Objective(s): Momentum for open access to research is growing. Funding agencies and publishers are increasingly requiring researchers make their data and research outputs open and publicly available. However, clinical researchers struggle to find real-world examples of Open Data sharing. The aim of this 1 hr virtual workshop is to provide real-world examples of Open Data sharing for both qualitative and quantitative data. Specifically, participants will learn: 1. Primary challenges and successes when sharing quantitative and qualitative clinical research data. 2. Platforms available for open data sharing. 3. Ways to troubleshoot data sharing and publish from open data. Workshop Agenda: 1. “Data sharing during the COVID-19 pandemic” - Speaker: Srinivas Murthy, Clinical Associate Professor, Department of Pediatrics, Faculty of Medicine, University of British Columbia. Investigator, BC Children's Hospital 2. “Our experience with Open Data for the 'Integrating a neonatal healthcare package for Malawi' project.” - Speaker: Maggie Woo Kinshella, Global Health Research Coordinator, Department of Obstetrics and Gynaecology, BC Children’s and Women’s Hospital and University of British Columbia This workshop draws on work supported by the Digital Research Alliance of Canada. Data Description: Presentation slides, Workshop Video, and Workshop Communication Srinivas Murthy: Data sharing during the COVID-19 pandemic presentation and accompanying PowerPoint slides. Maggie Woo Kinshella: Our experience with Open Data for the 'Integrating a neonatal healthcare package for Malawi' project presentation and accompanying Powerpoint slides. This workshop was developed as part of Dr. Ansermino's Data Champions Pilot Project supported by the Digital Research Alliance of Canada., NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days. Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator on this page under "collaborate with the pediatric sepsis colab."

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)

The two primary goals of this workshop are: (1) to present an example of working with data that uses one of the files available through the Data Liberation Initiative (DLI); and (2) to provide a hands-on computing exercise that introduces some basic approaches to quantitative analysis. The study chosen for this example is the National Survey of Literacy Skills Used in Daily Activities conducted in 1989. In completing this example, three general strategies for performing quantitative analysis will be discussed.

The Supplementary Material for this article:Supplementary Table 1 | PRISMA 2009 checklist.Supplementary Table 2 | Search strategies.Supplementary Table 3 | Research information details and indicators dataset.Supplementary Table 4 | Specific information of indicators and studies under different profile.Supplementary Table 5 | Analysis results data.

The GAPs Data Repository provides a comprehensive overview of available qualitative and quantitative data on national return regimes, now accessible through an advanced web interface at https://data.returnmigration.eu/.

This updated guideline outlines the complete process, starting from the initial data collection for the return migration data repository to the development of a comprehensive web-based platform. Through iterative development, participatory approaches, and rigorous quality checks, we have ensured a systematic representation of return migration data at both national and comparative levels.

The Repository organizes data into five main categories, covering diverse aspects and offering a holistic view of return regimes: country profiles, legislation, infrastructure, international cooperation, and descriptive statistics. These categories, further divided into subcategories, are based on insights from a literature review, existing datasets, and empirical data collection from 14 countries. The selection of categories prioritizes relevance for understanding return and readmission policies and practices, data accessibility, reliability, clarity, and comparability. Raw data is meticulously collected by the national experts.

The transition to a web-based interface builds upon the Repository’s original structure, which was initially developed using REDCap (Research Electronic Data Capture). It is a secure web application for building and managing online surveys and databases.The REDCAP ensures systematic data entries and store them on Uppsala University’s servers while significantly improving accessibility and usability as well as data security. It also enables users to export any or all data from the Project when granted full data export privileges. Data can be exported in various ways and formats, including Microsoft Excel, SAS, Stata, R, or SPSS for analysis. At this stage, the Data Repository design team also converted tailored records of available data into public reports accessible to anyone with a unique URL, without the need to log in to REDCap or obtain permission to access the GAPs Project Data Repository. Public reports can be used to share information with stakeholders or external partners without granting them access to the Project or requiring them to set up a personal account. Currently, all public report links inserted in this report are also available on the Repository’s webpage, allowing users to export original data.

This report also includes a detailed codebook to help users understand the structure, variables, and methodologies used in data collection and organization. This addition ensures transparency and provides a comprehensive framework for researchers and practitioners to effectively interpret the data.

The GAPs Data Repository is committed to providing accessible, well-organized, and reliable data by moving to a centralized web platform and incorporating advanced visuals. This Repository aims to contribute inputs for research, policy analysis, and evidence-based decision-making in the return and readmission field.

