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

    • statista.com
    Updated Jun 26, 2025
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    Statista (2025). 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
    Jun 26, 2025
    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, **** percent of respondents stated that they preferred for their data to be collected via interactive surveys. Meanwhile, **** percent of respondents mentioned loyalty cards/programs as their favored data collection method.

  2. f

    Data collection methods for vital statistics.

    • plos.figshare.com
    • 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.

  3. f

    Breakdown of data collection methods per country.

    • datasetcatalog.nlm.nih.gov
    Updated Aug 20, 2016
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    Curtis, Valerie; Oxford, John; Greenland, Katie; Schmidt, Wolf; Aunger, Robert; Ploubidis, George (2016). Breakdown of data collection methods per country. [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0001528218
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    Dataset updated
    Aug 20, 2016
    Authors
    Curtis, Valerie; Oxford, John; Greenland, Katie; Schmidt, Wolf; Aunger, Robert; Ploubidis, George
    Description

    Breakdown of data collection methods per country.

  4. e

    Techniques of Data Collection

    • paper.erudition.co.in
    html
    Updated Sep 2, 2025
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    Einetic (2025). Techniques of Data Collection [Dataset]. https://paper.erudition.co.in/makaut/bachelor-of-business-administration/5/research-methodology
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    htmlAvailable download formats
    Dataset updated
    Sep 2, 2025
    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 Research Methodology, 5th Semester , Bachelor of Business Administration

  5. f

    Data collection tools, administration, sample size and analytical...

    • plos.figshare.com
    xls
    Updated May 31, 2024
    + more versions
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    Albino Kalolo; Anosisye M. Kesale; Mackfallen Anasel; Ntuli A. Kapologwe; Jennie Jaribu; Stella Mujaya; James T. Kengia (2024). Data collection tools, administration, sample size and analytical techniques. [Dataset]. http://doi.org/10.1371/journal.pone.0303552.t002
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    xlsAvailable download formats
    Dataset updated
    May 31, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Albino Kalolo; Anosisye M. Kesale; Mackfallen Anasel; Ntuli A. Kapologwe; Jennie Jaribu; Stella Mujaya; James T. Kengia
    License

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

    Description

    Data collection tools, administration, sample size and analytical techniques.

  6. n

    Keyphrase Metrics for Data Collection Methods

    • newsletterscan.com
    Updated Mar 26, 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
    Mar 26, 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.

  7. d

    TagX Data collection for AI/ ML training | LLM data | Data collection for AI...

    • datarade.ai
    .json, .csv, .xls
    Updated Jun 18, 2021
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    TagX (2021). TagX Data collection for AI/ ML training | LLM data | Data collection for AI development & model finetuning | Text, image, audio, and document data [Dataset]. https://datarade.ai/data-products/data-collection-and-capture-services-tagx
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    .json, .csv, .xlsAvailable download formats
    Dataset updated
    Jun 18, 2021
    Dataset authored and provided by
    TagX
    Area covered
    Colombia, Russian Federation, Saudi Arabia, Iceland, Antigua and Barbuda, Benin, Djibouti, Belize, Qatar, Equatorial Guinea
    Description

    We offer comprehensive data collection services that cater to a wide range of industries and applications. Whether you require image, audio, or text data, we have the expertise and resources to collect and deliver high-quality data that meets your specific requirements. Our data collection methods include manual collection, web scraping, and other automated techniques that ensure accuracy and completeness of data.

    Our team of experienced data collectors and quality assurance professionals ensure that the data is collected and processed according to the highest standards of quality. We also take great care to ensure that the data we collect is relevant and applicable to your use case. This means that you can rely on us to provide you with clean and useful data that can be used to train machine learning models, improve business processes, or conduct research.

    We are committed to delivering data in the format that you require. Whether you need raw data or a processed dataset, we can deliver the data in your preferred format, including CSV, JSON, or XML. We understand that every project is unique, and we work closely with our clients to ensure that we deliver the data that meets their specific needs. So if you need reliable data collection services for your next project, look no further than us.

  8. f

    Passive data collection methods.

