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  • 1
    Publication Date: 2022-05-25
    Description: Presented at AGU Fall Meeting, American Geophysical Union, Washington, D.C., 10 – 14 Dec 2018
    Description: Data repositories often transform submissions to improve understanding and reuse of data by researchers other than the original submitter. However, scientific workflows built by the data submitters often depend on the original data format. In some cases, this makes the repository’s final data product less useful to the submitter. As a result, these two workable but different versions of the data provide value to two disparate, non-interoperable research communities around what should be a single dataset. Data repositories could bridge these two communities by exposing provenance explaining the transform from original submission to final product. A subsequent benefit of this provenance would be the transparent value-add of domain repository data curation. To improve its data management process efficiency, the Biological and Chemical Oceanography Data Management Office (BCO-DMO, https://www.bco-dmo.org) has been adopting the data containerization specification defined by the Frictionless Data project (https://frictionlessdata.io). Recently, BCO-DMO has been using the Frictionless Data Package Pipelines Python library (https://github.com/frictionlessdata/datapackage-pipelines) to capture the data curation processing steps that transform original submissions to final data products. Because these processing steps are stored using a declarative language they can be converted to a structured provenance record using the Provenance Ontology (PROV-O, https://www.w3.org/TR/prov-o/). PROV-O abstracts the Frictionless Data elements of BCO-DMO’s workflow for capturing necessary curation provenance and enables interoperability with other external provenance sources and tools. Users who are familiar with PROV-O or the Frictionless Data Pipelines can use either record to reproduce the final data product in a machine-actionable way. While there may still be some curation steps that cannot be easily automated, this process is a step towards end-to-end reproducible transforms throughout the data curation process. In this presentation, BCO-DMO will demonstrate how Frictionless Data Package Pipelines can be used to capture data curation provenance from original submission to final data product exposing the concrete value-add of domain-specific repositories.
    Description: NSF #1435578
    Keywords: Provenance ; Frictionless Data ; Data management
    Repository Name: Woods Hole Open Access Server
    Type: Presentation
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  • 2
    Publication Date: 2022-10-21
    Description: Presented at 2022 OCB Summer Workshop, Woods Hole, MA, 20 - 23, June 2022
    Description: An unparalleled data catalog of well-documented, interoperable oceanographic data and information, openly accessible to all end-users through an intuitive web-based interface for the purposes of advancing marine research, education, and policy. Conference Website: https://web.whoi.edu/ocb-workshop/
    Description: NSF #1924618
    Keywords: Data management
    Repository Name: Woods Hole Open Access Server
    Type: Presentation
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  • 3
    Publication Date: 2022-10-21
    Description: Presented at Ocean Sciences, San Diego, 16-21, February 2020
    Description: BCO-DMO curates earth science data where models become increasingly important. The Biological and Chemical Oceanography Data Management Office (BCO-DMO) is a publicly accessible earth science data repository created to curate, publicly serve (publish), and archive digital data and information from biological, chemical and biogeochemical research conducted in coastal, marine, great lakes and laboratory environments. Recently, more and more of the projects submitted to BCO-DMO represent modeling efforts which further increase our knowledge of chemical and biological properties within the ocean ecosystem. We feel the time is at hand for the scientific community to begin a concerted and holistic approach to the curation of code and software.
    Description: Award(s): NSF #1924618
    Keywords: Data management ; Open science ; Survey ; Research needs
    Repository Name: Woods Hole Open Access Server
    Type: Presentation
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  • 4
    Publication Date: 2022-10-21
    Description: Presented at Ocean Sciences, San Diego, 16-21, February 2020
    Description: 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.
    Description: Award(s): NSF #1924618
    Keywords: Data management ; Open science ; Survey ; Research needs
    Repository Name: Woods Hole Open Access Server
    Type: Presentation
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  • 5
    Publication Date: 2022-10-21
    Description: Presented at AGU Fall Meeting 10 – 14 December 2018, Washington, D.C.
    Description: The Biological and Chemical Oceanography Data Management Office (BCO-DMO) is a publicly accessible earth science data repository created to curate, publicly serve (publish), and archive digital data and information from biological, chemical and biogeochemical research conducted in coastal, marine, great lakes and laboratory environments. The BCO-DMO repository works closely with investigators funded through the NSF OCE Division’s Biological and Chemical Sections and Antarctic Organisms & Ecosystems. The office provides services that span the full data life cycle, from data management planning support and DOI creation, to archiving with appropriate national facilities. Recently, more and more of the projects submitted to BCO-DMO represent modeling efforts which further increase our knowledge of the chemical and biological properties within the ocean ecosystem. But, as a repository traditionally focused on observational data as a primary research output, what roles should domain-specific data repositories play in this field? Recognizing code as a first class research product, how should repositories support the discovery, access and reuse of code and software used in hypothesis driven research? We feel the time is at hand for the community to begin a concerted and holistic approach to the curation of code and software. Such strategy development should begin with asking what is the appropriate output to curate? What is the minimum metadata required for re-use? How should code be stored and accessed? Should repositories support or facilitate peer reviewing code? The answers to these questions will better inform domain-specific repositories on how to better manage code as a first class research asset in order to support the scientific community. This presentation will explore these topics, inviting discussion from the audience to advance a collective strategy.
