York Amber D.

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York
First Name
Amber D.
ORCID
0000-0002-5133-5842

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  • Dataset
    Community feedback collected between June 2019 and February 2020 on how researchers search and access new data for research as well as feedback on potential enhancements to help improve BCO-DMO’s service to the research community.
    (Biological and Chemical Oceanography Data Management Office (BCO-DMO). Contact: bco-dmo-data@whoi.edu, 2020-10-06) Haskins, Christina ; Soenen, Karen ; Biddle, Mathew ; Copley, Nancy ; Rauch, Shannon ; York, Amber D. ; Kinkade, Danie ; Shepherd, Adam ; Saito, Mak A. ; Wiebe, Peter H.
    Oceanographic data, when well-documented and stewarded toward preservation, have the potential to accelerate new science and facilitate our understanding of complex natural systems. The Biological and Chemical Oceanography Data Management Office (BCO-DMO) is funded by the NSF to document and manage marine biological, chemical, physical, and biogeochemical data, ensuring their discovery and access, and facilitating their reuse. The task of curating and providing access to research data is a collaborative process, with associated actors and critical activities occurring throughout the data’s life cycle. BCO-DMO supports all phases of the data life cycle and works closely with investigators to ensure open access of well-documented project data and information. Supporting this curation process is a flexible cyberinfrastructure that provides the means for data submission, discovery, and access; ultimately enabling reuse. Based upon community feedback, this infrastructure is undergoing evaluation and improvement to better meet oceanographic research needs. This poster will introduce the repository and describe some of the strategic enhancements coming to BCO-DMO, and presents an opportunity for you to provide feedback on enhancements yet to come. We invite you to think about your own research workflow of searching and accessing new data for research, and to provide your feedback through the poster’s interactive sections. Your input can help BCO-DMO improve its service to the research community. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/825238
  • Presentation
    How can BCO-DMO help with your oceanographic data?
    (Woods Hole Oceanographic Institution, 2021-12-10) Soenen, Karen ; Gerlach, Dana ; Haskins, Christina ; Heyl, Taylor ; Kinkade, Danie ; Newman, Sawyer ; Rauch, Shannon ; Saito, Mak A. ; Shepherd, Adam ; Wiebe, Peter ; York, Amber D.
    BCO-DMO curates a database of research-ready data spanning the full range of marine ecosystem related measurements including in-situ and remotely sensed observations, experimental and model results, and synthesis products. We work closely with investigators to publish data and information from research projects supported by the National Science Foundation (NSF), as well as those supported by state, private, and other funding sources. BCO-DMO supports all phases of the data life cycle and ensures open access of well-curated project data and information. We employ F.A.I.R. Principles that comprise a set of values intended to guide data producers and publishers in establishing good data management practices that will enable effective reuse.
  • Dataset
    Numerical model simulating the sea ice and ocean conditions in the Amundsen Sea over the period Jan. 1, 2006 to Dec. 31, 2013
    (Biological and Chemical Oceanography Data Management Office (BCO-DMO). Contact: bco-dmo-data@whoi.edu, 2017-08-03) St-Laurent, Pierre ; Hofmann, Eileen E. ; Sherrell, Robert M. ; Stammerjohn, Sharon E. ; Yager, Patricia L. ; Biddle, Mathew ; York, Amber D.
    Numerous coastal polynyas fringe the Antarctic continent and strongly influence the productivity of Antarctic shelf systems. Of the 46 Antarctic coastal polynyas documented in a recent study, the Amundsen Sea Polynya (ASP) stands out as having the highest net primary production per unit area. Incubation experiments suggest that this productivity is partly controlled by the availability of dissolved iron (dFe). As a first step toward understanding the iron supply of the ASP, we introduce four plausible sources of dFe and simulate their steady spatial distribution using conservative numerical tracers. The modeled distributions replicate important features from observations including dFe maxima at the bottom of deep troughs and enhanced concentrations near the ice shelf fronts. A perturbation experiment with an idealized drawdown mimicking summertime biological uptake and subsequent resupply suggests that glacial meltwater and sediment-derived dFe are the main contributors to the prebloom dFe inventory in the top 100 m of the ASP. The sediment-derived dFe depends strongly on the buoyancy-driven overturning circulation associated with the melting ice shelves (the “meltwater pump”) to add dFe to the upper 300 m of the water column. The results support the view that ice shelf melting plays an important direct and indirect role in the dFe supply and delivery to polynyas such as the ASP. The data are from a numerical model simulating the sea ice and ocean conditions in the Amundsen Sea over the period Jan. 1, 2006 to Dec. 31, 2013. The data files provide the daily averaged model fields during this period. The numerical model and experiment are thoroughly described in St-Laurent et al., J. Geophys. Res. Oceans, doi:10.1002/2017jc013162.
  • Presentation
    Fitting square pegs into a round hole. Curating heterogeneous oceanographic data at BCO-DMO
    (Woods Hole Oceanographic Institution, 2024-02-22) Soenen, Karen ; Kinkade, Danie ; Shepherd, Adam ; Saito, Mak A. ; Gerlach, Dana ; Merchant, Lynne M. ; Newman, Sawyer ; Rauch, Shannon ; York, Amber D.
    BCO-DMO is a domain-specific repository containing 18 years of curated, heterogeneous oceanographic data. Data managers are at the core of the repository, applying the F.A.I.R. principles to every dataset coming in. This talk steers the audience through such a curated dataset, covering the advancements and challenges that comes with domain curation.