The Ten Adoption Drivers of Open Source Software That Enables e-Research in Data Factories for Open Innovations

The Ten Adoption Drivers of Open Source Software That Enables e-Research in Data Factories for Open Innovations

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"The purpose of this chapter is to explore what drives the adoption and diffusion of open source software that can usher in the vision of data factories. With the adoption of good software applications across the community, researchers can begin moving individual data sets developed by independent projects across geographic locations and disciplinary domains into a broader data ecosystem sustainable over the long term. The data ecosystem should also be easily accessible and used by present and future researchers not directly involved with data collection and documentation of the individual data sets."

ISBN

9783319591858

Publication Date

2017

Publisher

Springer

City

Cham, Switzerland

Disciplines

Databases and Information Systems | Software Engineering | Systems Architecture

Comments

In Sorin Adam Matei, Nicolas Jullien, and Sean P. Goggins (Eds.), Big Data Factories. Dr. Kee's chapter begins on page 51.

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Springer

The Ten Adoption Drivers of Open Source Software That Enables e-Research in Data Factories for Open Innovations

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