Title
The Ten Adoption Drivers of Open Source Software That Enables e-Research in Data Factories for Open Innovations
Files
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Description
"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
Recommended Citation
Kee K.F. (2017). The ten adoption drivers of open source software that enables e-research in data factories for open innovations. In S. Matei, N. Jullien, & S. Goggins (Eds.), Big data factories. Cham: Springer. https://doi.org/10.1007/978-3-319-59186-5_5
Copyright
Springer
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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