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)

This dataset presents a compendium of field-based earthworm data sources and associated meta-data from across the United Kingdom and Ireland (‘Worm source’). These were compiled up to 2021 and include 257 data sources, the earliest dating back to 1891. Source meta-data covers the type of quantitative earthworm data (i.e. incidence, abundance, biomass, taxa), methodological details (e.g. sampling method/s, location/s, whether sampled plots were natural or experimental, sampling year/s), and environmental information (e.g. habitat/land-use, inclusion of climate data and basic soil properties). Data sources were collected through literature searches on Web of Science and Google Scholar, as well as directly from original authors/data holders where possible. The data sources were compiled with the aim of gathering quantitative data on earthworm species and populations to develop earthworm abundance and niche models, and toward a modelling framework for earthworm impacts on soil processes. This work is part of the Soil Organic Carbon Dynamics (SOC-D) project funded by the NERC UK-SCAPE programme (Grant reference NE/R016429/1).

Activity data for small molecules are invaluable in chemoinformatics. Various bioactivity databases exist containing detailed information of target proteins and quantitative binding data for small molecules extracted from journals and patents. In the current work, we have merged several public and commercial bioactivity databases into one bioactivity metabase. The molecular presentation, target information, and activity data of the vendor databases were standardized. The main motivation of the work was to create a single relational database which allows fast and simple data retrieval by in-house scientists. Second, we wanted to know the amount of overlap between databases by commercial and public vendors to see whether the former contain data complementing the latter. Third, we quantified the degree of inconsistency between data sources by comparing data points derived from the same scientific article cited by more than one vendor. We found that each data source contains unique data which is due to different scientific articles cited by the vendors. When comparing data derived from the same article we found that inconsistencies between the vendors are common. In conclusion, using databases of different vendors is still useful since the data overlap is not complete. It should be noted that this can be partially explained by the inconsistencies and errors in the source data.

BackgroundAs more people living with HIV are identified and prescribed antiretroviral treatment in Zambia, detecting new HIV infections to complete the last mile of epidemic control is challenging. To address this, innovative targeted testing strategies are essential. Therefore, Right to Care Zambia developed and implemented a novel digital health surveillance application, Lynx, in three Zambian provinces—Northern, Luapula, and Muchinga in 2018. Lynx offers real-time HIV testing data with geo-spatial analysis for targeted testing, and has proven effective in enhancing HIV testing yield. This cross-sectional mixed methods study assessed the acceptability of Lynx among HIV testing healthcare workers in Zambia.MethodsA quantitative Likert scale (1–5) survey was administered to 176 healthcare workers to gauge Lynx’s acceptability. Additionally, six qualitative key person interviews and five focus group discussions were conducted to gain an in-depth understanding of acceptability, and identify relevant barriers and facilitators. Quantitative data were analysed by averaging survey responses and running descriptive statistics. Qualitative data were transcribed and analysed in thematic coding. Data triangulation was utilised between the data sources to verify findings.ResultsOverall, the average survey score of perceived ease of use was 3.926 (agree), perceived usefulness was 4.179 (strongly agree) and perceived compatibility was 3.574 (agree). Survey questions related to network requirements, resource availability, and IT support had the most “strongly disagree” responses. The qualitative data collection revealed that Lynx was perceived as useful, and easy to use. Training for staff and regular updates were identified as facilitators, while conflicting work priorities and inconsistent IT support were identified barriers.ConclusionLynx was identified as acceptable by health workers due to its perceived usefulness, staff trainings, and regular updates. For a mobile health intervention to be embraced in rural Zambian settings, key facilitators include robust IT support, comprehensive training, user feedback-based updates, and consideration of facility staff priorities.

All quantitative source data generated in this study.

Objectives: In quantitative research, understanding basic parameters of the study population is key for interpretation of the results. As a result, it is typical for the first table (“Table 1”) of a research paper to include summary statistics for the study data. Our objectives are 2-fold. First, we seek to provide a simple, reproducible method for providing summary statistics for research papers in the Python programming language. Second, we seek to use the package to improve the quality of summary statistics reported in research papers.

Materials and Methods: The tableone package is developed following good practice guidelines for scientific computing and all code is made available under a permissive MIT License. A testing framework runs on a continuous integration server, helping to maintain code stability. Issues are tracked openly and public contributions are encouraged.

Results: The tableone software package automatically compiles summary statistics into publishable formats such...

