From 2018 to 2022, around ** percent of internet users surveyed in Brazil said they have used the internet to search for information about university studies, including college degrees, master's degrees, and PhD. Around ** percent of female internet users surveyed stated that they used the web to attend online courses.

This is the PhD raw data for the pilot study Prostate Cancer Health and Fitness Online. This contains ID codes for the participants who participated in an online computer tailored intervention, baseline, online behavioural data and the post intervention data outcome data.

This data was collected and analysed as part of a PhD thesis submitted in February 2019. The PhD research was concerned with understanding the role of Ministry of Information images in British cultural memory and, through the use of surveys, interviews and reverse image lookup, investigated how the images were remembered, interpreted and used online. The data consists of six files. The first includes demographic details of participants who took part in a Mass Observation survey in 2009. The second consists off the results of a content analysis of the responses of participants in the 2009 survey. The third consists of data collected as part of a survey with volunteers which took place between March and May 2017 and the fourth consists of the results of a content analysis of the survey data. The fifth file includes data collected through a study using reverse image lookup to locate and categorise web pages containing a particular set of Ministry of Information images and the sixth consists of a the results of a content analysis of this data.

The Survey of Doctorate Recipients (SDR) is a dataset created by the National Center for Science and Engineering Statistics (NCSES) under the U.S. National Science Foundation (NSF). It provides comprehensive data on individuals who earned research doctorates in science, engineering, or health (SEH) fields from U.S. academic institutions. The survey captures demographic information, educational background, career trajectories, employment status, and work experiences of doctorate holders, both within the U.S. and abroad. Its primary purpose is to inform policy and research on the SEH workforce, offering insights into career patterns, labor market dynamics, and the long-term impacts of doctoral education. Key features include its representative sampling of doctorate recipients (including those retired or seeking work), expanded coverage of specialized fields, and an online format to enhance data quality and participation. Unique aspects include integrated data on international and domestic recipients, enabling analysis of global career trends. The SDR is widely used by researchers, policymakers, and institutions to track workforce development, assess the return on investment in higher education, and shape STEM (science, technology, engineering, and mathematics) initiatives. Regular updates ensure relevance to evolving scientific and economic landscapes.

Study 2 (Chapter 3 in dissertation): Granularity matters: Comparing different ways of measuring self-regulated learning. This study concerned a narrative review comparing offline self-report questionnaires with online (behavioral) measures of student self-regulated learning, focusing on the degree of overlap between these two forms of measurement.

Data was collected for a PhD research project. The project investigated factors related to academic help-seeking behaviour in higher education using quantitative and qualitative methods. Quantitative data was collected via an online survey. Qualitative data was collected via semi-structured interviews. These were conducted via video calls.

It was found that reducing stigma, increasing positive attitudes and subjective norm, ensuring satisfaction, and providing timely and targeted promotion increase engagement with academic support. Universities can use these findings to improve academic support and ultimately student success.

The data methods are available in the Open Access publications from the Related publications link below.

The de-identified quantitative dataset is stored as an SPSS file (.sav). The SPSS files have also been exported in MS Excel (.xlxs) and CSV formats with the value labels. These files are available via conditional access i.e. negotiation with the Data Manager. The SPSS variable information and labels (codebook) are saved as a PDF file and can be downloaded and viewed (for context) via the link below.

The interview recordings (.m4a) and transcripts (MS Word and PDF), SPSS Amos files (.amw) and Nvivo project (.nvp) have been archived in secure storage. Access to these files is restricted.

Software/equipment used to create/collect the data: Qualtrics, Zoom

Software/equipment used to manipulate/analyse the data: SPSS, SPSS Amos, NVivo

This research aims to develop a principle-based framework for audit analytics implementation, which addresses the challenges of AA implementation and acknowledges its socio-technical complexities and interdependencies among challenges. This research relies on mixed methods to capture the phenomena from the research’s participants through various approaches, i.e., MICMAC-ISM, case study, and interview with practitioners, with literature exploration as the starting point. The raw data collected consists of multimedia data (audio and video recordings of interviews and focused group discussion), which is then transformed into a text file (transcript), complemented with a softcopy of the documents from the case study object.