    • datasetcatalog.nlm.nih.gov
    • figshare.com
    Updated Jul 8, 2022
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    Hagaman, Ashley; Kohrt, Brandon A.; van Heerden, Alastair; Boone, Clare; Poudyal, Anubhuti; Mercado, Damaris Lopez; Maharjan, Sujen Man; Bemme, Dörte; Thapa, Ada; Byanjankar, Prabin (2022). Passive data collection methods. [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000367014
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    Dataset updated
    Jul 8, 2022
    Authors
    Hagaman, Ashley; Kohrt, Brandon A.; van Heerden, Alastair; Boone, Clare; Poudyal, Anubhuti; Mercado, Damaris Lopez; Maharjan, Sujen Man; Bemme, Dörte; Thapa, Ada; Byanjankar, Prabin
    Description

    Passive data collection methods.

  9. d

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

    • catalog.data.gov
    • agdatacommons.nal.usda.gov
    • +1more
    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. 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.

  11. Z

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

    • data.niaid.nih.gov
    • zenodo.org
    Updated Jun 23, 2023
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    Anastasija Nikiforova (2023). Dataset: A Systematic Literature Review on the topic of High-value datasets [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_7944424
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    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

  12. 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.

  13. w

    Dataset of book subjects that contain Data collection : key debates and...

    • workwithdata.com
    Updated Nov 7, 2024
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    Work With Data (2024). Dataset of book subjects that contain Data collection : key debates and methods in social research [Dataset]. https://www.workwithdata.com/datasets/book-subjects?f=1&fcol0=j0-book&fop0=%3D&fval0=Data+collection+:+key+debates+and+methods+in+social+research&j=1&j0=books
    Explore at:
    Dataset updated
    Nov 7, 2024
    Dataset authored and provided by
    Work With Data
    License

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

    Description

    This dataset is about book subjects. It has 3 rows and is filtered where the books is Data collection : key debates and methods in social research. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

  14. n

    Data from: A new digital method of data collection for spatial point pattern...

    • data.niaid.nih.gov
    • search.dataone.org
    • +1more
    zip
    Updated Jul 6, 2021
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    Chao Jiang; Xinting Wang (2021). A new digital method of data collection for spatial point pattern analysis in grassland communities [Dataset]. http://doi.org/10.5061/dryad.brv15dv70
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    zipAvailable download formats
    Dataset updated
    Jul 6, 2021
    Dataset provided by
    Inner Mongolia University of Technology
    Chinese Academy of Agricultural Sciences
    Authors
    Chao Jiang; Xinting Wang
    License

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

    Description

    A major objective of plant ecology research is to determine the underlying processes responsible for the observed spatial distribution patterns of plant species. Plants can be approximated as points in space for this purpose, and thus, spatial point pattern analysis has become increasingly popular in ecological research. The basic piece of data for point pattern analysis is a point location of an ecological object in some study region. Therefore, point pattern analysis can only be performed if data can be collected. However, due to the lack of a convenient sampling method, a few previous studies have used point pattern analysis to examine the spatial patterns of grassland species. This is unfortunate because being able to explore point patterns in grassland systems has widespread implications for population dynamics, community-level patterns and ecological processes. In this study, we develop a new method to measure individual coordinates of species in grassland communities. This method records plant growing positions via digital picture samples that have been sub-blocked within a geographical information system (GIS). Here, we tested out the new method by measuring the individual coordinates of Stipa grandis in grazed and ungrazed S. grandis communities in a temperate steppe ecosystem in China. Furthermore, we analyzed the pattern of S. grandis by using the pair correlation function g(r) with both a homogeneous Poisson process and a heterogeneous Poisson process. Our results showed that individuals of S. grandis were overdispersed according to the homogeneous Poisson process at 0-0.16 m in the ungrazed community, while they were clustered at 0.19 m according to the homogeneous and heterogeneous Poisson processes in the grazed community. These results suggest that competitive interactions dominated the ungrazed community, while facilitative interactions dominated the grazed community. In sum, we successfully executed a new sampling method, using digital photography and a Geographical Information System, to collect experimental data on the spatial point patterns for the populations in this grassland community.

    Methods 1. Data collection using digital photographs and GIS

    A flat 5 m x 5 m sampling block was chosen in a study grassland community and divided with bamboo chopsticks into 100 sub-blocks of 50 cm x 50 cm (Fig. 1). A digital camera was then mounted to a telescoping stake and positioned in the center of each sub-block to photograph vegetation within a 0.25 m2 area. Pictures were taken 1.75 m above the ground at an approximate downward angle of 90° (Fig. 2). Automatic camera settings were used for focus, lighting and shutter speed. After photographing the plot as a whole, photographs were taken of each individual plant in each sub-block. In order to identify each individual plant from the digital images, each plant was uniquely marked before the pictures were taken (Fig. 2 B).

