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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 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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  • 3
    Publication Date: 2022-10-21
    Description: BCO-DMO, a repository funded by the National Science Foundation (NSF), supports the oceanographic research community’s data needs throughout the entire data life cycle. This guide describes the services available from BCO-DMO from proposal to preservation and highlights phases where researchers engage significantly with the office.
    Description: Curating and providing open access to research data is a collaborative process. This process may be thought of as a life cycle with data passing through various phases. Each phase has its own associated actors, roles, and critical activities. Good data management practices are necessary for all phases, from proposal to preservation.
    Description: NSF #1435578
    Keywords: Data management ; Provenance ; Data repository ; Worfklow
    Repository Name: Woods Hole Open Access Server
    Type: Other
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  • 4
    Publication Date: 2022-10-21
    Description: Presented at csv,conf,v4 Conference Portland, Oregon, May 5-8, 2019.
    Description: Frictionless Data (FD) initiatives out of the Open Knowledge Foundation provide attractive informatics and processing capabilities. The BCO-DMO data repository used FD tools on real-world datasets, and we have some lessons learned to share. By building upon existing FD tools, we found ways to reduce the amount of time data managers spend generating metadata, and writing custom scripts. We are also developing ways for data managers with varying levels of scripting ability to make use of Frictionless Data tools.
    Description: NSF #1435578
    Keywords: Open data ; Frictionless data ; Datapackage-pipelines ; Open knowledge ; Data processing ; Provenance ; Interoperability ; FAIR ; Workflows
    Repository Name: Woods Hole Open Access Server
    Type: Presentation
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  • 5
    Publication Date: 2022-05-26
    Description: Presented at Data Curation Network, May 15, 2020
    Description: At domain-specific data repositories, curation that strives for FAIR principles often entails transforming data submissions to improve understanding and reuse. The Biological and Chemical Oceanography Data Management Office (BCO-DMO, https://www.bco-dmo.org) has been adopting the data containerization specification of the Frictionless Data project (https://frictionlessdata.io) in an effort to improve its data curation process efficiency. In doing so, BCO-DMO has been using the Frictionless Data Package Pipelines library (https://github.com/frictionlessdata/datapackage-pipelines) to define the processing steps that transform original submissions to final data products. Because these pipelines are defined using a declarative language they can be serialized into formal provenance data structures using the Provenance Ontology (PROV-O, https://www.w3.org/TR/prov-o/). While there may still be some curation steps that cannot be easily automated, this method is a step towards reproducible transforms that bridge the original data submission to its published state in machine-actionable ways that benefit the research community through transparency in the data curation process. BCO-DMO has built a user interface on top of these modular tools for making it easer for data managers to process submission, reuse existing workflows, and make transparent the added value of domain-specific data curation.
    Description: NSF #1924618
    Keywords: Data Curation ; Provenance ; Workflows ; Frictionless Data ; Data management ; Data repository
    Repository Name: Woods Hole Open Access Server
    Type: Presentation
    Location Call Number Expected Availability
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  • 6
    Publication Date: 2022-05-26
    Description: Presented at USGS Data Management Working Group, 9, November 2020
    Description: At domain-specific data repositories, curation that strives for FAIR principles often entails transforming data submissions to improve understanding and reuse. The Biological and Chemical Oceanography Data Management Office (BCO-DMO, https://www.bco-dmo.org) has been adopting the data containerization specification of the Frictionless Data project (https://frictionlessdata.io) in an effort to improve its data curation process efficiency. In doing so, BCO-DMO has been using the Frictionless Data Package Pipelines library (https://github.com/frictionlessdata/datapackage-pipelines) to define the processing steps that transform original submissions to final data products. Because these pipelines are defined using a declarative language they can be serialized into formal provenance data structures using the Provenance Ontology (PROV-O, https://www.w3.org/TR/prov-o/). While there may still be some curation steps that cannot be easily automated, this method is a step towards reproducible transforms that bridge the original data submission to its published state in machine-actionable ways that benefit the research community through transparency in the data curation process. BCO-DMO has built a user interface on top of these modular tools for making it easier for data managers to process submission, reuse existing workflows, and make transparent the added value of domain-specific data curation.
    Description: NSF #1924618
    Keywords: Data Curation ; Provenance ; Workflows ; Frictionless Data ; Data management ; Data repository
    Repository Name: Woods Hole Open Access Server
    Type: Presentation
    Location Call Number Expected Availability
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  • 7
    Publication Date: 2022-05-26
    Description: Presented at FORCE2018 Conference, Montreal, Canada, October 10-12, 2018. FORCE: Future of Research Communications and e-Scholarship
    Description: At domain-specific data repositories, curation that strives for FAIR principles often entails transforming data submissions to improve understanding and reuse. The Biological and Chemical Oceanography Data Management Office (BCO-DMO, https://www.bco-dmo.org) has been adopting the data containerization specification of the Frictionless Data project (https://frictionlessdata.io) in an effort to improve its data curation process efficiency. In doing so, BCO-DMO has been using the Frictionless Data Package Pipelines library (https://github.com/frictionlessdata/datapackage-pipelines) to define the processing steps that transform original submissions to final data products. Because these pipelines are defined using a declarative language they can be serialized into formal provenance data structures using the Provenance Ontology (PROV-O, https://www.w3.org/TR/prov-o/). While there may still be some curation steps that cannot be easily automated, this method is a step towards reproducible transforms that bridge the original data submission to its published state in machine-actionable ways that benefit the research community through transparency in the data curation process.
    Description: NSF #1435578
    Keywords: Frictionless Data ; Data management ; Provenance ; Data repository ; Worfklow
    Repository Name: Woods Hole Open Access Server
    Type: Presentation
    Location Call Number Expected Availability
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