Large whale stranding, death, ship strike and entanglement incidents are all recorded to monitor the health of each population and track anthropogenic factors that influence their recovery. This Oracle developed database is meant to consolidate the various forms of data into one searchable source for the east coast. Biological and geographic information will be recorded and searchable along with fishing gear information (entanglements), vessel parameters (ship strikes) and serious injury determinations.

National (UK) database of marine accidents including persons and vessels involved, and details of the accident and investigation

An analysis carried out on a database of vessel accidents in Mediterranean port areas developed within the framework of the project ISY PORT (Integrated SYstem for navigation risk mitigation in PORTs). The analyses included distribution of accidents in port areas by gross tonnage, distribution of accidents in port areas by age of the ship at the time of the accident, distribution of accidents in port areas by ship’s category, distribution of accidents in port areas by causality event, distribution of accidents in port areas by weather conditions, number of fatalities and injured and lost at sea caused by accidents in the port areas.

The database contains details of ships that may have been the subject of a Marine Accident Investigation Branch (MAIB) investigation, or which were third parties in an incident but supplied, for example, Voyage Data Recorders downloads to assist with an investigation.

Information collected about marine accidents, and Marine Accident Investigation Branch's (MAIB) analysis in the course of its investigations.

This database, and the accompanying website called ‘SurgeWatch’ (http://surgewatch.stg.rlp.io), provides a systematic UK-wide record of high sea level and coastal flood events over the last 100 years (1915-2014). Derived using records from the National Tide Gauge Network, a dataset of exceedence probabilities from the Environment Agency and meteorological fields from the 20th Century Reanalysis, the database captures information of 96 storm events that generated the highest sea levels around the UK since 1915. For each event, the database contains information about: (1) the storm that generated that event; (2) the sea levels recorded around the UK during the event; and (3) the occurrence and severity of coastal flooding as consequence of the event. The data are presented to be easily assessable and understandable to a wide range of interested parties. The database contains 100 files; four CSV files and 96 PDF files. Two CSV files contain the meteorological and sea level data for each of the 96 events. A third file contains the list of the top 20 largest skew surges at each of the 40 study tide gauge site. In the file containing the sea level and skew surge data, the tide gauge sites are numbered 1 to 40. A fourth accompanying CSV file lists, for reference, the site name and location (longitude and latitude). A description of the parameters in each of the four CSV files is given in the table below. There are also 96 separate PDF files containing the event commentaries. For each event these contain a concise narrative of the meteorological and sea level conditions experienced during the event, and a succinct description of the evidence available in support of coastal flooding, with a brief account of the recorded consequences to people and property. In addition, these contain graphical representation of the storm track and mean sea level pressure and wind fields at the time of maximum high water, the return period and skew surge magnitudes at sites around the UK, and a table of the date and time, offset return period, water level, predicted tide and skew surge for each site where the 1 in 5 year threshold was reached or exceeded for each event. A detailed description of how the database was created is given in Haigh et al. (2015). Coastal flooding caused by extreme sea levels can be devastating, with long-lasting and diverse consequences. The UK has a long history of severe coastal flooding. The recent 2013-14 winter in particular, produced a sequence of some of the worst coastal flooding the UK has experienced in the last 100 years. At present 2.5 million properties and £150 billion of assets are potentially exposed to coastal flooding. Yet despite these concerns, there is no formal, national framework in the UK to record flood severity and consequences and thus benefit an understanding of coastal flooding mechanisms and consequences. Without a systematic record of flood events, assessment of coastal flooding around the UK coast is limited. The database was created at the School of Ocean and Earth Science, National Oceanography Centre, University of Southampton with help from the Faculty of Engineering and the Environment, University of Southampton, the National Oceanography Centre and the British Oceanographic Data Centre. Collation of the database and the development of the website was funded through a Natural Environment Research Council (NERC) impact acceleration grant. The database contributes to the objectives of UK Engineering and Physical Sciences Research Council (EPSRC) consortium project FLOOD Memory (EP/K013513/1).

The Marine Casualty and Pollution Data files provide details about marine casualty and pollution incidents investigated by Coast Guard Offices throughout the United States. The database can be used to analyze marine accidents and pollution incidents by injury.