The published data in this dataset, consists of the summarized or analyzed data, as the raw data (including transcript) is not allowed to be published according to the decision by the Human Research Ethics Committee pertinent to this research (Approval #1979, 14 February 2022). This dataset's published data are text files representing the summarized/analyzed raw data as an online appendices to the thesis.

Study Title Design, implementation and evaluation of a postgraduate workshop on cross-border healthcare in Europe – Mixed methods research. Study Description The main research question of this study was: ‘How does the workshop entitled “Creating Cross-border Collaborators” with elements of contextual, collaborative and reflective learning enhance trainees’ awareness of the challenges and opportunities of cross-border healthcare?’ Data were collected by means of surveys and focus-group interviews. The respective data collection instruments were iteratively constructed by four authors (JB, DV, MB and DD). The purpose of the survey was to get an overall impression of how participants experienced the workshop and of how the learning principles enhanced or hindered their learning, learning outcomes and the relation between them. The purpose of the focus-group interviews was to gain insight into participants’ perceptions of the workshop design. The workshop was held three times, twice in June and once in November 2020. Participants received information about the evaluation survey and interview at registration. Two weeks prior to the online session, participants received the preparatory assignment and a letter informing them about the research procedure. Before the online session took place, they were also asked to give informed consent. Directly after this online session, one of the trainers (DV) conducted the focus-group interviews. The focus-group interviews took approximately fifteen minutes and were audio-recorded and transcribed non-verbatim by the first author (JB). The surveys were conducted directly after the reflection assignment, one to threeweeks after the online session. Surveys were conducted using a licensed online survey tool (Qualtrics). The main conclusion was that, according to participating trainees, a workshop with elements of contextual, collaborative and reflective learning did improve trainee awareness of cross-border healthcare. This study highlights the fact that theoretical insights into learning can and should inform the design and evaluation of workshops. Description of Data Type: Survey responses and non-verbatim transcribed semi-structured focus-groups. Participants: Trainees in a European border region, participating in a workshop (N=16). Language: English and Dutch.

The dataset was produced for a scientometric study on French PhD theses in the field of sustainable development, presented at the Twenty-Fifth International Conference on Grey Literature "Confronting Climate Change with Trusted Grey Resources", OBA Congres, November 13-14, 2023, Oosterdokskade, Amsterdam, The Netherlands. We reused a dataset with metadata of 431,997 theses ("Thèses soutenues en France depuis 1985") produced by ABES and available as public open data at the following address: https://www.data.gouv.fr/fr/datasets/theses-soutenues-en-france-depuis-1985/ The ABES dataset was downloaded in csv format on August 16, 2023. Our dataset is a subsample of the ABES dataset; it contains 3,467 theses which represent 0.8% of the total number of theses in the ABES file. The purpose of the study is to assess the French PhD theses on sustainable development, with two objectives: to give a scientometric overview on the French PhD landscape in the field of sustainable development; and to show how PhD theses (as a major part of grey literature) and related tools can be helpful for the scientometric study of science. The review is based on data from the French national portal theses.fr. The results of our study provide a detailed review of the French PhD research on sustainable development from 1985 to 2022, including the main French research universities in the field of sustainable development and the most eminent academic scholars, the disciplinary distribution of the research on sustainable development, and the accessibility of the PhD theses on sustainable development (open science). The analysis of the year of defense will allow a longitudinal approach to these aspects. The dataset contains personal data from theses.fr This is the personal data notice of ABES regarding theses.fr https://www.theses.fr/donnees_personnelles « theses.fr, which includes personal information concerning in particular doctors, thesis directors and members of the defense jury, has been the subject of a normal declaration to the CNIL No. 1537454 v0. In accordance with the European General Data Protection Regulation (GDPR), you have the right to access, rectify and delete data concerning you, online on this site. To exercise this right, you can contact the ABES help desk. »

