Find research datasets worth reusing

IODP Expedition 353 P-wave velocity bayonet (section)

P-wave velocity data were measured on undisturbed section halves using pairs of piezoelectric transducers mounted in bayonets that are inserted into soft sediment along the JRSO-defined y-axis and/or z-axis. Report includes P-wave velocity in y and/or z direction, bayonet separation, traveltime between transducers, and first arrival picks.

IODP Expedition 353 P-wave velocity caliper (section)

P-wave velocity data were measured on undisturbed section halves (JRSO-defined x-axis) and/or discrete cube and cylinder samples (x, y, or z-axis) using pairs of piezoelectric transducers mounted on a caliper system. Report includes P-wave velocity in x, y, and/or z-direction, caliper separation, traveltime between transucers, and first arrival picks.

IODP Expedition 353 Section-half images

Digital section images were taken of the flat face of split cores on the Section Half Imaging Logger (SHIL) using a linescan camera at a resolution of 20 lines/mm (50 micron pixels). Cores were imaged as soon as possible after splitting to minimize color changes that occur through oxidation and drying. The SHIL produces TIF files as well as reduced-size JPG files. The TIF files are not kept online but users may request them from the <a href="mailto:database@iodp.tamu.edu">IODP-JRSO Data Librarian</a>.

IODP Expedition 353 Thin section images

Hard rock and sediment thin section images were acquired using either the JRSO-developed Petrographic Image Capture and Archival Tool (PICAT) imager or (rarely) an upright microscope and a digital camera. Sample images are acquired in unpolarized, polarized, and/or cross-polarized light. Image files are presented compressed by hole.

IODP Expedition 353 Section summary

Report includes data for individual core sections: coring/drilling depths and recovery, database identifiers for the whole section and section halves, and number of samples taken from the section before and after splitting.

opencc-by-4.0May 2017View details →

IODP Expedition 359 Laser height profile (section half)

Height profile data were measured on the Section Half Multisensor Logger (SHMSL) by a rangefinding laser and recorded in uncorrected height units in millimeters in CSV files.

opencc-by-4.0May 2017View details →

IODP Expedition 359 Section-half images

opencc-by-4.0May 2017View details →

IODP Expedition 359 Section summary

opencc-by-4.0Nov 2021View details →

Section 5.1 "Task Area 1: Image (meta)data formats and standardization)" Figure 8

Figure 8. A FAIR-IO bundle combines the necessary acquisition and provenance metadata together with multi-resolution, chunked binary data in a single cloud-compatible format for simplified sharing and re-use. from NFDI Grant Application, "National Research Data Infrastructure for Microscopy and Bioimage Analysis" (NFDI4BIOIMAGE)

opencc-by-4.0Sep 2022View details →

Dataset for "Cognitive behavioural therapy self-help intervention preferences among informal caregivers of adults with chronic kidney disease: an online cross-sectional survey"

Data and R code used for the analysis of data for the publication: Coumoundouros et al., Cognitive behavioural therapy self-help intervention preferences among informal caregivers of adults with chronic kidney disease: an online cross-sectional survey. BMC Nephrology Summary of study An online cross-sectional survey for informal caregivers (e.g. family and friends) of people living with chronic kidney disease in the United Kingdom. Study aimed to examine informal caregivers' cognitive behavioural therapy self-help intervention preferences, and describe the caregiving situation (e.g. types of care activities) and informal caregiver's mental health (depression, anxiety and stress symptoms). Participants were eligible to participate if they were at least 18 years old, lived in the United Kingdom, and provided unpaid care to someone living with chronic kidney disease who was at least 18 years old. The online survey included questions regarding (1) informal caregiver's characteristics; (2) care recipient's characteristics; (3) intervention preferences (e.g. content, delivery format); and (4) informal caregiver's mental health. Informal caregiver's mental health was assessed using the 21 item Depression, Anxiety, and Stress Scale (DASS-21), which is composed of three subscales measuring depression, anxiety, and stress, respectively. Sixty-five individuals participated in the survey. See the published article for full study details. Description of uploaded files 1. ENTWINE_ESR14_Kidney Carer Survey Data_FULL_2022-08-30: Excel file with the complete, raw survey data. Note: the first half of participant's postal codes was collected, however this data was removed from the uploaded dataset to ensure participant anonymity. 2. ENTWINE_ESR14_Kidney Carer Survey Data_Clean DASS-21 Data_2022-08-30: Excel file with cleaned data for the DASS-21 scale. Data cleaning involved imputation of missing data if participants were missing data for one item within a subscale of the DASS-21. Missing values were imputed by finding the mean of all other items within the relevant subscale.  3. ENTWINE_ESR14_Kidney Carer Survey_KEY_2022-08-30: Excel file with key linking item labels in uploaded datasets with the corresponding survey question. 4. R Code for Kidney Carer Survey_2022-08-30: R file of R code used to analyse survey data. 5. R code for Kidney Carer Survey_PDF_2022-08-30: PDF file of R code used to analyse survey data.

