Have a personal or library account? Click to login
Reproducibility in Research: Systems, Infrastructure, Culture Cover

Reproducibility in Research: Systems, Infrastructure, Culture

Open Access
|Nov 2017

References

  1. Andreessen, M “Why Software Is Eating The World,” The Wall Street Journal, August 2011. Available online: http://online.wsj.com/news/articles/SB10001424053111903480904576512250915629460.
  2. Royal Society 2012 “Science as an open enterprise,” Available from: https://royalsociety.org/policy/projects/science-public-enterprise/report/.
  3. Editorial 2011 “Devil in the details,” Nature, 470(7334): 305306, DOI: 10.1038/470305b
  4. Alberts, B, Cicerone, R J, Fienberg, S E, Kamb, A, McNutt, M, Nerem, R M, Schekman, R, Shiffrin, R, Stodden, V, Suresh, S, Zuber, M T, Kline Pope, B and Jamieson, K 2015 “Self-correction in science at work,” Science, 348(6242): 14201422. DOI: 10.1126/science.aab3847
  5. Collberg, C and Proebsting, T A 2016 “Repeatability in Computer Systems Research,” Communications of the ACM, 59(3): 6269. DOI: 10.1145/2812803
  6. Crick,T, De Vos, M, Brain, M and Fitch, J 2009 “Generating Optimal Code using Answer Set Programming.” In: Proceedings of 10th International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR’09), Lecture Notes in Computer Science, 5753: 554559, Springer. DOI: 10.1007/978-3-642-04238-6_57
  7. Berdine, J, Cook, B and Ishtiaq, S 2011 “SLAyer: Memory Safety for Systems-Level Code,” In: Proceedings of the 23rd International Conference on Computer Aided Verification (CAV 2011), of Lecture Notes in Computer Science, 6806: 178183, Springer. DOI: 10.1007/978-3-642-22110-1_15
  8. De Roure, D. “Replacing the Paper: The Twelve Rs of the e-Research Record.” Available from: http://www.scilogs.com/eresearch/replacing-the-paper-the-twelve-rs-of-the-e-research-record/, November 2011.
  9. Stodden, V, Guo, P and Ma, Z 2013 “Toward Reproducible Computational Research: An Empirical Analysis of Data and Code Policy Adoption by Journals,” PLoS ONE, 8(6). DOI: 10.1371/journal.pone.0067111
  10. Fursin, G and Dubach, C 2014 “Community-Driven Reviewing and Validation of Publications,” In: Proceedings of the 1st ACM SIGPLAN Workshop on Reproducible Research Methodologies and New Publication Models in Computer Engineering (TRUST’14), pp. 14, ACM Press. DOI: 10.1145/2618137.2618142
  11. National Academies of Sciences, Engineering, and Medicine 2016 Statistical Challenges in Assessing and Fostering the Reproducibility of Scientific Results: Summary of a Workshop. The National Academies Press.
  12. Galiani, S, Gertler, P and Romero, M. “Incentives for Replication in Economics,” Tech. rep., National Bureau of Economic Research, July 2017. NBER Working Paper No. 23576.
  13. Barnes, N 2010 “Publish your computer code: it is good enough,” Nature, 467(753). DOI: 10.1038/467753a
  14. Morin, A, Urban, J, Adams, P D, Foster, I, Sali, A, Baker, D and Sliz, P 2012 “Shining Light into Black Boxes,” Science, 336(6078): 159160. DOI: 10.1126/science.1218263
  15. Joppa, L N, McInerny, G, Harper, R, Salido, L, Takeda, K, O’Hara, K, Gavaghan, D and Emmott, S 2013 “Troubling Trends in Scientific Software Use,” Science, 340(6134): 814815. DOI: 10.1126/science.1231535
  16. Bechhofer, S, Buchan, I, De Roure, D, Missier, P, Ainsworth, J, Bhagata, J, Couch, P, Cruickshank, D, Delderfield, M, Dunlop, I, Gamble, M, Michaelides, D, Owen, S, Newman, D, Sufi, S and Goble, C 2013 “Why linked data is not enough for scientists,” Future Generation Computer Systems, 29(2): 599611. DOI: 10.1016/j.future.2011.08.004
  17. Osherovich, L 2011 “Hedging against academic risk,” Science-Business eXchange, 4(15).
  18. Hesman Saey, T 2015 “Repeat Performance: Too many studies, when replicated, fail to pass muster,” Science News, 187(2): 2126. DOI: 10.1002/scin.2015.187002014
  19. Goble, C 2014 “Better Software, Better Research,” IEEE Internet Computing, 18(5): 48. DOI: 10.1109/MIC.2014.88
  20. Chirigati, F, Troyer, M, Shasha, D and Freire, J 2013 “A Computational Reproducibility Benchmark,” IEEE Data Engineering Bulletin, 36(4): 5459.
