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Papers here are interdisciplinary and applications-oriented, focusing on techniques and tools that enable challenging computational simulations to be performed, for which the use of supercomputers or distributed computing platforms is often required. Includes material in ACM Subject Classes J.2, J.3, and J.4 (economics).'", "bibtexKey": "samuel2024fair" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2ff633d6d69367b3f746e7e9d361e3c40/diglezakis", "tags" : [ "forschungsdaten","jupyter","reproducibility","review","software" ], "intraHash" : "ff633d6d69367b3f746e7e9d361e3c40", "interHash" : "67afed508c800096507357e959613c2a", "label" : "Computational reproducibility of Jupyter notebooks from biomedical publications", "user" : "diglezakis", "description" : "", "date" : "2023-06-13 11:13:56", "changeDate" : "2023-06-13 11:13:56", "count" : 1, "pub-type": "misc", "year": "2022", "url": "", "author": [ "Sheeba Samuel","Daniel Mietchen" ], "authors": [ {"first" : "Sheeba", "last" : "Samuel"}, {"first" : "Daniel", "last" : "Mietchen"} ], "eprint" : "2209.04308", "archiveprefix" : "arXiv", "primaryclass" : "cs.CE", "bibtexKey": "samuel2022computational" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/291fbd4bda38caff696eaae08a9d40c9e/diglezakis", "tags" : [ "analyticalreproducibility","forschungsdaten","psychology","reproducibility","software" ], "intraHash" : "91fbd4bda38caff696eaae08a9d40c9e", "interHash" : "208c621c75c228a714e7cb963bc84547", "label" : "Studies in Analytical Reproducibility: the Conquaire Project", "user" : "diglezakis", "description" : "", "date" : "2023-02-21 12:48:43", "changeDate" : "2023-02-21 12:48:43", "count" : 1, "pub-type": "book", "year": "2021", "url": "https://pub.uni-bielefeld.de/record/2942780", "author": [ "Philipp Cimiano","Christian Pietsch","Cord Wiljes" ], "authors": [ {"first" : "Philipp", "last" : "Cimiano"}, {"first" : "Christian", "last" : "Pietsch"}, {"first" : "Cord", "last" : "Wiljes"} ], "pages": "8057464 bytes","note": "Artwork Size: 8057464 bytesISBN: 9783943363067Medium: application/pdfPublisher: Universität Bielefeld","abstract": "This book is a direct result of the Conquaire (Continuous Quality Control for Research Data to Ensure Reproducibility) project, which was funded by the DFG between 2016 and 2019. The goal of the project was to understand in how far principles from continuous quality control and test-driven development can be applied to the management of research data to increase its quality and potential for re-use. In order to arrive at such an understanding, we have been closely working together with researchers from different disciplines at Bielefeld University ranging from biology, over chemistry, economics, linguistics, psychology through to computer science / robotics. Within these use cases we have aimed at reproducing one central part of a previously published research article. In doing this, we have limited ourselves to reproducing the computational analysis leading to the particular result, as reproducing the actual experiments would have been outside of the scope of the Conquaire project. The book that lies in front of you documents these eight case studies and describes what we have done to reproduce the specific results. The work conducted in the case studies has provided us with a detailed understanding of the analytical workflows used by all the case study partners and has allowed us to get a deep understanding of barriers and challenges in reproducing published results. The book concludes with recommendations and lessons learned from the practical attempt to reproduce a number of published results.", "copyright" : "Creative Commons Attribution 4.0 International", "shorttitle" : "Studies in Analytical