Scientific Community-Driven Ecosystem as a Supporter to Co-Create and Co-Evolute Science

Scientific Community-Driven Ecosystem as a Supporter to Co-Create and Co-Evolute Science

Helio Aisenberg Ferenhof, Marcos Paulo Alves de Sousa
Copyright: © 2022 |Pages: 14
DOI: 10.4018/978-1-7998-4843-1.ch003
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Abstract

One critical aspect of science is the ability to reproduce the same experiment by another researcher. In other to do so, the same ambient, variables, data, setup should be considered. The method tells how the original researcher planned and did their research, but how can others replicate or even advance the preview research? The scientific community has been focusing on efforts to increase transparency and reproducibility and develop a “culture of reproducibility.” When researchers share their data, their workflow, and co-evolute a way of doing research, all the players win. The value co-creation is established in a business ecosystem. The actor who is part of the business platform by the co-creation can leverage the advantage of one or more partners that make up the platform. Thus, the knowledge created from the interaction between the different technological domains and knowledge shared on the platform can improve all the research and researchers. Stating that, this chapter proposes a business ecosystem model to ensure research repeatability.
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Introduction

This chapter promotes the use of a business ecosystem to co-create and co-evolute science. According to Ziouvelou and McGroarty (2017, p. 1), “business success in this complex and constantly evolving system is determined by the ecosystem’s ability to bring together a variety of strategic business elements in order to jointly co-created shared value”. One critical aspect of science is the ability to reproduce the same experiment by another researcher. In order to do so, the same ambient, variables, data, setup should be considered. The method tells how the original researcher plan and did their research, but how can others have the same environment to check the consistency, replicate, or even advance the preview research? In computer science is not different; the same issues appear; how can other researchers repeat the experiment? Think, many different variables are not considered when describing the methodology, which should be — hardware, Software, Operational System, Database, Indexes, among others. So, the ability to reproduce the results of other researchers is a core tenet of the scientific method, and computational science has driven scientific development in many knowledge areas (Peng, 2011).

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