  21. Stodden, V and Miguez, S 2014 “Best Practices for Computational Science: Software Infrastructure and Environments for Reproducible and Extensible Research,” Journal of Open Research Software, 2(1): 16. DOI: 10.5334/jors.ay
  22. Stodden, V, Miguez, S and Seiler, J 2015 ResearchCompendia.org: Cyberinfrastructure for Reproducibility and Collaboration in Computational Science,” Computing in Science & Engineering, 17(12). DOI: 10.1109/MCSE.2015.18
  23. Stodden, V, McNutt, M, Bailey, D H, Deelman, E, Gil, Y, Hanson, B, Heroux, M A, Ioannidis, J P and Taufer, M 2016 “Enhancing reproducibility for computational methods,” Science, 354(6317): 12401241. DOI: 10.1126/science.aah6168
  24. Fomel, S and Claerbout, J F 2008 “Reproducible Research,” Computing in Science & Engineering, 11(1).
  25. “Reproducible Research” 2010 Computing in Science & Engineering, 12(5): 813. DOI: 10.1109/MCSE.2010.113
  26. Gent, I P “The Recomputation Manifesto.” Available from: http://arxiv.org/abs/1304.3674, April 2013.
  27. Fursin, G, Miceli, R, Lokhmotov, A, Gerndt, M, Baboulin, M, Malony, A D, Chamski, Z, Novillo, D and Del Vento, D 2014 “Collective mind: Towards practical and collaborative auto-tuning,” Scientific Programming, 22(4): 309329. DOI: 10.1155/2014/797348
  28. Bailey, D, Borwein, J and Stodden, V 2013 “Set the Default to “Open”,” Notices of the AMS.
  29. James, D, Wilkins-Diehr, N, Stodden, V, Colbry, D, Rosales, C, Fahey, M R, Shi, J, da Silva, R F, Lee, K, Roskies, R, Loewe, L, Lindsey, S, Kooper, R, Barba, L, Bailey, D H, Borwein, J M, Corcho, Ó, Deelman, E, Dietze, M C, Gilbert, B, Harkes, J, Keele, S, Kumar, P, Lee, J, Linke, E, Marciano, R, Marini, L, Mattmann, C, Mattson, D, McHenry, K, McLay, R T, Miguez, S, Minsker, B S, Pérez-Hernández, M S, Ryan, D, Rynge, M, Pérez, I S, Satyanarayanan, M, Clair, G S, Webster, K, Hovig, E, Katz, D S, Kay, S, Sandve, G K, Skinner, D, Allen, G, Cazes, J, Cho, K W, Fonseca, J, Hwang, L, Koesterke, L, Patel, P, Pouchard, L, Seidel, E and Suriarachchi, I 2014 “Standing Together for Reproducibility in Large-Scale Computing: Report on reproducibility@XSEDE,” Tech. rep., XSEDE.
  30. Prlić, A and Procter, J B 2012 “Ten Simple Rules for the Open Development of Scientific Software,” PLoS Computational Biology, 8(12): e1002802. DOI: 10.1371/journal.pcbi.1002802
  31. Masum, H, Rao, A, Good, B M, Todd, M H, Edwards, A M, Chan, L, Bunin, B A, Su, A I, Thomas, Z and Bourne, P E 2013 “Ten Simple Rules for Cultivating Open Science and Collaborative R&D,” PLoS Computational Biology, 9(9): e1003244. DOI: 10.1371/journal.pcbi.1003244
  32. Sandve, G, Nekrutenko, A, Taylor, J and Hovig, E 2013 “Ten Simple Rules for Reproducible Computational Research,” PLoS Computational Biology, 9(10): e1003285. DOI: 10.1371/journal.pcbi.1003285
  33. Osborne, J M, Bernabeu, M O, Bruna, M, Calderhead, B, Cooper, J, Dalchau, N, Dunn, S-J, Fletcher, A G, Freeman, R, Groen, D, Knapp, B, McInerny, G J, Mirams, G R, Pitt-Francis, J, Sengupta, B, Wright, D W, Yates, C A, Gavaghan, D J, Emmott, S and Deane, C 2013 “Ten Simple Rules for Effective Computational Research,” PLoS Computational Biology, 10(3): e1003506. DOI: 10.1371/journal.pcbi.1003506
  34. Goodman, A, Pepe, A, Blocker, A W, Borgman, C L, Cranmer, K, Crosas, M, Di Stefano, R, Gil, Y, Groth, P, Hedstrom, M, Hogg, D W, Kashyap, V, Mahabal, A, Siemiginowska, A and Slavkovic, A 2014 “Ten Simple Rules for the Care and Feeding of Scientific Data,” PLoS Computational Biology, 10(4): e1003542. DOI: 10.1371/journal.pcbi.1003542
  35. Chue Hong, N P, Crick, T, Gent, I P, Kotthoff, L and Takeda, K 2015 “Top Tips to Make Your Research Irreproducible.” Available from: http://arxiv.org/abs/1504.00062.