opencc-by-4.0Jan 2023View details →

Sri Ksetra, Myanmar. Cross-section of the Excavations at the Yahanda Mound (2014-16) HMA.59 (test pit 8 & 9)

Janice Stargardt, Sri Ksetra, Myanmar. Cross-section of the Excavations at the Yahanda Mound (2014-16) HMA.59 (test pit 8 & 9) carried out under <a href="https://cordis.europa.eu/project/id/609823">ERC synergy grant 609823.</a>

opencc-by-4.0Dec 2022View details →

The spatial landscape of gene expression isoforms in tissue sections

This upload provides raw in situ sequencing (ISS) data used to validate Spatial Isoform Transcriptomics (SiT), as well as R scripts required for SiT analysis. GenePlots.zip and Reads.zip are ISS data generated and collected by the CARTANA ISS service. The following data description is cited from the report provided by CARTANA ISS service: "Folder "Reads" contains coordinates and gene information of segmented spots. The coordinates are in pixel unit. Scaling factor is 0.32 um/pixel. (0,0) is at northwest (top-left corner). With Low/High Threshold, we refer to the quality thresholding. Our technology is fluorescence based, i.e. with the thresholding one can balance how certain the signals are. Files ending with _LowThreshold: reads not matching with any known barcode were already discarded. Files ending with _HighThreshold: has information only about spots that passed additional quality check. Folder "GenePlots" has plotted images in static .png format, fully zoomed out. LowThreshold and HighThreshold follow the same thresholding strategy as in reads files."   SiT-master.zip is a download of the GitHub repository <a href="https://github.com/ucagenomix/SiT">https://github.com/ucagenomix/SiT</a>, providing figures and analysis scripts for SiT.   Related SiT data are deposited through GEO, accession number <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE153859">GSE153859</a>

Assessment of non-communicable diseases screening practices among university lecturers in Ghana – a cross sectional single centre study

This section highlights the various methods used for this study. It covered study setting, study design, study approach, study population, sampling techniques, sample size calculation, inclusion and exclusion criteria, ethical consideration, data collection, data management and data analysis.   Study Setting The study was carried out at Kwame Nkrumah University of Science and Technology (KNUST), Kumasi between February to August, 2022.  The study covered all the six (6) Colleges in the University.   Study Design This was a cross sectional study to ascertain health check practices among university lecturers.   Study Approach The study employed quantitative approach in which data was collected using questionnaires with both closed- and open-ended questions. Study Population The study population involved 838 Lecturers across the six Colleges at Kwame Nkrumah University of Science and Technology (KNUST), Kumasi. A study of the lecturer population per college revealed that Colleges of Health Sciences (highest) and Agric /Natural resources (lowest) were the outliers (Quality Assurance and Planning Office, 2020).   Sampling Technique   Simple probability technique was used to select the name of a college and the day/date to visit. Two sets of papers were folded with names of colleges (set 1) and day/date of visit (set 2). A picker picked one folded paper from each set and the name of the college and the day/date to visit was matched. In this case, the ordering of date and visit gave 1st College of Humanities & Social Sciences, 2nd College of Agric and Natural Resources, 3rd College of Art & Built Environment, 4th College of Engineering, 5th College of Science and 6th College of Health Sciences. We then used the ‘walk in’’ system to select the study participants. Within the days to visit a college, any lecturer we meet in his/ her office was a potential study participant.       Sample Size Calculation The sample size was obtained using Yamane, 1967 formulae as shown below:     Where n= is the population of Lecturers in at KNUST E= is the level of precision Therefore:             n= 838                                       1+838 (0.0025) n =    838 1+ 2.098   838 3.095                                                                                                                 n=270                                                                       However, due to logistical constrains, 205 participants were contacted across the 6 Colleges at Kwame Nkrumah University of Science and Technology. We then applied simple proportions to get the number of lecturers to be consulted in each college.   Inclusion and Exclusions Criteria Inclusion criteria was made up of all Lecturers on KNUST campus who are in active service and consented to participate. All other staff not within this category were excluded from this research.   Ethical Considerations Ethical approval was sought from the CHRPE, KNUST with approval reference no: CHRPE/AP/581/21. The aim of the research was explained to participants. Those who consented to participate in the research were given consent forms to sign and date. Again, participants were assured of confidentiality. Participants were told that, they were free to withdraw from the study in the cause of time. In other words, study participants were not coerced into the study.   Data Collection Tool Data was collected using structured questionnaires. The questionnaires covered dietary intake, alcohol intake, issues on physical inactivity and tobacco use. Aside these four main risk factors of NCDs, the questionnaire also captured frequency of blood pressure checks, blood pressure outcome anytime it is checked (systolic and diastolic), frequency of general body check-up, frequency of anthropometric measurement checks (weight and height), an assessment of impressions about the outcome of weight and height checks, an assessment of intended measures to be taken depending on the outcomes of weight and health checked. Again, the general observation of the nature of job as a lecturer and health status especially the outcome of blood pressure monitoring were also assessed. The questionnaire also captured the socio-demographic status of Lecturers,   Data Management Only the Research Team had access to data. Data was kept confidential. The researchers had planned of disposing data from the storage 5 years after the publication of this research. Collected data was entered and cleaned using Microsoft Excel spread sheet, and then imported into STATA version 14.0 (Stata Corp LP, College Station, Texas, USA) for statistical analysis and results.   Data Analysis Descriptive statistics were used to summarize the characteristics of the study population by employing frequencies and percentages for categorical data. In addition, the degree of relatedness (association) was evaluated using Chi-square (χ2) or Fisher’s exact tests where appropriate with a p ≤0.05 assumed to be statistically significant. Both bivariate and multivariate logistic regression analyses were performed and adjusted for colleges effect to identify associations among the variables of interest. Variables having significant association in the logistic regression models were set at p≤0.05 with 95% confidence interval (95% CI) for both unadjusted and adjusted odds ratios (OR, AOR).   Variables BP was selected as the dependent variable, and in turn define as Normal: ≤ 120/80 mmHg; Elevated: Systolic between 120-129 and diastolic ≤ 80; Hypertension: Systolic ≥ 130 or diastolic ≥ 80. Then dichotomized into Normal blood pressure: ≤ 120/80 mmHg and high blood pressure (Hypertension): ≥ 130/90 mmHg for logistic regression analyses. Independent variables were socio-demographics; gender, age, marital status, staff rank and lecturer’s colleges (categorized into binary variable; COHS /COS/COE and CABE/CANR/COHSS), family history of NCDs and health check status. In this study, the variable “very often” denotes (doing the activity in question more than 4 times a month), “often” denotes (doing the activity in question at least twice a month), and “not often” denotes (doing the activity in question once a month).

