Hawaii law requires that fish dealers report all purchases made directly from fishers to the Hawaii Division of Aquatic Resources (DAR). The term "fish dealers" includes fish auctions, fish markets, stores, restaurants, or any business buying fish directly from fishers, and even fishers themselves if they peddle their own fish. In January 2000, DAR implemented a computerized data processing system for fish dealer data collected state-wide. From 2000 through 2019, most dealers submitted paper forms supplied by DAR while a few of the larger dealers provided data electronically. In June 2016, DAR launched a self reporting web application used by fishers who peddle their own fisher. In October 2019, DAR launched a self reporting web application for use by fish dealers buying fish directly from fishers. Currently the majority of sales are self reported.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Data are from underwater visual surveys of fish stocks from 41 survey sites on the islands of Oahu and Hawaii, conducted by biologists and technicians of Hawaii's Division of Aquatic Resources (DAR). Survey data at Kealakekua Bay, Island of Hawaii, begin in 1952. Data begin in 1968 for all other sites. The datasets end in 2000, although updates are pending. Serious weaknesses of the data include that (1) transect dimensions were not consistent even within survey sites, and have not generally been recorded on datasheets; (2) survey locations are generally given as place names which are at least somewhat meaningful (e.g. the Monument site at Kealakekua Bay is in front of Cook's Monument), but lat/long of start and end points are not given, and even more fundamentally depth ranges are not given; and (3) some surveys were conducted on SCUBA and some on snorkel but, again, that has not been consistently recorded on datasheets. Additional DAR data from other locations and dates are planned for digitization.

This dataset provides information about the number of properties, residents, and average property values for Dar Lane cross streets in North East, PA.

Hawaii law requires that all fishers who take marine life for commercial purposes report their catch and effort to the Hawaii Division of Aquatic Resources (DAR). From 1948 through 2009, fishers submitted their effort and catch using paper forms supplied by DAR. The forms were revised multiple times over the years therefore the exact elements tracked depends on the year. In January 2010, DAR launched a self reporting web application to replace the paper forms. A minority of fishers still submit paper forms which are then entered into the web application by DAR staff. All data from 1948 through today has been migrated into a single modern database.

Darling Ingredients - Aktuella värden, historiska data, prognoser, statistik, diagram och ekonomisk kalender - Mar 2025.Data for Darling Ingredients including historical, tables and charts were last updated by Trading Economics this last March in 2025.

[Metadata] Moku boundaries, extended out three miles past the shoreline. Source: State of Hawaii, Department of Land and Natural Resources, Division of Aquatic Resources (DAR), August, 2020. Created by DAR for use in collecting data to be grouped/organized in ridge to reef summaries of stream, estuary and marine survey data. For additional information, please refer to complete metadata at https://files.hawaii.gov/dbedt/op/gis/data/moku_ridge_to_reef_dar.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

This zip folder contains ASCII text files of vectors at the specified volcano at 12-hour intervals, from January 1, 1990 through December 28, 2009. The wind vectors are divided into five files, names by their elevation range above sea level in the atmosphere: 00-05km.txt; 05-11km.txt; 11-16km.txt; 16-24km.txt; and 24-30km.txt. The zip folder also contains a subfolder "figures", with Wind rose plots of wind direction and speed over this time period. The plots are by season, and by elevation, given a total of 20 plots (4 seasons, 5 elevation ranges). A summary plot is also included which gives the year-round wind pattern at the volcano, at 0-5 km elevation. Plots are in both jpg and pdf format.

[Metadata] Description: Military De Facto Marine Protected Areas in the Main Hawaiian Islands as of June, 2016. De Facto Marine Protected Areas are delineated areas of the marine environment where human access is restricted or where specific activities or uses are regulated for reasons other than conservation or natural or cultural resource management,. The Military De Facto MPAs in this layer were extracted from the NOAA De Facto MPA database by DAR staff and / or DAR contractors.This data is intended for informational purposes and not for legal or navigational use. Data represent best efforts to ensure accuracy but data are as is with no expressed warranty of any kind.For additional information, please refer to complete metadata at https://files.hawaii.gov/dbedt/op/gis/data/military_de_facto_mpas_dar.pdf or contact the Hawaii Statewide GIS Program, Office of Planning, State of Hawaii; PO Box 2359, Honolulu, HI. 96804; (808) 587-2846; email: gis@hawaii.gov; website: https://planning.hawaii.gov/gis.

Abstract

The DPHS in Dar es Salaam was conducted in two rounds in November-December 2017 and in September 2018, with the objective to assess the role of poverty and other social factors in urban flooding in the city. The survey data collected in 2017 focused on exposure to frequent flooding, while the follow up survey in 2018, targeting the same households, focused on the impact of a flood event that happened in April 2018. During the follow up survey in 2018, additional households were also added to the sample. The data collected is representative at the city level and overrepresented in areas that are flood prone.

This project was a collaborative effort between Global Facility for Disaster Reduction and Recovery (GFDRR), the Tanzanian Urban Resilience Program (TURP), the Poverty Global Practice and Urban, Disaster Risk Management, Resilience and Land Global Practice (GPURL). Data collection was carried out by UDA Consulting under World Bank supervision.