Reproducibility", "doi" : "10.4119/UNIBI/2942780", "urldate" : "2023-02-21", "bibtexKey": "cimiano_studies_2021" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2f6f951b2b1e0587b77c4b4563649279e/hermann", "tags" : [ "berlin","diss","forschungsdaten","reproducibility","software" ], "intraHash" : "f6f951b2b1e0587b77c4b4563649279e", "interHash" : "01d7498336840907ee88166b61328e19", "label" : "Artifact Evaluation: Is It a Real Incentive?", "user" : "hermann", "description" : "", "date" : "2019-11-27 15:03:04", "changeDate" : "2019-12-08 12:45:03", "count" : 1, "pub-type": "inproceedings", "booktitle": "2017 IEEE 13th International Conference on e-Science (e-Science)", "year": "2017", "url": "https://ieeexplore.ieee.org/document/8109184/", "author": [ "B. R. Childers","P. K. Chrysanthis" ], "authors": [ {"first" : "B. R.", "last" : "Childers"}, {"first" : "P. K.", "last" : "Chrysanthis"} ], "pages": "488-489","abstract": "It is well accepted that we learn hard lessons when implementing and re-evaluating systems, yet it is also acknowledged that science faces a crisis in reproducibility. Experimental computer science is far from immune, although it should be easier for CS than other sciences, given the emphasis on experimental artifacts, such as source code, data sets, workflows, parameters, etc. The data management community pioneered methods at ACM SIGMOD 2007 and 2008 to encourage and incentivize authors to improve their software development and experimental practices. Now, after 10 years, the broader CS community has started to adopt Artifact Evaluation (AE) to review artifacts along with papers. In this paper, we examine how AE has incentivized authors, and whether the process is having a measurable impact. Our answer can help guide CS, and more broadly, other computationally-oriented sciences, in encouraging peer-review of software artifacts and developing additional community practices for incentives.", "issn" : "null", "doi" : "10.1109/eScience.2017.79", "bibtexKey": "childers2017artifact" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2e005aeb058ff4034ddb2170612aa4ea5/hermann", "tags" : [ "berlin","diss","forschungsdaten","reproducibility","software" ], "intraHash" : "e005aeb058ff4034ddb2170612aa4ea5", "interHash" : "9fdef98ed4b502bdd22b8549918bbef5", "label" : "Incentivizing reproducibility", "user" : "hermann", "description" : "", "date" : "2019-11-27 14:57:56", "changeDate" : "2019-12-08 12:46:02", "count" : 2, "pub-type": "article", "journal": "Communications of the ACM","publisher":"Association for Computing Machinery (ACM)", "year": "2016", "url": "https://doi.org/10.1145%2F2994031", "author": [ "Ronald F. Boisvert" ], "authors": [ {"first" : "Ronald F.", "last" : "Boisvert"} ], "volume": "59","number": "10","pages": "5--5", "doi" : "10.1145/2994031", "bibtexKey": "Boisvert_2016" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/25d61c30b0b2ac5d6dcd637b668ef88d6/hermann", "tags" : [ "diss","forschungsdaten","reproducibility","software" ], "intraHash" : "5d61c30b0b2ac5d6dcd637b668ef88d6", "interHash" : "1332196bd2ff3e5a8db0a9e4bf9f9232", "label" : "Committing to Data Quality Review", "user" : "hermann", "description" : "", "date" : "2019-10-23 10:57:34", "changeDate" : "2019-11-27 13:55:33", "count" : 2, "pub-type": "article", "journal": "International Journal of Digital Curation","publisher":"Edinburgh University Library", "year": "2014", "url": "https://doi.org/10.2218%2Fijdc.v9i1.317", "author": [ "Limor Peer","Ann Green","Elizabeth Stephenson" ], "authors": [ {"first" : "Limor", "last" : "Peer"}, {"first" : "Ann", "last" : "Green"}, {"first" : "Elizabeth", "last" : "Stephenson"} ], "volume": "9","number": "1","pages": "263--291", "doi" : "10.2218/ijdc.v9i1.317", "bibtexKey": "peer2014committing" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2d2260d8bcf30d2358a8f5113c43706c0/diglezakis", "tags" : [ "artificialIntelligence","forschungsdaten","reproducibility","software" ], "intraHash" : "d2260d8bcf30d2358a8f5113c43706c0", "interHash" : "d751c2dec9822c6feb4557861102c792", "label" : "State of the Art: Reproducibility in Artificial Intelligence", "user" : "diglezakis", "description" : "", "date" : "2018-02-19 08:43:57", "changeDate" : "2018-02-19 07:45:06", "count" : 4, "pub-type": "inproceedings", "booktitle": "Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18)", "year": "2018", "url": "", "author": [ "Odd Erik Gundersen","Sigbjørn Kjensmo" ], "authors": [ {"first" : "Odd Erik", "last" : "Gundersen"}, {"first" : "Sigbjørn", "last" : "Kjensmo"} ], "editor": [ "Sheila McIlraith","Kilian Weinberger" ], "editors": [ {"first" : "Sheila", "last" : "McIlraith"}, {"first" : "Kilian", "last" : "Weinberger"} ], "language" : "en", "eventtitle" : "The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18)", "eventdate" : "February 2\u20137, 2018", "venue" : "New Orleans, Louisiana, USA", "bibtexKey": "gundersen2018state" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2c487a1a1262bde3205470f7bdc0579a1/diglezakis", "tags" : [ "reproducibility","software","softwareLizenzMotivation" ], "intraHash" : "c487a1a1262bde3205470f7bdc0579a1", "interHash" : "2d7cb8674f6207a5415b3be74710752b", "label" : "Repeatability and Benefaction in Computer Systems Research", "user" : "diglezakis", "description" : "", "date" : "2017-09-13 10:24:53", "changeDate" : "2017-09-13 08:24:53", "count" : 2, "pub-type": "misc", "year": "2015", "url": "http://reproducibility.cs.arizona.edu/v2/RepeatabilityTR.pdf", "author": [ "Christian Collberg","Todd Proebsting","Alex M. Warren" ], "authors": [ {"first" : "Christian", "last" : "Collberg"}, {"first" : "Todd", "last" : "Proebsting"}, {"first" : "Alex M.", "last" : "Warren"} ], "abstract": "e describe a study into the extent to which Computer Systems researchers share their\r\ncode and data and the extent to which such code builds. Starting with 601 papers from ACM\r\nconferences and journals, we examine 402 papers whose results were backed by code. For 32.3%\r\nof these papers we were able to obtain the code and build it within 30 minutes; for 48.3% of the\r\npapers we managed to build the code, but it may have required extra effort; for 54.0% of the\r\npapers either\r\nwe\r\nmanaged to build the code or the authors stated the code would build with\r\nreasonable effort. We also propose a novel\r\nsharing specification\r\nscheme that requires researchers\r\nto specify the level of sharing that reviewers and readers can assume from a paper", "urldate" : "21.6.2017", "bibtexKey": "collberg2015repeatability" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/28bf997c8af607c68320a5df06e82c49b/diglezakis", "tags" : [ "docker","forschungsdaten","reproducibility","software","softwareLizenzMotivation" ], "intraHash" : "8bf997c8af607c68320a5df06e82c49b", "interHash" : "ff6c224775947fbda408aea734165c00", "label" : "An Introduction to Docker for Reproducible Research", "user" : "diglezakis", "description" : "An introduction to Docker for reproducible research", "date" : "2017-09-12 16:24:17", "changeDate" : "2017-09-12 14:24:17", "count" : 2, "pub-type": "article", "journal": "SIGOPS Oper. Syst. Rev.","publisher":"ACM","address":"New York, NY, USA", "year": "2015", "url": "http://doi.acm.org/10.1145/2723872.2723882", "author": [ "Carl Boettiger" ], "authors": [ {"first" : "Carl", "last" : "Boettiger"} ], "volume": "49","number": "1","pages": "71--79","abstract": "As computational work becomes more and more integral to many aspects of scientific research, computational reproducibility has become an issue of increasing importance to computer systems researchers and domain scientists alike. Though computational reproducibility seems more straight forward than replicating physical experiments, the complex and rapidly changing nature of computer environments makes