Phytoplankton data collected by the IBSS staff during a cruise in the Black Sea in May 1957. This dataset contains abundance (individuals per liter) and biomass (mg/m³) data for phytoplankton taxa. No additional metadata is available.

This table contains the numbers of passengers (excluding crew members) arriving by cruise ship on Bonaire. The figures published here are entirely based on available registers, i.e. the accuracy of these figures depends on the quality of the registers and Statistics Netherlands has conducted numerous plausibility checks on these registers, for example by establishing mutual links among these registers.

Data available from: January 2012

Status of the figures: The figures for 2014 to 2021 are final. The figures for 2022 to 2025 are provisional.

Changes as of May 16, 2025: - The previously published figures for 2021 have been made final. - From 2014 to 2021, the final quarterly figures have been added. - From 2022 to 2025, the provisional figures for the months, quarters and years have been added.

When will new figures be published? The new figures will be published within three months after expiration of the period available.

Geospatial Synthesis of Chromophoric (color-absorbing) Dissolved Organic Matter (CDOM) Distribution in the Gulf of Mexico

PI: Christopher Osburn, Dept. Marine, Earth, and Atmospheric Sciences, NC State University

Co-PIs: Thomas Bianchi, Texas A&M University, Bob Chen, University of Massachusetts-Boston; Paula Coble, University of South Florida; Eurico D'Sa, Louisiana State University

This dataset is affiliated with the North American Carbon Program (NACP). For additional information, please see the entry at the NACP site.

This data set will be a synthesis of bio-optical data on chromophoric or color-absorbing dissolved organic matter (CDOM) in the coastal regions the Gulf of Mexico - an immediate goal of the NACP and OCB programs. Absorption spectra and DOC concentrations from the Organic Matter Cycli project will be reported. In addition to in situ absorption spectra and DOC concentrations some study locations may also report fluorescence (estimate of chlorophyll a concentration), plus CTD and dissolved oxygen measurements

CDOM affects on water quality and water clarity are part of a high priority issue identified by the Gulf of Mexico Alliance (GOMA). Each of the PI's listed has historical CDOM data from coastal regions of the Gulf of Mexico, ranging from the Texas coast to West Florida Shelf.

The historic CDOM synthesis data set will provide a resource for validating remote sensing algorithms that predict water clarity properties in the coastal areas of the Gulf of Mexico. Each dataset to be shared by a PI is linked to specific research cruises. Thus the database has temporal and spatial coverage and associated metadata. In Years 1-2 of the project, data will be collated from each PI and transformed into a format amenable to data rescue by BCO-DMO. The structure of the resulting database will provide a mechanism by which future data sets may be integrated by members of the scientific community, through the project. In Year 2, as data comes online, it will be used to validate a coastal CDOM remote sensing algorithm for the Gulf of Mexico. Co-PI D'Sa has a decision support science website (http://gulf-coast.lsu.edu/index.html) that will provide water clarity data products based on CDOM algorithms.

The goal of the project is to have a functional database of CDOM information for two objectives. One objective is to provide coastal oceanographers with a clearinghouse for CDOM data that can be accessed and to which future cruise-related data acquisitions can be added. The second objective is to provide a resource for decision makers who require water clarity data on spatial and time scales for which satellite imagery may be used. For the second goal to be met, we have as an objective the validation of CDOM algorithms using the proposed database. Once the algorithm is validated, water clarity data products can be generated by users using the GCIS website, which will link to the CDOM database hosted by BCO-DMO.

The CDOM database will also provide pilot data for research proposals to NSF from our team. Part of our evolving project is to produce geospatial models of CDOM distributions in the Gulf of Mexico from the inflows of multiple rivers as well as the Loop Current. Functional models of CDOM distributions will further aid in remote sensing algorithm development and validation and in the general understanding of terrestrial C flux to the Gulf of Mexico.

Modification History:
September 2010: added processed Atchafalaya data from Chris Osburn
December 2010: raw/unprocessed Mississippi Plume absorption coefficients were added but then quickly removed
June 2011: added processed Mississippi Plume data from Bob Chen; a_lambda units corrected to \"per meter\" (had been incorrectly specified as \"per nanometer\" in earlier version)

