100+ datasets found
  1. Leading data collection methods among U.S. consumers 2023

    • statista.com
    Updated Jun 6, 2025
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    Statista (2025). Leading data collection methods among U.S. consumers 2023 [Dataset]. https://www.statista.com/statistics/1269920/first-party-data-usa/
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    Dataset updated
    Jun 6, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Dec 2023
    Area covered
    United States
    Description

    During a 2023 survey carried out among working-age consumers from the United States, nearly half of respodents stated that they preferred for their data to be collected via interactive surveys. Roughly a third name a loyalty card/program as their favored data collection method.

  2. Leading data collection methods among UK consumers 2023

    • statista.com
    Updated Feb 29, 2024
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    Statista (2024). Leading data collection methods among UK consumers 2023 [Dataset]. https://www.statista.com/statistics/1453941/data-collection-method-consumers-uk/
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    Dataset updated
    Feb 29, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Nov 2023 - Dec 2023
    Area covered
    United Kingdom
    Description

    During a late 2023 survey among working-age consumers in the United Kingdom, 47.8 percent of respondents stated that they preferred for their data to be collected via interactive surveys. Meanwhile, 47.6 percent of respondents mentioned loyalty cards/programs as their favored data collection method.

  3. a

    Research - Comparing Traffic Data Collection Methods

    • data-insight-tfwm.hub.arcgis.com
    Updated Oct 30, 2023
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    Transport for West Midlands (2023). Research - Comparing Traffic Data Collection Methods [Dataset]. https://data-insight-tfwm.hub.arcgis.com/documents/6893b1b21c7f4e40b72f118e48f2e7e0
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    Dataset updated
    Oct 30, 2023
    Dataset authored and provided by
    Transport for West Midlands
    Description

    Earlier this year, the TfWM Data Insight team applied for a research grant to work with a university masters student at the University of Essex through the Local Government Data Research Centre to understand the functionality and output differences between pneumatic tube counters and video-based camera data and develop a machine learning model to reduce the difference found.The TfWM Data Insight team worked with the student over the course of the summer of 2022 to undertake the project. The following is a summary of the report delivered to TfWM, analysing data from a number of week pairs between October and November 2021 across 5 locations in the West Midlands, totalling around one thousand observations aggregated to 15-minute intervals.Analysing traffic volume data enables improvements in traffic control decision making to be made to achieve a healthier, happier, better connected and more prosperous West Midlands. In this project we looked at two methods of gathering, computing, and transferring data: pneumatic tubes (commonly referred to as an ATC in the industry) placed parallel to the direction of traffic on the surface of the roads, which are regarded as accurate but insufficient due to the high installation and maintenance costs, and traffic cameras, mounted on column infrastructure facing the flow of traffic on the road.

  4. f

    Data collection methods for vital statistics.

    • plos.figshare.com
    xls
    Updated May 31, 2023
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    Eliana Jimenez-Soto; Andrew Hodge; Kim-Huong Nguyen; Zoe Dettrick; Alan D. Lopez (2023). Data collection methods for vital statistics. [Dataset]. http://doi.org/10.1371/journal.pone.0106234.t001
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    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Eliana Jimenez-Soto; Andrew Hodge; Kim-Huong Nguyen; Zoe Dettrick; Alan D. Lopez
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Notes: DMC, data collection method; MCOD, medical certification of death; VA, verbal autopsy; COD, cause-of-death.Data collection methods for vital statistics.

  5. d

    Data from: Site description and associated GPS data collected at eleven...

    • catalog.data.gov
    • data.usgs.gov
    • +2more
    Updated Jul 6, 2024
    + more versions
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    U.S. Geological Survey (2024). Site description and associated GPS data collected at eleven study sites within the Grand Bay National Estuarine Research Reserve in Mississippi [Dataset]. https://catalog.data.gov/dataset/site-description-and-associated-gps-data-collected-at-eleven-study-sites-within-the-grand-
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Mississippi
    Description

    Shoreline change analysis is an important environmental monitoring tool for evaluating coastal exposure to erosion hazards, particularly for vulnerable habitats such as coastal wetlands where habitat loss is problematic world-wide. The increasing availability of high-resolution satellite imagery and emerging developments in analysis techniques support the implementation of these data into coastal management, including shoreline monitoring and change analysis. Geospatial shoreline data were created from a semi-automated methodology using WorldView (WV) satellite data between 2013 and 2020. The data were compared to contemporaneous field-surveyed Real-time Kinematic (RTK) Global Positioning System (GPS) data collected by the Grand Bay National Estuarine Research Reserve (GBNERR) and digitized shorelines from U.S. Department of Agriculture National Agriculture Imagery Program (NAIP) orthophotos. Field data for shoreline monitoring sites was also collected to aid interpretation of results. This data release contains digital vector shorelines, shoreline change calculations for all three remote sensing data sets, and field surveyed data. The data will aid managers and decision-makers in the adoption of high-resolution satellite imagery into shoreline monitoring activities, which will increase the spatial scale of shoreline change monitoring, provide rapid response to evaluate impacts of coastal erosion, and reduce cost of labor-intensive practices. For further information regarding data collection and/or processing methods, refer to the associated journal article (Smith and others, 2021).

  6. U

    A refined electrofishing technique for collecting Silver Carp: Implications...

    • data.usgs.gov
    • search.dataone.org
    • +4more
    Updated Dec 28, 2024
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    Kristen Bouska; Wesley Bouska (2024). A refined electrofishing technique for collecting Silver Carp: Implications for management. Supporting data [Dataset]. http://doi.org/10.5066/F7S46Q4W
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    Dataset updated
    Dec 28, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Kristen Bouska; Wesley Bouska
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Time period covered
    Aug 1, 2012 - Aug 31, 2013
    Description

    The table provides all fish collected using two different electrofishing methods at Illinois River sites in 2012 and 2013. Length and weights were taken on most species and gender was taken from Silver Carp. Fishes were categorized whether they were netters (caught by nets) or jumpers (jumped in the boat while sampling) and only netters were used in analyses. Large numbers of shad were collected in 2013 and an additional spreadsheet includes abundance data in an aggregated form for those sites. The data is not sensitive/classified and there are no legal restrictions on who may obtain or use the data.