This data set contains the replication data for the article "Knowing and doing: The development of information literacy measures to assess knowledge and practice." This article was published in the Journal of Information Literacy, in June 2021. The data was collected as part of the contact author's PhD research on information literacy (IL). One goal of this study is to assess students' levels of IL using three measures: 1) a 21-item IL test 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. 2) a source-evaluation measure to assess students' abilities to critically evaluate information sources in practice. This is a "DO-measure," intended to measure what students do in practice, in actual assignments. 3) a source-use measure to assess students' abilities to use sources correctly when writing. This is a "DO-measure," intended to measure what students do in practice, in actual assignments. The data set contains survey results from 626 Norwegian and international students at three levels of higher education: bachelor, master's and PhD. The data was collected in Qualtrics from fall 2019 to spring 2020. In addition to the data set and this README file, two other files are available here: 1) test questions in the survey, including answer alternatives (IL_knowledge_tests.txt) 2) details of the assignment-based measures for assessing source evaluation and source use (Assignment_based_measures_assessing_IL_skills.txt) Publication abstract: This study touches upon three major themes in the field of information literacy (IL): the assessment of IL, the association between IL knowledge and skills, and the dimensionality of the IL construct. Three quantitative measures were developed and tested with several samples of university students to assess knowledge and skills for core facets of IL. These measures are freely available, applicable across disciplines, and easy to administer. Results indicate they are likely to be reliable and support valid interpretations. By measuring both knowledge and practice, the tools indicated low to moderate correlations between what students know about IL, and what they actually do when evaluating and using sources in authentic, graded assignments. The study is unique in using actual coursework to compare knowing and doing regarding students’ evaluation and use of sources. It provides one of the most thorough documentations of the development and testing of IL assessment measures to date. Results also urge us to ask whether the source-focused components of IL – information seeking, source evaluation and source use – can be considered unidimensional constructs or sets of disparate and more loosely related components, and findings support their heterogeneity.

Data for Figures 2-5. This dataset is associated with the following publication: Shanks, O., A. Diedrich, M. Sivaganesan, J. Willis, and A. Shrifi. Quantitative fecal source characterization of urban municipal storm sewer system outfall ‘wet’ and ‘dry’ weather discharges. WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 259: 121857, (2024).

This dataset provides foundational factor and portfolio return data used in empirical finance and asset pricing research. It contains: - Fama–French 3-Factor and 5-Factor models - Size (ME), Book-to-Market (B/M), Operating Profitability (OP), and Investment (Inv) portfolios - Bivariate portfolios (e.g., 2x3 Size-B/M sorts) - Industry portfolio returns All data originate from the Kenneth R. French Data Library and are based on CRSP and Compustat databases. Data are value-weighted and expressed in percentages.

Some files in this dataset contain header comments describing data sources and methodology (as shown below):

This file was created using the 202508 CRSP database.
The 1-month TBill rate data until 202405 are from Ibbotson Associates. 
Starting from 202406, the 1-month TBill rate is from ICE BofA US 1-Month Treasury Bill Index.

To correctly read such files in Python (pandas), use the comment parameter — it automatically ignores all lines starting with a specific symbol (e.g., none here, so you can skip manually):

Example 1 — Automatically detect header rows:

import pandas as pd

# Detect the first numeric line to find where data starts
file_path = "F-F_Research_Data_5_Factors_2x3.csv"

with open(file_path) as f:
  lines = f.readlines()

# Find where the header line (column names) appears
for i, line in enumerate(lines):
  if "Mkt-RF" in line:
    skip_rows = i
    break

df = pd.read_csv(file_path, skiprows=skip_rows, sep=r"\s+")
print(df.head())

Example 2 — Skip a known number of comment lines manually:

df = pd.read_csv("F-F_Research_Data_5_Factors_2x3.csv", skiprows=3, sep=r"\s+")

Example 3 — If comments are prefixed (e.g., with #):

df = pd.read_csv("F-F_Research_Data_5_Factors_2x3.csv", comment="#", sep=",")

File Structure Example

The file contains supporting data sources for the research paper entitled "QUANTITATIVE EVALUATION OF SUSTAINABLE MARKETING EFFECTIVENESS: A POLISH CASE STUDY" submitted to a selected scientific journal for a prospective publication.