Directory of Files: A. Filename: Combine_CCTDI.zip
Short description: Quantitative Data. The zip files contain 6 Excel files which store students' raw data. This raw data set consists of student's input on each CCTDI item. The pre-data were collected through an online survey, while post-data were collected through pen and paper. The data will be analysed by ANOVA to compare the effectiveness of the intervention. (California Critical Thinking Disposition Inventory (CCTDI) has been widely employed in the field of education to investigate the changes in students’ Critical Thinking (CT) attitudes resulting from teaching interventions by comparing the pre- and post-tests. This 6-point scale self-reporting instrument requires respondents to rate themselves, ranging from “rating 1” for not describing them at all to “rating 6” for extremely well. The instrument has 40 questions categorized in seven subsets covering various CT dispositions dimensions, namely: i) truth-seeking, ii) open-mindedness, iii) analyticity, iv) systematicity, v) inquisitiveness, vi) maturity, and vii) self-confidence.

B. Filename: Combine_TCTSPS.zip
Short description: Quantitative Data. The zip files contains 6 excel files which stores students' raw data. consists of student's input on each TCTSPS item. The pre-data were collected through an online survey, while post-data were collected through pen and paper. The data will be analysed by ANOVA to compare the effectiveness of the intervention. (Test of Critical Thinking Skills for Primary and Secondary School Students (TCTS-PS) consists of 24 items divided into five subscales measuring distinct yet correlated aspects of CT skills, namely: (I) differentiating theory from assumptions, (II) deciding evidence, (III) inference, (IV) finding an alternative theory, and (V) evaluation of arguments. The instrument yields a possible total score of 72. The instrument is intended for use in measuring gains in CT skills resulting from instruction, predicting success in programs where CT is crucial, and examining relationships between CT skills and other abilities or traits.)

C. Filename: Combine_SMTSL.zip
Short description: Quantitative Data. The zip files contains 5 excel files which stores students' raw data. consists of student's input on each SMTSL item. The pre-data were collected through an online survey, while post-data were collected through pen and paper. The data will be analysed by ANOVA to compare the effectiveness of the intervention. (Students' Motivation Towards Science learning (SMTSL) defined six factors that related to the motivation in science learning including self-efficacy, active learning strategies and so on, in order to measure participants' motivation towards science learning: A. Self-efficacy, B. Active learning , trategies, C. Science learning value, D. Performance goal, E. Achievement goal, and F. Learning environment stimulation)

D. Filename: Combine_Discourse Transcription_1.zip and Combine_Discourse Transcription_2.zip
Short description: Qualitative Data.The zip files contains 6 excel files which 6 teachers' classroom teaching discourse transcriptions. The data will be analysed by thematic analysis to compare the effectiveness of the intervention. (38 science classroom discourse videos of 8th graders were transcribed and coded by Academically Productive Talk framework (APT). APT is drawing from sociological, linguistic, and anthropological perspectives, comprises four primary constructs or objectives.)

E. Filename: Combine_Inquiry Report.zip
Short description: Qualitative Data. The zip files contains 2 excel files which 2 schools' inquiry report scores according rubrics. The data will be analysed by thematic analysis to compare the effectiveness of the intervention. (To assess the quality of students' arguments, a validated scoring rubric was employed to evaluate the student's written argument. These aspects primarily concentrated on the student's proficiency in five perspectives (Walker & Sampson, 2013, p. 573): (AR1) Provide a well-articulated, adequate, and accurate claim that answers the research question, (AR2) Use genuine evidence to support the claim and to present the evidence in an appropriate manner, (AR3) Provide enough valid and reliable evidence to support the claim, (AR4) Provide a rationale is sufficient and appropriate, and (AR5) Compare his or her findings with other groups in the project.)

F. Filename: Combined_Interview Transcription.xlsx
Short description: Qualitative Data. The file contains all the students' interview transcriptions. The data will be analysed by thematic analysis to compare the effectiveness of the intervention. (A semi-structured interviews was conducted to gather interviewees' motivation of CT and learning motivation in the context of science. The interview data would be used to complement the quantitative results (i.e., TCTS-PS, CCTDI, and SMTSL scores).

