An Interdisciplinary Model for Graphical Representation

Abstract

The paper questions whether data-driven and problem-driven models are sufficient for a software to automatically represent a meaningful graphical representation of scientific findings. The paper presents descriptive and prescriptive case studies to understand the benefits and the shortcomings of existing models that aim to provide graphical representations of data-sets. First, the paper considers data-sets coming from the field of software metrics and shows that existing models can provide the expected outcomes for descriptive scientific studies. Second, the paper presents data-sets coming from the field of human mobility and sustainable development, and shows that a more comprehensive model is needed in the case of prescriptive scientific fields requiring interdisciplinary research. Finally, an interdisciplinary problem-driven model is proposed to guide the software users, and specifically scientists, to produce meaningful graphical representation of research findings. The proposal is indeed based not only on a data-driven and/or problem-driven model but also on the different knowledge domains and scientific aims of the experts, who can provide the information needed for a higher-order structure of the data, supporting the graphical representation output.

Smart-Graph: Graphical Representations for Smart Contract on the Ethereum Blockchain

“…As to what concerns Q2, "Is there a better way to visually represent the smart contracts' source code? ", the paper argued that the novelty of the tool "Smart Graph" is precisely the fact that it allows to visualize additional information, which was not provided by traditional UML class diagrams [38]. Indeed, in "Smart Graph" the user can drill down into a specific function, to look for information specific to the Solidity programming language.…”

“…Based on previous studies on graphical representations in different fields [35], multiple representations of the same smart contract source code have been preferred over the traditional UML class diagram. This technique allows to quickly visualize complex systems and guarantees better readability.…”