Activities and tools of planning, monitoring, rating and rewarding collaboration actors based on the KPIs.

ICT Management

Management activities and supporting tools for managing easy-to-access and operational infrastructure that will allow collaboration actors with different applications.

Administrative, Legal & Financial 3 Collaboration Launching

Refine the SaaS collaboration plan and its governance principles, to formulate and model contracts and agreements and to put the collaboration into operation.

Collaboration Agreement

Setting up the terms in which the collaboration will take place.

Marketing Management

Management activities and supporting tools that will support the strategic formulation process, including the marketing and branding activities 3 Financial Management Planning income and expenditure, and making decisions that will enable the enterprises survive financially.

2 Accounting Management Activities to guarantee the enterprise financial health and ensure the effective and efficient and use of the resources.

IPR Management

Agreement about the terms of the Intellectual Property Rights within the collaboration. Once identified each process should be more formally specified in order to be more properly understood and used. This would correspond to the 'how' to do the collaboration. This work has applied the ISO/IEC 15504 standard for that. A PRM (Process Reference Model) describes the implementation mechanisms of every single process, providing: process' domain and scope, process purpose,


Juliana Sayuri Kurumoto
email: kurumoto@sc.usp.br

Fábio Müller Guerrini
email: guerrini@sc.usp.br

Technical Components and Requirements Model for Supporting Collaboration in the Product Technology Transfer Process

Keywords:

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

Introduction

Collaboration is considered an important instrument for the development and success of the entrepreneurial firms by providing competitive advantage, given that the links between the enterprises are knowledge and technology transfer factors which support innovative processes [START_REF] Dowling | Product development success through cooperation: a study of entrepreneurial firms[END_REF], [START_REF]Organização para a Cooperação e Desenvolvimento Econômico -OCDE. Manual de Oslo: proposta de diretrizes para coleta e interpretação de dados sobre Inovação tecnológica[END_REF].

Participating in a collaborative network is an organizational solution for those firms that do not have certain skills or know-how to develop a new product. According to [START_REF] Stock | A typology of project-level technology transfer processes[END_REF], acquisitions and use of new technologies from an external source can contribute to the operational success of the firms.

One mechanism to obtain this expertise is the product technology transfer process. This process involves a range of technological knowledge, scientific basis for specific processes, knowledge and competences through and interactive process in which different stakeholders absorb, assimilate and exchange knowledge in a social or physical context [START_REF] Autio | Measurement and evaluation of technology transfer: review of technology transfer mechanisms and indicators[END_REF], [START_REF] Rogers | The nature of technology transfer[END_REF], [START_REF] Autio | A framework of industrial knowledge spillovers in bigscience centers[END_REF]. This iterative process not only transfers knowledge between organizations, but also facilitates the creation of new knowledge and product solutions [START_REF] Hardy | knowledge and influence: The organizational effects of interorganizational collaboration[END_REF], [START_REF] Aragon-Correa | Leadership and organizational learning's role on innovation and performance: Lessons from Spain[END_REF].

The technology transfer is not an easy activity due to the risks and problems that may arise during the product development, committing the time to market, generating excessive costs and functionality issues [START_REF] Iansiti | Technology Integration: Making Critical Choices in a Dynamic World[END_REF], [START_REF] Nobelius | Linking product development to applied research: transfer experiences from automotive company[END_REF]. Throughout the process is necessary to have a high level of interaction among stakeholders in terms of communication, coordination and cooperation [START_REF] Tatikonda | Product technology transfer in the upstream supply chain[END_REF]. This interaction reduces the chaos in the innovation process increasing the probability of developing a successful innovation [START_REF] Ojasalo | Management of innovation networks: a case study of different approaches[END_REF] However, according to [START_REF] Qureshi | The effect of electronic collaboration in distributed project management[END_REF], the communication and the coordination of the activities are some challenges of this environment, requiring different project management methodology from traditional approaches and a much more robust information system (IS) to support the project [START_REF] Chen | A Collaborative Project Management Architecture[END_REF]. In this way, the paper purposes a technical components and requirements model that supports a collaborative environment to transfer technologies.

This paper is organized as follows: Section 2 presents the literature review on collaborative networks and product technology transfer. Section 3 describes the research methodology. Section 4 presents the technical components and requirements model proposed by this research. Finally, Section 5 provides the conclusions and futures researches.