Explore the GAPs Data Repository at https://data.returnmigration.eu/.

Transparency in data visualization is an essential ingredient for scientific communication. The traditional approach of visualizing continuous quantitative data solely in the form of summary statistics (i.e., measures of central tendency and dispersion) has repeatedly been criticized for not revealing the underlying raw data distribution. Remarkably, however, systematic and easy-to-use solutions for raw data visualization using the most commonly reported statistical software package for data analysis, IBM SPSS Statistics, are missing. Here, a comprehensive collection of more than 100 SPSS syntax files and an SPSS dataset template is presented and made freely available that allow the creation of transparent graphs for one-sample designs, for one- and two-factorial between-subject designs, for selected one- and two-factorial within-subject designs as well as for selected two-factorial mixed designs and, with some creativity, even beyond (e.g., three-factorial mixed-designs). Depending on graph type (e.g., pure dot plot, box plot, and line plot), raw data can be displayed along with standard measures of central tendency (arithmetic mean and median) and dispersion (95% CI and SD). The free-to-use syntax can also be modified to match with individual needs. A variety of example applications of syntax are illustrated in a tutorial-like fashion along with fictitious datasets accompanying this contribution. The syntax collection is hoped to provide researchers, students, teachers, and others working with SPSS a valuable tool to move towards more transparency in data visualization.

In order to request access to this data please complete the data request form.* * University of Bristol staff should use this form instead. The ASK feasibility trial: a randomised controlled feasibility trial and process evaluation of a complex multicomponent intervention to improve AccesS to living-donor Kidney transplantation This trial was a two-arm, parallel group, pragmatic, individually-randomised, controlled, feasibility trial, comparing usual care with a multicomponent intervention to increase access to living-donor kidney transplantation. The trial was based at two UK hospitals: a transplanting hospital and a non-transplanting referral hospital. 62 participants were recruited. 60 participants consented to data sharing, and their trial data is available here. 2 participants did not consent to data sharing and their data is not available. This project contains: 1. The ASK feasibility trial dataset 2. The trial questionnaire 3. An example consent form 4. Trial information sheet This dataset is part of a series: ASK feasibility trial documents: https://doi.org/10.5523/bris.1u5ooi0iqmb5c26zwim8l7e8rm The ASK feasibility trial: CONSORT documents: https://doi.org/10.5523/bris.2iq6jzfkl6e1x2j1qgfbd2kkbb The ASK feasibility trial: Wellcome Open Research CONSORT checklist: https://doi.org/10.5523/bris.1m3uhbdfdrykh27iij5xck41le The ASK feasibility trial: qualitative data: https://doi.org/10.5523/bris.1qm9yblprxuj2qh3o0a2yylgg

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...

Raw data supporting the Springer Nature Data Availability Statement (DAS) analysis in the State of Open Data 2024. SOOD_2024_special_analysis_DAS_SN.xlsx contains the DAS, DOI, publication date, DAS categories and related country by Insitution of any author.SOOD 2024_DAS_analysis_sharing.xlsx contains the summary data by country and data sharing type.Utilizing the Dimensions database, we identified articles containing key DAS identifiers such as “Data Availability Statement” or “Availability of Data and Materials” within their full text. Digital Object Identifiers (DOIs) of these articles were collected and matched against Springer Nature’s XML database to extract the DAS for each article. The extracted DAS were categorized into specific sharing types using text and data matching terms. For statements indicating that data are publicly available in a repository, we matched against a predefined list of repository identifiers, names, and URLs. The DAS were classified into the following categories:1. Data are available from the author on request. 2. Data are included in the manuscript or its supplementary material. 3. Some or all of the data are publicly available, for example in a repository.4. Figure source data are included with the manuscript. 5. Data availability is not applicable.6. Data are declared as not available by the author.7. Data available online but not in a repository.These categories are non-exclusive: more than one can apply to any one article. Publications outside the 2019–2023 range and non-article publication types (e.g., book chapters) that were initially included in the Dimensions search results were excluded from the final dataset. Articles were included in the final analysis after applying the exclusion criteria. Upon processing, it was found that only 370 results were returned for Botswana across the five-year period; due to this low number, Botswana was not included in the DAS focused country-level analysis. This analysis does not assess the accuracy of the DAS in the context of each individual article. There was no manual verification of the categories applied; as a result, terms used out of context could have led to misclassification. Approximately 5% of articles remained unclassified following text and data matching due to these limitations.