    Description: NSF #1435578
    Keywords: Data management ; Provenance ; Data repository ; Worfklow ; Modeling Conference Name: AGU 2018 Conference Location: Washington, D.C
    Repository Name: Woods Hole Open Access Server
    Type: Presentation
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  • 6
    Publication Date: 2022-10-21
    Description: Presented at OCB Summer Workshop, June 24-27 2019, Woods Hole MA.
    Description: 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 ecosystem 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. This poster describes some of the existing infrastructure and strategic enhancements at BCO-DMO in support of the F.A.I.R principles.
    Keywords: Data management ; F.A.I.R data ; Open science ; Open data
    Repository Name: Woods Hole Open Access Server
    Type: Presentation
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  • 7
    Publication Date: 2022-10-21
    Description: Presented at OCB Summer Workshop, June 24-27 2019, Woods Hole MA.
    Description: 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 ecosystem 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 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 will help BCO-DMO improve its service to the research community.
    Description: Award(s): NSF #1435578
    Keywords: Data management ; Open science ; Survey ; Research needs
    Repository Name: Woods Hole Open Access Server
    Type: Presentation
    Location Call Number Expected Availability
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  • 8
    Publication Date: 2022-10-21
    Description: Presented at Fall AGU (ESIP Data Helpdesk), New Orleans, 11-17, December 2021
    Description: 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.
    Description: Award(s): NSF #1924618
    Keywords: Data management ; Open science ; Survey ; Research needs
    Repository Name: Woods Hole Open Access Server
    Type: Presentation
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  • 9
    Publication Date: 2022-10-31
    Description: Dataset: Trichodesmium field metaproteomes - sequence fasta
    Description: FASTA file of sequences in Trichodesmium field metaproteomes analyzed by 2D LC-MS/MS mapped to a Trichodesmium metagenome (IMG ID 2821474806) plus cyanoGEBA species genomes (Shih et al, 2013). Samples were collected in North Atlantic surface waters, at station BATS (Bermuda Atlantic Time-series Study), and station ALOHA (A Long-Term Oligotrophic Habitat Assessment) between 2000 and 2018. Related datasets: Trichodesmium field metaproteomes - peptide spectral counts: https://www.bco-dmo.org/dataset/787168 Trichodesmium field metaproteomes - protein spectral counts: https://www.bco-dmo.org/dataset/787147 Trichodesmium sample provenance: https://www.bco-dmo.org/dataset/787093 - Sample provenance file, which includes sample locations, filter sizes 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/787181
    Description: Gordon and Betty Moore Foundation (GBMF) GBMF3934, Gordon and Betty Moore Foundation: Marine Microbiology Initiative (MMI) GBMF3782, NSF Division of Ocean Sciences (NSF OCE) OCE-1657766, NSF Division of Ocean Sciences (NSF OCE) OCE-1850719
    Keywords: Trichodesmium ; Metaproteomics
    Repository Name: Woods Hole Open Access Server
    Type: Dataset
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  • 10
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    Biological and Chemical Oceanography Data Management Office (BCO-DMO). Contact: bco-dmo-data@whoi.edu
    Publication Date: 2022-10-31
    Description: Dataset: Trichodesmium field metaproteomes - protein spectral counts in alternative format
    Description: Metaproteomes of Trichodesmium from samples collected in North Atlantic surface waters, at station BATS (Bermuda Atlantic Time-series Study), and station ALOHA (A Long-Term Oligotrophic Habitat Assessment) between 2000 and 2018. 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/787078
    Description: Gordon and Betty Moore Foundation (GBMF) GBMF3934, Gordon and Betty Moore Foundation: Marine Microbiology Initiative (MMI) GBMF3782, NSF Division of Ocean Sciences (NSF OCE) OCE-1657766, NSF Division of Ocean Sciences (NSF OCE) OCE-1850719
    Keywords: Trichodesmium ; Metaproteomics
    Repository Name: Woods Hole Open Access Server
    Type: Dataset
    Location Call Number Expected Availability
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