ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Publication Date: 2022-05-25
    Description: This work is licensed under a Creative Commons 1.0 Public Domain Dedication. The definitive version was published in Journal of eScience Librarianship 6 (2017): e1114, doi:10.7191/jeslib.2017.1114.
    Description: To ensure that resources designed to teach skills and best practices for scientific research data sharing and management are useful, the maintainers of those materials need to evaluate and update them to ensure their accuracy, currency, and quality. This paper advances the use and process of outside peer review for community resources in addressing ongoing accuracy, quality, and currency issues. It further describes the next step of moving the updated materials to an online collaborative community platform for future iterative review in order to build upon mechanisms for open science, ongoing iteration, participation, and transparent community engagement.
    Description: DataONE is supported by US National Science Foundation Awards 08- 30944 and 14-30508, William Michener, Principal Investigator; Matthew Jones, Patricia Cruse, David Vieglais, and Suzanne Allard, Co-Principal Investigators.
    Keywords: Research data management ; GitHub ; Peer review ; Academic libraries
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 2
    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
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 3
    Publication Date: 2022-10-31
    Description: Dataset: Share Your Thoughts
    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. 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
    Description: NSF Division of Ocean Sciences (NSF OCE) OCE-1924618
    Keywords: Data management. stakeholder needs ; Oceanography ; BCO-DMO ; Repository ; Community building
    Repository Name: Woods Hole Open Access Server
    Type: Dataset
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 4
    Publication Date: 2022-05-26
    Description: Presented at OceanObs’19, Honolulu, HI, September 16-20 2019
    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
    Repository Name: Woods Hole Open Access Server
    Type: Presentation
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 5
    Publication Date: 2022-05-26
    Description: Presented at OceanObs’19, Honolulu, HI, September 16-20 2019
    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. This poster will introduce the repository and describe some of the strategic enhancements coming to BCO-DMO.
    Repository Name: Woods Hole Open Access Server
    Type: Presentation
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 6
    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
    BibTip Others were also interested in ...
  • 7
    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
    BibTip Others were also interested in ...
  • 8
    Publication Date: 2022-05-26
    Description: Presented at Ocean Sciences Meeting (OSM), San Diego, CA, 16 - 21 February 2020
    Description: BCO-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.
    Description: Award(s): NSF #1924618
    Keywords: Data Curation ; Data management ; Data repository
    Repository Name: Woods Hole Open Access Server
    Type: Presentation
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 9
    Publication Date: 2022-05-26
    Description: Presented at AGU Ocean Sciences, 11 - 16 February 2018, Portland, OR
    Description: The 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.
    Description: NSF #1435578
    Keywords: Data management ; Data tools ; Data sharing ; Data re-use ; Data citation ; Data repository
    Repository Name: Woods Hole Open Access Server
    Type: Presentation
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 10
    Publication Date: 2022-05-26
    Description: © The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Biodiversity Data Journal 5 (2017): e10989, doi:10.3897/BDJ.5.e10989.
    Description: The Ocean Biogeographic Information System (OBIS) is the world’s most comprehensive online, open-access database of marine species distributions. OBIS grows with millions of new species observations every year. Contributions come from a network of hundreds of institutions, projects and individuals with common goals: to build a scientific knowledge base that is open to the public for scientific discovery and exploration and to detect trends and changes that inform society as essential elements in conservation management and sustainable development. Until now, OBIS has focused solely on the collection of biogeographic data (the presence of marine species in space and time) and operated with optimized data flows, quality control procedures and data standards specifically targeted to these data. Based on requirements from the growing OBIS community to manage datasets that combine biological, physical and chemical measurements, the OBIS-ENV-DATA pilot project was launched to develop a proposed standard and guidelines to make sure these combined datasets can stay together and are not, as is often the case, split and sent to different repositories. The proposal in this paper allows for the management of sampling methodology, animal tracking and telemetry data, biological measurements (e.g., body length, percent live cover, ...) as well as environmental measurements such as nutrient concentrations, sediment characteristics or other abiotic parameters measured during sampling to characterize the environment from which biogeographic data was collected. The recommended practice builds on the Darwin Core Archive (DwC-A) standard and on practices adopted by the Global Biodiversity Information Facility (GBIF). It consists of a DwC Event Core in combination with a DwC Occurrence Extension and a proposed enhancement to the DwC MeasurementOrFact Extension. This new structure enables the linkage of measurements or facts - quantitative and qualitative properties - to both sampling events and species occurrences, and includes additional fields for property standardization. We also embrace the use of the new parentEventID DwC term, which enables the creation of a sampling event hierarchy. We believe that the adoption of this recommended practice as a new data standard for managing and sharing biological and associated environmental datasets by IODE and the wider international scientific community would be key to improving the effectiveness of the knowledge base, and will enhance integration and management of critical data needed to understand ecological and biological processes in the ocean, and on land.
    Keywords: Darwin Core Archive ; Sample event ; Species occurrence ; Environmental data ; Ecosystem data ; Telemetry data ; Data standardisation ; Oceanographic data
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...