These datasets support the conclusions in the journal article entitled " Population vulnerability of residents, employees, and cruise-ship passengers to tsunami hazards in complex seismic regions: a case study of the U.S. Virgin Islands" as described in the abstract below: Reducing the potential for loss of life from tsunamis is challenging on islands located in complex seismic regions given the multiple sources that surround islands, differences among islands in the amount of time to evacuate before wave arrival, and the high number of residents, employees, and tourists in tsunami-hazard zones. We examine variations in population vulnerability in island communities to multiple tsunami threats and use the United States territory of the U.S. Virgin Islands (USVI), including St. Thomas, St. John, and St. Croix islands, as our case study. We estimate the tsunami-hazard exposure of residents, employees, and cruise-ship passengers on vessels docking at USVI marine facilities, as well as model pedestrian travel times out of inundation zones for 13 credible tsunami scenarios. Results indicate that the threat to life safety in USVI posed by tsunamis is not equal among the three islands, both in terms of the magnitude of people in hazard zones and the amount of time available to evacuate for the various scenarios. The number of employees and cruise-ship passengers in tsunami-hazard zones is orders of magnitude higher than the number of residents, suggesting that risk assessments that only account for residents are under-estimating threats to life safety from tsunamis. Finally, reducing departure delays has a greater impact than increasing pedestrian travel speeds on reducing the number of people that may have insufficient time to evacuate hazard zones before wave arrival.

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Analysis of ‘COVID-19 dataset in Japan’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/lisphilar/covid19-dataset-in-japan on 28 January 2022.

--- Dataset description provided by original source is as follows ---

1. Context

This is a COVID-19 dataset in Japan. This does not include the cases in Diamond Princess cruise ship (Yokohama city, Kanagawa prefecture) and Costa Atlantica cruise ship (Nagasaki city, Nagasaki prefecture). - Total number of cases in Japan - The number of vaccinated people (New/experimental) - The number of cases at prefecture level - Metadata of each prefecture

Note: Lisphilar (author) uploads the same files to https://github.com/lisphilar/covid19-sir/tree/master/data

This dataset can be retrieved with CovsirPhy (Python library).

pip install covsirphy --upgrade

import covsirphy as cs
data_loader = cs.DataLoader()
japan_data = data_loader.japan()
# The number of cases (Total/each province)
clean_df = japan_data.cleaned()
# Metadata
meta_df = japan_data.meta()

Please refer to CovsirPhy Documentation: Japan-specific dataset.

Note: Before analysing the data, please refer to Kaggle notebook: EDA of Japan dataset and COVID-19: Government/JHU data in Japan. The detailed explanation of the build process is discussed in Steps to build the dataset in Japan. If you find errors or have any questions, feel free to create a discussion topic.

1.1 Total number of cases in Japan

covid_jpn_total.csv Cumulative number of cases: - PCR-tested / PCR-tested and positive - with symptoms (to 08May2020) / without symptoms (to 08May2020) / unknown (to 08May2020) - discharged - fatal

The number of cases: - requiring hospitalization (from 09May2020) - hospitalized with mild symptoms (to 08May2020) / severe symptoms / unknown (to 08May2020) - requiring hospitalization, but waiting in hotels or at home (to 08May2020)

In primary source, some variables were removed on 09May2020. Values are NA in this dataset from 09May2020.

Manually collected the data from Ministry of Health, Labour and Welfare HP:
厚生労働省 HP (in Japanese)
Ministry of Health, Labour and Welfare HP (in English)

The number of vaccinated people: - Vaccinated_1st: the number of vaccinated persons for the first time on the date - Vaccinated_2nd: the number of vaccinated persons with the second dose on the date - Vaccinated_3rd: the number of vaccinated persons with the third dose on the date

Data sources for vaccination: - To 09Apr2021: 厚生労働省 HP 新型コロナワクチンの接種実績(in Japanese) - 首相官邸 新型コロナワクチンについて - From 10APr2021: Twitter: 首相官邸（新型コロナワクチン情報）

1.2 The number of cases at prefecture level

covid_jpn_prefecture.csv Cumulative number of cases: - PCR-tested / PCR-tested and positive - discharged - fatal

The number of cases: - requiring hospitalization (from 09May2020) - hospitalized with severe symptoms (from 09May2020)

Using pdf-excel converter, manually collected the data from Ministry of Health, Labour and Welfare HP:
厚生労働省 HP (in Japanese)
Ministry of Health, Labour and Welfare HP (in English)

Note: covid_jpn_prefecture.groupby("Date").sum() does not match covid_jpn_total. When you analyse total data in Japan, please use covid_jpn_total data.

