Biological and Chemical Oceanography Data Management Office (BCO-DMO)
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The Biological and Chemical Oceanography Data Management Office (BCO-DMO) staff members work with investigators to serve data online from research projects funded by the Biological and Chemical Oceanography Sections, the Division of Polar Programs Arctic Sciences and Antarctic Organisms & Ecosystems Program at the U.S. National Science Foundation.
BCO-DMO is a combination of the formerly independent Data Management Offices formed in support of the US JGOFS and US GLOBEC programs. The BCO-DMO staff members are the curators of the data collections created by those respective programs, as well as data from more recent NSF Geosciences Directorate (GEO) Division of Ocean Sciences (OCE) Biological and Chemical Oceanography Sections, Division of Polar Programs (PLR) Antarctic Sciences (ANT) Organisms & Ecosystems, and Arctic Sciences (ARC) awards. The BCO-DMO project is funded by NSF OCE and ANT programs, NSF award number OCE-1435578.
Data sets managed by BCO-DMO and hosted in WHOAS, can be found here.
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Browsing Biological and Chemical Oceanography Data Management Office (BCO-DMO) by Subject "Data management"
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OtherBCO-DMO Quick Guide( 2018-09-19) Kinkade, Danie ; Shepherd, Adam ; Ake, Hannah ; Biddle, Matt ; Copley, Nancy ; Rauch, Shannon ; York, AmberCurating 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.
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PresentationBiological & Chemical Oceanography Data Management Office : a domain-specific repository for oceanographic data from around the world [poster]( 2018-02-14) Ake, Hannah ; Biddle, Matt ; Copley, Nancy ; Kinkade, Danie ; Rauch, Shannon ; Saito, Mak A. ; Shepherd, Adam ; Switzer, Megan ; Wiebe, Peter ; York, AmberThe Biological and Chemical Oceanography Data Management Office (BCO-DMO) is a domain-specific digital data repository that works with investigators funded under the National Science Foundation’s Division of Ocean Sciences and Office of Polar Programs to manage their data free of charge. Data managers work closely with investigators to satisfy their data sharing requirements and to develop comprehensive Data Management Plans, as well as to ensure that their data will be well described with extensive metadata creation. Additionally, BCO-DMO offers tools to find and reuse these high-quality data and metadata packages, and services such as DOI generation for publication and attribution. These resources are free for all to discover, access, and utilize. As a repository embedded in our research community, BCO-DMO is well positioned to offer knowledge and expertise from both domain trained data managers and the scientific community at large. BCO-DMO is currently home to more than 9000 datasets and 900 projects, all of which are or will be submitted for archive at the National Centers for Environmental Information (NCEI). Our data holdings continue to grow, and encompass a wide range of oceanographic research areas, including biological, chemical, physical, and ecological. These data represent cruises and experiments from around the world, and are managed using community best practices, standards, and technologies to ensure accuracy and promote re-use. BCO-DMO is a repository and tool for investigators, offering both ocean science data and resources for data dissemination and publication.
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PresentationBiological and Chemical Oceanography Data Management Office: Supporting a New Vision for Adaptive Management of Oceanographic Data [poster](Woods Hole Oceanographic Institution, 2022-06-21) Shepherd, Adam ; Gerlach, Dana ; Heyl, Taylor ; Kinkade, Danie ; Nagala, Shravani ; Newman, Sawyer ; Rauch, Shannon ; Saito, Mak A. ; Schloer, Conrad ; Soenen, Karen ; Wiebe, Peter ; York, AmberAn 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/
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PresentationCapturing Provenance of Data Curation at BCO-DMO(Woods Hole Oceanographic Institution, 2020-05-15) Shepherd, Adam ; York, Amber ; Schloer, Conrad ; Kinkade, Danie ; Rauch, Shannon ; Biddle, Matt ; Copley, Nancy ; Haskins, Christina ; Soenen, Karen ; Saito, Mak A. ; Wiebe, PeterAt 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.
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PresentationCapturing Provenance of Data Curation at BCO-DMO(Woods Hole Oceanographic Institution, 2020-11-09) Shepherd, Adam ; York, Amber ; Schloer, Conrad ; Kinkade, Danie ; Rauch, Shannon ; Copley, Nancy ; Gerlach, Dana ; Haskins, Christina ; Soenen, Karen ; Saito, Mak A. ; Wiebe, PeterAt 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.
