| title | output | bibliography | ||||
|---|---|---|---|---|---|---|
A review of Open Science and Computational Ecology |
|
Biblio.bib |
1.Ecologistslack a culture of data sharing [@Wilson2017; @Mislan2016; @Marina2018]
2.Treat data as an enduring product of research
3.Basicaly to address large-scale questions
1.Organize, document, and preserve data for posterity
2.Share data @Marina2018
3.Collaborate with networks of colleagues to bring together heterogeneous datasets to address larger scale questions 4.Address data management issues with students and peers
- Ecology can make critical contributions to large-scale environmental questions and close many knowledge gaps that are likely to persist in big-science initiatives, but only if ecologists are willing to participate in the big-data landscape
Como dice Carly Strasser :
Scientists who are cautious about open science can start small by sharing data for a project that they have already completed. Specialists in the field offer this advice:
-
Document a data-deposition plan while working on publications, so that the data and the paper will be ready for publication at the same time. It is not necessary, however, to release data alongside a paper, unless a funder mandates it.
-
Craft a very explicit statement about data reuse — including who can use the data, how to use them and how to attribute them.
-
Machine-readable data will be most easily combined with other data sets. Avoid proprietary data formats, such as Microsoft spreadsheets, or colour-coded cells that are readable only by humans.
-
Permanently archive data in reputable repositories such as FigShare or Zenodo, not on a personal website.
-
If you choose to share data from a new project, make sure to generate the relevant metadata as you go. It is very hard to reconstruct important details after the fact. Tools such as those on Zenodo enable researchers to document such details throughout a project, so that all you have to do is flip a switch when you are ready to share.
GEWIN, Virginia. Data sharing: An open mind on open data. Nature, 2016, vol. 529, no 7584, p. 117-119.
An old joke says that doing the research is the first 90% of any project; writing up is the other 90%
##Results
###Responses to Data Requests
Total 49 corresponding authors:
*21 had shared some data with Wicherts et al.
*13 corresponding authors failed to respond to the request or any of the two reminders.
*3 corresponding authors refused to share data either because the data were lost or because they lacked time to retrieve the data and write a codebook.
* 12 corresponding authors promised to share data at a later date, but have not done so in the
past six years (we did not follow up on it).
These authors commonly indicated that the data were not readily available or that they first needed to write a codebook
##Otro ejemplo
Chen H, Gurmesa GA, Zhang W, Zhu X, Zheng M, Mao Q, Zhang T, Mo J (2016)
La hipótesis de saturación de nitrógeno (N) sugiere que cuando un ecosistema alcanza la saturación de N, la entrada continua de N provocará una mayor lixiviación de N, emisión de óxido nitroso (N2O) y tasas de mineralización y nitrificación de N. También sugiere que un elemento diferente se convertirá en el principal factor limitante cuando se haya alcanzado la saturación de N. Aunque esta hipótesis ha sido probada en bosques templados, aún no se ha abordado si se pueden aplicar directamente a los bosques tropicales saturados de nitrógeno. Para probar esta hipótesis, el N inorgánico del suelo, la mineralización del N del suelo y la tasa de nitrificación, la tasa de emisión de N2O del suelo y la tasa de lixiviación del nitrato (imagen en línea) se midieron en un bosque tropical saturado de N en el sur de China...
Equivalente a mandar todo a la licuadora. No?