Rapid Deployment of a RESTful Service for Oceanographic Research Cruises

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Abstract:

The Rolling Deck to Repository (R2R) program has the mission to capture, catalog, and describe the underway environmental sensor data from US oceanographic research vessels and submit the data to public long-term archives. Information about vessels, sensors, cruises, datasets, people, organizations, funding awards, logs, reports, etc. is published online as Linked Open Data, accessible through a SPARQL endpoint. In response to user feedback, we are developing a RESTful service based on the Elda open-source Java package to facilitate data access. Our experience shows that constructing a simple portal with limited schema elements in this way can significantly reduce development time and maintenance complexity compared to PHP or Servlet based approaches.

History

DateCreated ByLink
June 4, 2014
23:14:02
Linyun FuDownload

Related Projects:

TW LogoRolling Deck to Repository (R2R)
Co Investigator: Vicki Ferrini
Description: With their global capability and diverse array of sensors, the U.S. academic research fleet is an essential mobile observing platform for ocean science. Data collected on every expedition are of high value, especially given the high costs and increasingly limited resources for ocean exploration. The Rolling Deck to Repository (R2R) program aims to develop comprehensive fleet-wide management of underway data to ensure preservation of and access to our national oceanographic research data resources.

Related Research Areas:

Data Science
Lead Professor: Peter Fox
Description: Science has fully entered a new mode of operation. Data science is advancing inductive conduct of science driven by the greater volumes, complexity and heterogeneity of data being made available over the Internet. Data science combines of aspects of data management, library science, computer science, and physical science using supporting cyberinfrastructure and information technology. As such it is changing the way all of these disciplines do both their individual and collaborative work.

Data science is helping scienists face new global problems of a magnitude, complexity and interdisciplinary nature whose progress is presently limited by lack of available tools and a fully trained and agile workforce.

At present, there is a lack formal training in the key cognitive and skill areas that would enable graduates to become key participants in escience collaborations. The need is to teach key methodologies in application areas based on real research experience and build a skill-set.

At the heart of this new way of doing science, especially experimental and observational science but also increasingly computational science, is the generation of data.

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