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PresentationCode and Software: How would you share yours? [poster](Woods Hole Oceanographic Institution, 2020-02-21) Biddle, Matt ; Copley, Nancy ; Haskins, Christina ; Rauch, Shannon ; Soenen, Karen ; York, Amber ; Kinkade, Danie ; Saito, Mak A. ; Shepherd, Adam ; Wiebe, PeterBCO-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.
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PresentationData Help Desk BCO-DMO Lightning Talk(Woods Hole Oceanographic Institution, 2020-02-18) Biddle, Matt ; Shepherd, Adam ; Kinkade, Danie ; Haskins, Christina ; Soenen, Karen ; Rauch, Shannon ; Copley, Nancy ; York, Amber ; Schloer, Conrad ; Saito, Mak A. ; Wiebe, PeterBCO-DMO is the Biological and Chemical Oceanography Data Management Office. We help oceanography researchers who are funded by the National Science Foundation’s (NSF's) Division of Ocean Sciences' (OCE) Biological or Chemical Oceanography Sections or the Division of Polar Programs' Antarctic Organisms & Ecosystems Program manage their data, making them accessible over the internet. This lightning talk gives a brief overview of who we are, who we work with, and the types of data we manage.
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PresentationData Management and Reporting: BCO-DMO Data Management Services and Best Practices(Woods Hole Oceanographic Institution, 2019-06-14) Rauch, Shannon ; Kinkade, Danie ; Biddle, Matt ; Copley, Nancy ; York, Amber ; Soenen, Karen ; Shepherd, AdamThe University-National Oceanographic Laboratory System (UNOLS) hosted an Early Career Chief Scientist Training Workshop in June 2019. The goal of this workshop was to help early-career marine scientists plan and write effective cruise proposals, develop collaborative sampling strategies and plans, become familiar with shipboard equipment and sampling at sea, and communicate major findings through writing of manuscripts and cruise reports. This presentation provides information on data management and reporting best practices for chief scientists. It includes information on: National Science Foundation (NSF) data policy requirements, writing a Data Management Plan (DMP), the data lifecycle, data publication, and shipboard data management recommendations.
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PresentationThe Data Management Process and Lessons Learned From U.S. GEOTRACES(Woods Hole Oceanographic Institution, 2018-11-09) Rauch, Shannon ; Kinkade, Danie ; Shepherd, Adam ; Copley, Nancy ; Biddle, Matt ; York, AmberIn an effort to explore and develop international community interest for a potential future "Biogeotraces-like" program, a working group of 28 scientists from 9 nations met in Woods Hole in November 2018. The result of this workshop is a new research effort termed "Biogeoscapes". This presentation highlighted data management lessons and recommendations from based on past experience handling data from a similarly-scaled global research project, GEOTRACES.
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PresentationData Science Training Camp at Woods Hole Oceanographic Institution: Syllabus and slide presentations in 2020(Woods Hole Oceanographic Institution, 2020-08-21) Beaulieu, Stace E. ; Raymond, Lisa ; Mickle, Audrey ; Futrelle, Joe ; Symmonds, Nick ; Mazzoli, Roberta ; Brey, Rich ; Kinkade, Danie ; Rauch, ShannonWith data and software increasingly recognized as scholarly research products, and aiming towards open science and reproducibility, it is imperative for today's oceanographers to learn foundational practices and skills for data management and research computing, as well as practices specific to the ocean sciences. This educational package was developed as a data science training camp for graduate students and professionals in the ocean sciences and implemented at the Woods Hole Oceanographic Institution (WHOI) in 2019 and 2020. Here we provide materials for the 2020 camp which was delivered in-person during two afternoons (total of 8 hours), with two modules per afternoon. We aimed for ~40 participants per camp, with disciplines spanning Earth and life sciences and engineering. Disciplines at each table were mixed on the first afternoon but similar on the second afternoon. Contents of this package include the syllabus and slide presentations for each of the four modules: 1 "Good enough practices in scientific computing," 2 Data management, 3 Software development and research computing, and 4 Best practices in the ocean sciences. The 3rd module is split into two parts. We also include a poster presented at the 2020 Ocean Science Meeting, which has some results from pre- and post-surveys. Funding: The camp was funded by WHOI Academic Programs Office through a Doherty Chair in Education Award, with additional support from WHOI Ocean Informatics Working Group, WHOI Information Services, MBLWHOI Library, the NSF-funded Biological and Chemical Oceanography Data Management Office (BCO-DMO), and an NSF-funded XSEDE Jetstream Education Allocation TG-OCE190011. We also utilized resources from the NSF-funded Pangeo project.