  7. e

    Techniques of Data Collection

    • paper.erudition.co.in
    html
    Updated Apr 1, 2021
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    Einetic (2021). Techniques of Data Collection [Dataset]. https://paper.erudition.co.in/makaut/bachelor-in-business-administration-2020-2021/3/business-research-methods
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    htmlAvailable download formats
    Dataset updated
    Apr 1, 2021
    Dataset authored and provided by
    Einetic
    License

    https://paper.erudition.co.in/termshttps://paper.erudition.co.in/terms

    Description

    Question Paper Solutions of chapter Techniques of Data Collection of Business Research Methods, 3rd Semester , Bachelor in Business Administration 2020 - 2021

  8. n

    Keyphrase Metrics for Data Collection Methods

    • newsletterscan.com
    Updated Jun 2, 2025
    + more versions
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    (2025). Keyphrase Metrics for Data Collection Methods [Dataset]. https://newsletterscan.com/topic/data-collection-methods
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    Dataset updated
    Jun 2, 2025
    Variables measured
    Mentions, Growth Rate, Growth Category
    Description

    A dataset of mentions, growth rate, and total volume of the keyphrase 'Data Collection Methods' over time.

  9. d

    Data from: Comparing three collection methods for pollinating insects within...

    • catalog.data.gov
    • agdatacommons.nal.usda.gov
    Updated Apr 21, 2025
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    Agricultural Research Service (2025). Data from: Comparing three collection methods for pollinating insects within electric transmission rights-of-ways [Dataset]. https://catalog.data.gov/dataset/data-from-comparing-three-collection-methods-for-pollinating-insects-within-electric-trans-7ef08
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    Dataset updated
    Apr 21, 2025
    Dataset provided by
    Agricultural Research Service
    Description

    Insect pollinator community data collected from three types of insect traps/collecting methods (colored pan traps, blue vane traps, targeted sweep netting) from four power line right of ways in Alabama. Data are from one growing season (May-October 2018), and collection methods were employed once per month. Data include: 1) insect pollinator community composition data; 2) relative diversity calculations by insect Order; 3) overall insect pollinator community diversity summary by trap type/collecting method and month. These data reflect the community as sampled through different means in the same time period. Resources in this dataset: Resource title: Insect Pollinator Community Composition Matrix File name: Pollinator communty matrix.csv Resource description: Pollinator community composition (taxon, abundance) by site, insect trap type, and season. See Supplemental Table 1 in Campbell et al. 2023 for detailed taxa information. Resource title: Insect Pollinator Community Diversity by Order File name: Pollinator community diversity by Order.csv Resource description: Insect Pollinator community diversity metrics separated by Order for each site, for each insect trap type and season. Resource title: Summary of Overall Insect Pollinator Community Diversity File name: Overall Pollinator community diversity.csv Resource description: Overall Insect Pollinator community diversity summarized by trap type and season. Resource title: Dataset key File name: Dataset key table.pdf Resource description: Column titles and variable descriptions for three datasets, of: 1) Pollinator Community Composition; 2) Pollinator Community Diversity by Order; and 3) Overall Pollinator Community Diversity summarized by Trap Type and Season

  10. o

    Collection method

    • opencontext.org
    Updated Feb 20, 2022
    + more versions
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    Lucas Proctor; Alexia Smith (2022). Collection method [Dataset]. https://opencontext.org/predicates/ae6c2532-cda5-40ce-945e-564545abaa4f
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    Dataset updated
    Feb 20, 2022
    Dataset provided by
    Open Context
    Authors
    Lucas Proctor; Alexia Smith
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    An Open Context "predicates" dataset item. Open Context publishes structured data as granular, URL identified Web resources. This "Variables" record is part of the "Fuel and Plant Use in Northern Mesopotamia" data publication.

  11. w

    Demographic and Health Survey 1996 - Uzbekistan

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +1more
    Updated Jun 21, 2017
    + more versions
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    Institute of Obstetrics & Gynecology (2017). Demographic and Health Survey 1996 - Uzbekistan [Dataset]. https://microdata.worldbank.org/index.php/catalog/1516
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    Dataset updated
    Jun 21, 2017
    Dataset authored and provided by
    Institute of Obstetrics & Gynecology
    Time period covered
    1996
    Area covered
    Uzbekistan
    Description

    Abstract

    The 1996 Uzbekistan Demographic and Health Survey (UDHS) is a nationally representative survey of 4,415 women age 15-49. Fieldwork was conducted from June to October 1996. The UDHS was sponsored by the Ministry of Health (MOH), and was funded by the United States Agency for International Development. The Institute of Obstetrics and Gynecology implemented the survey with technical assistance from the Demographic and Health Surveys (DHS) program.

    The 1996 UDHS was the first national-level population and health survey in Uzbekistan. It was implemented by the Research Institute of Obstetrics and Gynecology of the Ministry of Health of Uzbekistan. The 1996 UDHS was funded by the United States Agency for International development (USAID) and technical assistance was provided by Macro International Inc. (Calverton, Maryland USA) through its contract with USAID.

    OBJECTIVES AND ORGANIZATION OF THE SURVEY

    The purpose of the 1996 Uzbekistan Demographic and Health Survey (UDHS) was to provide an information base to the Ministry of Health for the planning of policies and programs regarding the health of women and their children. The UDHS collected data on women's reproductive histories, knowledge and use of contraception, breastfeeding practices, and the nutrition, vaccination coverage, and episodes of illness among children under the age of three. The survey also included, for all women of reproductive age and for children under the age of three, the measurement of the hemoglobin level in the blood to assess the prevalence of anemia and measurements of height and weight to assess nutritional status.

