افزایش داده‌‌‌‌‌ها و پیشرفت علم

نوع مقاله : علمی - پژوهشی

نویسنده

عضو هیئت علمی دانشگاه علامه طباطبایی

چکیده

برخلاف آنچه که ممکن است به نظر برسد برخی شاخص‌ها نشان می‌دهند که علم از حدود ربع چهارم قرن بیستم به بعد دچار رکود شده است و از کشف‌های بزرگ کمتر نشانی هست. این در حالی است که این دوره شاهد بیشترین تعداد دانشمند، بیشترین بودجه تحقیقاتی و بیشترین تعداد مقالات علمی در جهان بوده است. افزون‌براین، انواعی از ابزارهای سخت و نرم جدید، انبوهی از داده‌های تجربی در عموم رشته‌ها از میکروفیزیک تا نجوم و از زیست‌شناسی تا علوم اجتماعی را فراهم کرده‌اند که علی‌القاعده باید به رشد علم شتاب بیشتری بدهند.

این مقاله با بررسی این شاخص‌ها از چرایی واقعه می‌پرسد و بر این نکته متمرکز می‌شود که انبوهی داده‌ها مشکل چندانی از رشد علم حل نمی‌کند؛ زیرا رشد علم در گرو فرضیات آزمون‌پذیر است و داده‌های انبوه‌تر و گرفتن متغیر‌های بیشتر امکان فرضیه‌پردازی را دشوار می‌کند. به‌دیگرسخن، پشتوانه تجربی همواره کمک‌کننده به غنای تبیینی نیست، بلکه گاه منافی آن است.

کلیدواژه‌ها


Belluz, Julia, et. all, (2016), “The 7 Biggest problems facing science, according to 270 scientists”, Vox com, 7 September. https://www.vox.com/2016/7/14/12016710/science-challeges-research-funding-peer-review-process.
Chalmers, David (1992), “High level perception, representation, and analogy: A critique of artificial intelligence methodology”, Journal of Experimental & theoretical Artificial Intelligence, 4 (3), pp. 185-211.
Collison Patrick, Nielsen, Michael (2018), “Science is getting less bang for its buck”, The Atlantic, 16 November.
Cunningham, Alastair (1997), “Quantifying survey data”, Bank of England, Quarterly Bulletin, 37 (3), pp. 292-300.
Davidowitz,  Stephene (2017), Every body lies: Big data, New data, and what the internet can tell us …, Dey Street Books.
Duhem, piere (1989), La Theorie physique, Son object, sa structure, Paris, Vrin.
Elowitz, Michael (2002), “Stochastic Gene Expression in a Single Cell”, Science,  16 August,
297,( 5584), pp. 1183-1186, DOI: 10.1126/science.1070919
Evett, IW (1996), “Expert Evidence and forensic misconceptions of the nature of exact science”, Science and Justice, 36 (2), pp. 118-122.
Gabrys, Jennifer, et. all (2016), “Just good enough data”, Big data & Society,1 december, Doi.org/10.1177/2053951716679677
Gordon, Robert (2016), The rise and fall of American growth, Princeton university press.
Herrera Juan (2010), “Evaluation of traffic data obtained via GPS”, Transportation Research: Emerging Technologies, 18 (4), pp. 568-583.
Hidary, Jack (2019), Quantom computing: An applied Approch, Springer.
Horgan, John (1996), The End of science, Basik Books.

Kim, Y.S. (2007), “Can you do quantum mechanics without Einstein?”, AIP Conference Proceedings 889, 152, 15 March, https://doi.org/10.1063/1.2713454. https://aip.scitation.org/ doi/abs/10.1063/1.2713454.

Knapton, Sarah (2018), “Nine in Ten Cancers Caused by Lifstyle”, http://www.telegraph.co.uk/news/ health/news/12055206/html. -

Kurzweil, Ray (2005), The accelerating power of technology, Ted Talk. https://www.ted.com/talks/ray_kurzweil_the_accelerating_power_of_technology?language=en

Lehrer, Jonah (2011), The difficulty of discovery (where have all geniuses gone?), Wired, 26 January, https://www.wired.com/2011/01/the-difficulty-of-discovery/
Machlis, Sharon (2013), “More data isn’t always better”, Computerworld, 8/ may/  2013.
Martin, Douglas (2005), H. Bentley Glass, Provocative Science Theorist, New York Times, 20 January
Miyakawa, Tsuyoshi (2020), “ no raw data, no science”, Molecular brain, 13 (24), Editorial, 21 february.

Moskvitch, Katia (2018), “What if everything we know about dark matter is totally wrong?”, Wired, 28 September. https://www.wired.co.uk/article/dark-matter-worth-searching-for-null-results

Murdock, John (1980), “Numerical data indexing”, Journal of chemical information and computer sciences 20 (3), pp. 132-136.
Pearson, Helen (2006), “What is gene?”, Nature, 441, pp. 398- 401,24 may. https://www.nature.com/articles/441398a.
Ramirez, Israel (2018), Why isn’t science advancing faster?, Quora, 27 September. https://www.forbes.com/sites/quora/2018/09/27/why-isnt-science-advancing-faster/#451d7e463c14
Rothman, Milton (1970), Discovering the natural laws: The experimental basis of physics, Dover publication, New York.
Saxena, Anurag (2007), “Exploring Models for the growth of literature data”, Journal of library & information Technology, 27 (3), pp. 45-67.

Schwanhausser, Bjorn, et. all (2011). “Global quantification of mammalian gene expression control”, Nature, 473, pp. 337-342.

Tomasetti, Christian, Lu Li, Bert Vogelstein, (2017) “Stem cell divisions, somatic mutations, cancer etiology, and cancer prevention”, Science, Vol. 355, Issue 6331, pp. 1330-1334.
Tretkoff, Emie (2005), “Einstein’s quest for a unified theory”, American Physical Society, 14 (11). https://www.aps.org/publications/apsnews/200512/history.cfm
Tufecki, Zeynep (2019), “Big data and small decisions”, Scientific American, 320, pp. 3-73, doi: !0.1038/scientificamerican0319-73.
Van Lang, Christopher (2017), What is the most difficult part of drug discovery?, Quora, 10 November. https://www.forbes.com/sites/quora/2017/11/10/what-is-the-mos-tdifficult-part-of-drug- discovery?/#
Vander, steven (1997), “When cacges aren’t enough: Data prefetching techniques”, Computer 30 (7), pp. 23-30.
Zeng, An & Stanley, Eugene (2017), “The science of science: from the perspective of complex  systems”, Physics Reports, V. 714-715, 16 November, Doi. Org/10.1016/j.physicdp.2017.10001.