The data management system for the VENUS and NEPTUNE cabled observatories

Abstract

The VENUS (http://venus.uvic.ca/) and NEPTUNE Canada (http://neptunecanada.ca/) cabled ocean observatories have been envisioned from their inception as underwater extensions of the Internet. Having sensors connected to a network opens up tremendous opportunities, from real-time access to sensor measurements to the interactive control of remote assets. Moreover, with a software system in control, data from all sensors can be managed, archived and made available to the wider community. Finally, a data management system can also offer features that are unique to centrally managed instrumentation: thanks to communication standards, autonomous event detection and reaction becomes a very powerful possibility. This talk will summarize the salient features of DMAS (Data Management and Archiving System) that have been implemented over the past four years as well as the planned features to be delivered soon. DMAS consists of two main components: The Data Acquisition Framework (DAF) takes care of the interaction with instruments in terms of control, monitoring as well as data acquisition and storage. The framework also contains operation control tools. The user interaction features include data search and retrieval, data distribution. Current developments in the Web 2.0 area will provide a complete research environment where users will have the ability to work and interact on-line with colleagues, process and visualize data, establish observation schedules and pre-program autonomous, event detection and reaction. We call this environment "Oceans 2.0".The architecture of DMAS is focused on limiting the amount of data loss and maximizing up time. It is a service oriented architecture, making use of some of the more advanced tools available. The code is written in Java and makes use of an Enterprise Service Bus and of the publish-and-subscribe paradigm.The paper also describes the management approaches that were adopted to build DMAS. Good code quality, the continuous support of VENUS and the need for flexibility in dealing with rapidly changing requirements were the drivers behind the adoption of in-house development, the Agile development methodology and the creation of three teams. The development team deals with requirement collection, analysis, design, coding and unit testing; the QA/QC team performs software tests and regression in a production-like environment. The systems/operations team focuses on the hardware and system software preparation and support, receives and installs new code releases after QA approval and monitors systems operations. We are vying to perform new code releases twice a month. The method has worked well during the four years of the system development phase and has allowed for a constant support of VENUS. DMAS will be completed well under budget.

The New Seafloor Observatory (OBSEA) for Remote and Long-Term Coastal Ecosystem Monitoring

“…The newer cabled underwater observatories, in contrast, are modular, flexible and adaptable to different uses and specifications. Cabled observatories allow the interdisciplinary long-term monitoring of the oceans, combining data acquisition from different fields in an effort to understand ecosystem dynamics at different scales [ 41 ] with the use of various underwater oceanographic sensors [ 42 , 43 ]. Additionally, with the use of video imaging systems, important time series of bio-data related to temporal variations in species presence or population size can be also obtained [ 44 ].…”

The potential of video imagery from worldwide cabled observatory networks to provide information supporting fish-stock and biodiversity assessment

“…Deployment and maintenance costs for such marine observatory infrastructures are high because they require extensive ship assets and specialized equipment (e.g. cable laying ships or the use of Remotely Operated Vehicles-ROVs), a wide range of dedicated personnel including mechanics, engineers, marine scientists, data analysts, and an extensive shore-based data distribution platform (Pirenne and Guillemot, 2009;Cristini et al, 2016). For example, the cost to operate ONC's observatories since the deployment of its first seafloor monitoring assets in 2003 has been in excess of 114 M CA$ (https://www.oceannetworks.ca/about-us/ funders-partners/funders).…”