Literature DB >> 29854241

ProvCaRe Semantic Provenance Knowledgebase: Evaluating Scientific Reproducibility of Research Studies.

Joshua Valdez1, Matthew Kim2, Michael Rueschman2, Vimig Socrates1, Susan Redline2, Satya S Sahoo1.   

Abstract

Scientific reproducibility is critical for biomedical research as it enables us to advance science by building on previous results, helps ensure the success of increasingly expensive drug trials, and allows funding agencies to make informed decisions. However, there is a growing "crisis" of reproducibility as evidenced by a recent Nature journal survey of more than 1500 researchers that found that 70% of researchers were not able to replicate results from other research groups and more than 50% of researchers were not able reproduce their own research results. In 2016, the National Institutes of Health (NIH) announced the "Rigor and Reproducibility" guidelines to support reproducibility in biomedical research. A key component of the NIH Rigor and Reproducibility guidelines is the recording and analysis of "provenance" information, which describes the origin or history of data and plays a central role in ensuring scientific reproducibility. As part of the NIH Big Data to Knowledge (BD2K)-funded data provenance project, we have developed a new informatics framework called Provenance for Clinical and Healthcare Research (ProvCaRe) to extract, model, and analyze provenance information from published literature describing research studies. Using sleep medicine research studies that have made their data available through the National Sleep Research Resource (NSRR), we have developed an automated pipeline to identify and extract provenance metadata from published literature that is made available for analysis in the ProvCaRe knowledgebase. NSRR is the largest repository of sleep data from over 40,000 studies involving 36,000 participants and we used 75 published articles describing 6 research studies to populate the ProvCaRe knowledgebase. We evaluated the ProvCaRe knowledgebase with 28,474 "provenance triples" using hypothesis-driven queries to identify and rank research studies based on the provenance information extracted from published articles.

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Year:  2018        PMID: 29854241      PMCID: PMC5977728     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  19 in total

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Journal:  Proc AMIA Symp       Date:  2000

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Authors:  Ida Sim; Samson W Tu; Simona Carini; Harold P Lehmann; Brad H Pollock; Mor Peleg; Knut M Wittkowski
Journal:  J Biomed Inform       Date:  2013-11-13       Impact factor: 6.317

Review 4.  Scaling Up Scientific Discovery in Sleep Medicine: The National Sleep Research Resource.

Authors:  Dennis A Dean; Ary L Goldberger; Remo Mueller; Matthew Kim; Michael Rueschman; Daniel Mobley; Satya S Sahoo; Catherine P Jayapandian; Licong Cui; Michael G Morrical; Susan Surovec; Guo-Qiang Zhang; Susan Redline
Journal:  Sleep       Date:  2016-05-01       Impact factor: 5.849

5.  1,500 scientists lift the lid on reproducibility.

Authors:  Monya Baker
Journal:  Nature       Date:  2016-05-26       Impact factor: 49.962

6.  Policy: NIH plans to enhance reproducibility.

Authors:  Francis S Collins; Lawrence A Tabak
Journal:  Nature       Date:  2014-01-30       Impact factor: 49.962

7.  The open biomedical annotator.

Authors:  Clement Jonquet; Nigam H Shah; Mark A Musen
Journal:  Summit Transl Bioinform       Date:  2009-03-01

8.  Informatics and data mining tools and strategies for the human connectome project.

Authors:  Daniel S Marcus; John Harwell; Timothy Olsen; Michael Hodge; Matthew F Glasser; Fred Prior; Mark Jenkinson; Timothy Laumann; Sandra W Curtiss; David C Van Essen
Journal:  Front Neuroinform       Date:  2011-06-27       Impact factor: 4.081

9.  Reproducible Research Practices and Transparency across the Biomedical Literature.

Authors:  Shareen A Iqbal; Joshua D Wallach; Muin J Khoury; Sheri D Schully; John P A Ioannidis
Journal:  PLoS Biol       Date:  2016-01-04       Impact factor: 8.029

10.  Why most published research findings are false.

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Journal:  PLoS Med       Date:  2005-08-30       Impact factor: 11.613

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  2 in total

1.  ProvCaRe: Characterizing scientific reproducibility of biomedical research studies using semantic provenance metadata.

Authors:  Satya S Sahoo; Joshua Valdez; Matthew Kim; Michael Rueschman; Susan Redline
Journal:  Int J Med Inform       Date:  2018-11-03       Impact factor: 4.046

2.  Can reproducibility be improved in clinical natural language processing? A study of 7 clinical NLP suites.

Authors:  William Digan; Aurélie Névéol; Antoine Neuraz; Maxime Wack; David Baudoin; Anita Burgun; Bastien Rance
Journal:  J Am Med Inform Assoc       Date:  2021-03-01       Impact factor: 4.497

  2 in total

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