Literature Review

Collaborative Networks. A collaborative network is an alliance formed by several entities that are autonomous, geographically distributed and heterogeneous with regard to the operating environment, culture, social capital and goals, but they share information, resources and responsibilities to jointly plan, implement and evaluate the activities in order to achieve common and compatible objectives [START_REF] Camarinha-Matoes | Collaborative networks: reference modeling[END_REF], [START_REF] Camarinha-Matos | Collaborative networked organizations: status and trends in manufacturing[END_REF]. Besides, the members of networks use information and communication technology to coordinate and support the activities [START_REF] Chituc | Interoperability in collaborative networks: Independent and industry-specific initiatives -the case of the footwear industry[END_REF].

Collaborative networks promote technological development through the creation, generation and dissemination of knowledge, supporting the learning between Organizations, the sharing of technological skills, allowing firms to transfer knowledge and technology that they would not be able to develop [START_REF] Pyka | Innovation Networks[END_REF], [START_REF]Organização para a Cooperação e Desenvolvimento Econômico -OCDE. Manual de Oslo: proposta de diretrizes para coleta e interpretação de dados sobre Inovação tecnológica[END_REF]. These networks are already recognized as a way for firms to survive in dynamic environments, where technology, society and markets are constantly changing. Collaborative networks are considered a way to create value because they generate new capabilities for dealing with uncertainty, need for innovation, competition and mass customization [START_REF] Camarinha-Matos | Collaborative networked organizations: status and trends in manufacturing[END_REF].

According to [START_REF] Yao | Absorptive capacity and social network: internal ability and external opportunity for product innovation[END_REF], these networks allow the individuals involved in the knowledge transfer develop a common understanding required for the receiver fully understands the function of knowledge provided by a source. Social ties can help a firm to explore new scientific and technological knowledge.

Product Technology Transfer. The product technology transfer is a process that manages the acquisition, handling, and incorporation of tangible and intangible objects originating from external product-based sources, in order to commercialize an innovation or meet the needs through the synergistic combination of resources.

The integration of different technologies into products at the end of the technological development represents the interface between technology and product development [START_REF] Schulz | Development and integration of winning technologies as key to competitive advantage[END_REF]. This interface is a critical activity because it can affect the scope of the project, lead-time, cost and quality of a new product [START_REF] Nobelius | Linking product development to applied research: transfer experiences from automotive company[END_REF].

According to [START_REF] Lee | Technology transfer between university research centers and industry in Singapore[END_REF], the transfer of technology provides some benefits such as: opportunity to place students in industry, access to industry for both fundamental and applied research, improvement in new technology implementation, new product development and spin-offs, cost savings, access to the university's physical facilities and the expertise of its staff, gained technical knowledge, quality improvement, new markets and, manufacturing and lead time reduction.

For technology transfer through collaboration be successful is necessary communication, sharing information, developer-user partnerships and early user involvement, credibility of parties, capacity to transmit and receive information [START_REF] Greiner | Barriers and bridges for successful environmental technology transfer[END_REF].

Methodology

This research was developed in three phases: the literature review, the case study and the information system modeling.

Phase1: the literature review was conducted on collaborative information system and product technology transfer inserted in the areas of inter-organizational networks and management of technology and innovation. The databases used were: Science Direct, Web of Science, Compendex, and Emerald.

Phase 2: the case study was based on seven Brazilian small and medium-sized high-technology firms, according to classification criteria of the European Observatory for SMEs (1995). This research investigated small and medium-sized high-technology firms because they have been considered important to the technological and economic development of countries worldwide, as well as the revitalization of outlying regions [START_REF] Heydebreck | Innovation support for new technology-based firms: the Swedish teknopol approach[END_REF], [START_REF] Fontes | Contribution of new technology-based firms to the strengthening of technological capabilities in intermediate economies[END_REF], [START_REF] Grinstein | Characterizing the technology firm: an exploratory study[END_REF].

Semi-structured interview with Research and Development managers was used as an instrument of data collection. E-mail communication was also used to clarify doubts and supplement the model. The interview script aimed to understand the characteristics of the firms and the information system used to support the collaboration and the product technology transfer. Some of questions were: 1-which markets does the firm serve? 2-how many products were launched in the last five years? 3-what are the goals of the system? 4-Which are the important requirements regarding functional and non-functional requirements?. This paper is part of a larger research that was conducted between August 2011 and September 2012.