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Coastal flooding caused by extreme sea levels can produce devastating and wide-ranging consequences. The ‘SurgeWatch’ v1.0 database systematically documents and assesses the consequences of historical coastal flood events around the UK. The original database was inevitably biased due to the inconsistent spatial and temporal coverage of sea-level observations utilised. Therefore, we present an improved version integrating a variety of ‘soft’ data such as journal papers, newspapers, weather reports, and social media. SurgeWatch2.0 identifies 329 coastal flooding events from 1915 to 2016, a more than fivefold increase compared to the 59 events in v1.0. Moreover, each flood event is now ranked using a multi-level categorisation based on inundation, transport disruption, costs, and fatalities: from 1 (Nuisance) to 6 (Disaster). For the 53 most severe events ranked Category 3 and above, an accompanying event description based upon the Source-Pathway-Receptor-Consequence framework was produced. The database contains 57 files: 1 XLSX file, 54 PDF files and 1 CSV file. The first file is a spreadsheet (XLSX) containing the list of all 329 coastal flood events in the database categorised according to the severity scale that we devised. The second and third files are PDF documents containing the short commentaries for all Category 1 and 2 events. There are an additional 53 PDF files containing the longer event commentaries for events ranked Category 3 and higher. A final CSV file contains the digitised storm tracks for the 53 Category 3 and higher events. Each of these files is self-describing and is accompanied by extensive metadata. SurgeWatch v2.0 provides the most comprehensive and coherent historical record of UK coastal flooding. It is designed to be a resource for research, planning and management and education. Haigh et al. (2017) provides more detail. Collation of the database and the development of the website was funded through a Natural Environment Research Council (NERC) impact acceleration grant. The database contributes to the objectives of UK Engineering and Physical Sciences Research Council (EPSRC) consortium project FLOOD Memory (EP/K013513/1).

This dataset is a record of all verified stranded (live sick/injured, dead beached/floating) southern sea otters (Enhydra lutris nereis) in California. The data collected include the date and location of stranding, condition, age class and sex of the animal, morphometrics, and very general external and internal necropsy findings. These data have been collected continually since 1968 and are used to identify unusual mortality events, track causes of anthropogenic mortality for mitigation, and inform resource managers about the extent and causes of mortality affecting the southern sea otter population. These data may also be used during or after an oil spill for Natural Resource Damage Assessment purposes, or to inform best achievable recovery and care of live animals. Prior to 2019, the data were managed by the U.S. Geological Survey (USGS) and data from 1985 to 2018 are available on the USGS website. Data from the earliest years are not yet available in a standardized electronic format, but a subset of the database from 2019 onward is available through this portal. A stranding summary report is also provided for each year starting in 2019. This data and metadata were submitted by California Department of Fish and Wildlife (CDFW) Staff though the Data Management Plan (DMP) framework with the id: DMP000394. For more information, please visit https://res1wildlifed-o-tcad-o-tgov.vcapture.xyz/Data/Sci-Data.

The advent of large-scale cabled ocean observatories brought about the need to handle large amounts of ocean-based data, continuously recorded at a high sampling rate over many years and made accessible in near-real time to the ocean science community and the public. Ocean Networks Canada (ONC) commenced installing and operating two regional cabled observatories on Canada’s Pacific Coast, VENUS inshore and NEPTUNE offshore in the 2000s, and later expanded to include observatories in the Atlantic and Arctic in the 2010s. The first data streams from the cabled instrument nodes started flowing in February 2006. This paper describes Oceans 2.0 and Oceans 3.0, the comprehensive Data Management and Archival System that ONC developed to capture all data and associated metadata into an ever-expanding dynamic database. Oceans 2.0 was the name for this software system from 2006–2021; in 2022, ONC revised this name to Oceans 3.0, reflecting the system’s many new and planned capabilities aligning with Web 3.0 concepts. Oceans 3.0 comprises both tools to manage the data acquisition and archival of all instrumental assets managed by ONC as well as end-user tools to discover, process, visualize and download the data. Oceans 3.0 rests upon ten foundational pillars: (1) A robust and stable system architecture to serve as the backbone within a context of constant technological progress and evolving needs of the operators and end users; (2) a data acquisition and archival framework for infrastructure management and data recording, including instrument drivers and parsers to capture all data and observatory actions, alongside task management options and support for data versioning; (3) a metadata system tracking all the details necessary to archive Findable, Accessible, Interoperable and Reproducible (FAIR) data from all scientific and non-scientific sensors; (4) a data Quality Assurance and Quality Control lifecycle with a consistent workflow and automated testing to detect instrument, data and network issues; (5) a data product pipeline ensuring the data are served in a wide variety of standard formats; (6) data discovery and access tools, both generalized and use-specific, allowing users to find and access data of interest; (7) an Application Programming Interface that enables scripted data discovery and access; (8) capabilities for customized and interactive data handling such as annotating videos or ingesting individual campaign-based data sets; (9) a system for generating persistent data identifiers and data citations, which supports interoperability with external data repositories; (10) capabilities to automatically detect and react to emergent events such as earthquakes. With a growing database and advancing technological capabilities, Oceans 3.0 is evolving toward a future in which the old paradigm of downloading packaged data files transitions to the new paradigm of cloud-based environments for data discovery, processing, analysis, and exchange.

