Gerlach Dana

No Thumbnail Available
Last Name
Gerlach
First Name
Dana
ORCID
0000-0003-3781-4641

Filters

2020 - 2024 4
4
4
Reset filters

Settings
Subject: Data management ×

Search Results

Now showing 1 - 4 of 4
Thumbnail Image
Presentation

Capturing Provenance of Data Curation at BCO-DMO

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.

View
Thumbnail Image
Presentation

Data Management and Reporting: BCO-DMO Data Management Services & Best Practices

2024-08-20 , Rauch, Shannon , Kinkade, Danie , Soenen, Karen , Gerlach, Dana , Merchant, Lynne M. , Newman, Sawyer , York, Amber , Schloer, Conrad , Shepherd, Adam

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 in accordance with F.A.I.R. (Findable, Accessible, Interoperable, Reuseable) data principles.

View
Thumbnail Image
Presentation

Biological and Chemical Oceanography Data Management Office: Supporting a New Vision for Adaptive Management of Oceanographic Data [poster]

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/

View
Thumbnail Image
Presentation

How can BCO-DMO help with your oceanographic data?

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.

View