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Tom Greenwood: What Does Green Digital Accessibility Mean to You?
<p>Tom Greenwood, co-founder of Wholegrain digital, shares his thoughts on green digital accessibility for the Green Digital Accessibility Conference.</p>
Carlo Eugeni: What Does Green Digital Accessibility Mean to You?
<p>Dr Carlo Eugeni from the University of Leeds shares his thoughts on green digital accessibility for the Green Digital Accessibility Conference.</p>
Poses of People in Art: A Data Set for Human Pose Estimation in Digital Art History
<p>Throughout the history of art, the pose—as the holistic abstraction of the human body's expression—has proven to be a constant in numerous studies. However, due to the enormous amount of data that so far had to be processed by hand, its crucial role to the formulaic recapitulation of art-historical motifs since antiquity could only be highlighted selectively. This is true even for the now automated estimation of human poses, as domain-specific, sufficiently large data sets required for training computational models are either not publicly available or not indexed at a fine enough granularity. With the <em>Poses of People in Art</em> data set, we introduce the first openly licensed data set for estimating human poses in art and validating human pose estimators. It consists of 2,454 images from 22 art-historical depiction styles, including those that have increasingly turned away from lifelike representations of the body since the 19<sup>th</sup> century. A total of 10,749 human figures are precisely enclosed by rectangular bounding boxes, with a maximum of four per image labeled by up to 17 keypoints; among these are mainly joints such as elbows and knees. For machine learning purposes, the data set is divided into three subsets—training, validation, and testing—, that follow the established JSON-based Microsoft COCO format, respectively. Each image annotation, in addition to mandatory fields, provides metadata from the art-historical online encyclopedia WikiArt.</p>
DATASET: Digital humanities at global scale
<p>Dataset to analyse the scientific production of the Digital humanities at global scale. Databases consulted: App Dimensions, Web of Science (WoS), Scopus.</p> <p>Dataset to analyze the scientific production with reference: </p> <p>Bocanegra Barbecho, L., Ros Muñoz, S., González-Blanco García, E., & Toscano, M. (2023). Digital humanities at global scale. Interdisciplinary Science Reviews, 48(3), 446–459. https://doi.org/10.1080/03080188.2023.2193799</p>
Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium
<p>Dataset includes 2.5 hours real-world data, for one participant from each of the technical validation study cohorts: ongestive heart failure (CHF), chronic obstructive pulmonary disease (COPD), healthy adult (HA), multiple sclerosis (MS), Parkinson’s (PD) and proximal femoral facture (PFF) linked to the manuscript entitled ‘Assessing real-world gait with digital technology? Validation, insights, and recommendations from the Mobilise-D consortium’. The attached documentation has 6 datasets and a README document.</p> <p>The MOBILISE-D project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 820820. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation program and the European Federation of Pharmaceutical Industries and Associations (EFPIA).</p> <p>Content on this publication reflects the author’s view and neither IMI nor the European Union, EFPIA, or any Associated Partners are responsible for any use that may be made of the information contained herein.</p>
Flujo de trabajo de Proyecto Humboldt Digital (ProHD). Digitalización
<p>Este diagrama contiene los pasos principales para digitalizar documentos en el contexto de Proyecto Humboldt Digital.</p>
Flujo de trabajo de Proyecto Humboldt Digital (ProHD). Edición
<p>Este diagrama contiene los pasos principales para editar documentos textuales en el contexto de Proyecto Humboldt Digital.</p>
Digital elevation models, ortho images and outlines of Yala Glacier, Langtang Valley, Nepal Himalaya