    Digital images were imported into a computer as JPEG files, and the position of each plant in the pictures was determined using GIS. This involved four steps: 1) A reference frame (Fig. 3) was established using R2V software to designate control points, or the four vertexes of each sub-block (Appendix S1), so that all plants in each sub-block were within the same reference frame. The parallax and optical distortion in the raster images was then geometrically corrected based on these selected control points; 2) Maps, or layers in GIS terminology, were set up for each species as PROJECT files (Appendix S2), and all individuals in each sub-block were digitized using R2V software (Appendix S3). For accuracy, the digitization of plant individual locations was performed manually; 3) Each plant species layer was exported from a PROJECT file to a SHAPE file in R2V software (Appendix S4); 4) Finally each species layer was opened in Arc GIS software in the SHAPE file format, and attribute data from each species layer was exported into Arc GIS to obtain the precise coordinates for each species. This last phase involved four steps of its own, from adding the data (Appendix S5), to opening the attribute table (Appendix S6), to adding new x and y coordinate fields (Appendix S7) and to obtaining the x and y coordinates and filling in the new fields (Appendix S8).

    1. Data reliability assessment

    To determine the accuracy of our new method, we measured the individual locations of Leymus chinensis, a perennial rhizome grass, in representative community blocks 5 m x 5 m in size in typical steppe habitat in the Inner Mongolia Autonomous Region of China in July 2010 (Fig. 4 A). As our standard for comparison, we used a ruler to measure the individual coordinates of L. chinensis. We tested for significant differences between (1) the coordinates of L. chinensis, as measured with our new method and with the ruler, and (2) the pair correlation function g of L. chinensis, as measured with our new method and with the ruler (see section 3.2 Data Analysis). If (1) the coordinates of L. chinensis, as measured with our new method and with the ruler, and (2) the pair correlation function g of L. chinensis, as measured with our new method and with the ruler, did not differ significantly, then we could conclude that our new method of measuring the coordinates of L. chinensis was reliable.

    We compared the results using a t-test (Table 1). We found no significant differences in either (1) the coordinates of L. chinensis or (2) the pair correlation function g of L. chinensis. Further, we compared the pattern characteristics of L. chinensis when measured by our new method against the ruler measurements using a null model. We found that the two pattern characteristics of L. chinensis did not differ significantly based on the homogenous Poisson process or complete spatial randomness (Fig. 4 B). Thus, we concluded that the data obtained using our new method was reliable enough to perform point pattern analysis with a null model in grassland communities.

  15. d

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

    • catalog.data.gov
    • data.usgs.gov
    • +1more
    Updated Jul 6, 2024
    + more versions
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    U.S. Geological Survey (2024). Riparian vegetation data used for comparing sampling methods along the Colorado River, Grand Canyon, Arizona [Dataset]. https://catalog.data.gov/dataset/riparian-vegetation-data-used-for-comparing-sampling-methods-along-the-colorado-river-gran
    Explore at:
    Dataset updated
    Jul 6, 2024
    Dataset provided by
    U.S. Geological Survey
    Area covered
    Arizona, Colorado River, Grand Canyon
    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 every plant species and ground cover element that touched the pin flag was recorded in the order it touched the pin flag from top to bottom, including any species that would touch the pin flag if it continued upward indefinitely. Each species was only recorded once at each point. Ocular quadrat data were collected at each of the 1 m2 quadrats. Cover estimates were recorded to the nearest 5% other than those estimates under 5% which were recorded as either 1% or “trace”. Observers calibrated their ocular estimates at the beginning of sampling and when a new observer started sampling. Observers were given reference cards illustrating multiple levels of percent cover (1 – 95%), which were used during calibration and throughout data collection. Five observers with three levels of experience participated in this study. Two observers had extensive experience with identification of plant species in the study area, as well as with the methods used. One observer was familiar with the methods as well as riparian plant identification, but had not previously worked in this study area. Two observers had not worked in this system or with these methods before, but had experience conducting vegetation surveys. All observers received on-site training. At each site, four observers sampled the entire site using both field methods.