being able to reproduce and extend such work a serious challenge. In this paper, I explore common reasons that code developed for one research project cannot be successfully executed or extended by subsequent researchers. I review current approaches to these issues, including virtual machines and workflow systems, and their limitations. I then examine how the popular emerging technology Docker combines several areas from systems research - such as operating system virtualization, cross-platform portability, modular re-usable elements, versioning, and a 'DevOps' philosophy, to address these challenges. I illustrate this with several examples of Docker use with a focus on the R statistical environment.", "issn" : "0163-5980", "acmid" : "2723882", "numpages" : "9", "issue_date" : "January 2015", "doi" : "10.1145/2723872.2723882", "bibtexKey": "Boettiger:2015:IDR:2723872.2723882" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/21b2f1b7a72c7629661584420a78bc024/diglezakis", "tags" : [ "forschungsdaten","litQSaFE","reproducibility","software","softwareLizenzMotivation" ], "intraHash" : "1b2f1b7a72c7629661584420a78bc024", "interHash" : "aa297c505dfda47a883e70b721a423bc", "label" : "Enhancing reproducibility for computational methods", "user" : "diglezakis", "description" : "", "date" : "2017-09-12 16:13:59", "changeDate" : "2018-08-22 15:22:18", "count" : 2, "pub-type": "article", "journal": "Science","publisher":"American Association for the Advancement of Science (AAAS)", "year": "2016", "url": "http://dx.doi.org/10.1126/science.aah6168", "author": [ "Victoria Stodden","Marcia McNutt","David H. Bailey","Ewa Deelman","Yolanda Gil","Brooks Hanson","Michael A. Heroux","John P.A. Ioannidis","Michela Taufer" ], "authors": [ {"first" : "Victoria", "last" : "Stodden"}, {"first" : "Marcia", "last" : "McNutt"}, {"first" : "David H.", "last" : "Bailey"}, {"first" : "Ewa", "last" : "Deelman"}, {"first" : "Yolanda", "last" : "Gil"}, {"first" : "Brooks", "last" : "Hanson"}, {"first" : "Michael A.", "last" : "Heroux"}, {"first" : "John P.A.", "last" : "Ioannidis"}, {"first" : "Michela", "last" : "Taufer"} ], "volume": "354","number": "6317","pages": "1240\u20131241", "eprint" : "http://science.sciencemag.org/content/354/6317/1240.full.pdf", "issn" : "0036-8075", "doi" : "10.1126/science.aah6168", "bibtexKey": "Stodden1240" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2c7971d8d6a474e4c5bf8a30d62d04ede/diglezakis", "tags" : [ "forschungsdaten","framework","hpc-computing","metadata","repository","software","softwareLizenzMotivation","reproducibility" ], "intraHash" : "c7971d8d6a474e4c5bf8a30d62d04ede", "interHash" : "8aa55fa398b71ec36da3eb98d8fff42e", "label" : "AiiDA: automated interactive infrastructure and database for computational science", "user" : "diglezakis", "description" : "", "date" : "2017-09-12 15:52:49", "changeDate" : "2017-09-12 14:22:14", "count" : 2, "pub-type": "article", "journal": "Computational Materials Science", "year": "2016", "url": "http://www.sciencedirect.com/science/article/pii/S0927025615005820", "author": [ "Giovanni Pizzi","Andrea Cepellotti","Riccardo Sabatini","Nicola Marzari","Boris Kozinsky" ], "authors": [ {"first" : "Giovanni", "last" : "Pizzi"}, {"first" : "Andrea", "last" : "Cepellotti"}, {"first" : "Riccardo", "last" : "Sabatini"}, {"first" : "Nicola", "last" : "Marzari"}, {"first" : "Boris", "last" : "Kozinsky"} ], "volume": "111","pages": "218 - 230","abstract": "Abstract Computational science has seen in the last decades a spectacular rise in the scope, breadth, and depth of its efforts. Notwithstanding this prevalence and impact, it is often still performed using the renaissance model of individual artisans gathered in a workshop, under the guidance of an established practitioner. Great benefits could follow instead from adopting concepts and tools coming from computer science