TitleChapter 4. Achieving ‘something that everybody has invested in’: Perspectives of diverse stakeholders during co-creation of a transition to residency curriculum. Summary In chapter 4, we sought to understand the co-creation process in this setting which includes diverse groups of faculty and students. We did this by examining the viewpoints of the various stakeholders and the learners who participated in developing a transition to a residency curriculum. The two research questions that guided this study were: How did the learners and diverse stakeholders who were involved in co-creating the curriculum for the transition perceive the co-creation process? What are the power dynamics that occur in the presence of students with diverse stakeholders, and what measures can be taken to mitigate them? We conducted post‑hoc in‑depth interviews with the stakeholders involved in the co-creation sessions and incorporated the findings to build on the Framework of Stakeholders’ Involvement in Co‑creation. Description of the attached file The attached file provides data that was collected from the one hour-long semi-structured online interviews with 16 participants who were involved in the co-creation sessions. These interviews began with an open question such as “Describe your experience with CC”, and the subsequent answers were then explored with more specific questions. Questions for students included: “Did you feel comfortable contributing?”, “Did you feel valued and listened to?”, “How did your contribution add value to the curriculum?”. Faculty were asked to describe their experience with CC and their thoughts on student input. All interviews were recorded and transcribed. All participants verified and agreed on the one-page summary of their interview transcript (member check). All responses were pseudonymized by coding participants’ names and de-identifying all quotes.

Online questionnaire to PhD candidates, Interview guide PhD students, Participant information sheet, Consent form

This is the Repository of all the research data for PhD Thesis of the doctoral candidate Nan BAI from the Faculty Architecture and Built Environment at Delft University of Technology, with the title of '*Sensing the Cultural Significance with AI for Social Inclusion: A Computational Spatiotemporal Network-based Framework of Heritage Knowledge Documentation using User-Generated*', to be defended on October 5th, 2023.

Social Inclusion has been growing as a goal in heritage management. Whereas the 2011 UNESCO Recommendation on the Historic Urban Landscape (HUL) called for tools of knowledge documentation, social media already functions as a platform for online communities to actively involve themselves in heritage-related discussions. Such discussions happen both in “baseline scenarios” when people calmly share their experiences about the cities they live in or travel to, and in “activated scenarios” when radical events trigger their emotions. To organize, process, and analyse the massive unstructured multi-modal (mainly images and texts) user-generated data from social media efficiently and systematically, Artificial Intelligence (AI) is shown to be indispensable. This thesis explores the use of AI in a methodological framework to include the contribution of a larger and more diverse group of participants with user-generated data. It is an interdisciplinary study integrating methods and knowledge from heritage studies, computer science, social sciences, network science, and spatial analysis. AI models were applied, nurtured, and tested, helping to analyse the massive information content to derive the knowledge of cultural significance perceived by online communities. The framework was tested in case study cities including Venice, Paris, Suzhou, Amsterdam, and Rome for the baseline and/or activated scenarios. The AI-based methodological framework proposed in this thesis is shown to be able to collect information in cities and map the knowledge of the communities about cultural significance, fulfilling the expectation and requirement of HUL, useful and informative for future socially inclusive heritage management processes.

Some parts of this data are published as GitHub repositories:

WHOSe Heritage

The data of Chapter_3_Lexicon is published as https://github.com/zzbn12345/WHOSe_Heritage, which is also the Code for the Paper WHOSe Heritage: Classification of UNESCO World Heritage Statements of “Outstanding Universal Value” Documents with Soft Labels published in Findings of EMNLP 2021 (https://aclanthology.org/2021.findings-emnlp.34/).

Heri Graphs

The data of Chapter_4_Datasets is published as https://github.com/zzbn12345/Heri_Graphs, which is also the Code and Dataset for the Paper Heri-Graphs: A Dataset Creation Framework for Multi-modal Machine Learning on Graphs of Heritage Values and Attributes with Social Media published in ISPRS International Journal of Geo-Information showing the collection, preprocessing, and rearrangement of data related to Heritage values and attributes in three cities that have canal-related UNESCO World Heritage properties: Venice, Suzhou, and Amsterdam.

Stones Venice

The data of Chapter_5_Mapping is published as https://github.com/zzbn12345/Stones_Venice, which is also the Code and Dataset for the Paper Screening the stones of Venice: Mapping social perceptions of cultural significance through graph-based semi-supervised classification published in ISPRS Journal of Photogrammetry and Remote Sensing showing the mapping of cultural significance in the city of Venice.

