Developing a Linked Data convention for standardising scientific data encoded using netCDF

Dr Jonathan Yu1, Mr Mark Hedley2, Mr James Biard4, Dr Adam Leadbetter3

1Csiro , Clayton , Australia, 2UK Met Office, Exeter, United Kingdom, 3Marine Institute, Galway, Ireland, 4NOAA, , USA

 

netCDF is a format for encoding array-oriented scientific data and adoption in many domains including climatology, oceanography, and hydrology. The format is an open standard and an Open Geospatial Consortium (OGC) international standard.

A common practice is to use the Climate and Forecasting (CF) convention (http://cfconventions.org/) and the Attribute Convention for Data Discovery (ACDD) convention (http://wiki.esipfed.org/index.php/Attribute_Convention_for_Data_Discovery_1-3). Several communities are defining additional netCDF conventions for describing semantics relating to their different domains which are outside the scope of CF and ACDD. As the concurrent use of multiple, possibly clashing, conventions spreads, we are faced with the challenge of finding a common mechanism to validate and interpret metadata being embedded inside netCDF files.

Linked Data (LD) describes a method for encoding and publishing metadata to expose and connect data within and across datasets and become more useful through semantic queries. LD approaches present an opportunity for the netCDF community to address the above challenge and, beyond that, enhance data discovery and use.

We present some early work in a current OGC activity to define the netCDF-Classic-LD convention for constructing and interpreting metadata and structures found in netCDF files as LD. The aim is to enable netCDF data to be unambiguously linked with published conventions and controlled vocabularies, and to allow the semantics across files and datasets to be described. Specifically, netCDF-Classic-LD can be applied to support standardisation, validation and interpretation of netCDF content in relation to the conventions defined by different science disciplines and communities.


Biography:

Dr Jonathan Yu is a data scientist researching information and web architectures, data integration, Linked Data, data analytics and visualisation and applies his work in the environmental and earth sciences domain. He is part of the Environmental Informatics group in CSIRO Land and Water. He currently leads a number of initiatives to develop new approaches, architectures, methods and tools for transforming and connecting information flows across the environmental domain and the broader digital economy within Australia and internationally.

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