Abstract

Abstract

Background: Adolescent girls in Kenya are disproportionately affected by early and unintended pregnancies, unsafe abortion and HIV infection. The In Their Hands (ITH) programme in Kenya aims to increase adolescents' use of high-quality sexual and reproductive health (SRH) services through targeted interventions. ITH Programme aims to promote use of contraception and testing for sexually transmitted infections (STIs) including HIV or pregnancy, for sexually active adolescent girls, 2) provide information, products and services on the adolescent girl's terms; and 3) promote communities support for girls and boys to access SRH services.

Objectives: The objectives of the evaluation are to assess: a) to what extent and how the new Adolescent Reproductive Health (ARH) partnership model and integrated system of delivery is working to meet its intended objectives and the needs of adolescents; b) adolescent user experiences across key quality dimensions and outcomes; c) how ITH programme has influenced adolescent voice, decision-making autonomy, power dynamics and provider accountability; d) how community support for adolescent reproductive and sexual health initiatives has changed as a result of this programme.

Methodology ITH programme is being implemented in two phases, a formative planning and experimentation in the first year from April 2017 to March 2018, and a national roll out and implementation from April 2018 to March 2020. This second phase is informed by an Annual Programme Review and thorough benchmarking and assessment which informed critical changes to performance and capacity so that ITH is fit for scale. It is expected that ITH will cover approximately 250,000 adolescent girls aged 15-19 in Kenya by April 2020. The programme is implemented by a consortium of Marie Stopes Kenya (MSK), Well Told Story, and Triggerise. ITH's key implementation strategies seek to increase adolescent motivation for service use, create a user-defined ecosystem and platform to provide girls with a network of accessible subsidized and discreet SRH services; and launch and sustain a national discourse campaign around adolescent sexuality and rights. The 3-year study will employ a mixed-methods approach with multiple data sources including secondary data, and qualitative and quantitative primary data with various stakeholders to explore their perceptions and attitudes towards adolescents SRH services. Quantitative data analysis will be done using STATA to provide descriptive statistics and statistical associations / correlations on key variables. All qualitative data will be analyzed using NVIVO software.

Study Duration: 36 months - between 2018 and 2020.

Geographic coverage

Homabay county

Analysis unit

Households

Universe

Adolescent girls aged 15-19 years, parents and the community health volunteers

Sampling procedure

Quantitative Sampling

We estimated a sample size of 1,918 to detect a five percentage-point difference in the use of long term methods between baseline and endline time points at 80% power.As baseline, 23% of the adolescent girls reported that they were using long term methods in Homa Bay county. We sampled three sub counties—Ndhiwa, Homa Bay town and Kasipul for the endline survey. However, as fieldwork was interrupted due to the COVID-19 pandemic, we added one sub county—Karachuonyo sub county—when data collection resumed in September 2020. Sub counties and wards were purposively selected from sub counties that had been prioritized for the ITH program based on availability of ITH affiliated health facilities. The purposive selection of sub counties based on presence of ITH intervention affiliated health facilities meant that urban and peri-urban areas were oversampled due to the concentration of the health facilities in urban/peri-urban areas. In each ward, eight villages that formed the immediate catchment area for each ITH program affiliated health facilities were then selected for the study. We conducted a household listing of all households in each sampled village to identify households with an adolescent girl who met the study's inclusion criteria. Households were then randomly sampled from the list of households with eligible adolescents of age 15-19 years. To be eligible, an adolescent girl had to be aged 15-19 years, resident in the study area for at least six months preceding the study. Accordingly, students who stayed in boarding schools away from their parents were excluded from the study.

Qualitative Sampling

The qualitative component involved in-depth interviews (IDIs) with adolescent girls ages 15-19 years and focus group discussions (FGDs) with parents/adults and CHVs. We conducted IDIs with adolescent girls who had enrolled in the program but dropped out for various reasons, as well as girls who were enrolled and still using t-safe services. In addition, we conducted FGDs with CHVs and parents/adult caretakers of adolescents aged 15-19 years from the program areas. Participants were purposively selected from the villages included in the evaluation study. For the endline study, we conducted 17 IDIs with adolescents who had been enrolled in the ITH program and were receiving services or had dropped from the program. We also conducted two FGDs with CHVs and four FGDs with parents/adultcaretakers of adolescents aged 15-19 years.