    A secondary objective of the survey was to enhance the capabilities of institutions in Uzbekistan to collect, process and analyze population and health data so as to facilitate the implementation of future surveys of this type.

    MAIN RESULTS

    • Fertility Rates. Survey results indicate a total fertility rate (TFR) for all of Uzbekistan of 3.3 children per woman. Fertility levels differ for different population groups. The TFR for women living in urbml areas (2.7 children per woman) is substantially lower than for women living in rural areas (3.7). The TFR for Uzbeki women (3.5 children per woman) is higher than for women of other ethnicities (2.5). Among the regions of Uzbekistan, the TFR is lowest in Tashkent City (2.3 children per woman).
    • Family Planning. Knowledge. Knowledge of contraceptive methods is high among women in Uzbekistan. Knowledge of at least one method is 89 percent. High levels of knowledge are the norm for women of all ages, all regions of the country, all educational levels, and all ethnicities. However, knowledge of sterilization was low; only 27 percent of women reported knowing of this method.
    • Fertility Preferences. A majority of women in Uzbekistan (51 percent) indicated that they desire no more children. Among women age 30 and above, the proportion that want no more children increases to 75 percent. Thus, many women come to the preference to stop childbearing at relatively young ages when they have 20 or more potential years of childbearing ahead of them. For some of these women, the most appropriate method of contraception may be a long-acting method such as female sterilization, However, there is a deficiency of both knowledge and use of this method in Uzbekistan. In the interest of providing couples with a broad choice of safe and effective methods, information about this method and access to it should be made available so that informed choices about its suitability can be made by individual women and couples.
    • Induced Aboration : Abortion Rates. From the UDHS data, the total abortion rate (TAR)--the number of abortions a woman will have in her lifetime based on the currently prevailing abortion rates--was calculated. For Uzbekistan, the TAR for the period from mid-1993 to mid-1996 is 0.7 abortions per woman. As expected, the TAR for Uzbekistan is substantially lower than recent estimates of the TAR for other areas of the former Soviet Union such as Kazakstan (1.8), Romania (3.4 abortions per woman), and Yekaterinburg and Perm in Russia (2.3 and 2.8, respectively).
    • Infant mortality : In the UDHS, infant mortality data were collected based on the international definition of a live birth which, irrespective of the duration of pregnancy, is a birth that breathes or shows any sign of life (United Nations, 1992).
    • Mortality Rates. For the five-year period before the survey (i.e., approximately mid- 1992 to mid- 1996), infant mortality in Uzbekistan is estimated at 49 infant deaths per 1,000 births. The estimates of neonatal and postneonatal mortality are 23 and 26 per 1,000.
    • Maternal and child health : Uzbekistan has a well-developed health system with an extensive infrastructure of facilities that provide maternal care services. This system includes special delivery hospitals, the obstetrics and gynecology departments of general hospitals, women's consulting centers, and doctor's assistant/midwife posts (FAPs). There is an extensive network of FAPs throughout rural areas.
    • Nutrition : Breastfeeding. Breastfeeding is almost universal in Uzbekistan; 96 percent of children born in the three years preceding the survey are breastfed. Overall, 19 percent of children are breastfed within an hour of delivery and 40 percent within 24 hours of delivery. The median duration of breastfeeding is lengthy (17 months). However, durations of exclusive breastfeeding, as recommended by WHO, are short (0.4 months).
    • Prevalence of anemia : Testing of women and children for anemia was one of the major efforts of the 1996 UDHS. Anemia has been considered a major public health problem in Uzbekistan for decades. Nevertheless, this was the first anemia study in Uzbekistan done on a national basis. The study involved hemoglobin (Hb) testing for anemia using the Hemocue system. Women. Sixty percent of the women in Uzbekistan suffer from some degree of anemia. The great majority of these women have either mild (45 percent) or moderate anemia (14 percent). One percent have severe anemia.

    Geographic coverage

    National Seven raions were excluded from the survey because they were considered too remote and sparsely inhabited.

    Analysis unit

    • Household
    • Women age 15-49

    Universe

    The population covered by the 1996 UDHS is defined as the universe of all women age 15-49 in Uzbekistan

    Kind of data

    Sample survey data

    Sampling procedure

    The UDHS employed a probability sample of women age 15 to 49, representative of 98.7 percent of the country. Seven raions were excluded from the survey because they were considered too remote and sparsely inhabited. These raions are: Kungradskiyi, Muyinakskiyi, and Takhtakupyrskiyi in Karakalpakstan; Uchkudukskiyi, Tamdynskiyi, and Kanimekhskiyi in Navoiiskaya; and Romitanskiyi in Bukharskaya. The remainder of the country was divided into five survey regions. Tashkent City constituted a survey region by itself, while the remaining four survey regions consisted of groups of contiguous oblasts. The five survey regions were defined as follows: Region 1: Karakalpakstan and Khoresmskaya. Region 2: Navoiyiskaya, Bukharskaya, Kashkadarinskaya, and Surkhandarinskaya. Region 3: Samarkandskaya, Dzhizakskaya, Syrdarinskaya, and Tashkentskaya. Region 4: Namanganskaya, Ferganskaya, and Andizhanskaya. Region 5: Tashkent City.

    CHARACTERISTICS OF THE UDHS SAMPLE

    The sample for the UDHS was selected in three stages. In the rural areas, the primary sampling units (PSUs) corresponded to the raions which were selected with probabilities proportional to size, the size being the 1994 population. At the second stage, one village was selected in each selected raion. A complete listing of the households residing in each selected village was carried out. The lists of households obtained were used as the frame for third-stage sampling, which is the selection of the households to be visited by the UDHS interviewing teams during the main survey fieldwork. In each selected household, women between the ages of 15 and 49 were identified and interviewed.

