Created on Jan. 11, 2013, 11:48 p.m. by Hevok & updated by Hevok on May 2, 2013, 4:52 p.m.
Distributed Science will be a Game Changer in the way technology progresses (Acceleration Technology) .
Research Projects should be invoked by experienced Researchers (i.e. Experts). Their experience would allow to split a significant Research into pieces that a common person could accomplish. An experienced Researcher should also define methodology of Experiments, or even keep track on a regular basis. This would be beneficial for Researchers because it would increase the number of experiments they can do. That's about real experiments.
Research may also require data or information mining, and computer specialist, i.e. Programmers, will do it. Of course IT people should know why this is important.
Another area is building computer models: instead of running real experiments - do simulations.
The open-approach for Experiments may produce a lot data, and it would be difficult to differentiate between low quality and high quality data. Still an open Science approach has other huge advantages, namely:
These together will facilitate scientific advancement within a decade dramatically. It may even invoke a chain reaction changing how Science is conducted and revolutionize technology and medicine rapidly.
Yet another area is Design/Arts, educating and encouraging people to make useful artwork at the intersection of nature and technology and therefore enabling the effective promotion via diverse forms of media and hyping it so that the message can spread and the idea grow.
Media can be anything like Images, Sounds, Music, Videos, Animations, etc. This is also required to effectively deliver information to the broader public like teenagers and non-scientists.
In Science we trust a person because s/he provides valid data rather than data is valid because we trust this person (who has provided the data). The former is the right one. Building a network of distributed Research on the latter option is fundamentally wrong. It would not be Science.
There is a value of massive involvement of people into doing Experiments. An increase of Experiments, an increase of fact harvesting is one example. Another example is increasing a scientific literacy. Increasing a pool of people who would go into professional longevity Research is yet another one. These three cases requires similar software, however these are not the same.
Fact harvesting - One can do Experiments at home, however these experiments should be valuable for Aging Researchers. Check the affect of a substance to the longevity of two dozens of mice * number of people repeating the same experiment * different substances could be beneficial. But amateur scientists would hardly select the most interesting diet, not speaking about testing various diets as a part of a large experiment.
Scientific thinking is different to engineering or common sense or any other established way of looking to the world. It requires certain literacy in facts, theories, and methods. Frankly, it is a complex concept. Case studies are one of the ways to understand complex concepts. If one would go through a series of cases s/he could participate in the first case of distributed science.
Creating Researchers - If teenagers would go through through 2nd and later would participate in the 1st case there is higher chance they would become professional Researcher in the field of longevity Science.
However, all this provides a certain set of requirements that a framework should incorporate:
Provide Research Project management capabilitiesHave a knowledge base of scientific methods and rational for selecting one method and not another for a specific ProjectStore the Research data and Research resultsManage social collaboration
An amateur Researcher should know about other Researchers because it would motivate her/him to continue. If two or more independent clones (e.g. Research Projects checking the same diet) would lead to the same results, it would be trustworthy.
Comment on This Data Unit