1.3 Metadata of each prefecture

covid_jpn_metadata.csv - Population (Total, Male, Female): 厚生労働省 厚生統計要覧（2017年度）第１－５表 - Area (Total, Habitable): Wikipedia 都道府県の面積一覧 (2015)

• Hospital_bed: With the primary data of 厚生労働省 感染症指定医療機関の指定状況（平成31年4月1日現在）, 厚生労働省 第二種感染症指定医療機関の指定状況（平成31年4月1日現在）, 厚生労働省 医療施設動態調査（令和２年１月末概数）, 厚生労働省 感染症指定医療機関について and secondary data of COVID-19 Japan 都道府県別 感染症病床数,

  • Specific: Hospital beds of medical institutions designated for specific infectious diseases
  • Type-I: Hospital beds of medical institutions designated for type I infectious diseases
  • Type-II: Hospital beds of medical institutions designated for type II infectious diseases
  • Tuberculosis: Hospital beds of medical institutions designated for tuberculosis (outpatient care)
  • Care: long term care bed of hospitals
  • Total: Beds of all hospitals

• Clinic_bed: With the primary data of 医療施設動態調査（令和２年１月末概数） ,

  • Care: long term care beds of clinics
  • Total: Beds of all clinics

• Location: Data is from LinkData 都道府県庁所在地 (Public Domain) (secondary data).

  • Latitude
  • Longitude

• Admin

  • Capital: Prefectural capital city. Data is from LinkData 都道府県庁所在地 (Public Domain) (secondary data).
  • Region: Region name. Data is from WIkipedia (secondary data). "Kyushu-Okinawa region" was separated to "Kyushu" and "Okinawa" by this datasets' author.
  • Num: Prefecture code (JIS X 0401: Hokkaido=1,...Okinawa=47). Data is from 国土交通省 GIS HP Pref code. cf. (not source) Japan VIsitor: Japan Prefectures Map.

2. Acknowledgements

To create this dataset, edited and transformed data of the following sites was used.

厚生労働省 Ministry of Health, Labour and Welfare, Japan:
厚生労働省 HP (in Japanese)
Ministry of Health, Labour and Welfare HP (in English) 厚生労働省 HP 利用規約・リンク・著作権等 CC BY 4.0 (in Japanese)

国土交通省 Ministry of Land, Infrastructure, Transport and Tourism, Japan: 国土交通省 HP (in Japanese) 国土交通省 HP (in English) 国土交通省 HP 利用規約・リンク・著作権等 CC BY 4.0 (in Japanese)

Code for Japan / COVID-19 Japan: Code for Japan COVID-19 Japan Dashboard (CC BY 4.0) COVID-19 Japan 都道府県別 感染症病床数 (CC BY)

Wikipedia: Wikipedia

LinkData: LinkData (Public Domain)

Inspiration

1. Changes in number of cases over time
2. Percentage of patients without symptoms / mild or severe symptoms
3. What to do next to prevent outbreak

License and how to cite

Kindly cite this dataset under CC BY-4.0 license as follows. - Hirokazu Takaya (2020-2022), COVID-19 dataset in Japan, GitHub repository, https://github.com/lisphilar/covid19-sir/data/japan, or - Hirokazu Takaya (2020-2022), COVID-19 dataset in Japan, Kaggle Dataset, https://www.kaggle.com/lisphilar/covid19-dataset-in-japan

--- Original source retains full ownership of the source dataset ---

This data set is a compilation of close to 1000 epifaunal invertebrate sampling stations from over 20 research cruises to the northern Bering Sea (US side), Chukchi Sea (Russian and US sides) and Beaufort Sea (US side) from 1972 to 2012. The vast majority of stations were trawl hauls and a few were photographic sampling stations. Trawl hauls were conducted with a range of different nets including various otter trawls but mostly the 83-112 Eastern Otter trawl, and a plumb-staff beam trawl. Mesh sizes ranged from 4-38 mm in the cod end and 7-89 mm in the body of the net. Trawl duration ranged from 1-30 minutes and trawl speed ranged from 1.5-5 knots. Where available, variables compiled include cruise and station names, locations and water depth, haul and net information, contact information of data holder, as well as total abundance, biomass and taxon richness of epifaunal invertebrates. The latter is biased by varying levels of taxonomic resolution in the source data. Many fields are blank, either because the data have not yet been released as is the case for many recent cruises, or because hauls were not quantitative as is the case for some historic data sets. Data on fishes from the same hauls are not reported here. Column headers are explained in the readme file. Changes made to the original data sets provided by the project contacts or as found in data archives include, where possible: standardization of abundance to individuals per 1000 square meters; standardization of biomass to kilograms wet weight per 1000 square meters; and subtraction of obvious infaunal taxa, eggs and fragments from the taxon count. This dataset is part of the Pacific Marine Arctic Regional Synthesis (PacMARS) Project.