    In the urban areas, the PSUs were the cities and towns themselves. In the second stage, one health block was selected from each town except in self-representing cities (large cities that were selected with certainty), where more than one health block was selected. The selected health blocks were segmented prior to the household listing operation which provided the household lists for the third-stage selection of households.

    SAMPLE ALLOCATION

    The regions, stratified by urban and rural areas, were the sampling strata. There were thus nine strata with Tashkent City constituting an entire stratum. A proportional allocation of the target number of 4,000 women to the 9 strata would yield the sample distribution.

    The proportional allocation would result in a completely self-weighting sample but would not allow for reliable estimates for at least two of the five survey regions, namely Region 1 and Tashkent City. Results of other demographic and health surveys show that a minimum sample of 1,000 women is required in order to obtain estimates of fertility and childhood mortality rates at an acceptable level of sampling errors. Given that the total sample size for the UDHS could not he increased so as to achieve the required level of sampling errors, it was decided that the sample would be divided equally among the five regions, and within each region, it would be distributed proportionally to the urban and the rural areas. With this type of allocation, demographic rates (fertility and mortality) could not be produced for regions separately.

    The number of sample points (or clusters) to be selected for each stratum was calculated by dividing the

  12. Methods currently used by marketing companies to collect customer data UK...

    • statista.com
    Updated Jan 6, 2023
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    Statista (2023). Methods currently used by marketing companies to collect customer data UK 2020 [Dataset]. https://www.statista.com/statistics/1185729/customer-data-collection-methods-uk/
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    Dataset updated
    Jan 6, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Aug 2020
    Area covered
    United Kingdom
    Description

    According to a survey carried out in August 2020 in the United Kingdom (UK), 72 percent of marketing companies collected customer data through their website. Half did so through social media, while a slightly smaller share said they recorded customer data at organized events. Collection via purchase lists and preference centres were the least used methods.

  13. f

    A survey on adolescent health information seeking behavior related to...

    • plos.figshare.com
    docx
    Updated Jun 1, 2023
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    Somayeh Esmaeilzadeh; Hasan Ashrafi-rizi; Leila Shahrzadi; Firozeh Mostafavi (2023). A survey on adolescent health information seeking behavior related to high-risk behaviors in a selected educational district in Isfahan [Dataset]. http://doi.org/10.1371/journal.pone.0206647
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    docxAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Somayeh Esmaeilzadeh; Hasan Ashrafi-rizi; Leila Shahrzadi; Firozeh Mostafavi
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Isfahan
    Description

    BackgroundsThe characteristics and conditions of growth and development have made adolescence one of the most vital and influential ages for prevention and health promotion, especially in the area of high-risk behaviors. Accordingly, the aim of this study was to determine adolescent health information seeking behavior related to high-risk behaviors in a selected educational district in Isfahan (Iran).MethodologyThe present study was of an applied type, which was conducted using the survey research method. The statistical population consisted of adolescent students at public schools in Isfahan (6519 subjects), and the sample size was determined to be 364 based on Cochran's formula. The sampling method was of a cluster sampling type, and the data collection tool was a researcher-made questionnaire. The validity of the questionnaire was approved by medical librarians, and using the Cronbach's alpha method, the reliability was obtained to be 0.85. SPSS 16 software was used for data analysis at two statistical levels: descriptive and inferential (independent t-test, one-sample t-test, chi-square, Pearson correlation coefficient and Mann-Whitney).Findings"Lack of mobility" was the most important health information need related to adolescent high-risk behaviors. The most important sources to obtain health information related to high-risk behaviors were "the Internet" with a mean score of 3.69 and "virtual social media" with a mean score of 3.49 out of 5. Adolescents had a positive attitude towards health information. The most important barriers to seeking health information were mentioned as follows: "difficulty in determining the quality of information found", "absence of appropriate information", and "concerns about the disclosure of their problems or illness to others". From the perspective of adolescents, the most important criterion for the evaluation of information quality was "the trueness and correctness of the information" and the need for health information related to high-risk behaviors was higher in girls than in boys.Conclusions/SignificanceConsidering adolescents’ positive attitude towards use of health information, it is necessary to put valid information at their disposal through different information resources, taking into account their level of information literacy. Accordingly, medical librarians’ abilities are suggested to be used for the production, evaluation, and introduction of health-related reading materials in the field of high-risk behaviors in easy language and suitable for adolescents.

  14. n

    Full dataset for: Diversifying environmental volunteers by engaging with...

    • data.niaid.nih.gov
    • datadryad.org
    zip
    Updated Nov 24, 2020
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    Anita Diaz; Kayleigh Winch; Richard Stafford; Pippa Gillingham; Einar Thorsen (2020). Full dataset for: Diversifying environmental volunteers by engaging with online communities [Dataset]. http://doi.org/10.5061/dryad.fxpnvx0qd
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    zipAvailable download formats
    Dataset updated
    Nov 24, 2020
    Dataset provided by
    Bournemouth University
    Authors
    Anita Diaz; Kayleigh Winch; Richard Stafford; Pippa Gillingham; Einar Thorsen
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Description
    1. Environmental volunteering can benefit participants and nature through improving physical and mental wellbeing while encouraging environmental stewardship. To enhance achievement of these outcomes, conservation organisations need to reach different groups of people to increase participation in environmental volunteering. This paper explores what engages communities searching online for environmental volunteering.
      
    2. We conducted a literature review of 1032 papers to determine key factors fostering participation by existing volunteers in environmental projects. We found the most important factor was to tailor projects to the motivations of participants. Also important were: promoting projects to people with relevant interests; meeting the perceived benefits of volunteers and removing barriers to participation.
      
    3. We then assessed the composition and factors fostering participation of the NatureVolunteers’s online community (n = 2216) of potential environmental volunteers and compared findings with those from the literature review. We asked whether projects advertised by conservation organisations meet motivations and interests of this online community.
      
