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The role of metadata in reproducible computational research [article]

Jeremy Leipzig, Daniel Nüst, Charles Tapley Hoyt, Stian Soiland-Reyes, Karthik Ram, Jane Greenberg
2021 arXiv   pre-print
Reproducible computational research (RCR) is the keystone of the scientific method for in silico analyses, packaging the transformation of raw data to published results.  ...  In addition to its role in research integrity, RCR has the capacity to significantly accelerate evaluation and reuse.  ...  Specific to computational facets of scientific research, Reproducible Computational Research (RCR) 5 encompasses all aspects of in silico analyses, from the propagation of raw data collected from the  ... 
arXiv:2006.08589v2 fatcat:txxkodvwezc6bcdngu3by6wnni

Metadata and Reproducibility: A Case Study of Gravitational Wave Research Data Management

Jian Qin, Brian Dobreski, Duncan Brown
2016 International Journal of Digital Curation  
What metadata needs to be captured for tracking, reproducing, and reusing computational results is the starting point in developing metadata models to fulfil these functions of data management.  ...  The complexity of computationally-intensive scientific research poses great challenges for both research data management and research reproducibility.  ...  Acknowledgements This project is supported by the U.S. National Science Foundation grant #ACI-1443047.  ... 
doi:10.2218/ijdc.v11i1.399 fatcat:2dc7a343ubc5hfv34prijt7syy

Understanding experiments and research practices for reproducibility: an exploratory study

Sheeba Samuel, Birgitta König-Ries
2021 PeerJ  
The research practices followed by scientists in each domain play an essential role in the understandability and reproducibility of results.  ...  Insufficient metadata, lack of publicly available data, and incomplete information in study methods are considered to be the main reasons for poor reproducibility.  ...  The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.  ... 
doi:10.7717/peerj.11140 pmid:33976964 pmcid:PMC8067906 fatcat:cpneiyhyibgkjet5py6twwvwqu

The Role of Libraries in the Age of Computational Reproducibility

Vicky Steeves, Gabriele Hayden
2019 Zenodo  
A lighting talk at csv,conf,4 about how libraries and librarians are helping researchers with reproducibility.  ...  in classes ○ Consultations with community to help them make work reproducible • Collection of Research Materials ○ *area of improvement* --making sure the things we collect are reproducible (potential  ...  "… The actual scholarship is the complete software development environment and the complete set of instructions which generated the Figures We are interweaving these into holistic research reproducibility  ... 
doi:10.5281/zenodo.2692863 fatcat:m3rjtsp5ijgoll6ib452beldc4

Most computational hydrology is not reproducible, so is it really science?

Christopher Hutton, Thorsten Wagener, Jim Freer, Dawei Han, Chris Duffy, Berit Arheimer
2016 Water Resources Research  
The prominence of computational research across scientific disciplines-from big data analysis in genomic research to computational modeling in climate science-has brought increased focus on the reproducibility  ...  Yet in computational hydrology the code and data that actually produces published results are not regularly made available, inhibiting the ability of the community to reproduce and verify previous findings  ...  new forms of collaborative research in hydrology.  ... 
doi:10.1002/2016wr019285 fatcat:lh2zkr7jcvd2tfuo4igwbb5ghe

Practices, Challenges, and Prospects of Big Data Curation: a Case Study in Geoscience

Suzhen Chen, Bin Chen
2020 International Journal of Digital Curation  
Having started to embrace the digital age, the community have applied big data and data mining tools into the new type of research.  ...  We also identified current challenges, key elements, and prospects to construct a more robust and future-proof big data infrastructure for research and publication for the future, as well as the roles,  ...  In order to improve scientifc communication, give credit to scientifc contributions, and promote the reproducible and transparent research, reproducibility and computational provenance will be key review  ... 
doi:10.2218/ijdc.v14i1.669 fatcat:ctjzf3ndybd3pkfmunf5vbg5py

From FAIR research data toward FAIR and open research software

Wilhelm Hasselbring, Leslie Carr, Simon Hettrick, Heather Packer, Thanassis Tiropanis
2020 it - Information Technology  
Therefore, research data must be FAIR (Findable, Accessible, Interoperable, and Reusable) in order to advance the findability, reproducibility and reuse of research results.  ...  We review and analyze the current state in this area in order to give recommendations for making research software FAIR and open.  ...  Acknowledgment: The presented work was conducted while the first author was on sabbatical leave at the University of Southampton, UK.  ... 
doi:10.1515/itit-2019-0040 fatcat:pbzb2xiy2vh7hmpk33wdquvqbe

Practices for Data Transparency and Reproducibility: Some thoughts on the role of institutions

Lars Vilhuber
2020 Zenodo  
In the past 30 years, recurring concerns about the extent of replicability (or lack thereof) of the research in various disciplines have surfaced, including in economics.  ...  The solutions to these problems will change the way research will be taught and conducted, in economics in particular, and in the social sciences more broadly.  ...  … and findability relies on metadata A role for institutions?  ... 
doi:10.5281/zenodo.4311917 fatcat:azxfn6xdzjezpdkmozz4kumewa