<p>Datasets related to article "Up-glacier propagation of surface lowering of Yala Glacier, Langtang Valley, Nepal Himalaya". The data includes three digital elevation models (DEM), two ortho images and five outlines of Yala Glacier between 1981 and 2015.<br> </p> <p>Description of files:<br> 1) DEM and ortho image</p> <p>- 1981Yala_dem_20_-10_bias_cor.tif: 10 m resolution digital elevation model derived from a map that was generated using ground phogogrammetry images that were acquired in 1981 (Yokoyama, 1984; Fujita and Nuimura).</p> <p>- 2007Yala_dem_0_-4_bias_cor.tif: 2 m resolution digital elevation model derived from 14 oblique photographs that were acquired by a private jet with handheld cameras in 2007.<br> - 2007Yala_ortho.tif: an ortho images derived by the same data in 2007.</p> <p>- 2015Yala_dem_0_0_bias_cor.tif: 1 m resolution digital elevation model derived from 519 photographs that were acquired by a UAV-based photogrammetric survey in 2015.<br> - 2015Yala_ortho.tif: an ortho images derived by the same data in 2015.<br> <br> 2) Glacier boundary (shapefile Files)</p> <p>- Yala_area_1981: <br> - Yala_area_2007:<br> - Yala_area_2009:<br> - Yala_area_2012:<br> - Yala_area_2015:<br> <br> <br> Please see the related journal article for details on datasets.<br> <br> Sunako, S., Fujita, K., Izumi, T., Yamaguchi, S., Sakai, A., & Kayastha, R. (2023). Up-glacier propagation of surface lowering of Yala Glacier, Langtang Valley, Nepal Himalaya. Journal of Glaciology, 69(274), 425-432. doi:10.1017/jog.2022.118<br> </p>
INCA-CH seamless nowcasting system: 1km digital elevation model
<p>Digital elevation model at 1km horizontal resolution used in the INCA-CH seamless nowcasting system (in Swiss coordinates CH03). For INCA-CH parameters see here: <a href="https://zenodo.org/record/6470725">INCA-CH set of data</a></p>
Replication package for the study "Digital Sufficiency in Flexible Work"
<p>This dataset is published for transparency and open data purposes, as part of the work "<em>'We are always on, is that really necessary?' Exploring the Path to Digital Sufficiency in Flexible Work</em>" published at <a href="https://conf.researchr.org/home/ict4s-2023">ICT4S 2023</a> conference.</p> <p><strong>The study:</strong></p> <p>We conducted three focus groups with a total of 11 participants, inside two different companies. Our aim was to investigate the notion of digital sufficiency in the context of flexible work.</p> <p><strong>Content:</strong></p> <ul> <li><em>Preliminary interview guide.pdf</em>: the interview guide containing the questions for the preliminary interview</li> <li><em>Focus group slides.pdf</em>: the slides presented to the participants of the three focus groups</li> <li><em>Focus group participant print-outs.pdf</em>: the sheets distributed to the participants of the three focus groups, for individual note-taking</li> <li><em>Codebook.xlsx</em>: the codes extracted (with the help of the software <a href="http://www.saturateapp.com">Saturate</a>) from the transcripts of the three focus groups: <ul> <li>tab <em>CODEBOOK</em>: the codes, sorted by three levels and by research question, along with their definition and a description on when the code is applicable,</li> <li>tab <em>Code Count</em>: the number of occurrence of each code in the transcripts,</li> <li>tab <em>Clustering Tactics</em>: the thematic analysis performed on the codes with level 1 "tactic". Corresponds to the Table III in the paper</li> </ul> </li> </ul> <p>For privacy reason, all names are removed and the transcript and audio recording are not part of this replication package.</p>
Digital Tools for Handwriting Proficiency Evaluation in Children - DATASET
<p>Data to support the findings in the conference paper</p> <p>L. G. Dui, E. Calogero, M. Malavolti, C. Termine, M. Matteucci and S. Ferrante, "Digital Tools for Handwriting Proficiency Evaluation in Children," <em>2021 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI)</em>, Athens, Greece, 2021, pp. 1-4, doi: 10.1109/BHI50953.2021.9508539.</p> <ul> <li>Characterization.xls: an Excel file with sheets: <ul> <li>Characterization: <ul> <li>Subject ID</li> <li>School ID</li> <li>Class</li> <li>Age</li> <li>Sex</li> <li>Hand</li> <li>Years since starting writing in cursive</li> </ul> </li> <li>TabletSUS: score for the System Usability Scale referred to writing on tablet</li> <li>PenSUS: score for the System Usability Scale referred to writing on paper with the smart ink pen</li> <li>BVSCO-2: number of graphemes produced when writing on paper or tablet</li> </ul> </li> <li>pen_tablet_data.mat: a Matlab file with indicators and their names, computed with tablet and pen data</li> </ul>
Modest Digital Humanities as a Default Constraint on Philosophical Interpretation
<p>Talk at the <a href="https://www.digital-philosophy.org/">Philosophy [in:of:for:and] Digital Knowledge Infrastructures</a> online workshop (08/09/2022).</p>
Are there good ethical reasons why for profit publishers should no longer exist under the conditions of digital infrastructures? And what does this have to do with ethics as a reflexive discipline?
