Data Science as a New Frontier for Design
March 20, 2015 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Akin Osman, KazakΓ§i Mines
arXiv ID
1503.06201
Category
cs.AI: Artificial Intelligence
Cross-listed
stat.OT
Citations
9
Venue
arXiv.org
Last Checked
4 months ago
Abstract
The purpose of this paper is to contribute to the challenge of transferring know-how, theories and methods from design research to the design processes in information science and technologies. More specifically, we shall consider a domain, namely data-science, that is becoming rapidly a globally invested research and development axis with strong imperatives for innovation given the data deluge we are currently facing. We argue that, in order to rise to the data-related challenges that the society is facing, data-science initiatives should ensure a renewal of traditional research methodologies that are still largely based on trial-error processes depending on the talent and insights of a single (or a restricted group of) researchers. It is our claim that design theories and methods can provide, at least to some extent, the much-needed framework. We will use a worldwide data-science challenge organized to study a technical problem in physics, namely the detection of Higgs boson, as a use case to demonstrate some of the ways in which design theory and methods can help in analyzing and shaping the innovation dynamics in such projects.
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