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OpenML: An R Package to Connect to the Machine Learning Platform OpenML
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CC BY-NC-ND
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OpenML is an online machine learning platform where researchers can easily share data, machine learning tasks and experiments as well as organize them online to work and collaborate more efficiently. In this paper, we present an R package to interface with the OpenML platform and illustrate its usage in combination with the machine learning R package mlr (Bischl et al, 2016). We show how the OpenML package allows R users to easily search, download and upload data sets and machine learning tasks. Furthermore, we also show how to upload results of experiments, share them with others and download results from other users. Beyond ensuring reproducibility of results, the OpenML platform automates much of the drudge work, speeds up research, facilitates collaboration and increases the users’ visibility online.

Subject:
Social Science
Material Type:
Reading
Author:
Benjamin Hofner
Bernd Bischl
Dominik Kirchhoff
Heidi Seibold
Jakob Bossek
Joaquin Vanschoren
Michel Lang
Pascal Kerschke
Giuseppe Casalicchio
Date Added:
11/13/2020
Open Science in Software Engineering
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CC BY-NC-ND
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Open science describes the movement of making any research artefact available to the public and includes, but is not limited to, open access, open data, and open source. While open science is becoming generally accepted as a norm in other scientific disciplines, in software engineering, we are still strugglingin adapting open science to the particularities of our discipline, rendering progress in our scientific community cumbersome. In this chapter, we reflect upon the essentials in open science for software engineering including what open science is, why we should engage in it, and how we should do it. We particularly draw from our experiences made as conference chairs implementing open science initiatives and as researchers actively engaging in open science to critically discuss challenges and pitfalls, and to address more advanced topics such as how and under which conditions to share preprints, what infrastructure and licence model to cover, or how do it within the limitations of different reviewing models, such as double-blind reviewing. Our hope is to help establishing a common ground and to contribute to make open science a norm also in software engineering.

Subject:
Applied Science
Engineering
Social Science
Material Type:
Reading
Author:
Daniel Graziotin
Heidi Seibold
Stefan Wagner
Daniel Mendez
Date Added:
11/13/2020