Re: Call for Linked Research


while I agree with you all, I was thinking: is the lack of reproducibility an issue due to the way results are represented ?
Apart for some fields (e.g.: bioinformatics), materials, samples, experience are probably more relevant and much harder to reproduce.


Il giorno 28/lug/2014, alle ore 16:16, Paul Houle <> ha scritto:

> I'd add to all of this publishing the raw data,  source code,  and
> industrialized procedures so that results are truly reproducible,  as
> few results in science actually are.
> ᐧ
> On Mon, Jul 28, 2014 at 9:01 AM, Sarven Capadisli <> wrote:
>> Call for Linked Research
>> ========================
>> Purpose: To encourage the "do it yourself" behaviour for sharing and reusing
>> research knowledge.
>> Deadline: As soon as you can.
>> From :
>> Scientists and researchers who work in Web Science have to follow the rules
>> that are set by the publisher; researchers need to have read and reuse
>> access to other researchers work, and adopt archaic desktop-native
>> publishing workflows. Publishers try to remain as the middleman for
>> society’s knowledge acquisition.
>> Nowadays, there is more machine-friendly data and documentation made
>> available by the public sector than the Linked Data research community. The
>> general public asks for open and machine-friendly data, and they are
>> following up. Web research publishing on the other hand, is stuck on one ★
>> (star) Linked Data deployment scheme. The community has difficulty eating
>> its own dogfood for research publication, and fails to deliver its share of
>> the "promise".
>> There is a social problem. Not a technical one. If you think that there is
>> something fundamentally wrong with this picture, want to voice yourself, and
>> willing to continue to contribute to the Semantic Web vision, then please
>> consider the following before you write about your research:
>> Linked Research: Do It Yourself
>> 1. Publish your research and findings at a Web space that you control.
>> 2. Publish your progress and work following the Linked Data design
>> principles. Create a URI for everything that is of some value to you and may
>> be to others e.g., hypothesis, workflow steps, variables, provenance,
>> results etc.
>> 3. Reuse and link to other researchers URIs of value, so nothing goes to
>> waste or reinvented without good reason.
>> 4. Provide screen and print stylesheets, so that it is legible on screen
>> devices and can be printed to paper or output to desktop-native document
>> formats. Create a copy of a view for the research community to fulfil
>> organisational requirements.
>> 5. Announce your work publicly so that people and machines can discover it.
>> 6. Have an open comment system policy for your document so that any person
>> (or even machines) can give feedback.
>> 7. Help and encourage others to do the same.
>> There is no central authority to make a judgement on the value of your
>> contributions. You do not need anyone’s permission to share your work, you
>> can do it yourself, meanwhile others can learn and give feedback.
>> -Sarven
> -- 
> Paul Houle
> Expert on Freebase, DBpedia, Hadoop and RDF
> (607) 539 6254    paul.houle on Skype

Received on Monday, 28 July 2014 22:45:46 UTC