Human-driven machine-automation of engineering research

• Type: Article in International Conference Proceedings Book
• Date: 2018

Authors

Millen, MDL (Author) Other; Viana Da Fonseca, A (Author) Other; Xavier Romão (Author) FEUP

Conference proceedings International

Title: Numerical Methods in Geotechnical Engineering IX: Proceedings of the 9th European Conference on Numerical Methods in Geotechnical Engineering (NUMGE 2018), June 25-27, 2018, Porto, Portugal

Pages: 719-727

9th European Conference on Numerical Methods in Geotechnical Engineering (NUMGE 2018)

Porto, FEUP, June 2018

Indexing

Scopus - 0 Citations

Other information

Authenticus ID: P-011-Q77

DOI: 10.1201/9781351003629-90

Abstract (EN): This paper presents a framework for efficiently producing engineering research in a global collaborative effort in a rigorous scientific manner. The proposed framework reduces subjective analysis, automates several 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. © 2018 Taylor & Francis Group, London.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8