Information schema constructs for defining warehouse databases of genotypes and phenotypes of system manifestation features

Our long-term objective is to develop a software toolbox for pre-embodiment design of complex and heterogeneous systems, such as cyber-physical systems. The novelty of this toolbox is that it uses system manifestation features(SMFs) for transdisciplinary modeling of these systems. The main challenges of implementation of the toolbox are functional design- and language-independent computational realization of the warehouses, and systematic development and management of the various evolving implements of SMFs(genotypes, phenotypes, and instances). Therefore, an information schema construct(ISC) based approach is proposed to create the schemata of the associated warehouse databases and the above-mentioned SMF implements. ISCs logically arrange the data contents of SMFs in a set of relational tables of varying semantics. In this article we present the ISCs necessary for creation of genotypes and phenotypes. They increase the efficiency of the database development process and make the data relationships transparent. Our follow-up research focuses on the elaboration of the SMF instances based system modeling methodology.

Information schema constructs for instantiation and composition of system manifestation features

Complementing our previous publications, this paper presents the information schema constructs （ISCs） that underpin the programming of specific system manifestation feature （SMF） orientated information management and composing system models. First, we briefly present （1） the general process of pre-embodiment design with SMFs, （2） the procedures of creating genotypes and phenotypes of SMFs, （3） the specific procedure of instantiation of phenotypes of SMFs, and （4） the procedure of system model management and processing. Then, the chunks of information needed for instantiation of phenotypes of SMFs are discussed, and the ISCs designed for instantiation presented. Afterwards, the information management aspects of system modeling are addressed. Methodologically, system modeling involves （1） placement of phenotypes of SMF in the modeling space, （2） combining them towards the desired architecture and operation, （3） assigning values to the parameters and checking the satisfac- tion of constraints, and （4） storing the system model in the SMFs-based warehouse database. The final objective of the reported research is to develop an SMFs-based toolbox to support modeling of cyber-physical systems （CPSs）.