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."

We include the course syllabus used to teach quantitative research design and analysis methods to graduate Linguistics students using a blended teaching and learning approach. The blended course took place over two weeks and builds on a face to face course presented over two days in 2019. Students worked through the topics in preparation for a live interactive video session each Friday to go through the activities. Additional communication took place on Slack for two hours each week. A survey was conducted at the start and end of the course to ascertain participants' perceptions of the usefulness of the course. The links to online elements and the evaluations have been removed from the uploaded course guide.Participants who complete this workshop will be able to:- outline the steps and decisions involved in quantitative data analysis of linguistic data- explain common statistical terminology (sample, mean, standard deviation, correlation, nominal, ordinal and scale data)- perform common statistical tests using jamovi (e.g. t-test, correlation, anova, regression)- interpret and report common statistical tests- describe and choose from the various graphing options used to display data- use jamovi to perform common statistical tests and graph resultsEvaluationParticipants who complete the course will use these skills and knowledge to complete the following activities for evaluation:- analyse the data for a project and/or assignment (in part or in whole)- plan the results section of an Honours research project (where applicable)Feedback and suggestions can be directed to M Schaefer schaemn@unisa.ac.za

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)

These are the data sets in machine readable files from a quantitative dye tracer test conducted at Langle Spring November 13-December 2, 2017 as part of the USGS training class, GW2227 Advanced Field Methods in Karst Terrains, held at the Savoy Experimental Watershed, Savoy Arkansas. Langle Spring is NWIS site 71948218, latitude 36.11896886, longitude -94.34548871. One pound of RhodamineWT dye was injected into a sinking stream at latitude 36.116772 longitude -94.341883 NAD83 on November 13, 2017 at 22:50. The data sets include original fluorimeter data logger files from Langle and Copperhead Springs, Laboratory Sectra-fluorometer files from standards and grab samples, and processed input and output files from the breakthrough curve analysis program Qtracer2 (Field, USEPA, 2002 EPA/600/R-02/001).

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.

To address Toronto's 2012 budget gap of $774 million, City Council has launched a review of all of its services and implemented a multi-year financial planning process. This data set contains the responses to the multiple- choice questions on the Core Services Review Public Consultation Feedback Form from members of the public. Approximately 13,000 responses were received (full and partial). The consultation was held between May 11 and June 17, 2011. As a public consultation, respondents chose to participate, and chose which questions to answer. This produced a self-selected sample of respondents. The majority of the responses were from City of Toronto residents. There were some responses from GTA residents. City staff reviewed the data and removed personal information and input violating city policies (for example, contravenes the City's current anti-discrimination policy or confidentiality policy). The .SAV file may be viewed with Statistics software such as SPSS or SAS.

This data package includes a quantitative analysis of non-coral communities at sites along a water quality gradient off of Aua, American Samoa in 2022. These datasets were funded by the NOAA Coral Reef Conservation Program (CRCP) Project Number 31303 to study effects of land-based sources of pollution (LBSP) in Aua, American Samoa. In September 2022 Ecosystem Sciences Division (ESD) scientists of the Pacific Islands Fisheries Science Center (PIFSC) flew into American Samoa to survey 18 sites along a water quality gradient off of Aua. Three datasets are provided of the taxa species and counts of benthic foraminifera, benthic microalgae, and macroinvertebrates from samples collected between 9-28 September 2022. Samples were preserved in the field, and brought back to the NOAA Inouye Regional Center (IRC) and analyzed via microscopy. To analyze benthic foraminifera abundance, sediment samples were collected using a small sediment corer (60 ml syringe with the tip removed and a stopper placed there instead). Only the top 3 cm were retained. Under the microscope, benthic foraminifera were picked out of the sediment and identified. To analyze benthic microalgae, microscope slides were deployed on the seafloor at each site for 2 to 3 weeks. The benthic microalgae that settled was fixed and preserved in Lugol's solution and analyzed. Microalgae included diatoms (pennate and centric), dinoflagellates, chlorophyta, and cyanobacteria. To analyze macroinvertebrates: plastic scouring pads were deployed and attached to the substratum with zip-ties for 2 to 3 weeks. The scouring pads were removed after the settlement period, all plastic zip-ties and additional waste were removed from the reef. Macroinvertebrates that settled on the scouring pad were placed into sampling jars and fixed and preserved with 4% formalin, and subsequently analyzed under the microscope. These quantitative non-coral community surveys were one of several surveys conducted at the same sites across Aua reef in September 2022. Other surveys described and archived separately include surveys of water quality, CTD casts, coral demography, benthic imagery/benthic cover, and coral demography. These can be accessed under the 'Related Items' section of the InPort metadata record.

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.

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.

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.

Example of dose-response data set. The data set contains dataused to quantitate the dose (concentration) response (effect) relationships for different stressors. The xlsx workbook contain the following sheets:

Introduction: Brief explanation to the qData template and example data set included

README: The README file provides an overview of the basic features of the qData template. The sheet contains overview of all columns in the qData template (and example), explanation to column title in the template, description for the column content, format of data, and an examples.

qData: the sheet contain the data for one stressor, External gamma radiation from a Cobalt-60 radiation source. Test species is duckweed, lemna minor. The column titles contain brief description to the content of the columns.

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.

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.