    4. Using Facebook insights and Google Analytics we found that the online community were on average younger than extant communities observed in studies of environmental volunteering. Their motivations were also different as they were more interested in physical activity and using skills and less in social factors. They also exhibited preference for projects which are outdoor based, and which offer close contact with wildlife. Finally, we found that the online community showed a stronger preference for habitat improvement projects over those involving species-survey based citizen science.
      
    5. Our results demonstrate mis-matches between what our online community are looking for and what is advertised by conservation organisations. The online community are looking for projects which are more solitary, more physically active and more accessible by organised transport. We discuss how our results may be used by conservation organisations to better engage with more people searching for environmental volunteering opportunities online.
      
    6. We conclude that there is a pool of young people attracted to environmental volunteering projects whose interests are different to those of current volunteers. If conservation organisations can develop projects that meet these interests, they can engage larger and more diverse communities in nature volunteering.
      

    Methods The data set consists of separate sheets for each set of results presented in the paper. Each sheet contains the full data, summary descriptive statistics analysis and graphs presented in the paper. The method for collection and processing of the dataset in each sheet is as follows:

    The data set for results presented in Figure 1 in the paper - Sheet: "Literature"

    We conducted a review of literature on improving participation within nature conservation projects. This enabled us to determine what the most important factors were for participating in environmental projects, the composition of the populations sampled and the methods by which data were collected. The search terms used were (Environment* OR nature OR conservation) AND (Volunteer* OR “citizen science”) AND (Recruit* OR participat* OR retain* OR interest*). We reviewed all articles identified in the Web of Science database and the first 50 articles sorted for relevance in Google Scholar on the 22nd October 2019. Articles were first reviewed by title, secondly by abstract and thirdly by full text. They were retained or excluded according to criteria agreed by the authors of this paper. These criteria were as follows - that the paper topic was volunteering in the environment, including citizen science, community-based projects and conservation abroad, and included the study of factors which could improve participation in projects. Papers were excluded for topics irrelevant to this study, the most frequent being the outcomes of volunteering for participants (such as behavioural change and knowledge gain), improving citizen science data and the usefulness of citizen science data. The remaining final set of selected papers was then read to extract information on the factors influencing participation, the population sampled and the data collection methods. In total 1032 papers were reviewed of which 31 comprised the final selected set read in full. Four factors were identified in these papers which improve volunteer recruitment and retention. These were: tailoring projects to the motivations of participants, promoting projects to people with relevant hobbies and interests, meeting the perceived benefits of volunteers and removing barriers to participation.

    The data set for results presented in Figure 2 and Figure 3 in the paper - Sheet "Demographics"

    To determine if the motivations and interests expressed by volunteers in literature were representative of wider society, NatureVolunteers was exhibited at three UK public engagement events during May and June 2019; Hullabaloo Festival (Isle of Wight), The Great Wildlife Exploration (Bournemouth) and Festival of Nature (Bristol). This allowed us to engage with people who may not have ordinarily considered volunteering and encourage people to use the website. A combination of surveys and semi-structured interviews were used to collect information from the public regarding demographics and volunteering. In line with our ethics approval, no personal data were collected that could identify individuals and all participants gave informed consent for their anonymous information to be used for research purposes. The semi-structured interviews consisted of conducting the survey in a conversation with the respondent, rather than the respondent filling in the questionnaire privately and responses were recorded immediately by the interviewer. Hullabaloo Festival was a free discovery and exploration event where NatureVolunteers had a small display and surveys available. The Great Wildlife Exploration was a Bioblitz designed to highlight the importance of urban greenspaces where we had a stall with wildlife crafts promoting NatureVolunteers. The Festival of Nature was the UK’s largest nature-based festival in 2019 where we again had wildlife crafts available promoting NatureVolunteers. The surveys conducted at these events sampled a population of people who already expressed an interest in nature and the environment by attending the events and visiting the NatureVolunteers stand. In total 100 completed surveys were received from the events NatureVolunteers exhibited at; 21 from Hullabaloo Festival, 25 from the Great Wildlife Exploration and 54 from the Festival of Nature. At Hullabaloo Festival information on gender was not recorded for all responses and was consequently entered as “unrecorded”.

    OVERALL DESCRIPTION OF METHOD DATA COLLECTION FOR ALL OTHER RESULTS (Figures 4-7 and Tables 1-2)

    The remaining data were all collected from the NatureVolunteers website. The NatureVolunteers website https://www.naturevolunteers.uk/ was set up in 2018 with funding support from the Higher Education Innovation Fund to expand the range of people accessing nature volunteering opportunities in the UK. It is designed to particularly appeal to people who are new to nature volunteering including young adults wishing to expand their horizons, families looking for ways connect with nature to enhance well-being and older people wishing to share their time and life experiences to help nature. In addition, it was designed to be helpful to professionals working in the countryside & wildlife conservation sectors who wish to enhance their skills through volunteering. As part of the website’s development we created and used an online project database, www.naturevolunteers.uk (hereafter referred to as NatureVolunteers), to assess the needs and interests of our online community. Our research work was granted ethical approval by the Bournemouth University Ethics Committee. The website collects entirely anonymous data on our online community of website users that enables us to evaluate what sort of projects and project attributes most appeal to our online community. Visitors using the website to find projects are informed as part of the guidance on using the search function that this fully anonymous information is collected by the website to enhance and share research understanding of how conservation organisations can tailor their future projects to better match the interests of potential volunteers. Our online community was built up over the 2018-2019 through open advertising of the website nationally through the social media channels of our partner conservation organisations, through a range of public engagement in science events and nature-based festivals across southern England and through our extended network of friends and families, their own social media networks and the NatureVolunteers website’s own social network on Facebook and Twitter. There were 2216 searches for projects on NatureVolunteers from January 1st to October 25th, 2019.

