D.E.E.P: Discovering the Extent of Estimable Prediction in Science and Technology

This project is developing novel, innovative tools spanning network science, machine learning, natural language processing, and computational social science to yeild new insights and answers to the following questions:
  • Can we foresee new scientific discoveries and technological inventions? If so, what are the quantifiable signals of an impending scientific or engineering breakthrough?
  • Is the long-term impact of a scientific discovery or technological breakthrough predictable? If so, to what degree and how soon can we confidently predict impact? What are the key drivers behind uncovered predictability? 
  • What is best predicted in the domain of S&T—what represents the optimal balance of risk and reward in a funded research portfolio? Scientific and technical discoveries? Successful scientists, engineers, or research teams? Fruitful S&T fields or research strategies?

Deep Kickoff Slide Deck #1

Deep Kickoff Slide Deck #2

Relevant Publications:

A. Rzhetsky, J. G. Foster, I. T. Foster, J. A. Evans. "Choosing experiments to accelerate collective discovery." Proceedings of the National Academy of Sciences (2015).
R. Sinatra,  P. Deville, M. Szell, D. Wang, L. A. Barabasi. "A century of physics." Nature Physics (2015).
N. Cao, Y. R. Lin, F. Du, D. Wang. "Episogram: Visual summarization of egocentric social interactions". IEEE Computer Graphics and Applications (2015).
J. G. Foster, A. Rzhetsky, J. A. Evans. "Tradition and Innovation in Scientists’ Research Strategies." American Sociological Review (2015).
F. Shi, J. G. Foster, and J. A. Evans. "Weaving the fabric of science: Dynamic network models of science's unfolding structure." Social Networks (2015).
L. Yao, J. A. Evans, A. Rzhetsky. “A health research opportunity index reveals the (ir)rational allocation of research resources to health needs”. Nature Biotechnology (2015).
S. Allesina, C. Weinberger, J. A. Evans. “Ten Simple (Empirical) Rules for Writing Science.” PLOS Computational Biology (2015).
D. R. Blair, K. Wang, S. Nestorov, J. A. Evans, A. Rzhetsky. “Quantifying the Impact and Extent of Undocumented Biomedical Synonymy” PLOS Computational Biology (2014).
A. Gerow, J. A. Evans. 2014. “The Modular Community Structure of Linguistic Predication Networks.” ACM Proceedings of TextGraphs-9: the workshop on Graph-based Methods for Natural Language Processing (2014)
J. Wang, N. Srebro, J. A. Evans. “Active collaborative permutation learning” KDD ‘14 Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining (2014).
J. West, J. G. Foster, M. Rosvall, D. Villena, J. A. Evans, C. Bergstrom. 2014. “Finding Cultural Holes: How Structure and Culture Diverge in Networks of Scholarly Communication” Sociological Science (2014).
J. A. Evans, J. Shim, J. P. Ioannidis. “Attention to Local Health Burden and the Global Disparity of Health Research” PLOS ONE (2014).
H. Shen, et al. "Modeling and predicting popularity dynamics via reinforced Poisson processes." The Twenty-Eighth AAAI Conference on Artificial Intelligence (2014).
C. M. Macal, et al. “Modeling the transmission of Community-Associated Methicillin-Resistant Staphylococcus aureus: a dynamic agent-based simulation.” Journal of Translational Medicine (2014).
J. A. Evans. "Future Science" Science (2013).
D. Wang, C. Song, and A. Barabási. "Quantifying long-term scientific impact." Science (2013).
A. Barabási, C. Song, and D. Wang. "Publishing: Handful of papers dominates citation." Nature (2012).
J. A. Evans, J. G. Foster. "Metaknowledge," Science (2011).
J. A. Evans, A. Rzhetsky. “Advancing Science through Mining Libraries, Ontologies and Communities.” Journal of Biological Chemistry (2011).
A. Divoli, E. Mendonça, J. A. Evans, A. Rzhetsky. “Conflicting biomedical assumptions for mathematical modeling: The case of cancer metastasis”  PLoS Computational Biology (2011).
J. A. Evans. “Industry Collaboration, Scientific Sharing and the Dissemination of Knowledge.” Social Studies of Science (2010).
J. A. Evans. “Industry Induces Academic Science to Know Less About More.” American Journal of Sociology (2010).
L. Yao, A. Divoli, I. Mayzus, J. A. Evans, and A. Rzhetsky. 2010.  “Benchmarking Ontologies: Bigger or Better?” PLoS Computational Biology (2010).
J. A. Evans, A. Rzhetsky. "Machine Science," Science (2010).
J. A. Evans and J. Reimer, “Open Access and Global Participation in Science,” Science (2009).
L. Yao, J. A. Evans and A. Rzhetsky. “Novel Opportunities for computational biology and sociology in drug discovery.” Trends in Biotechnology (2009).
J. A. Evans, “Electronic publication and the narrowing of science and scholarship,” Science (2008).