The Global Historical Tsunami Database provides information on over 2,400 tsunamis from 2100 BC to the present in the the Atlantic, Indian, and Pacific Oceans; and the Mediterranean and Caribbean Seas. The database includes two related files. The first file includes information on the tsunami source such as the date, time, and location of the source event; cause and validity of the source, tsunami magnitude and intensity; maximum water height; the total number of fatalities, injuries, houses destroyed, and houses damaged; and total damage estimate (in U.S. dollars). The second related file contains information on the runups (the locations where tsunami waves were observed by eyewitnesses, reconnaissance surveys, tide gauges, and deep-ocean sensors) such as name, location, arrival time, maximum water height and inundation distance, and socio-economic data (deaths, injuries, damage) for the specific runup location.

About A Global Database on Migrant Boat Losses at Sea, 1990 to 2015 contains information on migrant boat losses worldwide between 1990 and 2015. To construct this database, we employed a mixed methodology designed to locate, record and analyse boat losses to fill gaps we identified in the border externalisation literature. This involved collecting data from media aggregators and additional sources using content analysis for descriptive and time series statistical analysis. Our novel contributions via the database included to generalise time and geography in our analysis of boat losses, use of statistical methods therein and the provision of new empirical evidence related to the claim in migration studies that tougher border enforcement in the name of deterrence is generally ineffective in reducing migrant flows. Summary While migration by boat is an ancient human phenomenon, recent increases in deaths of migrants crossing the sea reached historical highs among those trying to land on sovereign territory of nation-states of the “Global North”. Increases in deaths also were accompanied by significant increases in global media coverage and resources dedicated to enforcement operations in the annual budgets of border enforcement activities. Despite this, little existing scholarship tracked this relationship between increased enforcement and migrant losses at sea. This project, therefore, worked to empirically demonstrate correlations between observed boat losses and enforcement using statistical methods. Our findings were published in the journal International Migration in 2018 under the title, “Between Enforcement and Precarity: Externalization and Migrant Deaths at Sea”. In this article, and based on this database, we argued that although discourse about boat interception and externalisation has shifted to humanitarian rescue narratives, offshore enforcement by any other name continues to be highly correlated with migrant deaths. Our analysis continues to be timely due to empirical spikes in human displacement worldwide. Data Structure We built the collected data into a structured database sourced from targeted queries on two large media databases, LexisNexis and Factiva, as well as search engines to locate reports on migrant boat losses. We analysed and stored these articles in portable document format (PDF) for recording in our database. We were interested in a number of variables, including data of the loss incident, ship name, location, region, estimated passengers, estimated losses, ship origin, passenger origins, desired destination and related enforcement activities. The resulting data were linked through a comma-separated value (CSV) table to the PDF files for analysis in Stata 14. In terms of linkages in the database, we named each article file after the case it represents; “1.pdf”, therefore, represents the first case/observation. Multiple but distinct articles for the same case featured the same number appended by a lower-case Roman numeral (e.g., “1a.pdf” and “1b.pdf”). The database, “losses_at_sea_database_10102017.csv”, contains a variable, Files, which associated the given case with its corresponding articles. By the end of the project, we had collected 250 media reports on 218 discrete boat loss incidents and stored them per best practises in data management. We also catalogued 30 photographs related to these incidents that appeared in reports. Final case and report counts were obtained after quality assurance of all data. Data Sources As noted, our primary data sources were the media aggregator engines LexisNexis and Factiva; however, we also used search engines. While initial searches focused solely on terms like “migrant boat incident”, we quickly began to identify more robust keywords and phrases in order to create more accurate searches. In attempts to exhaust reports from these sources, we employed multiple search terms and compared our outputs to contemporary data sets. As we analysed the documents, we decided to code additional variables not previously considered. For example, while many reports had estimates of passenger survivals or deaths, it became apparent that they also recorded the number of passengers missing from a loss. Some variables we had sought to record, like ship name, were nearly universally absent from available reports, but were included as missing observations where appropriate. We also found that most incidents featured more than one report, some of which recorded different but important details for the project. As stated, we therefore stored and used multiple reports of the same boat loss or operation for the data sets to enhance the completeness and reliability of the data. If you use these data, please cite the original source at Williams, K., & Mountz, A. (2018). Between Enforcement and Precarity: Externalization and Migrant Deaths at Sea. International Migration, 56(5), 74-89. Should you have any comments, questions or requested edits or...

