A multi-service data management platform for scientific oceanographic products

Abstract

Abstract. An efficient, secure and interoperable data platform solution has been developed in the TESSA project to provide fast navigation and access to the data stored in the data archive, as well as a standard-based metadata management support. The platform mainly targets scientific users and the situational sea awareness high-level services such as the decision support systems (DSS). These datasets are accessible through the following three main components: the Data Access Service (DAS), the Metadata Service and the Complex Data Analysis Module (CDAM). The DAS allows access to data stored in the archive by providing interfaces for different protocols and services for downloading, variables selection, data subsetting or map generation. Metadata Service is the heart of the information system of the TESSA products and completes the overall infrastructure for data and metadata management. This component enables data search and discovery and addresses interoperability by exploiting widely adopted standards for geospatial data. Finally, the CDAM represents the back-end of the TESSA DSS by performing on-demand complex data analysis tasks.

Boosting a Weather Monitoring System in Low Income Economies Using Open and Non-Conventional Systems: Data Quality Analysis

“…The main open question is: could a 4ONSE system be a viable solution to monitor local phenomena in a sustainable and “effective way”, so as to meet the users’ needs? Unfortunately, despite the existence of research that investigated Open Hardware solutions [ 23 , 24 ] or Open Standard [ 25 , 26 ], to the knowledge of the authors, the combination of these two systems with open software and data has been investigated in only a few cases [ 27 , 28 , 29 ]. The question, which remains therefore largely under-explored, is partially addressed in this research which evaluates the quality of the 4ONSE system, and it is presented in the next sections.…”

“…The observed series should be acquired at regular steps and at fixed locations in time by a large number of stations. A continuous and reliable transmission permits the archival of data in a central data warehouse [ 28 ]. Long time series are mostly desired, while a long network lifetime is required.…”