Assessment of non-communicable diseases screening practices among university lecturers in Ghana – a cross sectional single centre study

Data Collection Tool Data were collected using structured questionnaires. The questionnaires covered dietary intake, alcohol intake, issues with physical inactivity, and tobacco use. Aside from these four main risk factors of NCDs, the questionnaire also captured the frequency of blood pressure checks, blood pressure outcome anytime it is checked (systolic and diastolic), frequency of general body check-ups, frequency of anthropometric measurement checks (weight and height), an assessment of impressions about the outcome of weight and height checks, an assessment of intended measures to be taken depending on the outcomes of weight and health checked. Again, the general observation of the nature of the job as a lecturer and health status especially the outcome of blood pressure monitoring were also assessed. The questionnaire also captured the socio-demographic status of Lecturers,   Data Management Only the Research Team had access to data. Data was kept confidential. The researchers had planned of disposing data from the storage 5 years after the publication of this research. Collected data was entered and cleaned using Microsoft Excel spread sheet, and then imported into STATA version 14.0 (Stata Corp LP, College Station, Texas, USA) for statistical analysis and results.   Data Analysis Descriptive statistics were used to summarize the characteristics of the study population by employing frequencies and percentages for categorical data. In addition, the degree of relatedness (association) was evaluated using Chi-square (χ2) or Fisher’s exact tests where appropriate with a p ≤0.05 assumed to be statistically significant. Both bivariate and multivariate logistic regression analyses were performed and adjusted for colleges' effect to identify associations among the variables of interest. Variables having significant association in the logistic regression models were set at p≤0.05 with 95% confidence interval (95% CI) for both unadjusted and adjusted odds ratios (OR, AOR).   Variables BP was selected as the dependent variable, and in turn define as Normal: ≤ 120/80 mmHg; Elevated: Systolic between 120-129 and diastolic ≤ 80; Hypertension: Systolic ≥ 130 or diastolic ≥ 80. Then dichotomized into Normal blood pressure: ≤ 120/80 mmHg and high blood pressure (Hypertension): ≥ 130/90 mmHg for logistic regression analyses. Independent variables were socio-demographics; gender, age, marital status, staff rank, and lecturer’s colleges (categorized into binary variables; Colleges, family history of NCDs, and health check status. In this study, the variable “very often” denotes (doing the activity in question more than 4 times a month), “often” denotes (doing the activity in question at least twice a month), and “not often” denotes (doing the activity in question once a month).

Input and output data for Experiment B2 (Deliverable 3.3 - Data assimilation in process-based models for algae bloom forecasting - Section 2)

The dataset contains: i. the meteorological forcing, hydrological boundary condition and chlorophyll-a files used as an input ii. the model output and skill produced for Experiment B2 (Deliverable 3.3 - Data assimilation in process-based models for algae bloom forecasting - Section 2)

Input and output data for Experiment B2 (Deliverable 3.3 - Data assimilation in process-based models for algae bloom forecasting - Section 1)

Input and output data for Experiment B2 (Deliverable 3.3 - Data assimilation in process-based models for algae bloom forecasting - Section 3)

opencc-by-4.0Apr 2023View details →

Diagnostic strategies for muscular dystrophies: a Cross-Sectional Study

Datos obtenido producto de un estudio de corte transversal con el fin de establecer la prevalencia de base hospitalaria en distrofias musculares, a través de un diseño de muestreo en fases.