Daniel Garijo
Skip Abstract Section
Abstract
The reproducibility of scientific experiments is crucial for corroborating, consolidating and reusing new scientific discoveries. However, the constant pressure for publishing results (Fanelli, 2010) has removed reproducibility from the agenda of many researchers: in a recent survey published in Nature (with more than 1500 scientists) over 70% of the participants recognize to have failed to reproduce the work from another colleague at some point in time (Baker, 2016). Analyses from psychology and cancer biology show reproducibility rates below 40% and 10% respectively (Collaboration, 2015) (Begley & Lee, 2012). As a consequence, retractions of publications have occurred in the last years in several disciplines (Marcus & Oransky, 2014) (Rockoff, 2015), and the general public is now skeptical about scientific studies on topics like pesticides, depression drugs or flu pandemics (American, 2010).
- American, S. (2010, October). In Science We Trust: Poll Results on How you Feel about Science. Scientific American.Google Scholar
- Baker, M. (2016). 1,500 scientists lift the lid on reproducibility. Nature, 533(7604). Retrieved from http://www.nature.com/news/1-500-scientists-lift-the-lid-on-reproducibility-1.19970Google Scholar
- Begley, C., & Lee, M. (2012, March). Drug development: Raise standards for preclinical cancer research., 483, 531--533.Google Scholar
- Belhajjame, K., Zhao, J., Garijo, D., Gamble, M., Hettne, K., Palma, R., ... Goble, C. (2015). Using a suite of ontologies for preserving workflow-centric Research Objects. Web Semantics: Science, Services and Agents on the World Wide Web. Google ScholarDigital Library
- Belhajjame, K., Zhao, J., Garijo, D., Garrido, A., Soiland-Reyes, S., Alper, P., & Corcho, O. (2013). A workflow PROV-corpus based on Taverna and Wings. In Proceedings of the Joint EDBT/ICDT 2013 Workshops (pp. 331--332). Genoa, Italy: ACM. Retrieved from Google ScholarDigital Library
- Bergmann, R., & Gil, Y. (2014). Similarity assessment and efficient retrieval of semantic workflows. Information Systems, 40, 115 -- 127. Retrieved from http://www.sciencedirect.com /science/article/pii/S0306437912001020 Google ScholarDigital Library
- Callahan, S. P., Freire, J., Santos, E., Scheidegger, C. E., Silva, C. T., & Vo, H. T. (2006). Vistrails: Visualization meets data management. In In ACM SIGMOD (pp. 745--747). ACM Press. Google ScholarDigital Library
- Chirigati, F., Shasha, D., & Freire, J. (2013). ReproZip: Using Provenance to Support Computational Reproducibility. In Proceedings of the 5th USENIX Workshop on the Theory and Practice of Provenance (pp. 1:1-1:4). Lombard, Illinois: USENIX Association. Retrieved from http://dl.acm.org/citation.cfm?id=2482949.2482951 Google ScholarDigital Library
- Collaboration, O. S. (2015). Estimating the reproducibility of psychological science. Science, 349(6251).Google Scholar
- Deelman, E., Blythe, J., Gil, Y., Kesselman, C., Mehta, G., Patil, S., ... Livny, M. (2004). Pegasus: Mapping Scientific Workflows onto the Grid. In M. Dikaiakos (Ed.), Grid Computing (Vol. 3165, pp. 11--20). Springer Berlin / Heidelberg.Google Scholar
- Dinov, I. D., Horn, J. D. V., Lozev, K. M., Magsipoc, R., Petrosyan, P., Liu, Z., ... Toga, A. W. (2009). Efficient, Distributed and Interactive Neuroimaging Data Analysis Using the LONI Pipeline. In Frontiers in Neuroinformatics (Vol. 3).Google Scholar
- Fanelli, D. (2010). Do Pressures to Publish Increase Scientists Bias? An Empirical Support from US States Data. PLoS ONE, 5(4). .0010271.Google ScholarCross Ref
- Filgueira, R., Atkinson, M., Bell, A., Main, I., Boon, S., Kilburn, C., & Meredith, P. (2014). eScience Gateway Stimulating Collaboration in Rock Physics and Volcanology. In e-Science (e-Science), 2014 IEEE 10th International Conference on (Vol. 1, pp. 187--195). IEEE. Google ScholarDigital Library
- Garijo, D., Corcho, O., Gil, Y., Braskie, M. N., Hibar, D., Hua, X., ... W.Toga, A. (2014). Workflow Reuse in Practice: A Study of Neuroimaging Pipeline Users. In 10th IEEE International Conference on eScience 2014. Google ScholarDigital Library
- Garijo, D., & Gil, Y. (2011). A New Approach for Publishing Workflows: Abstractions, Standards, and Linked Data. In Proceedings of the 6th workshop on Workflows in support of large-scale science (pp. 47--56). Seattle: ACM. Retrieved from http://dl.acm.org/citation.cfm?id=2110504 Google ScholarDigital Library
- Garijo, D., Kinnings, S., Xie, L., Xie, L., Zhang, Y., Bourne, P. E., & Gil, Y. (2013). Quantifying Reproducibility in Computational Biology: The Case of the Tuberculosis Drugome. PLoS ONE, 8(11), e80278. Retrieved fromGoogle ScholarCross Ref
- Giardine, B., Riemer, C., Hardison, R. C., Burhans, R., Elnitski, L., Shah, P., ... Nekrutenko, A. (2005, October). Galaxy: a platform for interactive large- scale genome analysis. Genome Research, 15(10), 1451--1455.Google ScholarCross Ref