The main aim of this work was to explore how online training events, outside of traditional academic courses, can support Social Science, Arts and Humanities (SHAPE) students to develop data skills. There is international demand for data skills in the workplace, and Governments are increasingly concerned with how quantitative data skills are acquired for 21st Century jobs. If SHAPE students are trained in data skills they can enter into statistical professions and data careers. Online learning has risen significantly in the last decade, and even more so since the COVID-19 pandemic. Within the field of social research methods, online learning has grown rapidly and there is an emerging literature on the pedagogy. Data skills are vital for research and there is acknowledgement that online learning can play a role in data skills training. The data collection contains anonymised transcripts from 8 qualitative semi-structured individual interviews with SHAPE students who attended UK Data Service online training events. The interviews explored why the student had attended the UKDS event, what they learnt from it, how it has supported the development of data skills and how this will help their career. Ten students participated in the original study – we have consent from eight of ten the students to share their anonymised data in this repository. The studied population were SHAPE students (postgraduate and undergraduate) who had attended UKDS foundational-level online training events. A sampling frame of attendees at UKDS online training events was used. A purposive sample was then drawn using the following eligibility criteria: attendees at foundational level online events between May 2021-March 2022 who self-identified as students (undergraduates or postgraduates undertaking taught or research degrees) from SHAPE disciplines and who had consented to be contacted for further research. Those identifying as STEM students and/or who had only attended events with a more advanced methods focus were excluded. This resulted in a final sample of 67 students, each of which was sent a personalised email asking them if they would like to participate in the research. This resulted in a final achieved sample of 10 students (9 postgraduates and 1 undergraduate at the time they attended the training event). Participating students came from a range of SHAPE disciplines including political science, criminology, sociology, economics, social policy, health and finance. Each student had attended at least one UKDS online training event and they had collectively attended 10 events, with some attending more than one event. Semi-structured interviews were conducted with the 10 students in July 2022, using a flexible interview protocol. Each interview lasted 30-40 minutes and was conducted online using Microsoft Teams. Interviews were recorded and consent was obtained both in writing and verbally. The interview involved questions on the participant’s experience of the event(s), why they attended, what they had learnt, whether they were using what they had learnt and if it had influenced their future work. Eight out of the ten students who were interviewed agreed for their data to be shared in a data repository.

Title: Peer-to-peer dialogue about teachers’ written feedback enhances students’ understanding on how to improve writing skills. Short description of study set-up: Sixty-three second-year university students participated in a pre-test-post-test design with mixed methods. Instruments: Questionnaires: Students’ perceptions of the quality of both the written feedback in terms of Feed up, Feed back and Feed forward and the feedback dialogue were measured using an adjusted version of a validated questionnaire by De Kleijn et al. (2014). The questionnaire contained 16 items of which one item targeted the overall quality of teachers’ written feedback on a ten-point scale, ranging from 1 to 10. The remaining 15 items were distributed among three subscales, specifically ‘Feed up’ (four items), ‘Feed back’ (six items) and ‘Feed forward’ (five items), and rated on a five-point Likert-type scale, ranging from 1 (fully disagree) to 5 (fully agree). An example of a feed-up item is: ‘By means of the written feedback it is clear what the assessment criteria of a scientific report are’. An example of a feed-back item is: ‘The written feedback indicates what I do wrong’ and an example of a feed-forward item is: ‘The written feedback indicates how I can improve my report’. The questionnaire that was administered before and after the intervention comprised similar items. In the post-test questionnaire, a few items were added to measure how students perceived the quality of the feedback dialogue. A reliability analysis of the feed-up, feed-back and feed-forward subscales within pre- and post-test questionnaires yielded acceptable reliability coefficients ranging from 0.79 to 0.91 (Peterson 1994). Preliminary pilot-tests were conducted to determine item clarity and adjustments were made to unclear items. Additionally, the logistics of the intervention were tested during the pilot-test. Focus groups: To provide more in-depth data focus groups were conducted (Stalmeijer et al. 2014). At the end of the last feedback dialogue session of both tracks, each student was invited for a focus group session. Eventually, two focus groups comprised six students and lasted approximately one hour. The third focus group contained 12 students; it was a combined group of two times six students, because we unfortunately scheduled the meetings at the same time. To ensure each student’s voice to be heard, this focus group continued for one and a half hour. Each focus group was guided by a moderator (fourth author) and was observed by one member of the research team. In semi-structured interviews, the actual topics discussed in the focus groups covered student experiences regarding the content of the written teacher feedback as well as the added value of the peer-to-peer dialogue about this written feedback. The interviews were audiotaped. Explanation of data files: The data files contain 114 anonymized pdf’s of the original questionnaires filled in by the participants; Focus group interviews; audio files of focus groups; transcripts of focus groups; SPSS Data file Schillings-complete DA.sav. Quantitative data files: 114 Original questionnaires (pdf’s), archived as questionnaires in pdf.7zip 1 Data file Schillings-complete DA.sav (SPSS file) Total SPSS tabellen (Word document): meaning and ranges or codings of all columns Study 2 variabelen kwantitatieve vragenlijst (pdf) Quantitative data files: Focus groep interview-gids (Word document) 8 audio files of 3 focus groups (6 m4a files; 2 wav files), as audio focusgroepen a.7zip; Transcripts of 3 focus group (Word documents)