  16. D

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

    • dataverse.no
    • dataverse.azure.uit.no
    • +1more
    Updated Oct 8, 2024
    + more versions
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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)

  17. Most popular click-and-collect methods in the U.S. 2019

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). Most popular click-and-collect methods in the U.S. 2019 [Dataset]. https://www.statista.com/statistics/1041948/common-reasons-internet-users-use-click-and-collect-services/
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    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Dec 2018 - Jan 2019
    Area covered
    United States
    Description

    During an October 2019 survey, ** percent of responding U.S. online users stated that they were interested in picking up their online order at a register. Overall, ** percent of respondents had already tried the service. Curbside pickup was ranked second with ** percent of respondents being interested in getting their orders delivered in such a manner.

  18. f

    Data from: Clues for the Paradigmatic Development of Online Qualitative...

    • scielo.figshare.com
    tiff
    Updated Jun 1, 2023
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    Newton Claizoni Moreno de Melo; Débora Coutinho Paschoal Dourado (2023). Clues for the Paradigmatic Development of Online Qualitative Methods [Dataset]. http://doi.org/10.6084/m9.figshare.20020370.v1
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    tiffAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    SciELO journals
    Authors
    Newton Claizoni Moreno de Melo; Débora Coutinho Paschoal Dourado
    License

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

    Description

    ABSTRACT Objective: in this paper, we problematize how online methods were reduced to mere adaptations from previous data collection techniques, and then discuss how some of the idiosyncratic properties of the online scope may drive the development of future, paradigmatic, online qualitative methods. Proposition: we identified five clues for the paradigmatic development of online qualitative methods: (1) the new socialities allowed by online interactions; (2) the processes involved in asserting identities and selves online; (3) the increasing difficulty in distinguishing what is private and what is public online, and what does privacy mean in this context; (4) the increase of participants’ agency in online qualitative research; and (5) the declining distinction between offline and online social phenomena. Conclusion: by using ontological and epistemological assumptions that do not consider the specificities of online experiences, and by focusing excessively on adapting known methods to the new settings, we researchers are bound to conceive the online experience and operate in it using offline categories. This way, we might be missing the opportunity to develop native, paradigmatic, online qualitative methods that, ultimately, would allow for a better understanding of the phenomena we investigate.

  19. Methods used by debt collection agencies to recover debt in the U.S. 2016

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). Methods used by debt collection agencies to recover debt in the U.S. 2016 [Dataset]. https://www.statista.com/statistics/829200/debt-collection-methods-usa/
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    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2016
    Area covered
    United States
    Description

    This statistic presents the methods used for debt collection in the United States in 2016. The results of the survey revealed that ** percent of third-party debt collection agencies sent letters to the debtors.

  20. V

    Data from: A possible alternative method for collecting mosquito larvae in...

    • data.virginia.gov
    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    • +1more
    html
    Updated Jul 23, 2025
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    National Institutes of Health (2025). A possible alternative method for collecting mosquito larvae in rice fields [Dataset]. https://data.virginia.gov/dataset/a-possible-alternative-method-for-collecting-mosquito-larvae-in-rice-fields
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    htmlAvailable download formats
    Dataset updated
    Jul 23, 2025
    Dataset provided by
    National Institutes of Health
    Description

    Background Rice fields are efficient breeding places for malaria vectors in Madagascar. In order to establish as easily as possible if a rice field is an effective larval site for anophelines, we compared classical dipping versus a net as methods of collecting larvae.

       Results
       Using similar collecting procedures, we found that the total number of anopheline larvae collected with the net was exactly double (174/87) that collected by dipping. The number of anopheline species collected was also greater with a net.
    
    
       Conclusions
       The net is an effective means of collecting anopheline larvae and can be used for qualitative ecological studies and to rapidly determine which rice fields are containing malaria vectors.
    
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Statista (2025). Leading data collection methods among UK consumers 2023 [Dataset]. https://www.statista.com/statistics/1453941/data-collection-method-consumers-uk/
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Leading data collection methods among UK consumers 2023

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Dataset updated
Jun 26, 2025
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, **** percent of respondents stated that they preferred for their data to be collected via interactive surveys. Meanwhile, **** percent of respondents mentioned loyalty cards/programs as their favored data collection method.

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