Zooplankton data collected by the IBSS staff on the R/V Knipovich in the Black Sea along the Yalta - Sukhumi transect, at the diurnal station 8, 50 km from Sukhumi on 20th April 1950. This dataset contains abundance data (individuals per liter) and biomass data (mg/m³) for zooplankton taxa. Also stage and size are registered for some species. No additional metadata is available.

Cruise track from R/V Atlantic Explorer AE1126 in the BATS site from November 2011. access_formats=.htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt acquisition_description=Control point navigation was obtained from the R2R catalog: https://www.rvdata.us/search/cruise/AE1126 awards_0_award_nid=514363 awards_0_award_number=OCE-0802004 awards_0_data_url=http://www.nsf.gov/awardsearch/showAward?AWD_ID=0802004 awards_0_funder_name=NSF Division of Ocean Sciences awards_0_funding_acronym=NSF OCE awards_0_funding_source_nid=355 awards_0_program_manager=David L. Garrison awards_0_program_manager_nid=50534 cdm_data_type=Other comment=Cruise track for deployment AE1126 Project: Ocean Microbial Observatory PIs: Carlson (UCSB) and Giovanonni (OSU)

version 20141222 Conventions=COARDS, CF-1.6, ACDD-1.3 data_source=extract_data_as_tsv version 2.3 19 Dec 2019 defaultDataQuery=&time<now doi=10.1575/1912/bco-dmo.543682.1 Easternmost_Easting=32.400753 geospatial_lat_max=-64.432035 geospatial_lat_min=-64.724967 geospatial_lat_units=degrees_north geospatial_lon_max=32.400753 geospatial_lon_min=32.154952 geospatial_lon_units=degrees_east infoUrl=https://www.bco-dmo.org/dataset/543682 institution=BCO-DMO instruments_0_acronym=GPS instruments_0_dataset_instrument_nid=543688 instruments_0_description=The Global Positioning System (GPS) is a U.S. space-based radionavigation system that provides reliable positioning, navigation, and timing services to civilian users on a continuous worldwide basis. The U.S. Air Force develops, maintains, and operates the space and control segments of the NAVSTAR GPS transmitter system. Ships use a variety of receivers (e.g. Trimble and Ashtech) to interpret the GPS signal and determine accurate latitude and longitude. instruments_0_instrument_external_identifier=https://vocab.nerc.ac.uk/collection/L05/current/POS03/ instruments_0_instrument_name=Global Positioning System Receiver instruments_0_instrument_nid=560 instruments_0_supplied_name=GPS metadata_source=https://www.bco-dmo.org/api/dataset/543682 Northernmost_Northing=-64.432035 param_mapping={'543682': {'lat': 'master - latitude', 'lon': 'master - longitude', 'ISO_DateTime_UTC': 'master - time'}} parameter_source=https://www.bco-dmo.org/mapserver/dataset/543682/parameters people_0_affiliation=University of California-Santa Barbara people_0_affiliation_acronym=UCSB-MSI people_0_person_name=Craig Carlson people_0_person_nid=50575 people_0_role=Lead Principal Investigator people_0_role_type=originator people_1_affiliation=Woods Hole Oceanographic Institution people_1_affiliation_acronym=WHOI BCO-DMO people_1_person_name=Nancy Copley people_1_person_nid=50396 people_1_role=BCO-DMO Data Manager people_1_role_type=related project=Ocean Microbial Observatory projects_0_acronym=Ocean Microbial Observatory projects_0_description=(Adapted from the NSF award abstract) The premise of this project is that stratified bacterioplankton clades engage in specialized biogeochemical activities that can be identified by integrated oceanographic and microbiological approaches. Specifically, the objective of this project is to assess if the mesopelagic microbial community rely on diagenetically altered organic matter and subcellular fragments that are produced by microbial processes in the euphotic zone and delivered into the upper mesopelagic by sinking or mixing. In past efforts this microbial observatory had greater success cultivating members of the euphotic zone microbial community, and revealed an unanticipated growth requirement for reduced sulfur compounds in alphaproteobacteria of the SAR11 clade. Genomic information showed that intense competition for substrates imposes trade-offs on bacterioplankton - there are regions of N dimensional nutrient space where specialists win. We postulate that specific growth requirements may explain some the regular spatial and temporal patterns that have been observed in upper mesopelagic bacterioplankton communities, and the difficulties of culturing some of these organisms. The specific objectives of this project are: 1) to produce 13C and 15N labeled subcellular (e.g., soluble, cell wall, and membrane) and DOM fractions from photosynthetic plankton cultures and use stable isotope probing to identify specific clades in the surface and upper mesopelagic microbial community that assimilate fractions of varying composition and lability. 2) to use fluorescence in situ hybridization approaches to monitor temporal and spatial variability of specific microbial populations identified from the SIP and HTC experiments. To increase resolution we will use CARD-FISH protocols. 3) to measure the proteomes of bacterioplankton communities to identify highly translated genes in the surface layer and upper mesopelagic, and community responses to seasonal nutrient limitation. 4) and, to cultivate these organisms via high throughput culturing (HTC) by pursuing the hypothesis that they require specific nutrient factors and/or diagenetically altered organic substrates. Complete genome sequences from key organisms will be sought and used as queries to study patterns of natural variation in genes and populations that have been associated with biogeochemically important functions. projects_0_end_date=2014-07 projects_0_geolocation=Bermuda Atlantic Time-Series study site projects_0_name=Transitions in the Surface Layer and the Role of Vertically Stratified Microbial Communities in the Carbon Cycle - An Oceanic Microbial Observatory projects_0_project_nid=514365 projects_0_project_website=http://www.bios.edu/research/projects/oceanic-microbial-observatory/ projects_0_start_date=2008-08 sourceUrl=(local files) Southernmost_Northing=-64.724967 standard_name_vocabulary=CF Standard Name Table v55 version=1 Westernmost_Easting=32.154952 xml_source=osprey2erddap.update_xml() v1.3