Abstract

This survey is the first detailed study on the phenomena of teacher absenteeism in Indonesia obtained from two unannounced visits to 147 sample schools in October 2002 and March 2003. The study was conducted by the SMERU Research Institute and the World Bank, affiliated with the Global Development Network (GDN). Similar surveys were carried out at the same time in seven other developing countries: Bangladesh, Ecuador, India, Papua New Guinea, Peru, Uganda, and Zambia.

This research focuses on primary school teacher absence rates and their relations to individual teacher characteristics, conditions of the community and its institutions, and the education policy at various levels of authority. A teacher was considered as absent if at the time of the visit the researcher could not find the sample teacher in the school.

This survey was conducted in randomly selected 10 districts/cities in four Indonesian regions: Java-Bali, Sumatera, Kalimantan-Sulawesi, and Nusa Tenggara.

Geographic coverage

Java-Bali, Sumatera, Kalimantan-Sulawesi and Nusa Tenggara regions

Analysis unit

• Teachers
• Schools

Kind of data

Sample survey data [ssd]

Sampling procedure

Information from Indonesian Statistics Agency (BPS) and the Ministry of Education was used as a basis to build a sample frame. The data gathered included the amount of total population, a list of villages and primary school facilities in each district/city. Due to limited time and resources, this research only focused on primary schools. In Indonesia, there are two types of primary education facilities: primary schools and primary madrasah. Primary schools are regulated by the Ministry of National Education, using the general curriculum, while primary madrasah are regulated by the Ministry of Religious Affairs, using a mixed (general and Islamic) curriculum.

A sample of districts/cities and schools (consisting of primary schools and primary madrasah) were selected using the following steps. First, Indonesia was divided into several regions based on the number of total population: Java-Bali, Sumatera, Kalimantan-Sulawesi, and Nusa Tenggara. Indonesian provinces that were suffering from various conflicts (such as Aceh, Central Sulawesi, Maluku, North Maluku, and Papua) were removed from the sample selection process. Then, from each region, a total of five districts and cities were randomly selected, taking into account the population of each district/city.

Second, 12 schools were selected in each district/city. Before choosing sampled schools, researchers randomly selected 10 villages in each district/city to be sampled, taking into account the location of these villages (in urban or rural areas). One of the 10 villages was a backup village to anticipate the possibility of a village that was too difficult to reach. In each village sampled, researchers asked residents about the location of primary schools/madrasah (both public and private) in these villages. They started visiting schools, giving priority to public primary schools/madrasahs. To meet the number of samples in each district/city, additional samples were selected from private schools.

Third, in each school sampled, the researcher would request a list of teachers. If a school visited was considered to be large, such as schools with more than 15 teachers, then the researcher would only interview 15 teachers chosen randomly to ensure that survey quality could be maintained despite the limited time and resources. Each school was visited twice, both on an unannounced date. From the 147 primary schools/madrasah in the sample, 1,441 teachers were selected in each visit (because this is a panel study, the teacher absence data that were used were taken only from teachers that could be interviewed or whose data were obtained from both visits). If there were teachers whose information was only obtained from one of the visits, then their data was not included in the dataset panel.

Mode of data collection

Face-to-face [f2f]

Research instrument

The following survey instruments are available:

• Teacher Questionnaire, First Visit
• Teacher Questionnaire, Second Visit.