to manage, preserve, and share these computational efforts. We illustrate here our paradigm sustaining such vision, based around the four pillars of Automation, Data, Environment, and Sharing. We then discuss its implementation in the open-source AiiDA platform (http://www.aiida.net), that has been tuned first to the demands of computational materials science. AiiDA\u2019s design is based on directed acyclic graphs to track the provenance of data and calculations, and ensure preservation and searchability. Remote computational resources are managed transparently, and automation is coupled with data storage to ensure reproducibility. Last, complex sequences of calculations can be encoded into scientific workflows. We believe that AiiDA\u2019s design and its sharing capabilities will encourage the creation of social ecosystems to disseminate codes, data, and scientific workflows.", "issn" : "0927-0256", "doi" : "https://doi.org/10.1016/j.commatsci.2015.09.013", "bibtexKey": "Pizzi2016218" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/284f8f8874293ce8f3f8c13d8228c5683/diglezakis", "tags" : [ "forschungsdaten","software","softwareLizenzMotivation","reproducibility" ], "intraHash" : "84f8f8874293ce8f3f8c13d8228c5683", "interHash" : "0a99c348d474e63e0cfd60e374170940", "label" : "Lessons from the JMCB archive", "user" : "diglezakis", "description" : "", "date" : "2017-09-12 15:35:32", "changeDate" : "2017-09-12 14:22:14", "count" : 1, "pub-type": "article", "journal": "Journal of money credit and banking", "year": "2006", "url": "http://dx.doi.org/10.1353/mcb.2006.0061", "author": [ "Kerry Anne McGeary","B. D. McCullough","Teresa Harrison" ], "authors": [ {"first" : "Kerry Anne", "last" : "McGeary"}, {"first" : "B. D.", "last" : "McCullough"}, {"first" : "Teresa", "last" : "Harrison"} ], "volume": "38","number": "4","pages": "1093-1107","abstract": "We examine the online archive of the Journal of Money, Credit, and Banking, in which an author is required to deposit the data and code that replicate the results of his paper. We find that most authors do not fulfill this requirement. Of more than 150 empirical articles, fewer than 15 could be replicated. Despite all this, there is no doubt that a data/code archive is more conducive to replicable research than the alternatives. We make recommendations to improve the functioning of the archive.", "doi" : "10.1353/mcb.2006.0061", "bibtexKey": "noauthororeditor" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2f00c070a260ea2e9a2eca96dda6f0924/diglezakis", "tags" : [ "forschungsdaten","litQSaFE","medizin","reproducibility","software","softwareLizenzMotivation" ], "intraHash" : "f00c070a260ea2e9a2eca96dda6f0924", "interHash" : "f3617952fb4dc7d1497ed5f8b31c4e69", "label" : "Ten Simple Rules for Reproducible Computational Research", "user" : "diglezakis", "description" : "", "date" : "2017-09-12 13:18:39", "changeDate" : "2018-08-22 15:26:06", "count" : 3, "pub-type": "article", "journal": "PLOS Computational Biology","publisher":"Public Library of Science", "year": "2013", "url": "https://doi.org/10.1371/journal.pcbi.1003285", "author": [ "Geir Kjetil Sandve","Anton Nekrutenko","James Taylor","Eivind Hovig" ], "authors": [ {"first" : "Geir Kjetil", "last" : "Sandve"}, {"first" : "Anton", "last" : "Nekrutenko"}, {"first" : "James", "last" : "Taylor"}, {"first" : "Eivind", "last" : "Hovig"} ], "volume": "9","number": "10","pages": "1-4","abstract": "Rule 1: For Every Result, Keep Track of How It Was Produced\r\nRule 2: Avoid Manual Data Manipulation Steps\r\nRule 3: Archive the Exact Versions of All External Programs Used\r\nRule 4: Version Control All Custom Scripts\r\nRule 5: Record All Intermediate Results, When Possible in Standardized Formats\r\nRule 6: For Analyses That Include Randomness, Note Underlying Random Seeds\r\nRule 7: Always Store Raw Data behind