- Gil, Y., Deelman, E., Ellisman, M., Fahringer, T., Fox, G., Gannon, D., ... Myers, J. (2007, December). Examining the Challenges of Scientific Workflows. Computer, 40(12), 24--32. .2007.421 Google ScholarDigital Library
- Gil, Y., Ratnakar, V., Kim, J., Gonzlez-Calero, P. A., Groth, P. T., Moody, J., & Deelman, E. (2011). Wings: Intelligent Workflow- Based Design of Computational Experiments. IEEE Intelligent Systems, 26(1), 62--72. Google ScholarDigital Library
- Goderis, A. (2008). Workflow re-use and discovery in Bioinformatics (Unpublished doctoral dissertation). School of Computer Science, The University of Manchester.Google Scholar
- Goderis, A., Sattler, U., Lord, P., & Goble, C. (2005). Seven Bottlenecks to Workflow Reuse and Repurposing. In The Semantic Web ISWC 2005 (Vol. 3729, pp. 323--337). Springer Berlin Heidelberg. Retrieved from Google ScholarDigital Library
- Holl, S. (2014). Automated Optimization Methods for Scientific Workflows in e-Science Infrastructures (Doctoral dissertation, University of Bonn). Retrieved from http://hss.ulb.uni-bonn.de/2014/3508/3508.htmGoogle Scholar
- Lebo, T., McGuiness, D., Belhajjame, K., Cheney, J., Corsar, D., Garijo, D., ... Zhao, J. (2013, April). The PROV ontology, W3c Recommendation (Tech. Rep.). WWW Consortium. Retrieved from http://www.w3.org/TR/2013/REC-prov-o-20130430/Google Scholar
- Ludscher, B., Altintas, I., Berkley, C., Higgins, D., Jaeger, E., Jones, M., ... Zhao, Y. (2006). Scientific workflow management and the Kepler system. Concurrency and Computation: Practice and Experience, 18(10), 1039--1065. Google ScholarDigital Library
- Marcus, A., & Oransky, I. (2014, December). Top retractions of 2014. The Scientist.Google Scholar
- Mates, P., Santos, E., Freire, J., & Silva, C. T. (2011). CrowdLabs: Social Analysis and Visualization for the Sciences. In 23rd International Conference on Scientific and Statistical Database Management (SS-DBM) (pp. 555--564). Springer. Google ScholarDigital Library
- Missier, P., Dey, S., Belhajjame, K., Cuevas-Vicenttn, V., & Ludscher, B. (2013). D-PROV: Extending the PROV Provenance Model with Workflow Structure. In Proceedings of the 5th USENIX Workshop on the Theory and Practice of Provenance (pp. 9:1-9:7). Lombard, Illinois: USENIX Association. Retrieved from http://dl.acm.org/citation .cfm?id=2482949.2482961 Google ScholarDigital Library
- Qasha, W., Cala, J., & Watson, P. (2016). A Framework for Scientific Workflow Reproducibility in the Cloud. In IEEE 12th International Conference on eScience.Google ScholarCross Ref
- Rockoff, J. D. (2015, September). Amgen Finds Data Falsified in Obesity-Diabetes Study Featuring Grizzly Bears. The Wall Street Journal. Retrieved from http://www.wsj.com/articles/amgen-finds-data-falsified-in-obesity-diabetes-study-featuring-grizzly-bears-1441123200Google Scholar
- Roure, D. D., Goble, C. A., & Stevens, R. (2009). The design and realisation of the myExperiment Virtual Research Environment for social sharing of workflows. Future Generation Comp. Syst., 25(5), 561--567. Google ScholarDigital Library
- Santana-Prez, I., & Prez-Hernndez, M. (2015). Towards Reproducibility in Scientific Workflows: An Infrastructure-Based Approach. Scientific Programming, 2015, 11. / 243180Google Scholar
- Starlinger, J., Brancotte, B., Cohen-Boulakia, S., & Leser, U. (2014). Similarity Search for Scientific Workflows. Proceedings of the VLDB Endowment, 7(12), 1143--1154. Google ScholarDigital Library
- Taylor, I. J., Deelman, E., Gannon, D. B., & Shields, M. (2006). Workflows for e-Science: Scientific Workflows for Grids. Secaucus, NJ, USA: Springer-Verlag New York, Inc. Google ScholarDigital Library
- Wolstencroft, K., Haines, R., Fellows, D., Williams, A., Withers, D., Owen, S., ... Goble, C. (2013). The Taverna workflow suite: designing and executing workflows of Web Services on the desktop, web or in the cloud. Nucleic Acids Research.Google Scholar
Recommendations
How can revivals of scientific publications be explained using bibliometric methods? A case study discovering booster papers for the 1985 Physics Nobel Prize paper
AbstractThe unusual citation profile of the 1985 Physics Nobel Prize paper has been analyzed. The number of citing papers per year exhibits a maximum of 123 citations in the mid-1980s and increases to more than 200 citations about two decades later. The ...
Journal self-citation study for semiconductor literature: synchronous and diachronous approach
Special issue: InformetricsThe present study investigates the self-citations of the most productive semiconductor journals by synchronous (self-citing rate) and diachronous (self-cited rate) approaches. Journal's productivity of 100 most productive semiconductor journals was ...
Team size and retracted citations reveal the patterns of retractions from 1981 to 2020
AbstractThe growth of the retraction databases reveals the disturbing trend in science and also the rising trend of citations of retracted papers is a serious concern. The objective of the study is to investigate the patterns of retractions through the ...
Comments