<p>Talk at the <a href="https://www.digital-philosophy.org/">Philosophy [in:of:for:and] Digital Knowledge Infrastructures</a> online workshop (08/09/2022).</p>
Dataset for "Teaching critical thinking about health information and choices in secondary schools: human-centred design of digital resources"
<p>A qualitative dataset for the article: Teaching critical thinking about health information and choices in secondary schools: human-centred design of digital resources</p> <p>We collected this data in Phase 2 of the work described in the article, to inform development of educational resources (<em>Be Smart About Your Health</em>) to support teaching critical thinking about health claims and making informed health choices for use in secondary schools, based on a set of Informed Health Choices Key Concepts. </p> <p>Data collection methods: individual and group interviews, observation of classroom pilots, in Kenya, Rwanda, and Uganda, and via email from an international advisory group. Timeframe for data collection and analysis: 2020-2022</p> <p>This dataset is a part of the research project: <em>Enabling sustainable public engagement in improving health and health equity, </em>2019-2024. Funded by GLOBVAC programme, Research Council of Norway. </p> <p> </p>
Dataset Digital Competence
<p>The dataset contains data on demographics (gender, age), education (type of study program, enrolled year, affiliation of studies to a scientific field, daily use of computer) and data on the self-assessed level of digital competence of the respondents.</p>
Berlin State Library (2023). Fulltexts of the Digitized Collections of the Berlin State Library (SBB)
<p>The motivation for creating this dataset was to enable research on the basis of fulltexts which are available in a cultural heritage institution on a large scale. Libraries such as the Berlin State Library (SBB) typically provide three kinds of data: Images (scans of books, illustrations contained in the scanned material, or else), metadata (descriptive data providing information on the digitized item) and texts. The latter are usually received via an implementation of optical character recognition (OCR) of the digitized books or manuscripts. In the <a href="https://digital.staatsbibliothek-berlin.de/">digitized collections of the Staatsbibliothek zu Berlin (SBB)</a>, the fulltexts can be downloaded manually, item by item. The publication of a set of about 5 million OCR’d pages alleviates the accessibility of the fulltexts. The basic funding interest in this data publication is the stimulation of innovation.</p> <p>The dataset consists of a single sqlite database containing ALL the fulltexts available in the digitized collections of the Berlin State Library as of August 21st, 2019, with information on languages and entropy added on March 1st, 2023. The size of the sqlite file is about 15.8 GB.</p>
The Svalbox Digital Model Database (DMDb)
<p><strong>The Svalbox Digital Model Database</strong><br> The Svalbox Digital Model Database (DMDb) is a regional DOM database geographically constrained to the Norwegian High Arctic Archipelago of Svalbard at 74-81 °N and 10-35 °E. Svalbard offers exceptional quality, vegetation-free outcrops with a wide range of lithologies and tectono-magmatic styles including extension, compression and magmatism. Data and metadata of the systematically digitized outcrops across Svalbard are shared according to FAIR principles through the Svalbox DMDb. Fully open-access and downloadable DOMs include not just the DOM itself but also the input data, processing reports and projects, and other data products such as footprints and orthomosaics. Rich metadata for each DOM comprises both the technical and geological parameters (metadata), enabling visualisation and integration with regional geoscientific data on the Svalbox portal.<br> <br> <strong>Release information</strong><br> The v2023.3 release of the Svalbox DMDb, documented in this contribution, covers 135 DOMs cumulatively covering 113.946 km2 and offering Proterozoic to Cenozoic stratigraphy.