Sources

  1. Aalst, W.M. (2016). Green Data Science – Using Big Data in an “Environmentally Friendly” Manner. ICEIS.
  2. Aalst, W. (n.d.). Responsible Data Science Ensuring Fairness, Accuracy, Confidentiality, and Transparency (FACT).
  3. David Donoho. 2015. 50 years of Data Science. Retrieved from http://courses.csail.mit.edu/18.337/2015/docs/ 50YearsDataScience.pdf.
  4. Donoho, D. (2015, September). 50 years of Data Science. In Princeton NJ, Tukey Centennial Workshop.
  5. Dwork, C. (2011). A firm foundation for private data analysis. Commun. ACM, 54, 86-95. doi: 10.1145/1866739.1866758
  6. France-Presse, A. (2017, November 30). Google Stole Data From 5 Million iPhone Users in the UK, Lawsuit Alleges. Retrieved December 08, 2017, from https://gadgets.ndtv.com/internet/news/google-iphone-snooping-5-million-users-uk-lawsuit-1781991
  7. Freire, J., Bonnet, P., & Shasha, D. (2012, May). Computational reproducibility: state-of- the-art,challenges, and database research opportunities. In Proceedings of the 2012 ACM SIGMOD international conference on management of data (pp. 593-596). ACM.
  8. Gavish, M., & Donoho, D. (2012). Three dream applications of verifiable computational results. Computing in Science & Engineering, 14(4), 26-31.
  9. Gavish, M., & Donoho, D. (2011). A universal identifier for computational results. Procedia Computer Science, 4, 637-647.
  10. Gordon, B., Zettelmeyer, F., Bhargava, N. and Chapsky, D. (2017). A Comparison of Approaches to Advertising Measurement: Evidence from Big Field Experiments at Facebook. SSRN Electronic Journal.
  11. Hilbert M, Lopez P (2011) The world’s technological capacity to store, communicate, and compute information. Science 332(6025):60–65
  12. Hildebrandt, M., Jacobs, B., Meijer, C., Ruiter, J.D., & Verheul, E.R. (2016). Polymorphic Encryption and Pseudonymisation for Personalised Healthcare. IACR Cryptology ePrint Archive, 2016, 411.
  13. Madigan, D., Stang, P. E., Berlin, J. A., Schuemie, M., Overhage, J. M., Suchard, M. A., … & Ryan, P. B. (2014). A systematic statistical approach to evaluating evidence from observational studies. Annual Review of Statistics and Its Application1, 11-39.
  14. Mansournia, M. and Altman, D. (2016). Inverse probability weighting. BMJ, p.i189.
  15. Marchi, M., & Albert, J. (2013). Analyzing baseball data with R. CRC Press.
  16. Manyika J, Chui M, Brown B, Bughin J, Dobbs R, Roxburgh C, Byers A (2011) Big data: the next frontier for innovation, competition, and productivity. McKinsey Global Institute, New York
  17. Mayo DG (1996) Error and growth of experimental knowledge. University of Chicago Press, Chicago
  18. Mcsherry, F. (2010). Privacy integrated queries. Communications of the ACM, 53(9), 89. doi:10.1145/1810891.1810916
  19. McNutt, M. (2014). Reproducibility. Science343(6168), 229-229.
  20. Mcsherry, F., & Talwar, K. (2007). Mechanism Design via Differential Privacy. 48th Annual IEEE Symposium on Foundations of Computer Science (FOCS07). doi:10.1109/focs.2007.66
  21. Pan, Z., Trikalinos, T. A., Kavvoura, F. K., Lau, J., & Ioannidis, J. P. (2005). Local literature bias in genetic epidemiology: an empirical evaluation of the Chinese literature. PLoS medicine2(12), e334.
  22. Peng, R. D. (2009). Reproducible research and biostatistics. Biostatistics10(3), 405-408.
  23. Cavoukian A. Privacy by design. Take the challenge. Information and privacy commissioner of Ontario, Canada; 2009.
  24. Schomberg, R. V. (2012). Prospects for technology assessment in a framework of responsible research and innovation. Technikfolgen abschätzen lehren, 39-61. doi:10.1007/978-3-531-93468-6_2
  25. Stodden, V., Leisch, F., & Peng, R. D. (Eds.). (2014). Implementing reproducible research. CRC Press.
  26. Stodden, V., & Miguez, S. (2013). Best practices for computational science: Software infrastructure and environments for reproducible and extensible research.
  27. van der Aalst, W. M. P., Bichler, M. & Heinzl, A. (2017). Responsible Data Science.. Business & Information Systems Engineering, 59, 311-313.
  28. White House (2016) Artificial intelligence, automation, and the economy. (Report released by the Executive Office of the President in December 2016). https://obamawhitehouse.archives. gov/sites/whitehouse.gov/files/documents/Artificial-IntelligenceAutomation-Economy.pdf. Accessed 11 June 2017