Automatic Data Standardization for the Global Cryosphere Watch Data Portal. (24th February 2020)

• Record Type: Journal Article
• Authors: Bavay, Mathias; Fiddes, Joel; Godøy, Øystein
• Is Part Of: Data science journal. Volume 19(2020)
• Publication Date: 2020-02-24
• Subjects: meteorological data -- data processing -- standardization -- publication -- automatic; Science -- Data processing -- Periodicals; Database management -- Periodicals; 502.85
• DOI: 10.5334/dsj-2020-006
• Languages: English
• ISSNs: 1683-1470

Abstract

The Global Cryosphere Watch (GCW) was initiated by the World Meteorological Organization (WMO) as a mechanism to support the delivery of Earth System monitoring, modelling and prediction services focused on the cryosphere. GCW fosters international coordination and partnerships with the goal of providing authoritative, clear and usable data, information and analyses on the past, current and future state of the cryosphere. It fosters sustained and mutually beneficial partnerships between research and operational institutions, by linking research and operations as well as scientists and practitioners. This is important as most available cryospheric data come from the scientific community. It is generally managed by research institutes which often do not have the infrastructure, the resources, nor the mandate to enable FAIR data management, which is necessary for interoperability and discovery at data level. This implies that data do not fit into standardized systems or dataflows for broader data access and exchange (as exists at the WMO) and thus have been unavailable for operational meteorological and climate applications. This lack of standardization also impairs the reuse of data within the scientific community. GCW is bridging this gap through a data portal and software stack enabling the transformation of sparsely documented and highly variable data into standardized and well documented data suitable for downstream applications with data level interoperability. A processing engine converts raw data provided by the data producers into NetCDF-CF standard files with NetCDF Attribute Convention for Dataset Discovery (ACDD) metadata. The data portal web front end harvests the metadata necessary for its search engine through an OPeNDAP server so no manual editing of the medatadata is necessary. When a user downloads some data from the web portal, it gets the requested data through the OPeNDAP server.