The marine mammals website (www.marinemammals.be) in its current form is the result of a long-standing collaboration between RBINS and the University of Liège and provides access to data from 50 years of marine mammal observations in Belgium. The database that backs it consists of two parts, i.e. observations and information on necropsied tissues and subsequent diagnoses on the cause of the death of the animal. The database records all stranding events in Belgium from recent years. The dataset provides the occurrences and associated data like putative circumstances and putative cause of death.

This dataset is a record of all verified stranded (live sick/injured, dead beached/floating) southern sea otters (Enhydra lutris nereis) in California. The data collected include the date and location of stranding, condition, age class and sex of the animal, morphometrics, and very general external and internal necropsy findings. These data have been collected continually since 1968 and are used to identify unusual mortality events, track causes of anthropogenic mortality for mitigation, and inform resource managers about the extent and causes of mortality affecting the southern sea otter population. These data may also be used during or after an oil spill for Natural Resource Damage Assessment purposes, or to inform best achievable recovery and care of live animals. Prior to 2019, the data were managed by the U.S. Geological Survey (USGS) and data from 1985 to 2018 are available on the USGS website. Data from the earliest years are not yet available in a standardized electronic format, but a subset of the database from 2019 onward is available through this portal. A stranding summary report is also provided for each year starting in 2019.

This data and metadata were submitted by California Department of Fish and Wildlife (CDFW) Staff though the Data Management Plan (DMP) framework with the id: DMP000394. For more information, please visit https://wildlife.ca.gov/Data/Sci-Data.

EMSA helps the European Commission and member states to improve maritime safety by analysing accident investigation reports and producing maritime casualty statistics. The European Marine Casualty Information Platform (EMCIP) run by EMSA is a centralised database where member states can store and analyse information on marine casualties and incidents. EMSA also hosts the Permanent Cooperation Framework where member states and the European Commission work together to facilitate cooperation among accident investigation bodies.

A later version of this dataset exists published 2019-01-18, accessible through the data links on this page.

This dataset contains records of sting events and specimen samples of jellyfish (Irukandji) along the north Queensland coast from December 1998 to March 2017. This dataset contains an extract (265 records in CSV format) of the publicly available data contained in the Venomous Jellyfish Database. The full database contains approximately 3000 sting events from around Australia and includes records from sources that have not yet been cleared for release.

This extract was made for eAtlas as part of the 2.2.3 NESP Irukandji forecasting system project and used as part of the development of the Irukandji forecasting model. The data was compiled from numerous sources (noted in each record), including Lisa-ann Gershwin and media reports.

The sting data includes primary information such as date, time of day and locality of stings, as well as secondary details such as age and gender of the sting victim, where on the body they were stung, their activity at the time of the sting and their general medical condition.

Limitations:

This data shows the occurrence of reported jellyfish stings and specimens along the north Queensland coast. It does NOT provide a prediction of where jellyfish or jellyfish sting events may occur.

These records represent a fraction of known sting events and specimen collections, with more being added to the list of publicly available data as permissions are granted.

Historical data dates may be coarse, showing month and year that the sting occurred in. Some events have date only.

Methods:

This data set contains information on sting events and specimen collections that have occurred around Australia, which involved venomous jellyfish (Irukandji syndrome-producing species in the genera Carukia, Malo, Morbakka).

This data was collected over numerous years by Lisa-ann Gershwin from various sources, predominantly news reports. This data was entered into an Excel spreadsheet, which formed the basis of the Venomous Jellyfish Database. This database was developed as part of the 2.2.3 NESP Irukandji forecasting system project.

Some data have been standardised, e.g., location information and sting site on the body. Data available to the public have been approved by the data owners, or came from a public source (e.g. newspaper reports, media alerts).

Format:

Comma Separated Value (CSV) table. eAtlas Note: The original database extract was provided as an Excel spreadsheet table. This was converted to a CSV file.

Data Dictionary:

• CSIRO_ID: Unique id
• EVENT_TYPE: Type of event – sting or specimen
• STATE: State in which event occurred
• REGION: Broader region of State the event occurred in
• LOCAL_GOV_AREA: Local government area that the event occurred in – if known
• MAIN_LOCALITY: Main locality that the event occurred in
• SITE_INFO: Site details/comments
• YEAR: Year event occurred
• MONTH: Month event occurred
• DAY: Day of the month the event occurred
• EVENT_TIME: Time the event occurred HH24:MI If time is unknown then NULL
• EVENT_RECORDED: time/date event reported e.g. early afternoon, morning, on weekend
• EVENT_COMMENTS: Comments about the event
• LAT: Latitude in decimal degrees
• LON: Longitude in decimal degrees
• LOCATION_ACCURACY: How accurate the location is
• EVENT_OFFSHORE_ONSHORE: Where the event occurred (if known) – beach, island, reef
• LOCATION_COMMENTS: Comments relating to the location of the event
• WATER_DEPTH_M: Depth of water, in metres, that the event occurred in (if known)
• AGE: Age of patient if known
• SEX: Gender of patient if known
• HOME: Home state/county of patient
• HOSPITAL: Hospital the patient was treated at (if known)
• STING_SITE_REPORTED: Reported sting site on the body
• STING_SITE_BODY: Standardised area on body that sting was reported – upper limb, lower limb etc.
• NUMBER_STINGS: Number of stings recorded, if known
• VISIBLE_STING: The nature of visible sting marks, if reported
• PPE_WORN: Was Personal Protective Equipment (PPE) worn?
• PATIENT_COMMENTS: Comments about the patient
• TIME_TO_ONSET: Delay between sting and onset of symptoms, if reported
• PATIENT_CONDITION: State the patient was in, e.g. distressed, calm, stable
• BLOOD_PRESSURE: Comments relating to blood pressure of the patient
• NAUSEA_VOMITING: Did the patient experience nausea and/or vomiting?
• PAIN: Location and/or intensity of pain experienced by the patient
• SWEATING: Did the patient experience sweating?
• TREATMENT: What treatment the patient was given
• DISCHARGED: When the patient was discharged from hospital
• ONGOING_SYMPTOMS: What ongoing symptoms the patient is experiencing
• NEMATO_SAMPLES: Were nematocyst samples taken?
• SPECIES_NAME: Species name, if determined
• PATROL: Was the sting on a patrolled beach
• CURATOR: Where the data came from e.g. Gershwin = Lisa-ann Gershwin
• DATA_CODE: Access constraint on data
• REFERENCE: Source of the information for event
• ENTERED_BY: Who entered the data
• ENTERED_DATE: When the data was entered

References:

Gershwin, L. (2013). Stung! On Jellyfish Blooms and the Future of the Ocean. Chicago, University of Chicago Press.

Lisa-Ann Gershwin , Monica De Nardi , Kenneth D. Winkel & Peter J. Fenner (2010) Marine Stingers: Review of an Under-Recognized Global Coastal Management Issue, Coastal Management, 38:1, 22-41, http://dx.doi.org/10.1080/08920750903345031

Gershwin L, Condie SA, Mansbridge JV, Richardson AJ. 2014 Dangerous jellyfish blooms are predictable. J. R. Soc. Interface 11: 20131168. http://dx.doi.org/10.1098/rsif.2013.1168

Gershwin, L., A. J. Richardson, K. D. Winkel, P. J. Fenner, J. Lippmann, R. Hore, G. Avila-Soria, D. Brewer, R. J. Kloser, A. Steven and S. Condie (2013). Biology and ecology of Irukandji jellyfish (Cnidaria: Cubozoa). Advances in Marine Biology 66: 1-85.

Data Location:

This dataset is filed in the eAtlas enduring data repository at: data\custodian\2016-18-NESP-TWQ-2\2.2.3_Jellyfish-early-warning\AU_NESP-TWQ-2-2-3_CSIRO_Venomous-Jellyfish-DB

The differential effects of climate change, sea level, and water mass circulation on deposition/erosion of marine sediments can be constrained from the distribution of unconformities in the world's oceans. I identified temporal and depth patterns of hiatuses ("hiatus events") from a large and chronologically well constrained stratigraphic database of deep-sea sediments. The Paleogene is characterized by few, several million year long hiatuses. The most significant Cenozoic hiatus event spans most of the Paleocene. The Neogene is characterized by short, frequent hiatus events nearly synchronous in shallow and deep water sediments. Epoch boundaries are characterized by peaks in deep water hiatuses possibly caused by an increased circulation of corrosive bottom water and sediment dissolution. The Plio-Pleistocene is characterized by a gradual decrease in the frequency of hiatuses. Future studies will focus on the regional significance of the hiatus events and their possible causes.

This database at http://www.icedata.ca describes collisions that have taken place in the northern hemisphere mainly over the last two hundred years, principally on the Grand Banks and North Atlantic but also including the waters of Alaska, Greenland and the Arctic. The site contains the original html version containing about 450 incidents as well as the new searchable Microsoft Access version which contains over 670 incidents including ship characteristics, images, ice charts, damage descriptions and any other known relevant factors. An Access version of the database is available for those who do not already have it installed on their computer. The Access database is updated from time to time as new information is found.