Geographic coverage

Dar es Salaam, Tanzania.

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

The selection of households in the survey design had two objectives. First, to select a sample that represents the population of Dar es Salaam and second, to interview enough people who had experienced floods to be able to detect patterns in their socio-economic characteristics.

The sample size was selected to confidently represent the population of Dar es Salaam given the income level and income distribution. Accordingly, a sample size of 105 EAs and 10 households per EA were selected using Probability Proportion to Size (PPS). In 2018, 28 EAs to the original sample as part of an additional round of data collection.

To capture enough households that had experienced floods, a flood risk stratum was designed using the Ramani Huria community flood map. EAs were categorized according to three flood risk strata, i.e., “no risk”, “low to medium risk” and “high risk”, depending on how much of the EA was covered by the flood layer in the map. This categorization of the city was used to oversample in high risk and low-to-medium risk areas by selecting more of those EAs compared to the population living there. Finally, all the selected households were randomly drawn within each EA using satellite imagery.

Sampling weights were calculated to compensate for the oversampling in high-risk areas. When applying the sample weights, the dataset is representative at the city level.

References:

ERMAN, A. E., TARIVERDI, M., OBOLENSKY, M. A. B., CHEN, X., VINCENT, R. C., MALGIOGLIO, S., & YOSHIDA, N. (2019). Wading out the storm: The role of poverty in exposure, vulnerability and resilience to floods in Dar Es Salaam. World Bank Policy Research Working Paper, (8976).

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The survey questionnaire consists of 13 sections that were used to collect the survey data. See the attached questionnaire.

Cleaning operations

The following data editing was done for anonymization purpose: • Precise location data, such as GPS coordinates, were dropped • Personal information, such as name, citizenship and phone number were dropped • Information on from which region or country the respondent moved from before settling in current dwelling and where respondent was born was categorized into “in Dar es Salaam” and “outside Dar es Salaam” to protect privacy while preserving valuable data. District level information on origin was dropped. • Household size exceeding seven household members was categorized as “above 7 members” • Household member information for 7th member and above was dropped to avoid reconstruction of the household size variable.

For more information on the anonymization process, see the Technical Document.

Response rate

In the 2018 follow up interview, 419 were reached and interviewed out of the 1058 households in the original sample.

A multi-sector rapid needs assessment facilitated by the SNAP with support from both organisations in Syria and international humanitarian organisations was carried out from mid-November to mid-December 2013 in Dar’a Governorate and covered a population of 692,000 people across 12 of the 17 sub-districts.

The Environment for Development Dar es Salaam Energy Survey (EFD-DES) consists of a household survey and an enterprise survey that took place from the 29th of January to the 13th of February 2020. The survey work was funded by the Swedish International Development Cooperation Agency (Sida), through the Swedish embassy in Tanzania. The primary goal of the household survey was to collect current and detailed information on the economic and socio-demographic profile of households in Dar es Salaam, with a specific focus on household energy use. In addition, the energy enterprise survey was intended to provide information on the nature of small-scale energy enterprises that sell and deliver fuels and cookstoves directly to households. The survey was conducted primarily to inform a World Bank Policy Note on the transition towards clean, affordable and sustainable household energy in Dar es Salaam. In addition, the household survey forms the baseline for a longer-term study on the impacts of a UNIDO bioethanol cookstove program in Dar es Salaam, as well as an important and current source of information to study fuel use in Dar es Salaam. The survey was designed and implemented by a collaborative group of researchers within the Environment for Development (EfD) network, including researchers at the University of Dar es Salaam, Duke University, the University of Gothenburg and the University of Cape Town. The household survey was based on an instrument developed by researchers at Duke University Sanford School of Public Policy, that has been used in Kenya and Nepal, allowing for some cross-country comparability. In total 1100 households, containing 4,396 individuals were interviewed. In addition, 225 energy enterprises were interviewed. The household survey questionnaire consists of a range of questions on energy, health, socio-economic status, stove use, asset ownership and intra-household dynamics. The full questionnaire is available with the survey materials. Table 1 in the attached document "Basic Information Document" (page 2) provides an overview of the structure of the household survey and gives more details about the household datasets. The EfD-DES consists of a range of data files. Each data file relates to a section of the respective questionnaire. The complete list of data files is listed in the Appendix of the attached document "Basic Information Document". The sampling strategy was designed in such a way that the resulting data would be able to meet the following goals: a) The sample should be as representative as possible of household energy use in Dar es Salaam. b) The sample should be structured in such a way that enables an impact evaluation of the UNIDO bioethanol cookstove program in a future follow-up survey. c) The household and enterprise surveys should take place in similar areas in order to inform an understanding of the energy enterprise landscape from a household perspective. A multi-stage stratified random sampling design was followed in the selection of final wards, streets and households to include in the survey. In the first stage, the intended sample size of 1000 was allocated between the three main districts of Dar es Salaam (Temeke, Ilala and Kinondoni). This was done in proportion to the population of each district, yielding the number of households to be interviewed in each district. The population numbers used were based on the 2012 Census data – the most recent census of households in Dar es Salaam In the second stage, the survey team visited the offices of the District councillors of each district and asked them to rank all the wards within their district by socio-economic status (from richest to poorest). District councillors were asked to assign a number to each ward in their District, where 1 is richest and n is the poorest (n depends on the number of wards per-district). This ranking was used to divide wards into three socio-economic status groups. These groups were "Relatively Poor" "Middle" and "Relatively Rich", corresponding to the bottom, middle and top thirds of the socio-economic status rankings assigned by District councillors . The primary reason for this exercise was to ensure the inclusion of households across the income distribution in the survey. Following this, six wards were selected from each District. Two “Relatively Poor” wards, two “Middle” wards and two “Relatively rich” wards were selected in each district, yielding a total number of 18 wards in this survey. The following process was used to select these 6 wards from each district: In order to ensure the sampling design would be compatible with a later impact evaluation of the UNIDO ethanol stove program, in each district, 3 of the 6 wards (1 poor, 1 middle, 1 rich) were randomly selected from the set of wards targeted by the Ethanol stove rollout. The other 3 wards (1 poor, 1 middle, 1 rich) were randomly selected from the set of wards not targeted by Ethanol stove rollout . Within each selected ward, two streets were randomly selected . Within each street, the number of households to be skipped by enumerators was determined by the dividing the estimated number of households per street (derived from the estimated number of main streets per ward) by the number of interviews to be completed on that street. Enumerators were then instructed to skip this number of households before interviewing another household. For details, see the attached document "Basic Information Document", section "Sample Design".