    The data set for results presented in Figure 2 and Figure 3 in the paper - Sheet "Demographics"

    On the website, users searching for projects were firstly asked to specify their expectations of projects. These expectations encompass the benefits of volunteering by asking whether the project includes social interaction, whether particular skills are required or can be developed, and whether physical activity is involved. The barriers to participation are incorporated by asking whether the project is suitable for families, and whether organised transport is provided. Users were asked to rate the importance of the five project expectations on a Likert scale of 1 to 5 (Not at all = 1, Not really = 2, Neutral = 3, It

  15. D

    Replication Data for: A Three-Year Mixed Methods Study of Undergraduates’...

    • dataverse.no
    • dataverse.azure.uit.no
    Updated Oct 8, 2024
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    Ellen Nierenberg; Ellen Nierenberg (2024). Replication Data for: A Three-Year Mixed Methods Study of Undergraduates’ Information Literacy Development: Knowing, Doing, and Feeling [Dataset]. http://doi.org/10.18710/SK0R1N
    Explore at:
    txt(21865), txt(19475), csv(55030), txt(14751), txt(26578), txt(16861), txt(28211), pdf(107685), pdf(657212), txt(12082), txt(16243), text/x-fixed-field(55030), pdf(65240), txt(8172), pdf(634629), txt(31896), application/x-spss-sav(51476), txt(4141), pdf(91121), application/x-spss-sav(31612), txt(35011), txt(23981), text/x-fixed-field(15653), txt(25369), txt(17935), csv(15653)Available download formats
    Dataset updated
    Oct 8, 2024
    Dataset provided by
    DataverseNO
    Authors
    Ellen Nierenberg; Ellen Nierenberg
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    Aug 8, 2019 - Jun 10, 2022
    Area covered
    Norway
    Description

    This data set contains the replication data and supplements for the article "Knowing, Doing, and Feeling: A three-year, mixed-methods study of undergraduates’ information literacy development." The survey data is from two samples: - cross-sectional sample (different students at the same point in time) - longitudinal sample (the same students and different points in time)Surveys were distributed via Qualtrics during the students' first and sixth semesters. Quantitative and qualitative data were collected and used to describe students' IL development over 3 years. Statistics from the quantitative data were analyzed in SPSS. The qualitative data was coded and analyzed thematically in NVivo. The qualitative, textual data is from semi-structured interviews with sixth-semester students in psychology at UiT, both focus groups and individual interviews. All data were collected as part of the contact author's PhD research on information literacy (IL) at UiT. The following files are included in this data set: 1. A README file which explains the quantitative data files. (2 file formats: .txt, .pdf)2. The consent form for participants (in Norwegian). (2 file formats: .txt, .pdf)3. Six data files with survey results from UiT psychology undergraduate students for the cross-sectional (n=209) and longitudinal (n=56) samples, in 3 formats (.dat, .csv, .sav). The data was collected in Qualtrics from fall 2019 to fall 2022. 4. Interview guide for 3 focus group interviews. File format: .txt5. Interview guides for 7 individual interviews - first round (n=4) and second round (n=3). File format: .txt 6. The 21-item IL test (Tromsø Information Literacy Test = TILT), in English and Norwegian. TILT is used for assessing students' knowledge of three aspects of IL: evaluating sources, using sources, and seeking information. The test is multiple choice, with four alternative answers for each item. This test is a "KNOW-measure," intended to measure what students know about information literacy. (2 file formats: .txt, .pdf)7. Survey questions related to interest - specifically students' interest in being or becoming information literate - in 3 parts (all in English and Norwegian): a) information and questions about the 4 phases of interest; b) interest questionnaire with 26 items in 7 subscales (Tromsø Interest Questionnaire - TRIQ); c) Survey questions about IL and interest, need, and intent. (2 file formats: .txt, .pdf)8. Information about the assignment-based measures used to measure what students do in practice when evaluating and using sources. Students were evaluated with these measures in their first and sixth semesters. (2 file formats: .txt, .pdf)9. The Norwegain Centre for Research Data's (NSD) 2019 assessment of the notification form for personal data for the PhD research project. In Norwegian. (Format: .pdf)

  16. Z

    Dataset: A Systematic Literature Review on the topic of High-value datasets

    • data.niaid.nih.gov
    Updated Jun 23, 2023
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    Nina Rizun (2023). Dataset: A Systematic Literature Review on the topic of High-value datasets [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_7944424
    Explore at:
    Dataset updated
    Jun 23, 2023
    Dataset provided by
    Charalampos Alexopoulos
    Nina Rizun
    Magdalena Ciesielska
    Andrea Miletič
    Anastasija Nikiforova
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset contains data collected during a study ("Towards High-Value Datasets determination for data-driven development: a systematic literature review") conducted by Anastasija Nikiforova (University of Tartu), Nina Rizun, Magdalena Ciesielska (Gdańsk University of Technology), Charalampos Alexopoulos (University of the Aegean) and Andrea Miletič (University of Zagreb) It being made public both to act as supplementary data for "Towards High-Value Datasets determination for data-driven development: a systematic literature review" paper (pre-print is available in Open Access here -> https://arxiv.org/abs/2305.10234) and in order for other researchers to use these data in their own work.

    The protocol is intended for the Systematic Literature review on the topic of High-value Datasets with the aim to gather information on how the topic of High-value datasets (HVD) and their determination has been reflected in the literature over the years and what has been found by these studies to date, incl. the indicators used in them, involved stakeholders, data-related aspects, and frameworks. The data in this dataset were collected in the result of the SLR over Scopus, Web of Science, and Digital Government Research library (DGRL) in 2023.

    Methodology

    To understand how HVD determination has been reflected in the literature over the years and what has been found by these studies to date, all relevant literature covering this topic has been studied. To this end, the SLR was carried out to by searching digital libraries covered by Scopus, Web of Science (WoS), Digital Government Research library (DGRL).