Plots\r\nRule 8: Generate Hierarchical Analysis Output, Allowing Layers of Increasing Detail to Be Inspected\r\nRule 9: Connect Textual Statements to Underlying Results\r\nRule 10: Provide Public Access to Scripts, Runs, and Results", "doi" : "10.1371/journal.pcbi.1003285", "bibtexKey": "10.1371/journal.pcbi.1003285" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/202f0bc01de3bd9cc0f2981d88cdfe6f2/diglezakis", "tags" : [ "forschungsdaten","repository","software","reproducibility" ], "intraHash" : "02f0bc01de3bd9cc0f2981d88cdfe6f2", "interHash" : "02965e087ae869fbe43f767142217f5a", "label" : "Git can facilitate greater reproducibility and increased transparency in science", "user" : "diglezakis", "description" : "", "date" : "2017-09-12 11:31:34", "changeDate" : "2017-09-12 14:22:14", "count" : 2, "pub-type": "article", "journal": "Source Code for Biology and Medicine", "year": "2013", "url": "https://doi.org/10.1186/1751-0473-8-7", "author": [ "Karthik Ram" ], "authors": [ {"first" : "Karthik", "last" : "Ram"} ], "volume": "8","number": "1","pages": "7","abstract": "Reproducibility is the hallmark of good science. Maintaining a high degree of transparency in scientific reporting is essential not just for gaining trust and credibility within the scientific community but also for facilitating the development of new ideas. Sharing data and computer code associated with publications is becoming increasingly common, motivated partly in response to data deposition requirements from journals and mandates from funders. Despite this increase in transparency, it is still difficult to reproduce or build upon the findings of most scientific publications without access to a more complete workflow.", "issn" : "1751-0473", "doi" : "10.1186/1751-0473-8-7", "bibtexKey": "Ram2013" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/24939e810ebe3299fcd41d8b7366726c7/diglezakis", "tags" : [ "forschungsdaten","software","reproducibility" ], "intraHash" : "4939e810ebe3299fcd41d8b7366726c7", "interHash" : "592d1db10662e3bb4b40da9c1aa50974", "label" : "Madagascar: open-source software project for multidimensional data analysis and reproducible computational experiments", "user" : "diglezakis", "description" : "Madagascar: open-source software project for multidimensional data analysis and reproducible computational experiments", "date" : "2017-09-12 11:21:10", "changeDate" : "2017-09-12 14:22:14", "count" : 1, "pub-type": "article", "journal": "Journal of Open Research Software", "year": "2013", "url": "http://dx.doi.org/10.5334/jors.ag", "author": [ "Sergey Fomel","Paul Sava","Ioan Vlad","Yang Liu","Vladimir Bashkardin" ], "authors": [ {"first" : "Sergey", "last" : "Fomel"}, {"first" : "Paul", "last" : "Sava"}, {"first" : "Ioan", "last" : "Vlad"}, {"first" : "Yang", "last" : "Liu"}, {"first" : "Vladimir", "last" : "Bashkardin"} ], "volume": "1","number": "1","abstract": "The Madagascar software package is designed for analysis of large-scale multidimensional data, such as those occurring in exploration geophysics. Madagascar provides a framework for reproducible research. By \u201Creproducible research\u201D we refer to the discipline of attaching software codes and data to computational results reported in publications. The package contains a collection of (a) computational modules, (b) data-processing scripts, and (c) research papers. Madagascar is distributed on SourceForge under a GPL v2 license https://sourceforge.net/projects/rsf/. By October 2013, more than 70 people from different organizations around the world have contributed to the project, with increasing year-to-year activity. The Madagascar website is http://www.ahay.org/.", "doi" : "10.5334/jors.ag", "bibtexKey": "fomel2013madagas" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2771d6e39b5ef728ddef2a555d22b4ad9/diglezakis", "tags" : [ "forschungsdaten","software","reproducibility" ], "intraHash" : "771d6e39b5ef728ddef2a555d22b4ad9", "interHash" : "af4aed7ea1c8c68d6ee2cb292d540a42", "label" : "ALAN TURING INSTITUTE SYMPOSIUM ON REPRODUCIBILITY FOR DATA-INTENSIVE RESEARCH--FINAL REPORT", "user" : "diglezakis", "description" : "", "date" : "2017-09-12 08:08:33", "changeDate" : "2017-09-12 14:22:14", "count" : 1, "pub-type": "article", "year": "2016", "url": "", "author": [ "Lucie C Burgess","David Crotty","David de Roure","Jeremy Gibbons","Carole Goble","Paolo Missier","Richard Mortier","Thomas E Nichols","Richard O\u2019Beirne" ], "authors": [ {"first" : "Lucie C", "last" : "Burgess"}, {"first" : "David", "last" : "Crotty"}, {"first" : "David", "last" : "de Roure"}, {"first" : "Jeremy", "last" : "Gibbons"}, {"first" : "Carole", "last" : "Goble"}, {"first" : "Paolo", "last" : "Missier"}, {"first" : "Richard", "last" : "Mortier"}, {"first" : "Thomas E", "last" : "Nichols"}, {"first" : "Richard", "last" : "O\u2019Beirne"} ], "bibtexKey": "burgess2016alan" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2d94d9765f54e55192a4a11c450c178ac/diglezakis", "tags" : [ "software","softwareLizenzMotivation","reproducibility" ], "intraHash" : "d94d9765f54e55192a4a11c450c178ac", "interHash" : "6f1000d38dfdf29777318905edd5adf9", "label" : "Reproducible Research for Scientific Computing: Tools and Strategies for Changing the Culture.", "user" : "diglezakis", "description" : "Reproducible Research for Scientific Computing: Tools and Strategies for Changing the Culture - IEEE Journals & Magazine", "date" : "2017-09-06 15:04:12", "changeDate" : "2017-09-12 14:22:14", "count" : 2, "pub-type": "article", "journal": "Computing in Science Engineering", "year": "2012", "url": "http://ieeexplore.ieee.org/document/6171147/", "author": [ "Victoria Stodden","Randall J. LeVeque","Ian Mitchell" ], "authors": [ {"first" : "Victoria", "last" : "Stodden"}, {"first" : "Randall J.", "last" : "LeVeque"}, {"first" : "Ian", "last" : "Mitchell"} ], "volume": "14","number": "4","pages": "13-17","abstract": "This article considers the obstacles involved in creating reproducible computational research as well as some efforts and approaches to overcome them.", "issn" : "1521-9615", "doi" : "10.1109/MCSE.2012.38", "bibtexKey": "6171147" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2d33566e93f18449cf91212c7ac11e67b/diglezakis", "tags" : [ "journals","software","softwareLizenzMotivation","reproducibility" ], "intraHash" : "d33566e93f18449cf91212c7ac11e67b", "interHash" : "932688cac193b5620c22c8a110b8ae94", "label" : "Toward Reproducible Computational Research: An Empirical Analysis of Data and Code Policy Adoption by Journals", "user" : "diglezakis", "description" : "Toward Reproducible Computational Research: An Empirical Analysis of Data and Code Policy Adoption by Journals", "date" : "2017-09-06 14:45:13", "changeDate" : "2017-09-12 14:22:14", "count" : 1, "pub-type": "article", "journal": "PLOS ONE","publisher":"Public Library of Science", "year": "2013", "url": "https://doi.org/10.1371/journal.pone.0067111", "author": [ "Victoria Stodden","Peixuan Guo","Zhaokun Ma" ], "authors": [ {"first" : "Victoria", "last" : "Stodden"}, {"first" : "Peixuan", "last" : "Guo"}, {"first" : "Zhaokun", "last" : "Ma"} ], "volume": "8","number": "6","pages": "1-8","abstract": "Journal policy on research data and code availability is an important part of the ongoing shift toward publishing reproducible computational science. This article extends the literature by studying journal data sharing policies by year (for both 2011 and 2012) for a referent set of 170 journals. We make a further contribution by evaluating code sharing policies, supplemental materials policies, and open access status for these 170 journals for each of 2011 and 2012. We build a predictive model of open data and code policy adoption as a