Cleaning operations

Detailed information about data editing procedures is available in "Data Cleaning Guide for PETS/QSDS Surveys" in external resources.

The STATA cleaning do-file and the data quality report on the dataset can also be found in external resources.

This dataset includes all the data files that were used for the studies in my Master Thesis: "The Choice of Aspect in the Russian Modal Construction with prixodit'sja/prijtis'". The data files are numbered so that they are shown in the same order as they are presented in the thesis. They include the database and the code used for the statistical analysis. Their contents are described in the ReadMe files. The core of the work is a quantitative and empirical study on the choice of aspect by Russian native speakers in the modal construction prixodit’sja/prijtis’ + inf. The hypothesis is that in the modal construction prixodit’sja/prijtis’ + inf the aspect of the infinitive is not fully determined by grammatical context but, to some extent, open to construal. A preliminary analysis was carried out on data gathered from the Russian National Corpus (www.ruscorpora.ru). Four hundred and forty-seven examples with the verb prijtis' were annotated manually for several factors and a statistical test (CART) was run. Results demonstrated that no grammatical factor plays a big role in the use of one aspect rather than the other. Data for this study can be consulted in the files from 01 to 03 and include a ReadMe file, the database in .csv format and the code used for the statistical test. An experiment with native speakers was then carried out. A hundred and ten native speakers of Russian were surveyed and asked to evaluate the acceptability of the infinitive in examples with prixodit’sja/prijtis’ delat’/sdelat’ šag/vid/vybor. The survey presented seventeen examples from the Russian National Corpus that were submitted two times: the first time with the same aspect as in the original version, the second time with the other aspect. Participants had to evaluate each case by choosing among “Impossible”, “Acceptable” and “Excellent” ratings. They were also allowed to give their opinion about the difference between aspects in each example. A Logistic Regression with Mixed Effects was run on the answers. Data for this study can be consulted in the files from 04 to 010 and include a ReadMe file, the text and the answers of the questionnaire, the database in .csv, .txt and pdf formats and the code used for the statistical test. Results showed that prijtis’ often admits both aspects in the infinitive, while prixodit’sja is more restrictive and prefers imperfective. Overall, “Acceptable” and “Excellent” responses were higher than “Impossible” responses for both aspects, even when the aspect evaluated didn’t match with the original. Personal opinions showed that the choice of aspect often depends on the meaning the speaker wants to convey. Only in very few cases the grammatical context was considered to be a constraint on the choice.

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

Instruments: Questionnaires: Students’ perceptions of the quality of both the written feedback in terms of Feed up, Feed back and Feed forward and the feedback dialogue were measured using an adjusted version of a validated questionnaire by De Kleijn et al. (2014). The questionnaire contained 16 items of which one item targeted the overall quality of teachers’ written feedback on a ten-point scale, ranging from 1 to 10. The remaining 15 items were distributed among three subscales, specifically ‘Feed up’ (four items), ‘Feed back’ (six items) and ‘Feed forward’ (five items), and rated on a five-point Likert-type scale, ranging from 1 (fully disagree) to 5 (fully agree). An example of a feed-up item is: ‘By means of the written feedback it is clear what the assessment criteria of a scientific report are’. An example of a feed-back item is: ‘The written feedback indicates what I do wrong’ and an example of a feed-forward item is: ‘The written feedback indicates how I can improve my report’. The questionnaire that was administered before and after the intervention comprised similar items. In the post-test questionnaire, a few items were added to measure how students perceived the quality of the feedback dialogue. A reliability analysis of the feed-up, feed-back and feed-forward subscales within pre- and post-test questionnaires yielded acceptable reliability coefficients ranging from 0.79 to 0.91 (Peterson 1994). Preliminary pilot-tests were conducted to determine item clarity and adjustments were made to unclear items. Additionally, the logistics of the intervention were tested during the pilot-test. Focus groups: To provide more in-depth data focus groups were conducted (Stalmeijer et al. 2014). At the end of the last feedback dialogue session of both tracks, each student was invited for a focus group session. Eventually, two focus groups comprised six students and lasted approximately one hour. The third focus group contained 12 students; it was a combined group of two times six students, because we unfortunately scheduled the meetings at the same time. To ensure each student’s voice to be heard, this focus group continued for one and a half hour. Each focus group was guided by a moderator (fourth author) and was observed by one member of the research team. In semi-structured interviews, the actual topics discussed in the focus groups covered student experiences regarding the content of the written teacher feedback as well as the added value of the peer-to-peer dialogue about this written feedback. The interviews were audiotaped. Explanation of data files: The data files contain 114 anonymized pdf’s of the original questionnaires filled in by the participants; Focus group interviews; audio files of focus groups; transcripts of focus groups; SPSS Data file Schillings-complete DA.sav. Quantitative data files: 114 Original questionnaires (pdf’s), archived as questionnaires in pdf.7zip 1 Data file Schillings-complete DA.sav (SPSS file)

Quantitative data in the database for Example 1.

