Idea farming: it is a good idea to have bad ideas in science
- Published
- Accepted
- Subject Areas
- Ecology, Human-Computer Interaction, Data Science
- Keywords
- open science, ideas, idea provenance, ecology, replication science, scientific outcomes, workflows
- Copyright
- © 2017 Lortie
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2017. Idea farming: it is a good idea to have bad ideas in science. PeerJ Preprints 5:e3282v2 https://doi.org/10.7287/peerj.preprints.3282v2
Abstract
There are few truly bad ideas in authentic science. We need to embrace science as a process- driven human endeavour to better understand the world around us. Products are important, but through better transparency, we can leverage ideas, good and bad, ours and others, to do better science. In a brief analysis here inspired by a recent discussion of the topic and previous introspections by other ecologists, it is proposed that whilst it is a good idea to track ideas and all the processes that generate outcomes such as publications, there is inherent merit in all scientific ideas. That said, organizing and framing our ideas into the networks that we already use to examine hypotheses and questions in science is a window into our workflows including ideation, implementation, data analyses, and how we can better map ideas into open science outcomes. Formalizing and describing the linkages between ideas, data, and projects we produce as scientists will enhance and diversify the value of the work we do individually and collectively.
Author Comment
Used the 'rticles' packages for R to knit to a better format using LaTex.