The Evolution of Data Science: A New Mode of Knowledge Production
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Cat Ferguson & Adam Marcus & Ivan Oransky, 2014. "Publishing: The peer-review scam," Nature, Nature, vol. 515(7528), pages 480-482, November.
- Eric Bender, 2016. "Challenges: Crowdsourced solutions," Nature, Nature, vol. 533(7602), pages 62-64, May.
- William S. Cleveland, 2001. "Data Science: an Action Plan for Expanding the Technical Areas of the Field of Statistics," International Statistical Review, International Statistical Institute, vol. 69(1), pages 21-26, April.
- Seth Cooper & Firas Khatib & Adrien Treuille & Janos Barbero & Jeehyung Lee & Michael Beenen & Andrew Leaver-Fay & David Baker & Zoran Popović & Foldit players, 2010. "Predicting protein structures with a multiplayer online game," Nature, Nature, vol. 466(7307), pages 756-760, August.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Iva Golubi´c & Janko Marovt, 2020. "On Some Applications of Matrix Partial Orders in Statistics," International Journal of Management, Knowledge and Learning, International School for Social and Business Studies, Celje, Slovenia, vol. 9(2), pages 223-235.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Christoph Safferling & Aaron Lowen, 2011. "Economics in the Kingdom of Loathing: Analysis of Virtual Market Data," Working Paper Series of the Department of Economics, University of Konstanz 2011-30, Department of Economics, University of Konstanz.
- Situngkir, Hokky, 2015. "Indonesia embraces the Data Science," MPRA Paper 66048, University Library of Munich, Germany.
- Kovacs, Attila, 2018. "Gender Differences in Equity Crowdfunding," OSF Preprints 5pcmb, Center for Open Science.
- Costa, Carlos & Santos, Maribel Yasmina, 2017. "The data scientist profile and its representativeness in the European e-Competence framework and the skills framework for the information age," International Journal of Information Management, Elsevier, vol. 37(6), pages 726-734.
- Daphne R. Raban & Avishag Gordon, 2020. "The evolution of data science and big data research: A bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(3), pages 1563-1581, March.
- Nils Hachmeister & Katharina Weiß & Juliane Theiß & Reinhold Decker, 2021. "Balancing Plurality and Educational Essence: Higher Education Between Data-Competent Professionals and Data Self-Empowered Citizens," Data, MDPI, vol. 6(2), pages 1-15, January.
- Serena Ng, 2017. "Opportunities and Challenges: Lessons from Analyzing Terabytes of Scanner Data," NBER Working Papers 23673, National Bureau of Economic Research, Inc.
- Naihui Zhou & Zachary D Siegel & Scott Zarecor & Nigel Lee & Darwin A Campbell & Carson M Andorf & Dan Nettleton & Carolyn J Lawrence-Dill & Baskar Ganapathysubramanian & Jonathan W Kelly & Iddo Fried, 2018. "Crowdsourcing image analysis for plant phenomics to generate ground truth data for machine learning," PLOS Computational Biology, Public Library of Science, vol. 14(7), pages 1-16, July.
- Stephan R. Sain, 2023. "Data science and climate risk analytics," Environmetrics, John Wiley & Sons, Ltd., vol. 34(2), March.
- Hassani, Hossein & Beneki, Christina & Silva, Emmanuel Sirimal & Vandeput, Nicolas & Madsen, Dag Øivind, 2021. "The science of statistics versus data science: What is the future?," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
- Göran Kauermann & Helmut Küchenhoff, 2016. "Statistik, Data Science und Big Data [Statistics, data science, and big data]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 10(2), pages 141-150, October.
- Sam Mavandadi & Stoyan Dimitrov & Steve Feng & Frank Yu & Uzair Sikora & Oguzhan Yaglidere & Swati Padmanabhan & Karin Nielsen & Aydogan Ozcan, 2012. "Distributed Medical Image Analysis and Diagnosis through Crowd-Sourced Games: A Malaria Case Study," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-8, May.
- Ayat Abourashed & Laura Doornekamp & Santi Escartin & Constantianus J. M. Koenraadt & Maarten Schrama & Marlies Wagener & Frederic Bartumeus & Eric C. M. van Gorp, 2021. "The Potential Role of School Citizen Science Programs in Infectious Disease Surveillance: A Critical Review," IJERPH, MDPI, vol. 18(13), pages 1-18, June.
- Gaute Wangen, 2015. "Conflicting Incentives Risk Analysis: A Case Study of the Normative Peer Review Process," Administrative Sciences, MDPI, vol. 5(3), pages 1-23, July.
- Vito D’Orazio & Michael Kenwick & Matthew Lane & Glenn Palmer & David Reitter, 2016. "Crowdsourcing the Measurement of Interstate Conflict," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-21, June.
- Yury Kryvasheyeu & Haohui Chen & Esteban Moro & Pascal Van Hentenryck & Manuel Cebrian, 2015. "Performance of Social Network Sensors during Hurricane Sandy," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-19, February.
- Siluo Yang & Dietmar Wolfram & Feifei Wang, 2017. "The relationship between the author byline and contribution lists: a comparison of three general medical journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(3), pages 1273-1296, March.
- Jonathan P. Tennant & Harry Crane & Tom Crick & Jacinto Davila & Asura Enkhbayar & Johanna Havemann & Bianca Kramer & Ryan Martin & Paola Masuzzo & Andy Nobes & Curt Rice & Bárbara Rivera-López & Tony, 2019. "Ten Hot Topics around Scholarly Publishing," Publications, MDPI, vol. 7(2), pages 1-24, May.
- Maryam Lotfian & Jens Ingensand & Maria Antonia Brovelli, 2021. "The Partnership of Citizen Science and Machine Learning: Benefits, Risks, and Future Challenges for Engagement, Data Collection, and Data Quality," Sustainability, MDPI, vol. 13(14), pages 1-19, July.
- Jonathan R Karr & Alex H Williams & Jeremy D Zucker & Andreas Raue & Bernhard Steiert & Jens Timmer & Clemens Kreutz & DREAM8 Parameter Estimation Challenge Consortium & Simon Wilkinson & Brandon A Al, 2015. "Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models," PLOS Computational Biology, Public Library of Science, vol. 11(5), pages 1-21, May.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jkm000:v:15:y:2019:i:2:p:97-109. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.