Software as a first class output in a FAIR ecosystem

Morane Gruenpeter
2021 Zenodo  
Software is a significant and vital component of research. It is integral to all stages of research and can play the role of a tool, a research result, or a research object.  ...  In September 2021 the working group published the first version of the FAIR for Research Software principles after a community review.  ...  Group (Clément-Fontaine, 2019) Make sure the specific nature of software is recognized and not considered as "just data" particularly in the context of discussion about the notion of FAIR data. in the  ... 
doi:10.5281/zenodo.5563027 fatcat:nooxzsiauzb5lj53k6vulbs2n4

FAIRSCAPE: A Framework for FAIR and Reproducible Biomedical Analytics [article]

Maxwell Adam Levinson, Justin Niestroy, Sadnan Al Manir, Karen D. Fairchild, Douglass E. Lake, J. Randall Moorman, Timothy Clark
2020 bioRxiv   pre-print
All results are annotated with FAIR metadata using the evidence graph model for access, validation, reproducibility, and re-use of archived data and software.  ...  It fully implements the FAIR data principles and extends them to provide FAIR Evidence, including provenance of datasets, software and computations, as metadata for all computed results  ...  This work was supported in part by the U.S.  ... 
doi:10.1101/2020.08.10.244947 fatcat:lqlqkjqm3zgqzlfe56e4zkxz6m

Implementing FAIR Data Infrastructures (Dagstuhl Perspectives Workshop 18472)

Natalia Manola, Peter Mutschke, Guido Scherp, Klaus Tochtermann, Peter Wittenburg, Michael Wagner
2019 Dagstuhl Reports  
infrastructures and to shape the role that the field of computer science has to play.  ...  The workshop aimed at bringing together computer scientists with digital infrastructure experts from different domains to discuss open issues implementing and adopting the FAIR principles in research data  ...  Acknowledgements We thank all participants of the workshop for their valuable contributions and the Dagstuhl team who have made this a successful event.  ... 
doi:10.4230/dagrep.8.11.91 dblp:journals/dagstuhl-reports/ManolaMSTW18 fatcat:ckgu7jpr45f67glmu6ce5va74i

Best practice data life cycle approaches for the life sciences

Philippa C. Griffin, Jyoti Khadake, Kate S. LeMay, Suzanna E. Lewis, Sandra Orchard, Andrew Pask, Bernard Pope, Ute Roessner, Keith Russell, Torsten Seemann, Andrew Treloar, Sonika Tyagi (+15 others)
2017 F1000Research  
The simultaneous transitions towards biology as a data science and towards a 'life cycle' view of research data pose new challenges.  ...  Throughout history, the life sciences have been revolutionised by technological advances; in our era this is manifested by advances in instrumentation for data generation, and consequently researchers  ...  Acknowledgements The authors thank Dan Bolser for his involvement in the EMBL-ABR Data Life Cycle workshops, and all workshop participants for sharing their experiences and useful discussions.  ... 
doi:10.12688/f1000research.12344.1 pmid:30109017 pmcid:PMC6069748 fatcat:qoh22nmk4vcjdovnblpkyk3vxq

An Overview of the Apache Airavata Software Stack for Science Gateways

Marlon Pierce, Eroma Abeysinghe, Marcus Christie, Eric Coulter, Suresh Marru, Sudhakar Pamidighantam, Rob Quick, Isuru Ranawaka, Jun Wang, Dimuthu Wannipurage
2021 Zenodo  
for job executions, capturing the metadata needed to audit and reproduce execution outcomes.  ...  usability requirements of different research communities.  ...  The Science Gateways Platform as a Service (SciGaP) is an operational deployment of the Airavata software stack that is run by the Indiana University Cyberinfrastructure Integration Research Center for  ... 
doi:10.5281/zenodo.5569497 fatcat:n3znwekuvjhy3npifzmnb4pwdi

Using ReproZip for Reproducibility and Library Services

Vicky Steeves, Rémi Rampin, Fernando Chirigati
2017 IASSIST Quarterly  
The dependencies required to reproduce the computational environments in which research happens can be exceptionally hard to track – in many cases, these dependencies are hidden or nested too deeply to  ...  Users face challenges in reproducing research across different operating systems, in using different versions of software across long projects and among collaborations, and in using publicly available  ...  Juliana Freire, the Principal Investigator of the ReproZip project, for her support in continuing to build ReproZip. We'd also like to thank Dr.  ... 
doi:10.29173/iq18 fatcat:oj4o6wbelvg7tofm5rf6d2q6tu

Implementing FAIR Data Infrastructures (Dagstuhl Perspectives Workshop 18472)

Natalia Manola, Peter Mutschke, Guido Scherp, Klaus Tochtermann, Peter Wittenburg, Kathleen Gregory, Wilhelm Hasselbring, Kees den Heijer, Paolo Manghi, Dieter Van Uytvanck
2020 Dagstuhl Manifestos  
In order to fulfill the promises of open science, reliable and sustainable research data infrastructures must be developed.  ...  to implementing and promoting the establishment of FAIR-compliant infrastructures for research data.  ...  The workshop was supported by funding of the Leibniz Research Alliance Open Science 107 within the funding line strategic networks of the Leibniz Association.  ... 
doi:10.4230/dagman.8.1.1 dblp:journals/dagstuhl-manifestos/ManolaMSTWGHHMU20 fatcat:6z4yhlp3xzahfp7whrdn3x2xa4
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