Data and analysis software to reproduce the main results discussed in Chapter 3 about the realization of a non-local CNOT gate between remote nodes. The data are organized in .npz files which are loaded, analyzed and plotted in the corresponding .ipynb files.

TitleChapter 3. Sailing the boat together: Co-creation of a model for learning during transition Summary In chapter 3, we have addressed the challenging periods of transition in medical education and highlighted the value of co-creating a transition to residency curriculum by engaging students in transition with diverse stakeholders from undergraduate and graduate medical education. We focused on answering the research question: What is the added value of involving stakeholders across the transition spectrum in co-creating a transition curriculum, and what are the components of this curriculum? Students in transition were involved in co-creating their final year curriculum with college and clinical faculty and chief residents. During eight online co-creation sessions, participants from all the stakeholder groups worked in small groups to define requirements and strategies for helping students transition to graduate medical education training. The discussions were guided by the 4S system of Schlossberg’s Transition Theory, where ‘situation’ refers to how the transition is perceived by the trainees; ‘self’ is about personal resources needed for transition; ‘support,’ signifies the support needed for transition, and finally, ‘strategies’ describe desirable approaches that can facilitate students’ transition. Thematic analysis for transcripts of these eight co-creation sessions was conducted, and the results were used to draft a quantitative survey sent to those who did not participate in the sessions. Mean scores with standard deviations were used for survey analysis. This was followed by two online consensus-building co-creation sessions with the original participants. During these sessions, the participants reviewed the survey results and reached a consensus on the support and strategies required. The transcripts of these two final sessions were then thematically analyzed to adjust and finalize the coding scheme. The insights that emerged from this collaborative process led to the identification of five themes that make up the Model of Learning during Transition (MOLT). This model consists of five pillars: adaptation, authenticity, autonomy, connectedness, and continuity, all of which are rooted in the idea of creating a supportive environment. For students to learn effectively during the transition, they need to adapt to the new learning environment, which involves authentic learning experiences. They need increased responsibility and opportunities to shadow professionals, allowing for maximum autonomy. Students need to feel connected and integrated within health professional teams. Furthermore, students benefit from continuity in learning, with a focus on spiral learning and integration within health professional teams. All these five pillars are integral to a supportive environment that includes various support-rich resources. These include college leaders, postgraduate educators, residents, and peers who provide support through supervision, feedback, and psychological and career counseling together with mentoring, as well as engaging students in study groups and in educational activities. Description of the attached file The attached file includes: 1) The qualitative data analysis of the 10 co-creation sessions. 2) The quantitative data analysis of the survey.

This archive includes the research data and code of the PhD dissertation "Small Scales, Vast Ocean: Submesoscale Ocean Topography with Bistatic Synthetic-aperture Radar Interferometry". It is split into three folders, one for each of the main chapters of the dissertation. The WSOA and data-driven phase sync chapters require a Conda environment, for which the environment.yml file should be used. The code of these chapters requires data that relate to the performance of the Harmony satellite, which are proprietary. Hence, they are omitted. Please contact us if you need assistance in setting up the simulations.

The code of the Spectral View of Sensitivity chapter is written in Julia and is provided in the form of a reproducible Code Ocean capsule. This is an export of the online version of the capsule available here.

