[open-science] Let us denonce the pseudo-open Public Library of Science

[Tom Moritz]

There are many points worthy of comment here!

First -- to take up Heathers original challenge -- in our experience
advocating for a "biodiversity commons" (more than fifteeen years ago!) we
had noble intentions for global sharing of biodiversity data worldwide. We
had members of our core group (subscribing to our principles) including the
Nature Conservancy, Conservation International, UNEP/WCMC, IUCN, Birdlife
International, etc BUT , in practice, these big orgs found it very, very
difficult to disclose/ release their data and information "assets" openly /
freely.
As always, personal and organizational protective reflexes often defeated
intention ( much more could be said!)

PLOS has (absolutely!) made important contributions providing exemplary
leadership....
BUT... yes, more can/ should be done...
Many important scientific orgs are failing to open their data and
information -- and today there is an urgent need for openness. The PLOS
model should be open and readily available for application by others...

Second, "open data" per se is not a solution to "replication" but open
standards for description of scientific workflow (a subset of "open data"?)
are... And there are open source models for such apps

Replication is one **method** in the process of science as "organized
skepticism" (Karl Popper)
And is intended to move us toward establishing the goal of **invariant**
and **objective**
Scientific knowledge...

Hope these comments are useful?

Tom
On Tue, Feb 14, 2017 at 7:34 AM Thomas Kluyver <takowl at gmail.com> wrote:

> On 14 February 2017 at 14:58, Paola Di Maio <paola.dimaio at gmail.com>
> wrote:
>
> 1. Does open data facilitate replicability? I argue that it does not. At
> most, open data permits repeat analysis of the same data. This is a good
> thing, but it is not replication. To replicate a study, one must repeat the
> study, sometimes with variations to eliminate limitations of prior studies,
> gather new data.
>
>
> to replicate a study, one must repeate the study -
>
> assuming that by 'study' you mean the application of a methodology
>
>
>  but to replicate the result of a study, one needs the  exact data that
> the study has used. what about if I get different results from the same
> study (method)?  what would that imply?
>
>
> To me, the key here is that a lot of modern science hinges on how you
> analyse the data. A classic experiment like the candle in a jar pulling up
> water has a clear result which doesn't require much analysis. But modern
> research often involves trying to determine whether a pattern or difference
> in some numbers represents a real phenomenon or just random chance. Things
> like confounding correlated factors, multiple tests and so forth can make a
> big difference. When more of the steps involve slicing and dicing numbers
> after the experiment itself, replication of the method to get from raw data
> to conclusions becomes more important.
>
> The polling for the US election is a good example of this. Almost all
> pollsters predicted a Clinton win, with varying degrees of confidence. We
> know how that turned out. I don't believe they were fabricating the raw
> poll results, but their segmentation and 'likely voter' adjustments weren't
> quite right. I've no idea if they release the raw data from that, and there
> may be issues with personal identifiability, but it would be interesting to
> reproduce their headline results and do some sensitivity analysis to see
> what assumptions might have been incorrect.
>
> We can also reproduce the analysis steps much more easily than steps that
> involve physical experiments, polling, etc. So sharing raw data is a useful
> part of replication, though clearly not the whole story.
>
> Thomas
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-- 





*Tom Moritz1968 1/2 South Shenandoah Street, Los Angeles, California
90034-1208  USA+1 310 963 0199 (cell) [GMT -8]tommoritz
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<http://www.linkedin.com/in/tmoritz>*

“Πάντα ῥεῖ καὶ οὐδὲν μένει” (Everything flows, nothing stands still.) --
*Heraclitus *
"It is . . . easy to be certain. One has only to be sufficiently vague." --
C.S. Peirce
"Kathambhutassa me rattindiva vitipatanti" (“The days and nights are
relentlessly passing; how well am I spending my time?”)  -- *"Ten Subjects
for Frequent Recollection by One Who Has Gone Forth"*
*"Il faut imaginer Sisyphe heureux."  ("One must imagine Sisyphus happy.")
-- Camus*
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