To main content

Data sharing practices and best data management for microplastics pollution


In recent years, concerns over microplastic (MP) pollution have increased, leading to an exponential growth in MP research. To support science-based policies, it is essential that the data associated with this research are findable, accessible, interoperable, and reusable. We present a bibliographic analysis of MP research data to determine their findability and accessibility. A subset of 785 MP peer-reviewed articles were randomly selected from 6608 total publications published between 2013 and 2021 for the bibliographic analysis. Of the 785 articles analyzed, only 28.5% had a data sharing statement. Of those with a data sharing statement, 38.8% shared the data in the supplementary material, and only 13.8% shared the data in a digital repository. In addition, we found that among 279 MP datasets available in open access repositories, only 15.4% and 18.2% had adequate metadata to determine the sampling location and media type, respectively. Based on the insights gained from this study, we offer five recommendations to the MP research community to support data sharing and data management practices. These include: use available metadata standards/practices to describe data, use a trusted repository, and link datasets to publications. Read more at


Academic lecture


  • Research Council of Norway (RCN) / 312262
  • Research Council of Norway (RCN) / 295174
  • Research Council of Norway (RCN) / 301157




  • Tia Jenkins
  • Bhaleka D. Persaud
  • Win Cowger
  • Kathy Szigeti
  • Dominique G. Roche
  • Erin Clary
  • Stephanie Slowinski
  • Benjamin Lei
  • Amila Abeynayaka
  • Ebenezer S. Nyadjro
  • Thomas Maes
  • Leah Thornton Hampton
  • Melanie Bergmann
  • Julian Aherne
  • Sherri A Mason
  • John F. Honek
  • Fereidoun Rezanezhad
  • Amy Lorraine Lusher
  • Andy Booth
  • Rodney D. L. Smith
  • Philippe Van Cappellen


  • Unknown
  • Norwegian Institute of Water Research
  • SINTEF Ocean / Climate and Environment

Presented at

IAGLR 66th Annual Conference on Great Lakes Research




08.05.2023 - 12.05.2023



View this publication at Cristin