Shepherd Adam

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Shepherd

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Adam

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Standards and practices for reporting plankton and other particle observations from images

(Woods Hole Oceanographic Institution, 2021-07-26) Neeley, Aimee ; Beaulieu, Stace E. ; Proctor, Chris ; Cetinić, Ivona ; Futrelle, Joe ; Soto Ramos, Inia ; Sosik, Heidi M. ; Devred, Emmanuel ; Karp-Boss, Lee ; Picheral, Marc ; Poulton, Nicole ; Roesler, Collin S. ; Shepherd, Adam

This technical manual guides the user through the process of creating a data table for the submission of taxonomic and morphological information for plankton and other particles from images to a repository. Guidance is provided to produce documentation that should accompany the submission of plankton and other particle data to a repository, describes data collection and processing techniques, and outlines the creation of a data file. Field names include scientificName that represents the lowest level taxonomic classification (e.g., genus if not certain of species, family if not certain of genus) and scientificNameID, the unique identifier from a reference database such as the World Register of Marine Species or AlgaeBase. The data table described here includes the field names associatedMedia, scientificName/ scientificNameID for both automated and manual identification, biovolume, area_cross_section, length_representation and width_representation. Additional steps that instruct the user on how to format their data for a submission to the Ocean Biodiversity Information System (OBIS) are also included. Examples of documentation and data files are provided for the user to follow. The documentation requirements and data table format are approved by both NASA’s SeaWiFS Bio-optical Archive and Storage System (SeaBASS) and the National Science Foundation’s Biological and Chemical Oceanography Data Management Office (BCO-DMO).
What role should a domain-specific repository play in treating code as a first class research product? [poster]

( 2018-12-13) Biddle, Matt ; Ake, Hannah ; Copley, Nancy ; Kinkade, Danie ; Rauch, Shannon ; Saito, Mak A. ; Shepherd, Adam ; Wiebe, Peter ; York, Amber

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.
Share 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, Peter

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.
The Biological and Chemical Oceanography Data Management Office: Accelerating Scientific Discovery Through Responsive Management of Observational Oceanographic Data [poster]

(Woods Hole Oceanographic Institution, 2019-09-16) Kinkade, Danie ; Shepherd, Adam ; Biddle, Matt ; Copley, Nancy ; Haskins, Christina ; Soenen, Karen ; Rauch, Shannon ; York, Amber ; Saito, Mak A. ; Wiebe, Peter

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.
In search of Frictionless Data

(Biological and Chemical Oceanography Data Management Office, 2017-09-21) Shepherd, Adam
Capturing 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, Peter

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.
Capturing 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, Peter

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.
Biological & 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, Amber

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.
Collaborative research : EarthCube building blocks, leveraging semantics and linked data for geoscience data sharing and discovery, OceanLink

( 2013-10-28) Wiebe, Peter H. ; Chandler, Cynthia L. ; Raymond, Lisa ; Shepherd, Adam ; Finin, Tim ; Narock, Tom ; Arko, Robert A. ; Carbotte, Suzanne M. ; Hitzler, Pascal ; Cheatham, Michelle ; Krisnadhi, Adila

The OceanLink EarthCube project will apply state-of-the-art Semantic Web Technologies to support data representation, discovery, analysis, sharing, and integration of datasets from the global oceans, and related resources including meeting abstracts and library holdings. Ships are a principal platform from which a wide spectrum of oceanographic data are collected. At the University of Maryland, Baltimore County, semantic relationships will be extracted from text for use in developing methods that efficiently identify relationships across distributed oceanographic datasets. At Wright State University integration of disparate data will occur by refining and applying leading edge technology from the Semantic Web, ontologies, and linked data. From the MBLWHOI Library, DSpace content will be published as Linked Open Data, providing relationships between oceanographic datasets, publications, conference presentations, and funded National Science Foundation projects. Teams of researchers at the Lamont-Doherty Earth Observatory and the Woods Hole Oceanographic Institution will develop Use Cases that represent the needs of the oceanographic research community and will publish oceanographic dataset catalogs as Linked Open Data. A key contribution will be semantically-enabled cyberinfrastructure components capable of automated data integration across distributed repositories. These efforts will ultimately lead to generalized computational techniques applicable to all of EarthCube.
BCO-DMO Quick Guide

( 2018-09-19) Kinkade, Danie ; Shepherd, Adam ; Ake, Hannah ; Biddle, Matt ; Copley, Nancy ; Rauch, Shannon ; York, Amber

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.
Use of Controlled Vocabularies: Potential applications to time series data [talk]

(Woods Hole Oceanographic Institution, 2019-09-13) Shepherd, Adam

Use of Controlled Vocabularies: Potential applications to time series data
Knowledge graphs to support real‐time flood impact evaluation