  36. List, M, Ebert, P and Albrecht, F 2017 “Ten Simple Rules for Developing Usable Software in Computational Biology,” PLoS Computational Biology, 13(1): e1005265. DOI: 10.1371/journal.pcbi.1005265
  37. Stodden, V 2008 “The Legal Framework for Reproducible Scientific Research: Licensing and Copyright,” Computing in Science & Engineering, 11(1).
  38. Haas, C N 2016 “Reproducible Risk Assessment,” Risk Analysis, 6(10): 18291833. DOI: 10.1111/risa.12730
  39. Crick, T, Hall, B A and Ishtiaq, S 2014 ““Can I Implement Your Algorithm?”: A Model for Reproducible Research Software,” In: 2nd International Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE2).
  40. Crick, T, Hall, B A, Ishtiaq, S and Takeda, K 2014 ““Share and Enjoy”: Publishing Useful (and Usable) Scientific Models,” In: Proceedings of the 7th IEEE/ACM International Conference on Utility and Cloud Computing, pp. 957961.
  41. Stallman, R M 2010 Free Software Free Society: Selected Essays of Richard M. Stallman. Free Software Foundation.
  42. Giles, J 2004 “Software company bans competitive users,” Nature, 429(6989). DOI: 10.1038/429231a
  43. Hess, B, Kutzner, C, van der Spoel, D and Lindahl, E 2008 “GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation,” Journal of Chemical Theory and Computation, 4(3): 435447. DOI: 10.1021/ct700301q
  44. Brooks, B R, Brooks, C L, Mackerell, A D, Nilsson, L, Petrella, R J, Roux, B, Won, Y, Archontis, G, Bartels, C, Boresch, S, Caflisch, A, Caves, L, Cui, Q, Dinner, A R, Feig, M, Fischer, S, Gao, J, Hodoscek, M, Im, W, Kuczera, K, Lazaridis, T, Ma, J, Ovchinnikov, V, Paci, E, Pastor, R W, Post, C B, Pu, J Z, Schaefer, M, Tidor, B, Venable, R M, Woodcock, H L, Wu, X, Yang, W, York, D M and Karplus, M 2009 “CHARMM: The biomolecular simulation program,” Journal of Computational Chemistry, 30(10): 15451614. DOI: 10.1002/jcc.21287
  45. Bowers, K J, Chow, E, Xu, H, Dror, R O, Eastwood, M P, Gregersen, B A, Klepeis, J L, Kolossvary, I, Moraes, M A, Sacerdoti, F D, Salmon, J K, Shan, Y and Shaw, D E 2006 “Scalable algorithms for molecular dynamics simulations on commodity clusters,” In: Proceedings of the 2006 ACM/IEEE Conference on Supercomputing, IEEE Press. DOI: 10.1109/SC.2006.54
  46. de Moura, L 2012 “Releasing the Z3 source code.” Available online: http://leodemoura.github.io/blog/2012/10/02/open-z3.html.
  47. “Open Source Licenses” http://opensource.org/licenses.
  48. Wilson, G 2006 “Software carpentry: Getting scientists to write better code by making them more productive,” Computing in Science & Engineering, 8(6). DOI: 10.1109/MCSE.2006.122
  49. Gonthier, G, Ziliani, B, Nanevski, A and Dreyer, D 2013 “How to make ad hoc proof automation less adhoc,” Journal of Functional Programming, 23(4): 357401. DOI: 10.1017/S0956796813000051
  50. Miller, G 2006 “A Scientist’s Nightmare: Software Problem Leads to Five Retractions,” Science, 314(5807): 18561857. DOI: 10.1126/science.314.5807.1856
  51. Smith, A M, Katz, D S and Niemeyer, K E and the FORCE11 Software Citation Working Group 2016, “Software Citation Principles,” PeerJ Computer Science, 2(e86).