    These databases were queried for keywords ("open data" OR "open government data") AND ("high-value data*" OR "high value data*"), which were applied to the article title, keywords, and abstract to limit the number of papers to those, where these objects were primary research objects rather than mentioned in the body, e.g., as a future work. After deduplication, 11 articles were found unique and were further checked for relevance. As a result, a total of 9 articles were further examined. Each study was independently examined by at least two authors.

    To attain the objective of our study, we developed the protocol, where the information on each selected study was collected in four categories: (1) descriptive information, (2) approach- and research design- related information, (3) quality-related information, (4) HVD determination-related information.

    Test procedure Each study was independently examined by at least two authors, where after the in-depth examination of the full-text of the article, the structured protocol has been filled for each study. The structure of the survey is available in the supplementary file available (see Protocol_HVD_SLR.odt, Protocol_HVD_SLR.docx) The data collected for each study by two researchers were then synthesized in one final version by the third researcher.

    Description of the data in this data set

    Protocol_HVD_SLR provides the structure of the protocol Spreadsheets #1 provides the filled protocol for relevant studies. Spreadsheet#2 provides the list of results after the search over three indexing databases, i.e. before filtering out irrelevant studies

    The information on each selected study was collected in four categories: (1) descriptive information, (2) approach- and research design- related information, (3) quality-related information, (4) HVD determination-related information

    Descriptive information
    1) Article number - a study number, corresponding to the study number assigned in an Excel worksheet 2) Complete reference - the complete source information to refer to the study 3) Year of publication - the year in which the study was published 4) Journal article / conference paper / book chapter - the type of the paper -{journal article, conference paper, book chapter} 5) DOI / Website- a link to the website where the study can be found 6) Number of citations - the number of citations of the article in Google Scholar, Scopus, Web of Science 7) Availability in OA - availability of an article in the Open Access 8) Keywords - keywords of the paper as indicated by the authors 9) Relevance for this study - what is the relevance level of the article for this study? {high / medium / low}

    Approach- and research design-related information 10) Objective / RQ - the research objective / aim, established research questions 11) Research method (including unit of analysis) - the methods used to collect data, including the unit of analy-sis (country, organisation, specific unit that has been ana-lysed, e.g., the number of use-cases, scope of the SLR etc.) 12) Contributions - the contributions of the study 13) Method - whether the study uses a qualitative, quantitative, or mixed methods approach? 14) Availability of the underlying research data- whether there is a reference to the publicly available underly-ing research data e.g., transcriptions of interviews, collected data, or explanation why these data are not shared? 15) Period under investigation - period (or moment) in which the study was conducted 16) Use of theory / theoretical concepts / approaches - does the study mention any theory / theoretical concepts / approaches? If any theory is mentioned, how is theory used in the study?

    Quality- and relevance- related information
    17) Quality concerns - whether there are any quality concerns (e.g., limited infor-mation about the research methods used)? 18) Primary research object - is the HVD a primary research object in the study? (primary - the paper is focused around the HVD determination, sec-ondary - mentioned but not studied (e.g., as part of discus-sion, future work etc.))

    HVD determination-related information
    19) HVD definition and type of value - how is the HVD defined in the article and / or any other equivalent term? 20) HVD indicators - what are the indicators to identify HVD? How were they identified? (components & relationships, “input -> output") 21) A framework for HVD determination - is there a framework presented for HVD identification? What components does it consist of and what are the rela-tionships between these components? (detailed description) 22) Stakeholders and their roles - what stakeholders or actors does HVD determination in-volve? What are their roles? 23) Data - what data do HVD cover? 24) Level (if relevant) - what is the level of the HVD determination covered in the article? (e.g., city, regional, national, international)

    Format of the file .xls, .csv (for the first spreadsheet only), .odt, .docx

    Licenses or restrictions CC-BY

    For more info, see README.txt

  17. f

    S1 Data -

    • plos.figshare.com
    xlsx
    Updated Oct 27, 2023
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    Muhammad Azeem; Javid Shabbir; Najma Salahuddin; Sundus Hussain; Musarrat Ijaz (2023). S1 Data - [Dataset]. http://doi.org/10.1371/journal.pone.0293628.s001
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Oct 27, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Muhammad Azeem; Javid Shabbir; Najma Salahuddin; Sundus Hussain; Musarrat Ijaz
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    In social surveys, the randomized response technique can be considered a popular method for collecting reliable information on sensitive variables. Over the past few decades, it has been a common practice that survey researchers develop new randomized response techniques and show their improvement over previous models. In majority of the available research studies, the authors tend to report only those findings which are favorable to their proposed models. They often tend to hide the situations where their proposed randomized response models perform worse than the already available models. This approach results in biased comparisons between models which may influence the decision of practitioners about the choice of a randomized response technique for real-life problems. We conduct a neutral comparative study of four available quantitative randomized response techniques using separate and combined metrics of respondents’ privacy level and model’s efficiency. Our findings show that, depending on the particular situation at hand, some models may be better than the other models for a particular choice of values of parameters and constants. However, they become less efficient when a different set of parameter values are considered. The mathematical conditions for efficiency of different models have also been obtained.

  18. p

    Population and Housing Census 2000 - Palau

    • microdata.pacificdata.org
    • catalog.ihsn.org
    Updated May 16, 2019
    + more versions
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    Office of Planning and Statistics (2019). Population and Housing Census 2000 - Palau [Dataset]. https://microdata.pacificdata.org/index.php/catalog/232
    Explore at:
    Dataset updated
    May 16, 2019
    Dataset authored and provided by
    Office of Planning and Statistics
    Time period covered
    2000
    Area covered
    Palau
    Description

    Abstract

    The 2000 Republic of Palau Census of Population and Housing was the second census collected and processed entirely by the republic itself. This monograph provides analyses of data from the most recent census of Palau for decision makers in the United States and Palau to understand current socioeconomic conditions. The 2005 Census of Population and Housing collected a wide range of information on the characteristics of the population including demographics, educational attainments, employment status, fertility, housing characteristics, housing characteristics and many others.

