Models and their Foundational Framework

The term model is mainly used in two meanings which are considered to be different: a model of a problem domain as a conceptualisation; a model of a set of formulas as an interpretation in which every formula within this set is true. A general theory of models has not yet been developed. H. Stachowiak proposes a phenomenal approach and ‘defines’ models by their properties of mapping, truncation and pragmatics. Meanwhile, a notion of the model has been developed. At the same time, it seems that there are rather different understandings of model in sciences and especially Mathematical Logics. Sciences treat models as reflections of origins. Mathematical logics considers models as an instantiation in which a set of statements is valid. So, mathematical model theory is often considered to be a completely different approach to modelling. We realise however that mathematical model theory is only a specific kind of modelling. We show that the treatment of models in logics and in sciences can be embedded into a more general framework. So, the theory of models is based on a separation of concern or orientation

Basic Taxonomic Structures and Levels of Abstraction

Taxonomic knowledge structures are often used to organize information. We compare basic taxonomic structures in four areas: thesaurus construction in information retrieval, semantic data models in database management systems, semantic networks in artificial intelligence, and mental structures in cognitive psychology. We then discuss levels of abstraction, in panicular the importance of intermediate levels. In mental structures these turn out to be basic levels that are more important cognitively than higher or lower levels. We explore the role of abstraction levels in other taxonomic structures and suggest possible future research in this area

On the evolution of conceptual modeling

Since the 1980s the need increased for overcoming idiosyncrasies of approaches to modeling in the various sub-disciplines of computing. The theoretical model of evolution is used in this paper for analyzing how computing and conceptual modeling have changed. It is concluded that computing has changed into a social phenomenon with a technical core and that therefore relying on (formal) model semantics as the sole tool for the discussion of conceptual modeling is no more adequate. A number of language games of computing is identified and the task set to describe these language games to the extent necessary for deciding whether or not they can serve as the foundation of computing

Towards a Shared, Conceptual Model-Based Understanding of Proteins and Their Interactions

[EN] Understanding the human genome is a big research challenge. The huge complexity and amount of genome data require extremely effective and efficient data management policies. A first crucial point is to obtain a shared understanding of the domain, which becomes a very hard task considering the number of different genome data sources. To make things more complicated, those data sources deal with different parts of genome-based information: we not only need to understand them well, but also to integrate and intercommunicate all the relevant information. The protein perspective is a good example: rich, well-known repositories such as UniProt provide a lot of valuable information that it is not easy to interpret and manage when we want to generate useful results. Proteomes and basic information, protein-protein interaction, protein structure, protein processing events, protein function, etc. provide a lot of information is that needs to be conceptually characterized and delimited. To facilitate the essential common understanding of the domain, this paper uses the case of proteins to analyze the data provided by Uniprot in order to make a sound conceptualization work for identifying the relevant domain concepts. A conceptual model of proteins is the result of this conceptualization process, explained in detail in this work. This holistic conceptual model of proteins presented in this paper is the result of achieving a precise ontological commitment. It establishes concepts and their relationships that are significant in order to have a solid basis to efficiently manage relevant genome data related to proteins.This work was supported in part by the Spanish State Research Agency under Grant TIN2016-80811-P, and in part by the Generalidad Valenciana under Grant PROMETEO/2018/176, co-financed with ERDF.León-Palacio, A.; Pastor López, O. (2021). Towards a Shared, Conceptual Model-Based Understanding of Proteins and Their Interactions. IEEE Access. 9:73608-73623. https://doi.org/10.1109/ACCESS.2021.3080040S7360873623

A review of Smart Contract Blockchain Based on Multi-Criteria Analysis: Challenges and Motivations

A smart contract is a digital program of transaction protocol (rules of contract) based on the consensus architecture of blockchain. Smart contracts with Blockchain are modern technologies that have gained enormous attention in scientific and practical applications. A smart contract is the central aspect of a blockchain that facilitates blockchain as a platform outside the cryptocurrency spectrum. The development of blockchain technology, with a focus on smart contracts, has advanced significantly in recent years. However research on the smart contract idea has weaknesses in the implementation sectors based on a decentralized network that shares an identical state. This paper extensively reviews smart contracts based on multi criteria analysis challenges and motivations. Therefore, implementing blockchain in multi-criteria research is required to increase the efficiency of interaction between users via supporting information exchange with high trust. Implementing blockchain in the multi-criteria analysis is necessary to increase the efficiency of interaction between users via supporting information exchange and with high confidence, detecting malfunctioning, helping users with performance issues, reaching a consensus, deploying distributed solutions and allocating plans, tasks and joint missions. The smart contract with decision-making performance, planning and execution improves the implementation based on efficiency, sustainability and management. Furthermore the uncertainty and supply chain performance lead to improved users confidence in offering new solutions in exchange for problems in smart contacts. Evaluation includes code analysis and performance while development performance can be under development.Comment: Revie

Relationship analysis : improving the systems analysis process

A significant aspect of systems analysis involves discovering and representing entities and their inter-relationships. Guidelines exist to identify entities but do not provide a rigorous and comprehensive process to explicitly capture the relationship structure of the problem domain. Whereas, other analysis techniques lightly address the relationship discovery process, Relationship Analysis is the only systematic, domain-independent analysis technique focusing exclusively on a domain\u27s relationship structure. The quality of design artifacts, such as class diagrams, and development time necessary to generate these artifacts can be improved by first representing the complete relationship structure of the problem domain. The Relationship Analysis Model is the first theory-based taxonomy to classify relationships. A rigorous evaluation was conducted, including a formal experiment comparing novice and experienced analysts with and without Relationship Analysis. It was shown that the Relationship Analysis Process based on the model does provide a fuller and richer systems analysis, resulting in improved quality of and reduced time in generating class diagrams. It also was shown that Relationship Analysis enables analysts of varying experience levels to achieve a similar level of quality of class diagrams. Relationship Analysis significantly enhances the systems analyst\u27s effectiveness, especially in the area of relationship discovery and documentation resulting in improved analysis and design artifacts

Developing an Evaluation Framework for Blockchain in the Public Sector : The Example of the German Asylum Process

The public sector presents several promising applications for blockchain technology. Global organizations and innovative ministries in countries such as Dubai, Sweden, Finland, the Netherlands, and Germany have recognized these potentials and have initiated projects to evaluate the adoption of blockchain technology. As these projects can have a far-reaching impact on crucial government services and processes, they should involve a particularly thorough evaluation. In this paper, we provide insights into the development of a framework to support such an evaluation for the German asylum process. We built this framework evolutionarily together with the Federal Office for Migration and Refugees. Its final version consists of three levels and eighteen categories of evaluation criteria across the technical, functional and legal domains and allows specifying use-case specific key performance indicators or knockout criteria