Title Exploring Perceptions and Practices of Interprofessional Shared Decision-Making Education in Palliative Care Settings Summary Introduction Palliative care teams provide support to patients and their caregivers during terminal illness, which requires inter- professional collaboration. One of the foundational skills is to assist patients with decision-making. This can be facilitated through interprofessional shared decision-making (IP-SDM). So far, IP-SDM education frameworks have only been used to a limited extent in the area of palliative care. AimThis study aims to explore perceptions and practices of faculty members, health professionals, and students toward IP-SDM education in palliative care and to indicate associated factors to implement an IP-SDM in undergraduate health professions education in palliative care settings. Methods We used a cross-sectional study design in which the data was obtained via an online self-administered questionnaire adapted from existing validated tools. The questionnaire was distributed to faculty members and health professionals (n = 125) and students (n = 334) at King Abdulaziz Medical City in Jeddah, Saudi Arabia. The sampling technique was a non-probability convenience sampling. Bivariate statistics, such as independent sample t-tests, one-way ANOVA, correlation coefficient, and linear multiple regression were conducted. Results The response rate was 54% (85 faculty members and health professionals and 164 students). Perceptions on IP-SDM did not differ between participants. From those who had previous experience with IP-SDM, the mean practices score was slightly higher for faculty members and health professionals (M = 83.1, SD = 15.9) than for students (M = 74.1, SD = 11.5), which was significant (p < 0.05). Factors such as gender, age, discipline, nationality, level of education, years of study, and previous experience that were associated with perceptions and practices were varied among participants. Conclusions The findings show high levels of perceptionss with low levels of practices of IP-SDM in palliative care. Other factors that could be associated with the topic should be addressed in further studies.

Abstract

High quality postgraduate training in science, technology, engineering and mathematics (STEM) related disciplines in sub-Saharan Africa (SSA) is important to strengthen research evidence to advance development and ensure countries achieve the Sustainable Development Goals (SDGs). Equally, participation of women in STEM careers is vital, to ensure that countries develop economies that work for all their citizens. However, women and girls remain underrepresented in STEM due to gender stereotyping, lack of visible role models, and unsupportive policies and work environments. Therefore, there is a need to consolidate information on participation and experiences of women in STEM related postgraduate training and careers in SSA to enhance their contribution to realizing the SDGs. The primary objective of this study is to examine the participation and experiences of women in postgraduate training, and their subsequent recruitment, retention and progression in STEM careers in East Africa. A secondary objective is to establish the gender gaps in training and career engagement in selected STEM related academic disciplines in East Africa. The descriptive study will employ a mixed methods approach, including a scoping review, qualitative interviews, and quantitative analysis of secondary data. We will synthesize results to inform the development of an effective gendered approach and framework to improve participation and experiences of women in STEM training and career engagements in SSA. We will conduct the study over a period of five years.

Geographic coverage

Regional coverage (East Africa Region)

Analysis unit

Individual Women in STEM

Universe

Qualitative data: Women in Science Technology Engineering and Mathematics (STEM) in postgraduate training and career Quantitative data: Postgraduate students, faculty, reseachers and supervisors (both men and women) in STEM in Inter-University Council for East Africa (IUCEA) member Universitiies

Sampling procedure

The study utilized a purposive sampling technique and targeted all universities that offered doctoral programs in applied sciences, technology, engineering, and mathematics. At the time, only 23 of the 74 universities in Kenya—equivalent to 30%—offered doctoral degrees in STEM. It was assumed that a similar or lower percentage would be found in the other five countries, namely Uganda, Tanzania, Rwanda, Burundi, and South Sudan.

Purposive sampling was used to recruit participants from purposively selected universities and national higher education commissions and agencies for the study. In universities, all students enrolled in doctoral programs in STEM were considered. Additionally, female and male students' lecturers, supervisors, mentors, and other faculty members and researchers in the identified institutions were also considered for participation in the study.

Purposive sampling of doctoral students, faculty, and early career researchers (post-doctoral fellows within the first six years since receiving their PhD) was conducted using the following inclusion criteria:

Inclusion criteria i. Worked in a STEM field/discipline ii. Enrolled in a doctoral program within a STEM field iii. Early career researchers in a STEM field in research organizations iv. Faculty in a STEM field at a university

Additionally, registrars, postgraduate training coordinators, heads of departments, and officials from national agencies and ministries related to postgraduate training and research were purposively selected from all the identified universities to provide input on existing policies, guidelines, and enrollment data. For each of the mentioned groups, 7-12 interviews were conducted, totaling 60 interviews.

Sampling deviation

Qualitative For the Key informant interviews one participant was interviewed from the engineers board despite the scope being Inter-University Council for East Africa (IUCEA) member Universities.

