Difference between revisions of "Template:Article of the week"

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(Updated article of the week text.)
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'''"[[Journal:A multi-service data management platform for scientific oceanographic products|A multi-service data management platform for scientific oceanographic products]]"'''
'''"[[Journal:The FAIR Guiding Principles for scientific data management and stewardship|The FAIR Guiding Principles for scientific data management and stewardship]]"'''


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, variable selection, data subsetting or map generation. Metadata Service is the heart of the information system of 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. ('''[[A multi-service data management platform for scientific oceanographic products|Full article...]]''')<br />
There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders — representing academia, industry, funding agencies, and scholarly publishers — have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This comment article represents the first formal publication of the FAIR Principles, and it includes the rationale behind them as well as some exemplar implementations in the community. ('''[[The FAIR Guiding Principles for scientific data management and stewardship|Full article...]]''')<br />
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''Recently featured'':  
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Revision as of 16:09, 26 June 2017

"The FAIR Guiding Principles for scientific data management and stewardship"

There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders — representing academia, industry, funding agencies, and scholarly publishers — have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This comment article represents the first formal publication of the FAIR Principles, and it includes the rationale behind them as well as some exemplar implementations in the community. (Full article...)

Recently featured:

A multi-service data management platform for scientific oceanographic products
MASTR-MS: A web-based collaborative laboratory information management system (LIMS) for metabolomics
The effect of a test ordering software intervention on the prescription of unnecessary laboratory tests - A randomized controlled trial