The State of Hawaii Department of Land and Natural Resources (DLNR) Division of Aquatic Resources (DAR) is the primary agency responsible for coordinating Hawaii's reef management efforts in the main Hawaiian Islands. The DAR marine monitoring program employs numerous methodologies developed by DAR scientists in collaboration with NOAA, USGS and the University of Hawaii (UH). Specific methods are used at study sites depending on the resource management concerns that DAR is looking to address, and include surveys of abundance of resource and herbivorous fish, smaller cryptic fish and recruits, urchins and larger mobile invertebrates, benthic habitat cover, coral health, and biological diversity. This layer includes the locations of DAR monitoring sites along the west coast of Hawaii Island (Big Island). For further information, please see: http://dlnr.hawaii.gov/coralreefs/monitoring/

Find details of American Dar Inc Titanic Furniture Buyer/importer data in US (United States) with product description, price, shipment date, quantity, imported products list, major us ports name, overseas suppliers/exporters name etc. at sear.co.in.

This dataset is about companies and is filtered where the company is Dar, featuring 5 columns: city, company, country, foundation year, and sector. The preview is ordered by revenues (descending).

The spatial distribution of biodiversity (i.e., the biogeography) of the hot-spring microbiome is critical for understanding the microbial ecosystems in hot springs. We investigated the microbiome diversity scaling (changes) over space by analyzing the diversity-area relationship (DAR), which is an extension to classic SAR (species-area relationship) law in biogeography. We built DAR models for archaea and bacteria with 16S-rRNA sequencing datasets from 165 hot springs globally. From the DAR models, we sketch out the biogeographic maps of hot-spring microbiomes by constructing: (i) DAR profile—measuring the archaea or bacteria diversity scaling over space (areas); (ii) PDO (pair-wise diversity overlap or similarity) profile—estimating the PDO between two hot springs; (iii) MAD (maximal accrual diversity) profile—predicting the global MAD; (iv) LRD/LGD (ratio of local diversity to regional or global diversity) profile. We further investigated the differences between archaea and bacteria in their biogeographic maps. For example, the comparison of DAR-profile maps revealed that the archaea diversity is more heterogeneous (i.e., more diverse) or scaling faster than the bacterial diversity does in terms of species numbers (species richness), but is less heterogeneous (i.e., less diverse) or scaling slower than bacteria when the diversity (Hill numbers) were weighted in favor of more abundant dominant species. When the diversity is weighted equally in terms of species abundances, archaea, and bacteria are equally heterogeneous over space or scaling at the same rate. Finally, unified DAR models (maps) were built with the combined datasets of archaea and bacteria.

Credit report of Dar-dar Llc 11 Urazova Str Gisar contains unique and detailed export import market intelligence with it's phone, email, Linkedin and details of each import and export shipment like product, quantity, price, buyer, supplier names, country and date of shipment.

This dataset is about artists and is filtered where the artworks includes Verdad: dar ver (Truth: To Give Sight) from the series AMAzone Palabrarmas, featuring 9 columns including artist, artworks, birth date, country, and creation start dates. The preview is ordered by number of artworks (descending).

Historical holdings data showing quarterly positions, market values, shares held, and portfolio percentages for DAR held by Perigon Wealth Management LLC from Q4 2013 to Q4 2024

This dataset is about books and is filtered where the book publisher is Dar-Web, featuring 7 columns including author, BNB id, book, book publisher, and ISBN. The preview is ordered by publication date (descending).