Sampling deviation

N/A

Mode of data collection

Face-to-face [f2f] for quantitative data collection and Focus Group Discussions and In Depth Interviews for qualitative data collection

Research instrument

An interviewer-administered questionnaire was used to collect data from adolescent girls. The questionnaire included questions on socio-demographic and household characteristics; SRH knowledge and sources of information; sexual activity and relationships; contraceptive knowledge, access, choice and use; and exposure to family planning messages and contraceptive decision making. To assess adolescents’ exposure to the t-safe program we included a series of questions drawn from similar project evaluation surveys as well as t-safe project program monitoring indicators. The questions assessed whether adolescents had ever heard the t-safe program, whether they have ever been contacted by mobilizers, whether they participated in any community event organized by the t-safe mobilizers, whether they received information about SRH through t-safe affiliated organizations Facebook or website, and whether they received SMS or WhatsApp messages focused on SRH from tsafe. For those who responded positively, the survey asked further questions on the sources; from which site on internet or Facebook’ or ‘which person or organization sent you these messages’ and ‘how many times have you received information’. Adolescents were also asked whether they had ever registered to a t-safe or Triggerise platform using a mobile phone after discussing with a mobilizer, after discussing with their peers or family members or by themselves after hearing from some other places. The questionnaire was developed in English and then translated into Kiswahili. Data were collected on android tablets programmed using the Open Data Kit (ODK)-based SurveyCTO platform.

For the qualitative component ;Semi-structured interview guides were developed by experienced researchers in consultation with the program partners for the qualitative interviews (with adolescent girls) and FGDs (with parents/adult caretakers of adolescents and CHVs). The guides included probes to explore adolescents' exposure to the ITH program; their experiences with program's SRH services; their perceptions on quality of services; as well as challenges and barriers to access of SRH services. The guides also included probes on the community’s "support" for adolescents' sexual and reproductive health services and; their perspectives on the effects of the program. The guides were developed in English and then translated into Kiswahili for data collection. The guides were pre-tested during the pilot study.

Cleaning operations

Quantitative data was collected on android tablets programmed using the Open Data Kit (ODK)-based SurveyCTO platform while qualitative data was collected using a recorder.Once quantitative data were confirmed to be complete, the data was approved for synchronization. Data were electronically transmitted to a secure password protected SurveyCTO server at the APHRC office. Backup versions of the data remained in the encrypted and password-protected tablets until the end of field activities when all the data were considered to have been synchronized. Subsequently, tablet was securely and permanently cleaned. Data on the server were retrieved by the data manager and then downloaded for use. For qualitative data, audio recordings from qualitative interviews were transcribed and saved in MS Word format. The transcripts were stored electronically in password protected computers and were only accessible to the evaluation team working on the project.

Response rate

N/A

Sampling error estimates

N/A

Databases of organismal traits that aggregate information from one or multiple sources can be leveraged for large-scale analyses in biology. Yet the differences among these data streams and how well they capture trait diversity have never been explored. We present the first analysis of the differences between phenotypes captured in free text of descriptive publications (‘monographs’) and those used in phylogenetic analyses (‘matrices’). We focus our analysis on osteological phenotypes of the limbs of four extinct vertebrate taxa critical to our understanding of the fin-to-limb transition. We find that there is low overlap between the anatomical entities used in these two sources of phenotype data, indicating that phenotypes represented in matrices are not simply a subset of those found in monographic descriptions. Perhaps as expected, compared to characters found in matrices, phenotypes in monographs tend to emphasize descriptive and positional morphology, be somewhat more complex, and relate to fewer additional taxa. While based on a small set of focal taxa, these qualitative and quantitative data suggest that either source of phenotypes alone will result in incomplete knowledge of variation for a given taxon. As a broader community develops to use and expand databases characterizing organismal trait diversity, it is important to recognize the limitations of the data sources and develop strategies to more fully characterize variation both within species and across the tree of life.

