Great comments! Thank you. I think that the storage capacity might be not such a big problem at all. The data can be stored on the respective scientists webpage and a pointer could be used. Only the pointer needs to be stored on the server. I personally think that there is a need for a semantic web for scientist. I do not fight any journal or institution. There is no need. Neither that a big name supports this. The need is real, because the traditional scientific concept can not deal with big data. If this is usefully the concept will speak for itself. I know already many people who wish this novel kind of publication. In respect to the question of review: Maybe we do not need the traditional reviewer. I think of post publication review in a social network context.
I still hope that Wikidata can offer a place for scientists. If anybody has specific interest to work more on this subject, please let me know. I will try in any case continue to work on a semantic web for scientists.
On Wed, Apr 4, 2012 at 8:57 PM, emijrp emijrp@gmail.com wrote:
I think that the problem is that Wikidata is not a storage in "the cloud" for all kind of scientific data. In the same fashion Wikipedia is not a portal for papers or academic publications, essays, lyrics, etc. Wikidata scope is not well defined yet, but it will have its limits, for sure.
2012/4/4 Leukippos Institute leukipposinstitute@googlemail.com
Emijrp The storage limit of the sever is a great point. In biomedicine is this also of importance - see e.g. the second generation sequencing data. One might need to go together with NIH and eventually Google to discuss this matter. As a first effort might be a doable focused database desirable. In order not to overload Wikidata server one might need to limit. However, in my opinion need the problem I sketched to be solved. If no solution can be found we might soon reach a point where it does make no sense to continue to collect new biomedical data. At a beginning point this discussion might be very theoretical, because many researchers still stuck to the 300 year old publication model. They do this out of fear for their career.A high impact journal paper results in a tax payer financed academic position. Thus their will be at the beginning a limited number of scientists who will comply and submit open access their raw data in real time. However, if this will be a successfully system, there will be for sure more founding for storage place on a server. The US government has just announced their support research on big data.
On Wed, Apr 4, 2012 at 7:13 PM, emijrp emijrp@gmail.com wrote:
I'm not sure if that kind of data will be desirable at Wikidata (not my personal opinion, just thinking about community).
For example, a lot of city articles contain info about temperature and precipitation[1], but, are we going to import into Wikidata all the temperature values from 1900 to present? (daily averages? minute-by minute?)
I don't know what are the limits of Wikidata, but, we need some limits to work, probably.
[1] http://en.wikipedia.org/wiki/Madrid#Climate
2012/4/4 Leukippos Institute leukipposinstitute@googlemail.com
Hi Sridhar,
Nice to hear from you. I hope we can find many scientist to discuss this with us. We need a wide support from the scientific community, because we need to agree on a standardized format for data submission.
I would like to know what other scientist think about the semantic web http://en.wikipedia.org/wiki/Semantic_Web as a structure to build a common data pool in which we publish directly our data?
I had an interesting discussion with David Bikardhttp://www.facebook.com/david.bikard on this subject on G+ Have a look here http://bit.ly/GWdmX4
David provided some interesting links: http://biocyc.org/ http://linkeddata.org/ http://semanticweb.org/ stackexchange.com
Best Gerd
On Wed, Apr 4, 2012 at 4:23 PM, Sridhar Gutam gutam2000@gmail.comwrote:
Gerd and brought out an important discussion. there is lots of data underutilized in agricultural research too. under the current research on climate change, we need to bring out the data stored in individual desktops and published literature for meaningful analysis.
I am also looking for the opportunity work with the community on development of platforms, mechanisms and advocay for open access to data.
wikidata project would be best to work with...
sridhar __________________________________________________________ Sridhar Gutam PhD, ARS, Patent Laws (NALSAR), IP & Biotech. (WIPO) Senior Scientist (Plant Physiology) Central Institute for Subtropical Horticulturehttp://www.cishlko.org Rehmankhera, Kakori Post Lucknow 227107, Uttar Pradesh, India Phone: +91-522-2841022/23/24; Fax: +91-522-2841025 Mobile:+91-9005760036/8005346136 https://www.facebook.com/gutamsridhar http://www.linkedin.com/in/sridhargutam http://twitter.com/gutam2000http://works.bepress.com/sridhar_gutam/rss.html
On 4 April 2012 19:42, Leukippos Institute < leukipposinstitute@googlemail.com> wrote:
Hi!
I am a synthetic biologist. I see big changes in the way we do science and how we will publish in the future.
I see a huge need to publish all scientific data (especially raw data) in a common free accessible data pool. This data should be machine readable. We face in science huge data amounts, huge number of publications. Nobody is longer able to read all the literature. We need a computer assisted system to analyze these data and develop novel concepts from them. We need a structuring of these data on a higher abstraction level. We need to be able to go from abstraction to detail.
Thus I see the Wiki data project of potentially big value for scientist. I would like that this project could serve in that manner the scientific community and provide standards for submission of data for scientist. Any plans in this direction?
A bit more about the reasons, why I find this very important:
I would summarize the upcoming trend in science as this: From Hypothesis to Data-Driven Research, or the End of the Age of Science, and the Dawn of the Age of Systemics. We can observe a paradigm change in science, and two computer developments are responsible. The first is the enormous storage capacity in the cloud. The second is that a huge number of computers have been connected and organized in social networks. These changes have resulted in huge quantities of data and complex systems, a problem normal science cannot solve. The traditional hypothesis method can deal with simple correlations between A and B. But the method fails if the problem becomes more complex. Science has been synonymous with a separating, reductionistic approach. Contemporary science has come to a point where we will change the perspective from reductionism to holism. We now move to a position that sees things together: short systemics. The data-driven science approach changes the scientific method and results in a practice called "science 2.0" (named after web 2.0). "Science" will happen in the cloud, with new publishing formats such as direct publishing on blogs and direct publishing of our data in a human and computer readable database, new and fast ways of collaboration in social networks, and systems theory as the new "science" paradigm. Systems theory is already important in fields such as systems biology and its practical application synthetic biology.see NextGen VOICES, Science 6 January 2012: vol. 335 no. 6064 pp. 36-38 DOI: 10.1126/science.335.6064.36 http://www.sciencemag.org/content/335/6064/36/suppl/DC1
Best Gerd
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