This collection contains an example MINUTE-ChIP dataset to run minute pipeline on, provided as supporting material to help users understand the results of a MINUTE-ChIP experiment from raw data to a primary analysis that yields the relevant files for downstream analysis along with summarized QC indicators. Example primary non-demultiplexed FASTQ files provided here were used to generate GSM5493452-GSM5493463 (H3K27m3) and GSM5823907-GSM5823918 (Input), deposited on GEO with the minute pipeline all together under series GSE181241. For more information about MINUTE-ChIP, you can check the publication relevant to this dataset: Kumar, Banushree, et al. "Polycomb repressive complex 2 shields naïve human pluripotent cells from trophectoderm differentiation." Nature Cell Biology 24.6 (2022): 845-857. If you want more information about the minute pipeline, there is a public biorXiv and a GitHub repository and official documentation.

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,Kakamega,Nakuru and Nairobi counties

Analysis unit

Private health facilities that provide T-safe services under the In Their Hands(ITH) Program.

Universe

1.Adolescent girls aged 15-19 who enrolled on the T-safe platform and received services and those who enrolled but did not receive services from the ITH facilities. 2.Service providers incharge of provision of T-safe services in the ITH facilities. 3.Mobilisers incharge of adolescent girls aged 15-19 recruitment into the T-safe program.

Sampling procedure

Qualitative Sampling

IDI participants were selected purposively from ITH intervention areas and facilities located in the four ITH intervention counties; Homa Bay, Nakuru, Kakamega and Nairobi respectively which were selected for the midline survey. Study participants were identified from selected intervention facilities. We interviewed one service provider of adolescent friendly ITH services per facility. Additionally, we conducted IDI's with adolescent girls' who were enrolled and using/had used the ITH platform to access reproductive health services or enrolled but may not have accessed the services for other reasons.

Sample coverage We successfully conducted a total of 122 In-depth Interviews with 54 adolescents enrolled on the T-Safe platform, including those who received services and those who were enrolled but did not receive services, 39 IDIS with service providers and 29 IDIs with mobilizers. The distribution per county included 51 IDI's in Nairobi City County (24 with adolescent girls, 17 with service providers and 10 with mobilisers), 15 IDI's in Nakuru County (2 with adolescent girls,8 with service providers and 5 with mobilisers), 34 IDI's in Homa Bay County (18 with adolescent girls,8 with service providers and 8 with mobilisers) and 22 IDI's in Kakamega County (10 with adolescent girls,6 with service providers and another 6 with mobilisers.)

Sampling deviation

N/A

Mode of data collection

Face-to-face [f2f]

Research instrument

The midline evaluation included qualitative in-depth interviews with adolescent T-Safe users, adolescents enrolled in the platform but did not use the services, providers and mobilizers to assess the adolescent user experience and quality of services as well as provider accountability under the T-Safe program. Generally,the aim of the qualitative study was to assess adolescents' T-Safe users experience across quality dimensions as well as provider's experiences and accountability. The dimensions assessed include adolescent's journey with the platforms, experience with the platform, perceptions of quality of services and how the ITH platforms changed provider behavior and accountability.

Adolescent in-depth interview included:Adolescent journey,Barriers to adolescents access to SRH services,Community attitudes towards adolescent use of contraceptives,Decision making,Factors influencing decision to visit a clinic,Motivating factors for girls to join ITH,Notable changes since the introduction of ITH,Parental support ,and Perceptions about T-Safe.

Service providers in-depth interview included;Personal and professional background,Provider's experience with ITH/T-safe platform,Notable changes/influences since the introduction of ITH/T-safe,Influence/Impact on the preference of adolescent service users and health care providers as a result of the program,Impact/influence of ITH on quality of care,Facilitators and barriers for adolescents to access SRH services,Mechanisms to address the barriers,Challenges related to the facility,Feedback about facility from adolescents,Types of support needed to improve SRH services provided to adolescents Scenarios of different clients accessing SRH services,and Free node.

Mobilisers in-depth interview included;Mobilizer responsibilities and designation,Job description,Motivation for joining ITH,Personal and professional background,Training,Mobilizer roles in ITH,Mobilization process ,Experience with ITH platform,Key messages shared with adolescent about ITH/ Tsafe during enrollment,Motivating factors for adolescents to join ITH/Tsafe,Community's attitude towards ITH/Tsafe,Challenges faced by mobilizers when mobilizing adolescents for Tsafe,Adolescents view regarding platform,Addressing the challenges ,andFree node

Cleaning operations

Qualitative interviews were audio-recorded and the audio recordings were transmitted to APHRC study team by uploading the audios to google drive which was only accessible to the team. Related interview notes, participant's description forms and Informed consent forms were transported to APHRC offices in Nairobi at the end of data collection where the data transcription and coding was conducted. 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. A qualitative software analysis program (NVIVO) was used to assist in coding and analyzing the data. A “thematic analysis” approach was used to organize and analyze the data, and to assist in the development of a codebook and coding scheme. Data was analyzed by first reading the full IDI transcripts, becoming familiar with the data and noting the themes and concepts that emerged. A thematic framework was developed from the identified themes and sub-themes and this was then used to create codes and code the raw data.

Response rate

N/A

Sampling error estimates

N/A

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...

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 28-29.06.2017

This was the second imaging campaign. Samples were aged.

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.

Quantitative PCR targeting Trichodesmium, UCYN-A, UCYN-B, gamma-24774A11, and Het1, based on the nifH gene.

Historical quantitative benthos grab samples from the Southern Baltic Sea, collected by Polish researchers. The dataset was digitised at the Christian-Albrechts-University Kiel; Leibniz Institute of Marine Sciences; Marine Ecology Division; Benthos Ecology section.