Project Overview Adolescence is a critical period for political development. Different political attitudes, political behaviors, and political interests tend to develop during adolescence and persist into adulthood. Welfare participation is associated with lower political participation and pessimistic views of politics among adults, yet we have not uncovered the extent to which welfare participation in adolescence affects political outcomes in adulthood. This project aims to address the disconnect in the literature between what we know about the effects of welfare program experiences and what we know about individual political development. Data and Data Collection Overview The broader project relied on both qualitative and quantitative data, including secondary data from the American National Election Studies (ANES), the National Longitudinal Survey of Youth 1997 (NLSY97) cohort, and the National Longitudinal Study of Adolescent Health (Add Health), which are not included here. The original data collected by the depositing researcher are included, as described below. The qualitative data included a focus group with seven participants and individual interviews with 30 other individuals recruited by the researcher. Interviews were chosen so that participants could be more comfortable sharing personal experiences in a private setting. This data collection technique also allowed the researcher to keep conversations on topic and to ask probing and follow-up questions more easily. The focus group technique was chosen to provide for interactions among the participants involved, thus allowing participants to react to each other’s experiences and comments, and going beyond top-of-mind themes for any one participant. Participants in Round 1 (including those in the focus group and individual interviews) and Round 2 were recruited from the undergraduate student body at a large midwestern public university (N=7), as well as from a local community college (N=13). They were recruited through IRB-approved mass emails to the undergraduate student bodies. Participants in the Round 3 data collection (N=10) were recruited from the sample of Qualtrics panel respondents who completed the Adolescent Hardship and Politics Attitudes Survey (AHPAS; more detail below). Among the ten individuals interviewed in Round 3, five were on welfare during their adolescence, and the other five were not on welfare but grew up in poverty. The Round 1 and Round 2 questionnaire data include the pseudonyms that were selected by participants from a list. The participants in Round 3 chose any name they wanted as a pseudonym. A list of Round 3 names chosen is included as documentation, so that they can be paired with the unique ID code that was used as part of the AHPAS survey. There were two key original quantitative data sources. First, the quantitative data included national-level survey data called the Adolescent Hardship and Political Attitudes Survey (AHPAS), fielded by the researcher via Qualtrics Research Services ( https://www.qualtrics.com/support/survey-platform/distributions-module/online-panels/ ). The AHPAS sample consisted of 1,137 respondents recruited by Qualtrics, who were surveyed in January 2025. About half of the sample had experienced means-tested welfare programs during adolescence, while the other half had not been on welfare, but was in poverty during the period. Second, quantitative data were separately derived from a questionnaire about political attitudes and demographic factors that interview participants from the Round 1 and Round 2 qualitative data collection also completed. After receiving IRB approval, a recruitment email was distributed with a screener survey to identify individuals with adolescent welfare program experience. Participants were selected based on the extent of their program experience (indexed in terms of number of programs used), as well as their availability to participate in the focus group or an interview. Participants were offered a $25 gift card incentive for their participation. To protect confidentiality and privacy, participants selected a pseudonym to use in the subsequent focus group The focus group and interview transcripts were analyzed using Atlas.ti. The transcripts were coded by combining deductive and inductive coding approaches. Selection and Organization of Shared Data Data files shared in this deposit include: The de-identified transcripts from the focus group discussion and the three rounds of individual interviews, all labeled with participants’ chosen pseudonyms, along with the researcher-collected questionnaire data from the same participants. The original national-level quantitative data from the AHPAS used for analysis are also shared, in a raw and clean version, in .dta and .csv formats. The Original version has the uncoded variables in it, while in the Clean version, the variables are coded/labeled, although there is no separate codebook. Secondary users who want to...

BackgroundThere is a scarcity of long time-span and geographically wide research on the health status of Corallium rubrum, including limited research on its historical ecology and carbon sequestration capacity.ObjectivesTo reconstruct the temporal trends of the most reported C. rubrum population parameters in the Northwestern Mediterranean Sea and to determine the changes in total carbon sequestration by this species.Data sourcesQuantitative and qualitative, academic and grey documents were collected from scientific web browsers, scientific libraries, and requests to scientists.Study eligibility criteriaDocuments with original information of basal diameter, height and/or weight per colony, with a depth limit of 60 m in the Catalan and Ligurian Seas were analyzed.Synthesis methodsWe calculated yearly average values of C. rubrum biometric parameters, as well as estimated total weight, carbon flux, and carbon fixation in the structures of C. rubrum’s colonies.ResultsIn both study areas, the values of the selected morphometric parameters for C. rubrum decreased until the 1990s, then increased from the 2000s, with average values surpassing the levels of the 1960s (Ligurian Sea) or reaching levels slightly lower than those of the 1980s (Catalan Sea). The difference in carbon sequestered between the oldest (1960s: Ligurian Sea; 1970s: Catalan Sea) and the lowest (1990s) biomass value of colonies is nearly double.LimitationsQuantitative data previous to the 1990s are very limited. Information on recent recovery trends in C. rubrum parameters is concentrated in a few areas and biased towards colonies in marine protected areas, with scarce quantitative information from colonies in other areas.ConclusionsThe halt in the C. rubrum decreasing trend coincided with the exhaustion of tree-like colonies and the first recovery response due to effective protection measures in some areas. Nevertheless, C. rubrum climate change mitigation capacity through carbon sequestration can be drastically reduced from its potential in only a few decades.