    Geographic coverage

    National

    Analysis unit

    • Household;
    • Individual.

    Universe

    The 1990, 1995 and 2000 censuses were all modified de jure censuses, counting people and recording selected characteristics of each individual according to his or her usual place of residence as of census day. Data were collected for each enumeration district - the households and population in each enumerator assignment - and these enumeration districts were then collected into hamlets in Koror, and the 16 States of Palau.

    Kind of data

    Census/enumeration data [cen]

    Sampling procedure

    No sampling - whole universe covered

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The 2000 censuses of Palau employed a modified list-enumerate procedure, also known as door-to-door enumeration. Beginning in mid-April 2000, enumerators began visiting each housing unit and conducted personal interviews, recording the information collected on the single questionnaire that contained all census questions. Follow-up enumerators visited all addresses for which questionnaires were missing to obtain the information required for the census.

    Cleaning operations

    The completed questionnaires were checked for completeness and consistency of responses, and then brought to OPS for processing. After checking in the questionnaires, OPS staff coded write-in responses (e.g., ethnicity or race, relationship, language). Then data entry clerks keyed all the questionnaire responses. The OPS brought the keyed data to the U.S. Census Bureau headquarters near Washington, DC, where OPS and Bureau staff edited the data using the Consistency and Correction (CONCOR) software package prior to generating tabulations using the Census Tabulation System (CENTS) package. Both packages were developed at the Census Bureau's International Programs Center (IPC) as part of the Integrated Microcomputer Processing System (IMPS).

    The goal of census data processing is to produce a set of data that described the population as clearly and accurately as possible. To meet this objective, crew leaders reviewed and edited questionnaires during field data collection to ensure consistency, completeness, and acceptability. Census clerks also reviewed questionnaires for omissions, certain inconsistencies, and population coverage. Census personnel conducted a telephone or personal visit follow-up to obtain missing information. The follow-ups considered potential coverage errors as well as questionnaires with omissions or inconsistencies beyond the completeness and quality tolerances specified in the review procedures.

    Following field operations, census staff assigned remaining incomplete information and corrected inconsistent information on the questionnaires using imputation procedures during the final automated edit of the data. The use of allocations, or computer assignments of acceptable data, occurred most often when an entry for a given item was lacking or when the information reported for a person or housing unit on an item was inconsistent with other information for that same person or housing unit. In all of Palau’s censuses, the general procedure for changing unacceptable entries was to assign an entry for a person or housing unit that was consistent with entries for persons or housing units with similar characteristics. The assignment of acceptable data in place of blanks or unacceptable entries enhanced the usefulness of the data.

    Sampling error estimates

    Human and machine-related errors occur in any large-scale statistical operation. Researchers generally refer to these problems as non-sampling errors. These errors include the failure to enumerate every household or every person in a population, failure to obtain all required information from residents, collection of incorrect or inconsistent information, and incorrect recording of information. In addition, errors can occur during the field review of the enumerators' work, during clerical handling of the census questionnaires, or during the electronic processing of the questionnaires. To reduce various types of non-sampling errors, Census office personnel used several techniques during planning, data collection, and data processing activities. Quality assurance methods were used throughout the data collection and processing phases of the census to improve the quality of the data.

    Census staff implemented several coverage improvement programs during the development of census enumeration and processing strategies to minimize under-coverage of the population and housing units. A quality assurance program improved coverage in each census. Telephone and personal visit follow-ups also helped improve coverage. Computer and clerical edits emphasized improving the quality and consistency of the data. Local officials participated in post-census local reviews. Census enumerators conducted additional re-canvassing where appropriate.

  19. U

    Riparian vegetation data used for comparing sampling methods along the...

    • data.usgs.gov
    • catalog.data.gov
    Updated Mar 5, 2024
    + more versions
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    Emily Palmquist (2024). Riparian vegetation data used for comparing sampling methods along the Colorado River, Grand Canyon, Arizona [Dataset]. http://doi.org/10.5066/P9N2RBIC
    Explore at:
    Dataset updated
    Mar 5, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Emily Palmquist
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Time period covered
    2019
    Area covered
    Colorado River, Arizona
    Description

    These data were collected as part of a methodological comparison for collecting riparian vegetation data. Two common methods for collecting vegetation data were used: line-point intercept and 1m2 ocular quadrats (visual cover estimates). At each site and transect, both methods were used to collect cover and composition data by four different observers. The same transects and quadrats were utilized for both methods and all observers. Field data collected included percent cover for total living foliar cover, each plant species encountered, litter, dead plant material that is still standing, and ground cover features (biological soil crust, rock, sand, and fine soil particles). Line-point intercept data were collected at 25 cm intervals along each transect and at four points along the edge of each 1m2 quadrat. Since transects varied in length, the number of data points collected along each transect also varied. A pin flag was dropped vertically to the ground at 25 cm intervals and ev ...

  20. U.S. legal professionals' customer feedback collection methods 2018

    • statista.com
    Updated Dec 10, 2024
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    Statista (2024). U.S. legal professionals' customer feedback collection methods 2018 [Dataset]. https://www.statista.com/statistics/941050/legal-services-customer-feedback-collection-methods-united-states/
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    Dataset updated
    Dec 10, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2018
    Area covered
    United States
    Description

    This statistic depicts the methods used by legal professionals in the United States to collect customer feedback in 2018. During the survey, 37 percent of respondents stated they do not regularly collect feedback from clients.

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Statista (2025). Leading data collection methods among U.S. consumers 2023 [Dataset]. https://www.statista.com/statistics/1269920/first-party-data-usa/
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Leading data collection methods among U.S. consumers 2023

Explore at:
Dataset updated
Jun 6, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Dec 2023
Area covered
United States
Description

During a 2023 survey carried out among working-age consumers from the United States, nearly half of respodents stated that they preferred for their data to be collected via interactive surveys. Roughly a third name a loyalty card/program as their favored data collection method.

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