(Association for the Advancement of Artificial Intelligence, 2022-03-31) Johnson, J. Michael ; Narock, Tom ; Singh-Mohudpur, Justin ; Fils, Douglas ; Clarke, Keith C. ; Saksena, Siddharth ; Shepherd, Adam ; Arumugam, Sankar ; Yeghiazarian, Lilit

A digital map of the built environment is useful for a range of economic, emergency response, and urban planning exercises such as helping find places in app driven interfaces, helping emergency managers know what locations might be impacted by a flood or fire, and helping city planners proactively identify vulnerabilities and plan for how a city is growing. Since its inception in 2004, OpenStreetMap (OSM) sets the benchmark for open geospatial data and has become a key player in the public, research, and corporate realms. Following the foundations laid by OSM, several open geospatial products describing the built environment have blossomed including the Microsoft USA building footprint layer and the OpenAddress project. Each of these products use different data collection methods ranging from public contributions to artificial intelligence, and if taken together, could provide a comprehensive description of the built environment. Yet, these projects are still siloed, and their variety makes integration and interoperability a major challenge. Here, we document an approach for merging data from these three major open building datasets and outline a workflow that is scalable to the continental United States (CONUS). We show how the results can be structured as a knowledge graph over which machine learning models are built. These models can help propagate and complete unknown quantities that can then be leveraged in disaster management.
Making 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, Peter

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.
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
The 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.
Biological 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, Amber

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/
The advantages of machine aided co-reference resolution for research cruise metadata

( 2017-05-31) Shepherd, Adam ; Chandler, Cynthia L. ; Arko, Robert A. ; Fils, Douglas ; Kinkade, Danie

One of the central incentives of deploying linked open data is the opportunity to leverage the linkages between source datasets to retrieve related information. The Biological and Chemical Oceanography Data Management Office (BCO-DMO) reaps these benefits by linking its cruise-level metadata to the Rolling Deck to Repository (R2R) – the trusted, authoritative source for cruises undertaken by the U.S. academic research fleet. Even though the process of identifying a link between these two repositories is easy for a human, this talk will explore the advantages of using a machine-aided process to suggest links to R2R cruises to a BCO-DMO data manager.
SeaView : bringing together an ocean of data

(The Oceanography Society, 2018-02-09) Stocks, Karen ; Diggs, Stephen ; Olson, Christopher ; Pham, Anh ; Arko, Robert A. ; Shepherd, Adam ; Kinkade, Danie

The Ocean Observatories Initiative (OOI) supports a comprehensive information management system for data collected by OOI assets, providing access to a wealth of new information for scientists. But what of those wishing to access data from the region of an OOI research array that is not from OOI assets, perhaps to look at longer term trends from before the launch of OOI, or to build a larger regional context? Despite the excellent work of ocean data repositories, finding, accessing, understanding, and reformatting data for use in a desired visualization or analysis tool remains challenging, especially when data are held in multiple repositories.
Data 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, Peter

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.
Aligned semantics to advance data interoperability across the ocean value chain - from raw data to societal goals [poster]

(Woods Hole Oceanographic Institution, 2019-09-16) Shepherd, Adam ; Caltagirone, Scott ; Kokkinaki, Alexandra ; Leadbetter, Adam ; Moncoiffe, Gwenaelle ; Simpson, Pauline ; Thomas, Robert ; Buttigieg, Pier Luigi

The FAIR principles (Findability, Accessibility, Interoperability, Re-usability) have pervaded discussions on data across disciplines and sectors.While data Findability and Accessibility has greatly improved, considerable difficulties in scalable interoperation remain. Without significant progress, the rapidly growing stores of ocean data risk being siloed for many years to come. A key aspect of Interoperability is "semantic": using knowledge representation (KR) to translate human understanding into machine-readable form. Quality KR allows machines to "understand" what any information artifact is about and relate it to similar artifacts, enabling discovery and enhancing reuse. KR products are usually expressed as vocabularies, glossaries, thesauri, or ontologies (collectively, terminologies), each with its own costs and benefits. Ironically, most marine terminologies are, themselves, not truly interoperable. This is an unfortunate but inevitable outcome of localised and transient funding, and the lack of sustained global infrastructures.Nonetheless, voluntary consortia are addressing this issue with urgency to realise the promise of KR in ocean observation. Here, we present 1) the alignment of well-adopted marine terminologies, 2) a collective strategy for sustained interoperability, and 3) a use case featuring the IOC-UNESCO Ocean Best Practice System. Initialised by the Biological and Chemical Oceanography Data Management Office, we are interlinking terminologies from the Natural Environment Research Council's Vocabulary Server, the Open Biological and Biomedical Ontologies Foundry, and the Earth Science Information Partners. To serve the UNESCO Decade of Ocean Science for Sustainable Development, this effort includes ontologies which represent both the Essential Ocean Variables and the UN Sustainable Development Goals. Finally, we provide perspectives on what measures are needed to meet the interoperability challenge at scale over the next decade.

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