The National Child Development Study (NCDS) is a continuing longitudinal study that seeks to follow the lives of all those living in Great Britain who were born in one particular week in 1958. The aim of the study is to improve understanding of the factors affecting human development over the whole lifespan.

The NCDS has its origins in the Perinatal Mortality Survey (PMS) (the original PMS study is held at the UK Data Archive under SN 2137). This study was sponsored by the National Birthday Trust Fund and designed to examine the social and obstetric factors associated with stillbirth and death in early infancy among the 17,000 children born in England, Scotland and Wales in that one week. Selected data from the PMS form NCDS sweep 0, held alongside NCDS sweeps 1-3, under SN 5565.

Survey and Biomeasures Data (GN 33004):
To date there have been ten attempts to trace all members of the birth cohort in order to monitor their physical, educational and social development. The first three sweeps were carried out by the National Children's Bureau, in 1965, when respondents were aged 7, in 1969, aged 11, and in 1974, aged 16 (these sweeps form NCDS1-3, held together with NCDS0 under SN 5565). The fourth sweep, also carried out by the National Children's Bureau, was conducted in 1981, when respondents were aged 23 (held under SN 5566). In 1985 the NCDS moved to the Social Statistics Research Unit (SSRU) - now known as the Centre for Longitudinal Studies (CLS). The fifth sweep was carried out in 1991, when respondents were aged 33 (held under SN 5567). For the sixth sweep, conducted in 1999-2000, when respondents were aged 42 (NCDS6, held under SN 5578), fieldwork was combined with the 1999-2000 wave of the 1970 Birth Cohort Study (BCS70), which was also conducted by CLS (and held under GN 33229). The seventh sweep was conducted in 2004-2005 when the respondents were aged 46 (held under SN 5579), the eighth sweep was conducted in 2008-2009 when respondents were aged 50 (held under SN 6137), the ninth sweep was conducted in 2013 when respondents were aged 55 (held under SN 7669), and the tenth sweep was conducted in 2020-24 when the respondents were aged 60-64 (held under SN 9412).

A Secure Access version of the NCDS is available under SN 9413, containing detailed sensitive variables not available under Safeguarded access (currently only sweep 10 data). Variables include uncommon health conditions (including age at diagnosis), full employment codes and income/finance details, and specific life circumstances (e.g. pregnancy details, year/age of emigration from GB).

Four separate datasets covering responses to NCDS over all sweeps are available. National Child Development Deaths Dataset: Special Licence Access (SN 7717) covers deaths; National Child Development Study Response and Outcomes Dataset (SN 5560) covers all other responses and outcomes; National Child Development Study: Partnership Histories (SN 6940) includes data on live-in relationships; and National Child Development Study: Activity Histories (SN 6942) covers work and non-work activities. Users are advised to order these studies alongside the other waves of NCDS.

From 2002-2004, a Biomedical Survey was completed and is available under End User Licence (EUL) (SN 8731) and Special Licence (SL) (SN 5594). Proteomics analyses of blood samples are available under SL SN 9254.

Linked Geographical Data (GN 33497):
A number of geographical variables are available, under more restrictive access conditions, which can be linked to the NCDS EUL and SL access studies.

Linked Administrative Data (GN 33396):
A number of linked administrative datasets are available, under more restrictive access conditions, which can be linked to the NCDS EUL and SL access studies. These include a Deaths dataset (SN 7717) available under SL and the Linked Health Administrative Datasets (SN 8697) available under Secure Access.

Multi-omics Data and Risk Scores Data (GN 33592)
Proteomics analyses were run on the blood samples collected from NCDS participants in 2002-2004 and are available under SL SN 9254. Metabolomics analyses were conducted on respondents of sweep 10 and are available under SL SN 9411.

Additional Sub-Studies (GN 33562):
In addition to the main NCDS sweeps, further studies have also been conducted on a range of subjects such as parent migration, unemployment, behavioural studies and respondent essays. The full list of NCDS studies available from the UK Data Service can be found on the NCDS series access data webpage.

