Conference paper Open Access

Human-driven Machine-automation of Engineering Research

Millen, Maxim; Viana da Fonseca, António; Romão, Xavier


Citation Style Language JSON Export

{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.3465443", 
  "title": "Human-driven Machine-automation of Engineering Research", 
  "issued": {
    "date-parts": [
      [
        2018, 
        6, 
        25
      ]
    ]
  }, 
  "abstract": "<p>This paper presents a framework for efficiently producing engineering research in a global collaborative<br>\neffort in a rigorous scientific manner. The proposed framework reduces subjective analysis, automates<br>\nseveral mundane research tasks and provides a suitable formal structure for efficient information sharing and collaboration. The implementation of the framework involves multiple research groups setting up different web-servers that can perform the steps of the scientific method and automatically determine the quality and value of new research by directly communicating between servers via public and private application programming interfaces (APIs) using a set of object-oriented protocols. The automation of many mundane research tasks (e.g. data manipulation), would allow researchers to focus more on the novel aspects of their research efforts. The increased clarity around the quality and value of research would allow the research efforts of individuals and available research funding to be better disbursed. The paper discusses the major aspects of the scientific method, object-orientated programming, the application of the proposed research framework for experimental/analytical/numerical engineering research, some of the potential benefits and drawbacks, as well as the current state of implementation.</p>", 
  "author": [
    {
      "family": "Millen, Maxim"
    }, 
    {
      "family": "Viana da Fonseca, Ant\u00f3nio"
    }, 
    {
      "family": "Rom\u00e3o, Xavier"
    }
  ], 
  "type": "paper-conference", 
  "id": "3465443"
}
5
5
views
downloads
All versions This version
Views 55
Downloads 55
Data volume 2.9 MB2.9 MB
Unique views 44
Unique downloads 55

Share

Cite as