The data was collected during the Nansen Legacy joint cruise (JC2-2, cruise number: 2021710) from 24.08 - 25.09.2021 onboard the research vessel RV Kronprins Haakon, along a transect in the Arctic Basin from 81N to 87N. The dataset contains abundance and biomass of sea-ice meiofauna (> 20 µm) including large protists such as foraminifers and ciliates and metazoans eggs. Sea-ice meiofauna were identified and counted with stereo microscopy and result are given as Individuals per liter (cells/L) and Individuals per square meter (Ind/m2). Biomass (μg C Ind.-1) was only determined for alive individuals according to carbon contents for ice meiofauna taxa based on literature summarized in Ehrlich et al. (2021, doi: https://doi.org/10.1525/elementa.2020.00169), and carbon values for foraminifers were provided by de Freitas et al. (2021) for benthic species (Bolivinia sp.: 0.00875 μg C Ind.-1; Elphidium sp.: 0.126 μg C Ind.-1, https://doi.org/10.2113/gsjfr.51.4.249) and Anglada-Ortiz et al. (submitted to PiO) for the pelagic species Neogloboquadrina pachyderma (0.0013 μg C Ind.-1).

Original provider: Dalhousie University

Dataset credits: Hal Whitehead, Department of Biology, Dalhousie University

Abstract: The Sargasso Sea cruise surveyed marine mammals in the Northeast Atlantic Ocean, during the spring and summer of 2005. This survey onboard the Valiant 40 ocean-going research vessel Balaena, consisted of two survey legs: a sail from the Caribbean to offshore waters north of the Bahamas (April 19 - June 2), and a sail north to Halifax, Nova Scotia. Sperm whales were surveyed using acoustics and visual techniques during both cruise legs by members of the Hal Whitehead laboratory.

Purpose: The purpose of this cruise was to study the behavior (principally social organization), ecology, and population biology of sperm whales. This is the second study year, after a similar cruise in the summer of 2004.

Supplemental information: This dataset includes cetacean observations and survey effort. The survey track was recorded by logging a position every 10 minutes using the vessel's GPS. The cetacean observations includes sightings during surveys (on effort) and during focal follows of sperm whale schools (off effort).

There are two types records for sperm whale, census and encounter. Encounters, which are defined as events where researchers observe whales by sight or acoustic techniques, are denoted 'S' (survey), 'E' (encounter), or 'AE' (acoustic encounter) in the [Enctr_type] field. These records do not have animal counts recorded, and count field for these records is null in the dataset.

In addition to encounters, this dataset includes sightings during 'census' surveys, which include group size data, as well as information on the radial distance and angle to each sighting. These survey metadata are available from the primary data providers.

Census records have non-zero animal counts as for other species. They are denoted C in [Enctr_type] field. Note that the [Enctr_type] field is not downloadable by the public, but may be available by request. Please request this data after obtaining permission from the primary data providers.