<br> <br> <strong>Release documentation</strong><br> The Svalbox DMDb v2023.3 is shared in the following formats:</p> <ul> <li>GeoJSON (.geojson)</li> <li>Geopackage (.gpkg)</li> </ul> <p>Documentation of the types and units associated with the data columns is documented through the SvalboxDMDb parameters files, available in:</p> <ul> <li>Comma-separated values (.csv)</li> <li>JSON (.json)</li> </ul> <p>Updated metadata is continuously updated to the Svalbox server and made available through:</p> <ul> <li><a href="https://www.svalbox.no/map/">https://www.svalbox.no/map/</a></li> <li>Svalbox ArcGIS REST access point (<a href="https://svalbox.unis.no/arcgis/rest/services/">https://svalbox.unis.no/arcgis/rest/services/</a>)</li> </ul> <p><strong>Citation</strong><br> In addition to model-specific DOIs, please cite the following papers when using the Svalbox DMDb and its models:</p> <ul> <li>Betlem, et al. "The Svalbox Digital Model Database: a geoscientific window to the High Arctic." Geosphere (in review).</li> <li>Senger, et al. "Using digital outcrops to make the high Arctic more accessible through the Svalbox database." Journal of Geoscience Education 69.2 (2021): 123-137.</li> </ul>
Dataset of Program Source Codes Solving Unique Programming Exercises Generated by Digital Teaching Assistant
<p>The programming exercises were automatically generated by the Digital Teaching Assistant (DTA) system that automates a massive Python programming course at MIREA – Russian Technological University (RTU MIREA). Source codes of the small programs grouped by the type of the solved task can be used for benchmarking source code classification and clustering algorithms. Moreover, the data can be used for training intelligent program synthesizers, or benchmarking mutation testing frameworks, and more applications are yet to be discovered. This dataset is a supplementary material for a paper entitled <a href="https://doi.org/10.3390/data8060109"><strong>Dataset of Program Source Codes Solving Unique Programming Exercises Generated by Digital Teaching Assistant</strong></a> submitted to the <strong>MDPI Data</strong> journal.</p>
The Transformative Storytelling Technique for Developing Guided Digital Narratives in Mental Health Support. Pilot study
<p>In a society where advances and innovations occur on a daily basis, the development of digital mental health tools continues at almost uncontrollable rates. Following trends in the utilization of storytelling across fields and reflecting on the lack of working models and frameworks for the application of storytelling for mental health support, the Transformative Storytelling Technique (TST) is designed and developed as a part of this work. This technique represents a new category for creating hybrid content to guide the experience of audiences, starting with the case of informal caregivers. In this pilot study, a TST caregiver story is assessed pre-post in an interventional study, investigating the potential role of mental health audio stories in supporting informal caregiver wellbeing. The anonymized raw dataset is available.</p>
Needs and preferences of different groups of informal caregivers towards designing digital solutions
<p>The project aimed to understand whether young adults who take care of a loved-one (young adult caregivers; YACs) differ in their perceived life balance and psychosocial functioning as compared to young adults without care responsibilities (non-YACs). In addition, this project aimed to understand how YACs evaluated a tool to support informal careg</p> <p>ivers. This tool (“Caregiver Balance”; <a href="https://balans.mantelzorg.nl">https://balans.mantelzorg.nl</a>) is specifically designed to support informal caregivers taking care of a loved-one in the palliative phase and could potentially be adapted to meet the needs of YACs. </p> <p>In this project, we collected data of 74 YACs and 