TL;DR: The Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) is introduced, a custom instance of the NASA Land Information System (LIS) framework used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa.
TL;DR: The original version of this Data Descriptor contained a typographical error in the spelling of the author Terence C. Wong, which was incorrectly given as Terrence C Wong as discussed by the authors.
Abstract: Scientific Data 1:140035 doi: 10.1038/sdata.2014.35 (2014); Published 30 September 2014; Updated 11 November 2014 The original version of this Data Descriptor contained a typographical error in the spelling of the author Terence C. Wong, which was incorrectly given as Terrence C. Wong. This has now been corrected in the PDF and HTML versions of the Data Descriptor.
TL;DR: This Data Descriptor describes a single unified and universally accessible data file, merging across 255 separate files and stitching data across 4 surveys, encompassing 41,474 individuals and 1,191 variables.
Abstract: The National Health and Nutrition Examination Survey (NHANES) is a population survey implemented by the Centers for Disease Control and Prevention (CDC) to monitor the health of the United States whose data is publicly available in hundreds of files. This Data Descriptor describes a single unified and universally accessible data file, merging across 255 separate files and stitching data across 4 surveys, encompassing 41,474 individuals and 1,191 variables. The variables consist of phenotype and environmental exposure information on each individual, specifically (1) demographic information, physical exam results (e.g., height, body mass index), laboratory results (e.g., cholesterol, glucose, and environmental exposures), and (4) questionnaire items. Second, the data descriptor describes a dictionary to enable analysts find variables by category and human-readable description. The datasets are available on DataDryad and a hands-on analytics tutorial is available on GitHub. Through a new big data platform, BD2K Patient Centered Information Commons (
http://pic-sure.org
), we provide a new way to browse the dataset via a web browser (
https://nhanes.hms.harvard.edu
) and provide application programming interface for programmatic access. Machine-accessible metadata file describing the reported data (ISA-Tab format)
TL;DR: The original version of this Data Descriptor contained a typographical error in the spelling of the author Xiaojing Wang which was incorrectly given as Xaojing Wang.
Abstract: Scientific Data 2:150022 doi: 10.1038/sdata.2015.22 (2015); Published 23 June 2015; Updated 21 July 2015
The original version of this Data Descriptor contained a typographical error in the spelling of the author Xiaojing Wang which was incorrectly given as Xaojing Wang. This has now been corrected in the PDF and HTML versions of the Data Descriptor.
TL;DR: In this article, the authors present an approach and method for distributing data from a central digital data processing system to remote DDPs and apparatus for storing data in DDP systems.
Abstract: Apparatus and method for distributing data from a central digital data processing system to remote digital data processing systems and apparatus for storing data in digital data processing systems. The central digital data system creates a data descriptor which describes the data and its source location. The central system provides the data descriptor to the remote systems. The remote systems employ the data descriptor to retrieve the data to be distributed and place it in a destination. A given digital data processing system may function as both a central system and a remote system. The data descriptor may be provided to the remote systems by means of magnetic media or a network and the data may be retrieved from magnetic media or via a network. When retrieval is via a network, the source of the data is an inventory library. The inventory library may be part of the central system or may be part of a different host system. The destination includes a live library and a run library. The data is retrieved to the live library, and when it is to be used, the remote system installs the data by placing it in the run library. Both test and production versions of data may be present in the destination and a test version may be converted to a production version. If both test and production versions are simultaneously present, one is always in the live library and the other always in the run library.