The case study allowed us to understand the information system used by them and also identify the requirements that the system should have. Furthermore, opportunities for information system improvements were identified. These improvements came from literature review. This phase helps to develop the proposed model.

Phase 3: the information system requirements modeling was based on the EKD (Enterprise Knowledge Development) methodology. In this phase, the data of the firms and the literature review contributed to the development of the proposed model. For this, the data was arranged in a table allowing identifying information presented by firms and that have not been referenced in literature. The opposite also occurred.

EKD provides a systematic and controlled way of analyzing, understanding, developing and documenting an enterprise and its components, by using Enterprise Modeling [START_REF] Bubenko | EKD user guide[END_REF], facilitates learning and organizational communication, develops a structured description of the business for analysts to discuss, determines the objectives and requirements of the systems, and produces a document called a knowledge repository which can be used to reason about the business, to discuss changes and components of the information system and, to trace the decisions [START_REF] Bubenko | EKD user guide[END_REF].

Proposal of Technical Components and Requirements Model

The Technical Components and Requirements Model presents properties that should compose a future information system and clarify the potential of the information technology to improve business process. According to [START_REF] Bubenko | EKD user guide[END_REF], the components of this model consist of the information system goals (measurable or non-measurable properties, focus, views, or directions); functional requirement (functional property information system) and non-functional requirement (political constraints, operations, information security etc.). Figure 1 shows the technical components and requirements model which guides the product technology transfer.

The information system plans and controls the project development (Information System -IS Goal 1.4), improves communication (IS Goal 2), supports management decisions (IS Goal 3), acquires information (IS Goal 4), exchanges information (IS Goal 5), keeps people updated on the project (IS Goal 6), provides information to the customer (IS Goal 7), manages data and information (IS Goal 8), manages production (IS Goal 9), accelerates the information identification (IS Goal 10), develops collaborative platform (IS Goal 11), ensures communication among the teams (IS Goal 12), and manages project portfolio (IS Goal 1) in terms of managing time (IS Goal 1.1), and human (IS Goal 1.3) and financial resources (IS Goal 1.2).

To manage the project portfolio (IS Goal 1), the system should enable visual management (IS Functional Requirement 5), send e-mail notification (IS Functional Requirement 3), allow the use of different project management methods (IS Functional Requirement 4), enable documentation of system functionality (IS Functional Requirement 6), and generate indicators (IS Functional Requirement 1) which support project progress evaluation (IS Functional Requirement SI 2).

To manage time (IS Goal 1.1), human (IS Goal 1.3) and financial resources (IS Goal 1.2), the system should generate reports in pdf (IS Functional Requirement 11).

To plan and control the project development (IS Goal 1.4), the system should control the deadlines (IS Functional Requirement 7), register tasks (IS Functional Requirement 8), re-plan the deadlines (IS Functional Requirement 9), enable project progress evaluation (IS Functional Requirement 10), and keep people updated on the project (IS Goal 6).

Fig. 1. Technical components and requirements model

Keep people updated on the project

IS Goal 6

Plan and control the project development

IS Goal 1.4

Provide information to the customer

IS Goal 7

Manage data and information

IS Goal 8

Manage project portfolio

IS Goal 1

Manage time

IS Goal 1.1

Manage financial resource

IS Goal 1.2

Manage human reource

IS Goal 1.3

Exchange information

IS Goal 5

Manage production

IS Goal 9

Be webbased

IS Freq 22

Improve communication

IS Goal 2

Send e-mail notifications

IS FReq 3

Acquire information

IS Goal 4

Support management decisions

IS Goal 3

Generate reports in pdf

IS FReq 11

Generate indicators

IS FReq 1

Integrate different areas

IS FReq 13

Store different files

IS FReq 20

Store documented projects

IS FReq 15

Store customer information

IS FReq 12

Store suppliers information

IS FReq 14

Accelerate the identification of information

IS Goal 10

Ensure data security

IS NFReq 1

Enable access control

Req F SI 19

Develop collaborative platform

IS Goal 11

Enable documentation of system funcionality

IS FReq 6

Ensure communication among the teams

IS Goal 12

Enable visual management

IS FReq 5

Enable evaluation of project progress

IS FReq 10

To allow consultation

IS FReq 17

Accelerate the search for documents

IS FReq 16

Allow multiusers

IS FReq 21

Re-plan the deadlines

IS FReq 9

Register task

IS FReq 8

Control the deadlines

IS Freq 7

Evaluate project progress

IS FReq 2

Modern and intuitive interface

IS Freq 18

Enable a virtual environment

IS Freq 23

Provide documents

IS FReq 25

Provide manuals To improve communication (IS Goal 2), the system should send e-mail notification (IS Functional Requirement 3) and have a modern and intuitive interface (IS Functional Requirement 18).

