Data Management
CIOOS_SIOOC Metadata Working Group

The recently established Canadian Integrated Ocean Observing System/Système Intégré d’Observation des Océans du Canada (CIOOS/SIOOC) is a national effort to facilitate the knowledge exchange in ocean sciences and to make oceanographic data from various public, private and academic stakeholders discoverable and accessible to the end-user. It is an initiative that is jointly funded by Fisheries and Oceans Canada (DFO) and the Marine Environmental, Observation, Prediction and Response Network (MEOPAR). In it’s pilot phase (2018 - 2020) CIOOS/SIOOC established three regional associations (RA); Pacific, St. Lawrence, and Atlantic, that will each build a data infrastructure in collaboration with their regional data providers and users. A national, centralized, open and web-based platform will aggregate the regionally managed ocean data, supporting a one-stop-shop approach to the discovery and access of information for ocean related research and decision making. Interoperability with international standards and organisations is an important aspect of the CIOOS/SIOOC initiative and will enable contributions to the global effort of better understanding the ocean, it’s issues and interactions with other earth systems.

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Data Visualization
Soundscape Atlas

Underwater noise generated by human activities such as shipping raises concerns about its potential impact on marine life, for instance, by affecting their ability to navigate, communicate, feed, and reproduce. With increased shipping activity along traditional routes and the opening of new shipping lanes, changes in noise distribution in Canadian waters are expected. The Canadian Species at Risk Act imposes to protect the habitats of endangered species from degradation. It is therefore imperative to better understand and quantify the impacts of shipping noise on marine life, so that adequate and efficient protective measures can be implemented where necessary. To aid these efforts, MERIDIAN and collaborators are developing a web-based, interactive Ocean Soundscape Atlas that will enable users to visualize and explore modeled noise levels in a multitude of dimensions including latitude, longitude, depth, time, frequency, and source type, and obtain impact risk estimates in areas of interest.

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Data Analysis
Passive Acoustic Monitoring

Passive acoustic monitoring has become an important tool in fisheries and ecological studies and we know very little about fish sounds, particularly in the Pacific Ocean. There are less than 1000 species of fish that have been documented to produce sound, compared to the 30,000 fish species that exist in the world. MERIDIAN team member, Amalis Riera is collaborating with a few captive facilities to try to describe as many fish sounds as possible from the Pacific Ocean. These will contribute to building a catalogue of known fish sounds that will then be used to identify sounds collected by passive acoustic studies. There are six locations where Amalis has collected acoustic recordings in search of fish sounds between Vancouver Island, Vancouver, Washington State and Oregon. So far there are over 3,000 hours of recordings, some of which have been analyzed and some others that still remain to be inspected. The tanks and net pens where the hydrophones were deployed contained fish species such as Arctic cod (Boreogadus saida), grunt sculpin (Rhamphocottus richardsonii), Herring (Clupea pallasii), Lingcod (Ophiodon elongatus), Northern ronquil (Ronquilus jordani), Pacific cod (Gadus macrocephalus) Red brotula (Brosmophycis marginata), sablefish (Anoplopoma fimbria), saffron cod (Eleginus gracilis), walleye pollock (Gadus chalcogrammus), and white sturgeon (Acipenser transmontanus). Amalis has already validated sounds from Arctic cod, walleye pollock and sablefish, thus contributing to the catalogue with two species of Pacific Ocean gadids and one Pacific deep sea species. A large number of recordings that were analyzed contained no fish sound. It is important to keep in mind that no sound heard doesn’t mean lack of capacity for sound production. The MERIDIAN team is working on creating automated detectors that can recognize several types of fish sounds. The more examples of sounds of a given species we get, and with low background noise, the better we can train neural networks to recognize that signal in large acoustic datasets.

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Data Analysis
Detection and classification of marine animal sounds using deep learning

Many marine species have evolved to rely primarily on sound for underwater navigation, prey detection, and communication. Marine biologists and other ocean researchers listen to the sounds generated by marine animals, for example, to detect the presence of an endangered species or to study social behavior. In recent years, increasing numbers of underwater listening and recording devices are being deployed worldwide, generating vast amounts of data that easily exceed our capacity for manual analysis. MERIDIAN is developing software packages and tools that apply state-of-the-art deep learning techniques to underwater bioacoustics. We aim to provide a library of pre-trained models that can be easily adapted or improved if necessary. We are working hard on the projects described below and will release the first outcomes in the next few months, so keep an eye on this page or subscribe to our newsletter.