246 non-YACs. Both groups completed questionnaires, and the YACs engaged in a usability test. The questionnaire data was used to compare the perceived life balance and psychological functioning between YACs and non-YACs, aged 18-25 years, and studying in the Netherlands (study 1). Furthermore, we examined the relationship between positive aspects of caregiving and relational factors, in particular, relationship quality and collaborative coping among YACs (study 2). Finally, we conducted a usability study where we interviewed YACs to understand the needs and preferences towards a supportive web-based solution (study 3).</p> <p><strong><em>Table: Study details and associated files</em></strong></p> <table> <tbody> <tr> <td>Number</td> <td>Study Name</td> <td>Study Aim</td> <td>Study Type</td> <td>Type of data</td> <td>Associated Files</td> </tr> <tr> <td>1</td> <td>Perceived life balance among young adult students: a comparison between caregivers and non-caregivers</td> <td>Compare the perceived life balance and psychological functions among student young adult caregivers aged 18-25 years (YACs) with young adult without care responsibilities</td> <td>Survey study</td> <td>Quantitative</td> <td> <ol> <li>ENTWINE_YACs_nonYACsSurvey_RawData</li> <li>ENTWINE_PerceivedLifeBalanceSurvey_YACs_nonYACs_CleanedData</li> <li>ENTWINE_ PerceivedLifeBalanceSurvey _Syntax</li> <li>ENTWINE_YACs_nonYACsSurvey_codebook</li> </ol> </td> </tr> <tr> <td>2</td> <td>Examining the relationship of positive aspects of caregiving with relational factors among young adult caregivers</td> <td>Examine the relationship of positive aspects of caregiving with relational factors, in particular, relationship quality and collaborative coping among a particular group of ICGs, young adult caregivers (YACs), aged 18-25 years.</td> <td>Survey study</td> <td>Quantitative</td> <td> <ol> <li>ENTWINE_YACs_nonYACsSurvey_RawData</li> <li>ENTWINE_PositiveAspectsCaregiving_Survey_YACs_cleanedData</li> <li>ENTWINE_PositiveAspectsCaregiving_Survey_Syntax</li> <li>ENTWINE_YACs_nonYACsSurvey_codebook</li> </ol> </td> </tr> <tr> <td>3</td> <td>Exploring the support needs of young adult caregivers, their issues, and preferences towards a web-based tool</td> <td>Explore (i) challenges and support needs of YACs in caregiving, (ii) their needs towards the content of the ‘MantelzorgBalans’ tool, and (iii) issues they encountered in using the tool and their preferences for adaptation of the tool.</td> <td>Usability study</td> <td> <p>Qualitative and Quantitative</p> </td> <td> <ol> <li>ENTWINE_Needs_Web-basedTools_YACs_Interview_Usability_RawData [to be determined whether data can be shared]</li> <li>ENTWINE_Needs_Web-basedTools_YACs_Questionnaires_RawData</li> </ol> </td> </tr> </tbody> </table> <p><strong>Description of the files to be uploaded</strong></p> <p><strong><em>Study 1: Perceived life balance among young adult students: a comparison between caregivers and non-caregivers</em></strong></p> <ol> <li>ENTWINE_YACs_nonYACsSurvey_RawData: SPSS file with the complete, raw, pseudonomyzed survey data. The following cleaned dataset ‘ENTWINE_PerceivedLifeBalanceSurvey_YACs_nonYACs_CleanedData’ was generated from this raw data.</li> <li>ENTWINE_PerceivedLifeBalanceSurvey_YACs_nonYACs_CleanedData: SPSS file with the cleaned dataset having the following metadata - <ol> <li><strong>Population:</strong> young adult caregivers and young adult non-caregivers aged 18-25 years studying in the Netherlands;</li> <li><strong>Number of participants:</strong> 320 participants in total (74 young adult caregivers and 246 young adult non-caregivers)</li> <li><strong>Time point of measurement:</strong> Data was collected from December 2020 till March 2022</li> <li><strong>Type of data:</strong> quantitative</li> <li><strong>Measurements included, topics covered:</strong> perceived life balance (based on the Occupational balance questionnaire [1]), burnout (Burnout Assessment Tool [2]), negative