How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:
For information on how to access biomedical data from NCDS that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.

Further information about the full NCDS series can be found on the Centre for Longitudinal Studies website.

The Social Participation and Identity project combined quantitative longitudinal data with a qualitative investigation of a sub-sample of the NCDS cohort when they were aged 50, presented here as a mixed-methods data collection containing both qualitative and quantitative data. This was the first attempt to interview members of a national, longitudinal cohort study in depth, with the possibility of linking such biographical narratives to structured survey data collected throughout the life course. Interviews were conducted with a sub-sample of 220 NCDS cohort members resident in Great Britain (England, Scotland and Wales). The interviews were organised into six main sections focussing on: 1) Neighbourhood and belonging; 2) Leisure activities and social participation; 3) Personal communities; 4) Life histories; 5) Identity; 6) Reflections on being part of the NCDS.

Further information:

• details of the qualitative NCDS project (and the rest of the NCDS series) can be found on the Centre for Longitudinal Studies website and Social Participation and Identity ESRC award webpage.
• A list of the UK Data Archive's NCDS holdings, both quantitative and qualitative, can be found on the NCDS key data page.

For the first and second editions of the study (2011 and 2012), the interview transcripts, interviewer observation summaries, gender identity diagrams and life trajectory diagrams for all participants were made available. For the third edition (July 2013), 179 essays collected from the subproject participants at the time of the NCDS2 wave (conducted 1969) were added to the study. See documentation for further details. (Users should note that an additional sample of transcribed essays from a wider set of NCDS2 participants is available from the Archive under SN 8313.)

The goal of this research is the investigation of potentials and limits of UV-VIS-NIR Hyperspectral Imaging (HSI) and Multispectral Imaging (MSI) for the non-destructive quantitative monitoring of spectral changes that occurs in historical papers and writing media during exhibitions at the Rijksmuseum. Four spectral imaging instruments in Europe have been tested using the same set of samples collected from original discarded papers of the Rijksmuseum and reference targets. The samples include: an historical blue paper, a light sensitive pastel, papers with foxing and metal intrusions, a sanguine (red chalk) and the Blue Wool Standard grade 1. Data presented here is part of the research and is the Multispectral imaging data captured using the Multispectral imaging system of the Centre for the Study of Manuscript Cultures in Hamburg. Imaging was performed on 07-08.12.2016 The research for project Z01 was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) within the Sonderforschungsbereich 950 (SFB 950). The research was conducted within the scope of the Centre for the Study of Manuscript Cultures (CSMC) at Universität Hamburg, in collaboration with the Migelien Gerritzen Fund/Rijksmuseum Fund. {"references": ["https://de.slideshare.net/rijksmuseum/23d-photography-2017-p-3-quantitative-monitoring-of-works-of-art-on-paper-with-spectral-imaging-roberto-padoan"]}

Biology students’ understanding of statistics is incomplete due to poor integration of these two disciplines. In some cases, students fail to learn statistics at the undergraduate level due to poor student interest and cursory teaching of concepts, highlighting a need for new and unique approaches to the teaching of statistics in the undergraduate biology curriculum. The most effective method of teaching statistics is to provide opportunities for students to apply concepts, not just learn facts. Opportunities to learn statistics also need to be prevalent throughout a student’s education to reinforce learning. The purpose of developing and implementing curriculum that integrates a topic in biology with an emphasis on statistical analysis was to improve students’ quantitative thinking skills. Our lesson focuses on the change in the richness of native species for a specified area with the aid of iNaturalist and the capacity for analysis afforded by Google Sheets. We emphasized the skills of data entry, storage, organization, curation and analysis. Students then had to report their findings, as well as discuss biases and other confounding factors. Pre- and post-lesson assessment revealed students’ quantitative thinking skills, as measured by a paired-samples t test, improved. At the end of the lesson, students had an increased understanding of basic statistical concepts, such as bias in research and making data-based claims, within the framework of biology.

Primary Image: Website screenshot of an iNaturalist observation (Clasping Milkweed – Asclepias amplexicalis). This image is an example of a data entry on iNaturalist. The data students export from iNaturalist is made up of hundreds, or even thousands, of observations like this one. This image is licensed under Creative Commons Attribution - Share Alike 4.0 International license. Source: Observation by cassi saari, 2014.

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.