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PresentationThe Frictionless Data Package : data containerization for addressing big data challenges [poster]( 2018-02-15) Shepherd, Adam ; Fils, Douglas ; Kinkade, Danie ; Saito, Mak A.At the Biological and Chemical Oceanography Data Management Office (BCO-DMO) Big Data challenges have been steadily increasing. The sizes of data submissions have grown as instrumentation improves. Complex data types can sometimes be stored across different repositories . This signals a paradigm shift where data and information that is meant to be tightly-coupled and has traditionally been stored under the same roof is now distributed across repositories and data stores. For domain-specific repositories like BCO-DMO, a new mechanism for assembling data, metadata and supporting documentation is needed. Traditionally, data repositories have relied on a human's involvement throughout discovery and access workflows. This human could assess fitness for purpose by reading loosely coupled, unstructured information from web pages and documentation. Distributed storage was something that could be communicated in text that a human could read and understand. However, as machines play larger roles in the process of discovery and access of data, distributed resources must be described and packaged in ways that fit into machine automated workflows of discovery and access for assessing fitness for purpose by the end-user. Once machines have recommended a data resource as relevant to an investigator's needs, the data should be easy to integrate into that investigator's toolkits for analysis and visualization. BCO-DMO is exploring the idea of data containerization, or packaging data and related information for easier transport, interpretation, and use. Data containerization reduces not only the friction data repositories experience trying to describe complex data resources, but also for end-users trying to access data with their own toolkits. In researching the landscape of data containerization, the Frictionlessdata Data Package (http://frictionlessdata.io/) provides a number of valuable advantages over similar solutions. This presentation will focus on these advantages and how the Frictionlessdata Data Package addresses a number of real-world use cases faced for data discovery, access, analysis and visualization in the age of Big Data.
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PresentationThe Frictionless Data Package : data containerization for automated scientific workflows [poster]( 2017-12-13) Shepherd, Adam ; Fils, Douglas ; Kinkade, Danie ; Saito, Mak A.As cross-disciplinary geoscience research increasingly relies on machines to discover and access data, one of the critical questions facing data repositories is how data and supporting materials should be packaged for consumption. Traditionally, data repositories have relied on a human's involvement throughout discovery and access workflows. This human could assess fitness for purpose by reading loosely coupled, unstructured information from web pages and documentation. In attempts to shorten the time to science and access data resources across may disciplines, expectations for machines to mediate the process of discovery and access is challenging data repository infrastructure. This challenge is to find ways to deliver data and information in ways that enable machines to make better decisions by enabling them to understand the data and metadata of many data types. Additionally, once machines have recommended a data resource as relevant to an investigator's needs, the data resource should be easy to integrate into that investigator's toolkits for analysis and visualization. The Biological and Chemical Oceanography Data Management Office (BCO-DMO) supports NSF-funded OCE and PLR investigators with their project's data management needs. These needs involve a number of varying data types some of which require multiple files with differing formats. Presently, BCO-DMO has described these data types and the important relationships between the type's data files through human-readable documentation on web pages. For machines directly accessing data files from BCO-DMO, this documentation could be overlooked and lead to misinterpreting the data. Instead, BCO-DMO is exploring the idea of data containerization, or packaging data and related information for easier transport, interpretation, and use. In researching the landscape of data containerization, the Frictionlessdata Data Package (http://frictionlessdata.io/) provides a number of valuable advantages over similar solutions. This presentation will focus on these advantages and how the Frictionlessdata Data Package addresses a number of real-world use cases faced for data discovery, access, analysis and visualization.
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PresentationHow 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.
