IDEAS home Printed from https://ideas.repec.org/a/wly/envmet/v34y2023i2ne2789.html
   My bibliography  Save this article

The role of data science in environmental digital twins: In praise of the arrows

Author

Listed:
  • Gordon S. Blair
  • Peter A. Henrys

Abstract

Digital twins are increasingly important in many domains, including for understanding and managing the natural environment. Digital twins of the natural environment are fueled by the unprecedented amounts of environmental data now available from a variety of sources from remote sensing to potentially dense deployment of earth‐based sensors. Because of this, data science techniques inevitably have a crucial role to play in making sense of this complex, highly heterogeneous data. This short article reflects on the role of data science in digital twins of the natural environment, with particular attention on how resultant data models can work alongside the rich legacy of process models that exist in this domain. We seek to unpick the complex two‐way relationship between data and process understanding. By focusing on the interactions, we end up with a template for digital twins that incorporates a rich, highly dynamic learning process with the potential to handle the complexities and emergent behaviors of this important area.

Suggested Citation

  • Gordon S. Blair & Peter A. Henrys, 2023. "The role of data science in environmental digital twins: In praise of the arrows," Environmetrics, John Wiley & Sons, Ltd., vol. 34(2), March.
    • Handle: RePEc:wly:envmet:v:34:y:2023:i:2:n:e2789
    DOI: 10.1002/env.2789
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/env.2789
    Download Restriction: no
    File URL: https://libkey.io/10.1002/env.2789?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. C. J. Wilkie & C. A. Miller & E. M. Scott & R. A. O'Donnell & P. D. Hunter & E. Spyrakos & A. N. Tyler, 2019. "Nonparametric statistical downscaling for the fusion of data of different spatiotemporal support," Environmetrics, John Wiley & Sons, Ltd., vol. 30(3), May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wesley S. Burr & Nathaniel K. Newlands & Andrew Zammit‐Mangion, 2023. "Environmental data science: Part 2," Environmetrics, John Wiley & Sons, Ltd., vol. 34(2), March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xiaoyu Xiong & Benjamin D. Youngman & Theodoros Economou, 2021. "Data fusion with Gaussian processes for estimation of environmental hazard events," Environmetrics, John Wiley & Sons, Ltd., vol. 32(3), May.
    2. E. Marian Scott, 2023. "Framing data science, analytics and statistics around the digital earth concept," Environmetrics, John Wiley & Sons, Ltd., vol. 34(2), March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:envmet:v:34:y:2023:i:2:n:e2789. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/1180-4009/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.