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Data Management
Data Discovery Service

One of MERIDIAN’s goals is to position itself as an indispensable data discovery platform for acoustic oceanographic and Automatic Identification System (AIS) data. However, MERIDIAN is not intended to be a data store, and this discovery platform will instead host metadata and include details on data access. To reach this goal, MERIDIAN has developed a custom data description profile (based on existing IOOS metadata conventions and the ISO 19115 and Darwin Core metadata standards) and is deploying a GeoNetwork server with a custom discovery layer. To increase MERIDIAN’s reach, we intend to harvest metadata from other services and expose them through our discovery portal. Ideally, other partners will harvest our metadata for their own discovery services. We are also collaborating with the Federated Research Data Repository (FRDR), which should be a useful tool for users who require online storage for their data. Once our metadata profile documentation is complete, we will be sharing it online for all to review and adopt. This will either precede or accompany the public release of our discovery service. Our data managers are currently working hard to make our data discovery service a reality, and we hope to have more to share with you soon.

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Data Management
The Data Discovery Portal for Underwater Acoustic data

Underwater acoustic data is important for understanding the oceans and how sound affects the marine environment. To record underwater sounds produced by, for instance, marine mammals, waves, and ships, and to capture the complexity and interactions of the marine soundscape, hydrophones and other acoustic recording devices are used. These devices capture massive amounts of unstructured data, which is difficult to manage. In addition, sound propagation models produce gridded data that are often used to visualize the propagation of noise over time. To improve discoverability, accessibility and reusability of underwater acoustic data we are developing and implementing a data discovery platform. This project consists of four main elements or sub-projects, (A) the development of a metadata standard to appropriately describe underwater acoustic data addressing the community’s needs, (B) the development and implementation of the technical backend, (C) a user-friendly information submission interface, and (D) a multi-layer search and discovery interface to ensure the data’s findability

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Data Visualization
Directional Acoustic Data Visualizations

MERIDIAN is working with JASCO to design a tool for visualizing underwater acoustic data with a directional component that indicates bearing for use by biologists and other researchers. This system will visualize data collected from hydrophone arrays that are capable of discerning the bearing of sound sources, which can help users distinguish between animals and track movement of vessels and wildlife. Where acoustic data is normally presented to biologists in the form of 2D Time versus Frequency spectrograms which use colour to indicate intensity, this system must also present the directional information in a way that is intuitive for the user. Experimentation with directional colours and filtering techniques has shown promise, but we are investigating solutions that take advantage of interaction, 3-dimensional views, and accompanying Time versus Direction plotting and animations. This system will allow biologists to analyze, classify, and annotate data, and to prepare reports for presentation. The accuracy of directional data can also be subject to environmental conditions surrounding the hydrophones, so we are investigating opportunities to use corresponding AIS (vessel tracking) data and machine/active learning techniques to assess and predict directional certainty. We are also researching secondary opportunities for machine learning to aid biologists in classification tasks.

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Data Analysis
Crowd-sourcing platform for underwater acoustic data

Despite the increasing amounts of underwater acoustic data that become available every day, only a small proportion is actually labelled. MERIDIAN is developing a crowdsourcing platform for labelling datasets, which can then be used to train machine learning models. The platform will allow users to create labelling sessions for their datasets and invite participants to label. With a flexible structure, it is possible to choose the public that will have access to a particular dataset, from a select group of experts to anyone with internet acess.

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Data Analysis
Modelling and predicting the efficiency of acoustic tracking arrays

Acoustic tracking is widely used by marine biologists to study the distributions and movements of fishes and marine mammals on time scales ranging from hours to months or even years. Highly powerful, the technique allows scientists to map the migration routes of salmon, or correlate the habitat use and movement of sharks, and correlate those locations in time with environmental variables. Such studies provide valuable data for decision making in relation to marine environmental management.

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Data Analysis
Acoustic monitoring of boating activity

In Miami, US, a research team led by Dr. Neil Hammerschlag from the University of Miami's Rosenstiel School of Marine and Atmospheric Science, is studying how coastal urbanization is affecting the distribution, movement, and health of coastal sharks. The study, known as the Urban Sharks project, is focusing on the Northern Biscayne Bay, which has been heavily impacted by the 2.5 million people living in and around Miami, not least through high levels of recreational boating activity. Together with OTN, Neil and his team have deployed a tracking array, which is being used to study the distribution and movements of individual tagged sharks. Moreover, they have deployed a number of broadband hydrophones, which they use to listen to underwater sounds, both man-made and from marine life.

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