IS
To support management decisions (IS Goal 3), the system should generate reports in pdf, (IS Functional Requirement 11), generate indicators (IS Functional Requirement SI 1), and accelerate the information identification (IS Goal 10).

To acquire information (Is Goal 4) the system must have a modern and intuitive interface (IS Functional Requirement 18) which allows multi-users (IS Functional Requirement 21) and performs consultation (IS Functional Requirement 17).

To exchange information (IS Goal 5), the system should store different files (IS Functional Requirement 20), the tool should be synchronous and asynchronous (IS Functional Requirement 32), allow sharing documents and files (IS Functional Requirement 33), have flexibility (IS Functional Requirement 28), send e-mail notification (IS Functional Requirement 3), and allow multi-users (IS Functional Requirement 21).

To allow multi-users (IS Functional Requirement 21), the system should be webbased (IS Functional Requirement 22) providing a virtual environment (IS Functional Requirement 23), blogs, forums and wikis (IS Functional Requirement 27), and should ensure data security (IS Non-Functional Requirement 1).

To ensure data security (IS Non-Functional Requirement 1), the system should enable access control (IS Functional Requirement 19), protect those involved in the collaboration (IS Functional Requirement 31), documents should be protected before, during and after transmission (IS Functional Requirement 30). Furthermore, the system should ensure fast response time (IS Non-Functional Requirement 2), reliable information (IS Non-Functional Requirement 4), be user-friendly (IS Non-Functional Requirement 3), and easy to learn (IS Non-Functional Requirement 5).

To keep people updated on the project (IS Goal 6), the system should send e-mail notification (IS Functional Requirement 3) and allow multi-users (IS Functional Requirement 21).

To provide information to the customer (IS Goal 7), the system should be webbased (IS Functional Requirement 22), provide documents (IS Functional Requirement 25) and manuals (IS Functional Requirement 4).

To manage data and information (IS Goal 8), the system should store suppliers information (IS Functional Requirement 14), store documented reports-projects (IS Functional Requirement 15), store customer information (IS Functional Requirement 12), and integrate different areas (IS Functional Requirement 13).

To manage production (IS Goal 9), it is necessary to integrate different areas (IS Functional Requirement 13) and generate reports in pdf (IS Functional Requirement 11).

To accelerate the information identification (IS Goal 10), the system should expedite document search (IS Functional Requirement 16).

To develop a collaborative platform (IS Goal 11), the system should be web-based (IS Functional Requirement 22), allow multi-users (IS Functional Requirement 21), and allow collaboration through intranet (IS Functional Requirement 29).

To ensure communication among the teams members, the system should be web-based (IS Functional Requirement 22), allow multi-users (IS Functional Requirement 21), and be synchronous and asynchronous tools (IS Functional Requirement 32).

Conclusions and Future Research

Technology and innovation have been considered essential factors for the competitiveness of the most Organizations. In this way, the firms are under pressure to have the capacity to develop new technologies with lower cost and time-to-market. However, developing all skills and know-how to generate an innovation is increasingly difficult since the technologies change rapidly and firms often do not have the right person at the right time. Therefore, technology transfer is essential, mainly for SMEs, since they have limited resources and managerial competences. Furthermore, these firms tend to use external networks to leverage their resources.

Considering such scenario, managing information and knowledge, as well as interaction and communication are important factors for the success of the technology transfer and collaboration. One way to be efficient and effective at these points is using an appropriate information system. Based on this along with the needs of business research and literature, the paper presented the technical components and requirements model to support developing a collaborative environment and assist the collaboration and product technology transfer. Consequently, this paper contributes to improve the collaborative project management. The proposed model presented part of the reality and organizational need with regard to the requirement of a collaborative information system to manage the transfer of technology. Furthermore, the model considers practices recommended in the literature. The next step suggested by this research is that future researches develop and test the information system based on the model proposed in such a manner that the system can help firms use information and knowledge as strategic resources to create innovations and improve competitiveness.