Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

If these data could talk.

Thomas Pasquier1, Matthew K Lau2, Ana Trisovic3,4

  • 1School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.

Scientific Data
|September 6, 2017
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Climate change intensifies plant-pollinator mismatch and increases secondary extinction risk for plants in northern latitudes.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

The LHCb Sprucing and Analysis Productions.

Computing and software for big science·2025
Same author

Incorporating responses of traits to changing climates into species distribution models: a path forward.

The New phytologist·2025
Same author

Bridging data silos to holistically model plant macrophenology.

The New phytologist·2025
Same author

Coexposure to extreme heat, wildfire burn zones, and wildfire smoke in the Western US from 2006 to 2020.

Science advances·2025
Same author

Optimal Sparse Survival Trees.

Proceedings of machine learning research·2024
Same journal

Dataset of Optimized Structures of Aliphatic Chains Chemisorbed on Si(110) and Si(111) Surfaces via First-Principles Methods.

Scientific data·2026
Same journal

EURO-PROBE - Manual segmentations of the prostate and intraprostatic urethra on T2-weighted MRI.

Scientific data·2026
Same journal

Chromosome-Level Genome Assembly of Southern Africa Mozambique Tilapia (Oreochromis mossambicus) using PacBio HiFi and Omni-C sequencing.

Scientific data·2026
Same journal

Ovarian Stainology: Database of evidence-based immunohistochemical antigen expression in ovarian tumors.

Scientific data·2026
Same journal

A dataset of small protein conformational ensembles from all-atom molecular dynamics simulations.

Scientific data·2026
Same journal

A real-world Fitbit-derived dataset of activity, sleep, and heart rate with matched clinical factors in on-treatment lung cancer patients.

Scientific data·2026
See all related articles

Formalizing scientific reporting enhances research reproducibility. Data provenance provides systematic records linking data, analysis, and publications, improving clarity and efficiency in data-driven science.

Area of Science:

  • Scientific inquiry
  • Data-driven methods
  • Computational science

Background:

  • Data-driven methods dominate scientific inquiry.
  • Open data and software accelerate data analysis.
  • Low reproducibility rates are a growing concern in science.

Purpose of the Study:

  • To address low reproducibility in scientific fields.
  • To highlight the need for formalism in reporting research results.
  • To introduce data provenance as a solution for enhancing reproducibility.

Main Methods:

  • Reviewing the impact of data-driven methods on scientific reproducibility.
  • Analyzing the challenges in reporting end-to-end research results.
  • Proposing data provenance as a systematic approach to formalize reporting.

Related Experiment Videos

Main Results:

  • Lack of formalism in reporting hinders reproducibility.
  • Accessibility of data and methods does not guarantee clarity.
  • Data provenance offers a structured way to document research.

Conclusions:

  • Formalized reporting is crucial for scientific reproducibility.
  • Data provenance systems can improve clarity and efficiency in research.
  • Implementing data provenance aids in tracking data sources, analysis, and publications.