  52. Boettiger, C 2015 “An introduction to Docker for reproducible research,” ACM SIGOPS Operating Systems Review, 49(1): 7179. Special Issue on Repeatability and Sharing of Experimental Artifacts. DOI: 10.1145/2723872.2723882
  53. Kauffman, S A 1969 “Metabolic stability and epigenesis in randomly constructed genetic nets,” Journal of Theoretical Biology, 22(3): 43767. DOI: 10.1016/0022-5193(69)90015-0
  54. Schaub, M A, Henzinger, T A and Fisher, J 2007 “Qualitative networks: a symbolic approach to analyze biological signaling networks,” BMC Systems Biology, 1: 4. DOI: 10.1186/1752-0509-1-4
  55. Benque, D, Bourton, S, Cockerton, C, Cook, B, Fisher, J, Ishtiaq, S, Piterman, N, Taylor, A and Vardi, M Y 2012 “BMA: visual tool for modeling and analyzing biological networks,” In: Proceedings of the 24th International Conference on Computer Aided Verification (CAV 2012), of Lecture Notes in Computer Science, 7358: 686692, Springer. DOI: 10.1007/978-3-642-31424-7_50
  56. Chaouiya, C, Berenguier, D, Keating, S M, Naldi, A, van Iersel, M P, Rodriguez, N, Drager, A, Buchel, F, Cokelaer, T, Kowal, B, Wicks, B, Goncalves, E, Dorier, J, Page, M, Monteiro, P T, von Kamp, A, Xenarios, I, de Jong, H, Hucka, M, Klamt, S, Thieffry, D, Le Novere, N, Saez-Rodriguez, J and Helikar, T 2013 “SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools,” BMC Systems Biology, 7.
  57. Moult, J, Fidelis, K, Kryshtafovych, A, Schwede, T and Tramontano, A 2014 “Critical assessment of methods of protein structure prediction (CASP) — round x,” Proteins: Structure, Function, and Bioinformatics, 82: 16. DOI: 10.1002/prot.24452
  58. Lensink, M F, Velankar, S and Wodak, S J 2017 “Modeling proteinprotein and proteinpeptide complexes: Capri 6th edition,” Proteins: Structure, Function, and Bioinformatics, 85(3): 359377.
  59. Hall, B A, Halim, K B A, Buyan, A, Emmanouil, B and Sansom, M S P 2014 “Sidekick for membrane simulations: Automated ensemble molecular dynamics simulations of transmembrane helices,” Journal of Chemical Theory and Computation, 10(5): 21652175. DOI: 10.1021/ct500003g
  60. Ofria, C and Wilke, C O 2004 “Avida: A Software Platform for Research in Computational Evolutionary Biology,” Artificial Life, 10(2): 191229. DOI: 10.1162/106454604773563612
  61. Crick, T, Dunning, P, Kim, H and Padget, J 2009 “Engineering Design Optimization using Services and Workflows,” Philosophical Transactions of the Royal Society A, 367(1898): 27412751.
  62. Olabarriaga, S, Pierantoni, G, Taffoni, G, Sciacca, E, Jaghoori, M, Korkhov, V, Castelli, G, Vuerli, C, Becciani, U, Carley, E and Bentley, B 2014 “Scientific Workflow Management – For Whom?,” in Proceedings of 10th IEEE International Conference on e-Science (e-Science 2014), 298305, IEEE Press. DOI: 10.1109/eScience.2014.8
  63. Hall, B A, Jackson, E, Hajnal, A and Fisher, J 2014 “Logic programming to predict cell fate patterns and retrodict genotypes in organogenesis,” Journal of The Royal Society Interface, 11(98). DOI: 10.1098/rsif.2014.0245
  64. Rollins, N D, Barton, C M, Bergin, S, Janssen, M A and Lee, A 2014 “A Computational Model Library for publishing model documentation and code,” Environmental Modelling & Software, 61: 5964. DOI: 10.1016/j.envsoft.2014.06.022
  65. Vardi, M Y 2014 “Openism, IPism, Fundamentalism, and Pragmatism,” Communications of the ACM, 57(8). DOI: 10.1145/2632265
  66. Hey, T, Tansley, S and Tolle, K (eds.) 2009 The Fourth Paradigm: Data-Intensive Scientific Discovery. Microsoft Research.
DOI: https://doi.org/10.5334/jors.73 | Journal eISSN: 2049-9647
Language: English
Submitted on: Mar 8, 2015
|
Accepted on: Aug 10, 2017
|
Published on: Nov 9, 2017
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2017 Tom Crick, Benjamin A. Hall, Samin Ishtiaq, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.