Quantitative The online survey was completed by some researchers not working/teaching in IUCEA member universities

Mode of data collection

Other [oth]

Research instrument

Quantitative data collection A. Online Survey This was carried out through an online survey questionnaire that was circulated via email and other digital platforms such as WhatsApp. The questionnaire had various parts: Part A - Participants characteristics This section mainly collected demographic details such as age, gender, nationality, residence, marital status, income, highest level of education completed, year of study, supervision and mentoship relationship, field of study in STEM (Science, Technology, Enginnering and Mathematics), mode of funding of postgraduate degree,

Part B - Status of Gender equality This section collected information on students enrollment and graduation in masters and PhD in STEM looking at gender distribution,

Part C - Factors that contribute to participation of women in STEM This section collected information on the factors or situations encountered while pursuing career in STEM in your specific discipline

Part D - Strategies for Optimizing Women's Engagement in STEM This section collected information on the strategies can maximize engagement of women in STEM training PhD level and subsequent careers

Part E - Effect of the COVID-19 pandemic on women's progression In this section collected information on COVID-19 pandemic affect on research progress or deadline for submission of thesis, COVID-19 pandemic affect on current research funding, COVID-19 pandemic caused researchers to work from home, working from affected progress in studies, any direct responsibilities caring for children, number of children being taken care of, change of domestic work responsibilities since the COVID-19 outbreak, change of domestic work responsibilities since the COVID-19 outbreak on studies, COVID-19 pandemic affect on access to these research tools which inlude: Computer or laptop, Reliable Internet, Assistive Technology, Laboratory equipment, University Library, Archives/special collections and Access to patients/research participants. It als collected information on: any benefits to COVID-19 pandemic for your work, some ways one thinks their supervisor or line manager could support or help one manage the impacts of COVID-19 on studies

The questionnaire was developed in English and was latertranslated into French to accommodate the French speaking countries i.e Burundi and Rwanda. The French questionnaire was backtlanslated to English to ensure the questions still maintained their original meaning. This work was done by an external consultant and the French questionnaires were reviewed by the research assistant from Burundi and tested among postgraduate students in Light University.

All questionnares and modules are provided as external resources.

Cleaning operations

Qualitative The data was collected through qualitative interviews (In-depth interviews) and focus group discussions. They were audio recorded and the recordings were transcribed on Ms Ofiice.The transcript were subjected to data quality checks and the clean transcripts were anonyzed for data protection.

QUANTITATIVE Secondary data The data was collected from the five countries in an Ms Excel designed data abstraction sheet. The data abstraction sheet helped the universities administrators and rergistrars to directly enter the data only in the required field and for the defined or specific variables. For the dataset that was in hardcopy format the data entry was also done using the data abstraction sheets. The data sets were subjected to data quality checks for data quality. We used a standard template to ensure data editing took place during data entry.

Online survey Data entry was in form of responding to the survey. Data editing was done while cleaning the data.

Response rate

Quantitaive The online survey link was circulated using contacts within universities and research institutions in East Africa via email and social media platforms such as WhatApp hence it is impossible to track those who received the survey and hence it is not possible t calculate the survey response rate.

Sampling error estimates

NA

This data file, compiled from multiple online sources, presents 2013–2017 publication counts—articles, articles in high-impact journals, books, and books from high-impact publishers—for 2,132 professors and associate professors in 426 U.S. departments of sociology. It also includes information on institutional characteristics (e.g., institution type, highest sociology degree offered, department size) and individual characteristics (e.g., academic rank, gender, PhD year, PhD institution).The data may be useful for investigations of scholarly productivity, the correlates of scholarly productivity, and the contributions of particular individuals and institutions.Complete population data are presented for the top 26 doctoral programs, doctoral institutions other than R1 universities, the top liberal arts colleges, and other bachelor's institutions. Sample data are presented for Carnegie R1 universities (other than the top 26) and master's institutions.All the data were compiled from publicly available sources, and the data collection process did not involve interaction with human subjects.

This repository contains the data generated during the PhD research titled ‘Study and Modelling of Surface Topography Changes During Running-in in Rolling-Sliding Contacts Under Mixed Lubrication’. The testing in this research used two tribometers: TE74 and MTM. The data in this repository is organized into five primary folders based on the type of tribometer and the nature of the data acquisition (online vs. offline).