For engineering service-oriented enterprises in the era of cloud computing
could EA notations be a lingua franca ?

Several developments, such as the success of cloud-computing show that not the ownership of IT resources but their management is the foundation for sustainable competitive advantage[1]. According to Ross et al. [2], smart companies define how they (will) do business (using an operating model) and design the processes and infrastructure critical to their current and future operations (using an enterprise architecture).

Enterprise Engineering (EE) is the application of engineering principles to the design of Enterprise Architectures (EA). It allows deriving the EA from the enterprise goals and strategy and aligning it with the enterprise resources as shown in Figure 1, EA aims (i) to understand the interactions and all kind of articulations between business and information technology, (ii) to define how to align business components and IT components, as well as business strategy and IT strategy, and more particularly (iii) to develop and support a common understanding and sharing of those purposes of interest. Enterprise architecture is used to map the enterprise goal and strategy to the enterprise’s resources (actors, assets, IT supports) and to take into account the evolution of this mapping. It also provides documentation on the assignment of enterprise resources to the enterprise goals and strategy.

There are different paradigms for creating enterprise architecture. The most important is to encapsulate the functionalities of IT resources as services, as shown in Figure 2. By this means, it is possible to clearly describe the contributions of IT both in terms of functionality and quality and to define a service-oriented enterprise architecture (SoEA). SoEA easily integrates wide-spread technological approaches such as SOA or emerging ones as cloud computing because they also use service as structuring and governing paradigm. The enterprise goals and strategies are mapped to a SoEA, as shown in Figure 1.

SoEA differentiates four layers of services, as shown in Figure 2. Thus, its scope is much broader than the scope of SOA and also includes services not accessible through software such as business and infrastructure services. Services of different layers may be interconnected in service (value) nets to provide higher level services.

1. Business services are services, which directly support business processes. Business processes can also be developed dynamically (on-the-fly) using business services which are available in a repository for a given business domain. An example is call-centre services provided by an external service provider.
2. Software services exist as two types: (i) human-oriented applications, which are provided as Software as a Service, (ii) application services which are part of so-called SOA [3] that are a popular paradigm for creating enterprise software.
3. Platform Services provide support of the development of applications. They provide services for the execution of applications, middleware stacks, web servers etc.
4. Infrastructure services are more hardware-flavoured services, which are provided using computers. They may have a human addressee but contain many infrastructure services such as providing computing power, storage etc. They are an important topic in management and practice collections such as ITILV3 [4] or standards such as ISO/IEC 20000 have gained a high popularity.

Today, foundations of social computing influence enterprise architecture in new ways. Hierarchical and top-down organizational structures are more and more replaced by egalitarian and bottom-up organizational structures. The senior management defines organizational structures no longer alone, but weak ties that are initiated by individuals superimpose the organization. Innovation is no longer a process guided by an elite, but can be initiated by every member of an organization. Decision are no longer made by experts but are results of collaborative processes. In addition, Big Data technology allows to process data with higher velocity, variety and volume. Batch-oriented analysis - as the ETL schema of classical data warehouses - is replaced by stream processing and the (near-) real-time detection of events. Big Data allows the creation of new information flows within enterprise architectures enabled by a number of technological advancements. However this requires integrating data services into enterprise architecture.