function of impact factor and publisher and find higher impact journals more likely to have open data and code policies and scientific societies more likely to have open data and code policies than commercial publishers. We also find open data policies tend to lead open code policies, and we find no relationship between open data and code policies and either supplemental material policies or open access journal status. Of the journals in this study, 38% had a data policy, 22% had a code policy, and 66% had a supplemental materials policy as of June 2012. This reflects a striking one year increase of 16% in the number of data policies, a 30% increase in code policies, and a 7% increase in the number of supplemental materials policies. We introduce a new dataset to the community that categorizes data and code sharing, supplemental materials, and open access policies in 2011 and 2012 for these 170 journals.", "doi" : "10.1371/journal.pone.0067111", "bibtexKey": "10.1371/journal.pone.0067111" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/219a32d2ea53f342e07923d2361022e26/hermann", "tags" : [ "forschungsdaten","reproducibility","software" ], "intraHash" : "19a32d2ea53f342e07923d2361022e26", "interHash" : "aa297c505dfda47a883e70b721a423bc", "label" : "Enhancing reproducibility for computational methods", "user" : "hermann", "description" : "", "date" : "2017-06-21 17:24:22", "changeDate" : "2017-06-21 15:25:06", "count" : 2, "pub-type": "article", "journal": "Science","publisher":"American Association for the Advancement of Science (AAAS)", "year": "2016", "url": "http://dx.doi.org/10.1126/science.aah6168", "author": [ "V. Stodden","M. McNutt","D. H. Bailey","E. Deelman","Y. Gil","B. Hanson","M. A. Heroux","J. P. A. Ioannidis","M. Taufer" ], "authors": [ {"first" : "V.", "last" : "Stodden"}, {"first" : "M.", "last" : "McNutt"}, {"first" : "D. H.", "last" : "Bailey"}, {"first" : "E.", "last" : "Deelman"}, {"first" : "Y.", "last" : "Gil"}, {"first" : "B.", "last" : "Hanson"}, {"first" : "M. A.", "last" : "Heroux"}, {"first" : "J. P. A.", "last" : "Ioannidis"}, {"first" : "M.", "last" : "Taufer"} ], "volume": "354","number": "6317","pages": "1240\u20131241", "doi" : "10.1126/science.aah6168", "bibtexKey": "stodden2016enhancing" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2c487a1a1262bde3205470f7bdc0579a1/hermann", "tags" : [ "reproducibility","software","zitieren" ], "intraHash" : "c487a1a1262bde3205470f7bdc0579a1", "interHash" : "2d7cb8674f6207a5415b3be74710752b", "label" : "Repeatability and Benefaction in Computer Systems Research", "user" : "hermann", "description" : "", "date" : "2017-06-21 06:11:26", "changeDate" : "2017-06-21 07:46:13", "count" : 2, "pub-type": "misc", "year": "2015", "url": "http://reproducibility.cs.arizona.edu/v2/RepeatabilityTR.pdf", "author": [ "Christian Collberg","Todd Proebsting","Alex M. Warren" ], "authors": [ {"first" : "Christian", "last" : "Collberg"}, {"first" : "Todd", "last" : "Proebsting"}, {"first" : "Alex M.", "last" : "Warren"} ], "abstract": "e describe a study into the extent to which Computer Systems researchers share their\r\ncode and data and the extent to which such code builds. Starting with 601 papers from ACM\r\nconferences and journals, we examine 402 papers whose results were backed by code. For 32.3%\r\nof these papers we were able to obtain the code and build it within 30 minutes; for 48.3% of the\r\npapers we managed to build the code, but it may have required extra effort; for 54.0% of the\r\npapers either\r\nwe\r\nmanaged to build the code or the authors stated the code would build with\r\nreasonable effort. We also propose a novel\r\nsharing specification\r\nscheme that requires researchers\r\nto specify the level of sharing that reviewers and readers can assume from a paper", "urldate" : "21.6.2017", "bibtexKey": "collberg2015repeatability" } ] }