Data architecture

Mirror legacy data architectures within new system/database(s). 

Data Architecture with details of the sources, uses, and ownership of each static data item System landscape showing the interactions of the various instances of the application Interfaces with diagrams (including networks, systems, and analytical equipment)... 

The information management system can be visualized as the environment that allows expression of concurrent processes and their actualization. While process expression requires relevant domain-specific languages (DSLs) their actualization requires three basic blocks data architecture (domain), distributed management firamework (operating system), and software services (domain-specific processor). 

A system framework for conducting SE is based on a complex architecture, since it is in turn a system of systems. Therefore, elaborating them requires the consideration of Autonomy, Complexify, Diversify, Integration strategy. Data architecture and System protection [62]. Among other critical factors, robustness and alignment to business processes and technology are to be taken into account. 

The data architecture including the plication, stem and enterprise data architectures as the same data may be used (and re-used) by several systems within the systems hierarchy. Each stem may interpret this data and attribute to it subtly different meanings ... 

Within the stem hierarchy data may be shared by many sterns. The stem level safety arguments should address the System Architecture and in particular the data architecture at the level of the Enterprise, System, and Application. These system level safety arguments should identify any data management and data verification tools. In particular the system level safety arguments should address the planning and implementation of data validation. In addition the system level safety arguments should address verification at the tystem boundary. 

Safety arguments for data provision should address the data origination, the tools used in the data supply chain and in the creation of the dataset. The use of a data supply chain requires that changes to the data architecture are rolled out across the data supply chain, the tools it employs and the criteria used to verify the data. 

The selection and identification of the system boundary is a key feature of the safety analysis. This safety analysis may used demonstrate that elements of the system attract high integrity requirements. A reformulation of the system design and its system architecture may yield elements of the system that attract lesser integrity requirements. This process of analysis and reformulation is also applicable to the data architecture and its constituent parts. The formulation of the system data architectures (enterprise, system and application) addresses the... 

The Data Architecture activity moves in a similar direct manner, starting with the design and identification of the necessary data and content categories that will support the CRM effort. It proceeds to creating the data sources to be accessed, identifying those responsible for ownership of the data, and instituting a test to determine that the correct information can be effectively accessed. The proper reports and analytical procedures are developed and the data model is finalized and tested under operating conditions. 

Variables can be grouped into a dataset. The goal of the dataset is to group data related to one simulation task and to simplify the handling of values. It is also very important to make data accessible and usable for nonexperts. For each dataset more profiles can be assigned. Each profile represents a particular combination of physical data sources but it must contain exactly the same group of variables as defined in the related dataset. Datasets and profiles create an abstract layer which is built on top of a physical layer. The overview of the data architecture is illustrated in Rg. 10.5. 

Fig. 10.5 Data architecture (not all relations between objects are depicted)...

The architecture of simulations is very similar to the data architecture described in the previous section. As defined in Sect. 10.3, a simulation module can be seen as a black box with an interface. It is an abstract layer in the architecture. The physical layer contains information about implementations of simulation tools interfaces and various configurations. 

Objects that have a similar data architecture and a similar behavior specification are grouped into a class. A class is a structure with a combined specification of the properties of a set of similar objects a class also serves as the bluqirint for the creation of new objects (which may subsequently be modified). 

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