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A database and framework for carbon ore resources and associated supply chain data.
Justman, Devin; Sabbatino, Michael; Montross, Scott; Pantaleone, Scott; Bean, Andrew; Rose, Kelly; Thomas, Randal B.
Afiliación
  • Justman D; National Energy Technology Laboratory, 1450 Queen Ave. SW, Albany, OR 97321, USA.
  • Sabbatino M; NETL Support Contractor, 1450 Queen Ave. SW, Albany, OR 97321, USA.
  • Montross S; National Energy Technology Laboratory, 1450 Queen Ave. SW, Albany, OR 97321, USA.
  • Pantaleone S; NETL Support Contractor, 1450 Queen Ave. SW, Albany, OR 97321, USA.
  • Bean A; National Energy Technology Laboratory, 1450 Queen Ave. SW, Albany, OR 97321, USA.
  • Rose K; NETL Support Contractor, 1450 Queen Ave. SW, Albany, OR 97321, USA.
  • Thomas RB; National Energy Technology Laboratory, 1450 Queen Ave. SW, Albany, OR 97321, USA.
Data Brief ; 40: 107761, 2022 Feb.
Article en En | MEDLINE | ID: mdl-35005150
The Carbon Ore Resources Database (CORD) is a working collection of 399 data files associated with carbon ore resources in the United States. The collection includes spatial/non-spatial, filtered, processed, and secondary data files with original data acquisition efforts focused on domestic coal resources. All data were acquired via open-source, online sources from a combination of 18 national, state, and university entities. Datasets are categorized to represent aspects of carbon ore resources, to include: Geochemistry, Geology, Infrastructure, and Samples. Geospatial datasets are summarized and analyzed by record and dataset density or the number of records or datasets per 400 square kilometer grid cells. Additionally, the "CORD Platform," an ArcGIS Online geospatial dashboard web application, enables users to interact and query with CORD datasets. The CORD provides a single database and location for data-driven analytical needs associated with the utilization of carbon ore resources.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Risk_factors_studies Idioma: En Revista: Data Brief Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Países Bajos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Risk_factors_studies Idioma: En Revista: Data Brief Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Países Bajos