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PresentationIn search of Frictionless Data(Biological and Chemical Oceanography Data Management Office, 2017-09-21) Shepherd, Adam
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PresentationMaking OCB Data F.A.I.R [poster]( 2019-06-24) Soenen, Karen ; Biddle, Matt ; Copley, Nancy ; Haskins, Christina ; Rauch, Shannon ; York, Amber ; Kinkade, Danie ; Saito, Mak A. ; Shepherd, Adam ; Wiebe, PeterOceanographic 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.
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ArticleOcean FAIR data services(Frontiers Media, 2019-08-07) Tanhua, Toste ; Pouliquen, Sylvie ; Hausman, Jessica ; O’Brien, Kevin ; Bricher, Phillippa ; de Bruin, Taco ; Buck, Justin J. H. ; Burger, Eugene ; Carval, Thierry ; Casey, Kenneth S. ; Diggs, Stephen ; Giorgetti, Alessandra ; Glaves, Helen ; Harscoat, Valerie ; Kinkade, Danie ; Muelbert, Jose H. ; Novellino, Antonio ; Pfeil, Benjamin ; Pulsifer, Peter L. ; Van de Putte, Anton ; Robinson, Erin ; Schaap, Dick ; Smirnov, Alexander ; Smith, Neville ; Snowden, Derrick ; Spears, Tobias ; Stall, Shelley ; Tacoma, Marten ; Thijsse, Peter ; Tronstad, Stein ; Vandenberghe, Thomas ; Wengren, Micah ; Wyborn, Lesley ; Zhao, ZhimingWell-founded data management systems are of vital importance for ocean observing systems as they ensure that essential data are not only collected but also retained and made accessible for analysis and application by current and future users. Effective data management requires collaboration across activities including observations, metadata and data assembly, quality assurance and control (QA/QC), and data publication that enables local and interoperable discovery and access and secures archiving that guarantees long-term preservation. To achieve this, data should be findable, accessible, interoperable, and reusable (FAIR). Here, we outline how these principles apply to ocean data and illustrate them with a few examples. In recent decades, ocean data managers, in close collaboration with international organizations, have played an active role in the improvement of environmental data standardization, accessibility, and interoperability through different projects, enhancing access to observation data at all stages of the data life cycle and fostering the development of integrated services targeted to research, regulatory, and operational users. As ocean observing systems evolve and an increasing number of autonomous platforms and sensors are deployed, the volume and variety of data increase dramatically. For instance, there are more than 70 data catalogs that contain metadata records for the polar oceans, a situation that makes comprehensive data discovery beyond the capacity of most researchers. To better serve research, operational, and commercial users, more efficient turnaround of quality data in known formats and made available through Web services is necessary. In particular, automation of data workflows will be critical to reduce friction throughout the data value chain. Adhering to the FAIR principles with free, timely, and unrestricted access to ocean observation data is beneficial for the originators, has obvious benefits for users, and is an essential foundation for the development of new services made possible with big data technologies.
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PresentationShare Your Thoughts [poster](Woods Hole Oceanographic Institution, 2020-02-21) Haskins, Christina ; Biddle, Matt ; Copley, Nancy J. ; Rauch, Shannon ; Soenen, Karen ; York, Amber ; Kinkade, Danie ; Saito, Mak A. ; Shepherd, Adam ; Wiebe, PeterOceanographic 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.
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PresentationShare Your Thoughts [poster](Woods Hole Oceanographic Institution, 2019-06-24) Soenen, Karen ; Biddle, Matt ; Copley, Nancy ; Haskins, Christina ; Rauch, Shannon ; York, Amber ; Kinkade, Danie ; Saito, Mak A. ; Shepherd, Adam ; Wiebe, PeterOceanographic 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.
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PresentationSharing Data Through the Biological and Chemical Oceanography Data Management Office [talk](Woods Hole Oceanographic Institution, 2020-01-15) Kinkade, DanieThis talk provides an overview of the Biological and Chemical Oceanography Data Management Office and the collaborative data sharing process that occurs between individual investigators and the BCO-DMO repository. The presentation includes background on the repository, what to expect after submitting your data, and helpful data management practices that can streamline data sharing and support open science.
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PresentationTowards capturing data curation provenance using Frictionless Data Package Pipelines [poster]( 2018-10-10) Shepherd, Adam ; Schloer, Conrad ; York, Amber ; Kinkade, DanieAt 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.