Quantitative Data from Different Groundwater locations The Data is provided ‘as-is’, without any guarantee of correctness.

Punctual measurements of the Water sources flow Girst and Weissbach. The files in the compressed archive are Tab delimited text files, with ‘.’ as comma separator.

This is a dataset of OCTA images used in the development of the manuscript OCTAVA: an open-source toolbox for quantitative analysis of optical coherence tomography angiography images

Wikipedia is the largest and most read online free encyclopedia currently existing. As such, Wikipedia offers a large amount of data on all its own contents and interactions around them, as well as different types of open data sources. This makes Wikipedia a unique data source that can be analyzed with quantitative data science techniques. However, the enormous amount of data makes it difficult to have an overview, and sometimes many of the analytical possibilities that Wikipedia offers remain unknown. In order to reduce the complexity of identifying and collecting data on Wikipedia and expanding its analytical potential, after collecting different data from various sources and processing them, we have generated a dedicated Wikipedia Knowledge Graph aimed at facilitating the analysis, contextualization of the activity and relations of Wikipedia pages, in this case limited to its English edition. We share this Knowledge Graph dataset in an open way, aiming to be useful for a wide range of researchers, such as informetricians, sociologists or data scientists.

There are a total of 9 files, all of them in tsv format, and they have been built under a relational structure. The main one that acts as the core of the dataset is the page file, after it there are 4 files with different entities related to the Wikipedia pages (category, url, pub and page_property files) and 4 other files that act as "intermediate tables" making it possible to connect the pages both with the latter and between pages (page_category, page_url, page_pub and page_link files).

The document Dataset_summary includes a detailed description of the dataset.

Thanks to Nees Jan van Eck and the Centre for Science and Technology Studies (CWTS) for the valuable comments and suggestions.

Although rapid and relatively accurate graphical techniques exist for interpreting the depth to magnetic sources, these have now been largely supplanted by a wide range of computerised forward modelling routines capable of giving detailed estimates of source geometry as well as the source depth. Computer routines which have automated the depth estimation process also exist; however, these require considerable judgement on the part of the user, as they can give misleading results.

Josh Richards' Tweets

A Quantitative Study

By Twitter [source]

About this dataset

This dataset presents an unprecedented look into the digital communication habits of Josh Richards - one of Twitter's most popular and influential users. Analyzing his tweets from the last several weeks, we can gain a comprehensive understanding of how he shapes content, engages with his followers, and links to outside sources. The data covers everything from the type of media posted to the level of engagement generated by each tweet - making it an invaluable resource for anyone interested in exploring how Josh Richards crafts his online presence. Uncover the strategies behind his remarkable impact on social media by taking a closer look at this exciting dataset!

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How to use the dataset

This dataset provides an in-depth look into the posts of Josh Richards, a well-known social media celebrity, on Twitter. The dataset includes columns such as the post's content, the type of media used (images, videos and text), metrics related to engagement (likes, retweets and a measure of engagement rate) and external links shared by Josh. To glean insights from this data you can conduct descriptive analysis on all columns to get an overview of what type of content he typically posts on Twitter. Additionally, you can perform correlation analysis to identify any relationships between different variables or formats (e.g. does Josh receive more likes when he uses images or videos?). Moreover, you can also use these data for predictive purposes by attempting to predict what type of content will engage his audience most based on past performance metrics such as likes and RTs per post

Research Ideas

• One clever idea that can be used with this dataset is to identify the types of content and media that are most effective in engaging Josh Richards' followers. Through analyzing the level of engagement with different post types and media, marketers can then use this information to craft more effective campaigns when targeting similar audiences.
• This dataset could be used to analyze how successful external links shared by Josh Richards are in driving traffic to other websites. By studying whether certain types of links (e.g., posts linking to video content) tend to generate more clicks than others, marketers could adjust their strategies accordingly when crafting content for similar audiences.
• A further use for this dataset involves studying the impact that posting frequency has on engagement levels with Josh Richard's posts, as well as on external link click-through activity from his followers. This knowledge could provide valuable insights into how consistently social media accounts must post content in order to maximize user engagement and drive traffic from followers elsewhere online

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Twitter.

HF183/BacR287 qPCR standard control material and water sample measurements used to compare Bayesian and Traditional Fecal Score models. This dataset is associated with the following publication: Sivaganesan, M., J. Willis, A. Diedrich, and O. Shanks. A fecal score approximation model for analysis of real-time quantitative PCR fecal source identification measurements. WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 255: 121482, (2024).