and positive affect (Positive and Negative Affect Schedule [3]), and life satisfaction (Satisfaction with Life Scale [4])</li> <li><strong>Short procedure conducted to receive data:</strong> online survey on Qualtrics platform</li> </ol> </li> <li>SPSS syntax file ‘ENTWINE_ PerceivedLifeBalanceSurvey _Syntax’ was used to clean and analyse ENTWINE_PerceivedLifeBalanceSurvey_YACs_nonYACs_CleanedData dataset</li> <li>ENTWINE_YACs_nonYACsSurvey_codebook: Codebook having the variable names, variable labels, and the associated code values and code labels for ENTWINE_PerceivedLifeBalanceSurvey_YACs_nonYACs_CleanedData dataset</li> </ol> <p><strong><em>Study 2: Examining the relationship of positive aspects of caregiving with relational factors among young adult caregivers</em></strong></p> <ol> <li>ENTWINE_YACs_nonYACsSurvey_RawData: SPSS file with the complete, raw survey data. The following cleaned dataset ‘ENTWINE_PositiveAspectsCaregiving_Survey_YACs_cleanedData’ was generated from this raw data.</li> <li>ENTWINE_PositiveAspectsCaregiving_Survey_YACs_cleanedData: SPSS file with the cleaned dataset having the following metadata - <ol> <li><strong>Population:</strong> young adult caregivers aged 18-25 years studying in the Netherlands;</li> <li><strong>Number of participants:</strong> 74 young adult caregivers</li> <li><strong>Time point of measurement:</strong> Data was collected from December 2020 till March 2022</li> <li><strong>Type of data:</strong> quantitative</li> <li><strong>Measurements included, topics covered:</strong> positive aspects of caregiving (positive aspects of caregiving scale [5]), relationship quality (Relationship Assessment Scale [6]), collaborative coping (Perception of Collaboration Questionnaire [7] )</li> <li><strong>Short procedure conducted to receive data:</strong> online survey on Qualtrics platform.</li> </ol> </li> </ol> <ol> <li>SPSS syntax file ‘ENTWINE_PositiveAspectsCaregiving_Survey_Syntax’ was used to clean and analyse ‘ENTWINE_PositiveAspectsCaregiving_Survey_YACs_cleanedData’ dataset.</li> <li>ENTWINE_YACs_nonYACsSurvey_codebook: Codebook having the variable names, variable labels, and the associated code values and code labels for ENTWINE_PositiveAspectsCaregiving_Survey_YACs_cleanedData dataset.</li> </ol> <p><strong><em>Study 3: Exploring the support needs of young adult caregivers, their issues, and preferences towards a web-based tool </em></strong></p> <ol> <li>ENTWINE_Needs_Web-basedTools_YACs_Interview_Usability_RawData: Pseudonymized word file including 13 transcripts having the qualitative data from interview and usability testing with the following metadata – <ol> <li><strong>Population:</strong> young adult caregivers aged 18-25 years studying in the Netherlands; 13 participants in total</li> <li><strong>Time point of measurement:</strong> data was collected from October 2021 till February 2022</li> <li><strong>Type of data:</strong> qualitative and quantitative</li> <li><strong>Measurements included, topics covered: </strong>Caregiving challenges, support needs and barriers, usability needs, preferences and issues towards eHealth tool</li> <li><strong>Short procedure conducted to receive data</strong>: Online interviews</li> </ol> </li> <li>ENTWINE_Needs_Web-basedTools_YACs_Questionnaires_RawData: Excel sheet having the quantitative questionnaire raw data with the following metadata <ol> <li><strong>Population:</strong> young adult caregivers aged 18-25 years studying in the Netherlands; 13 participants in total</li> <li><strong>Time point of measurement:</strong> data was collected from October 2021 till February 2022</li> <li><strong>Type of data:</strong> qualitative and quantitative</li> <li><strong>Measurements included, topics covered: </strong>User experience (user experience questionnaire [8]), satisfaction of using the web-based tool (After scenario questionnaire [9]), Intention of use and persuasive potential of the eHealth tool (persuasive potential questionnaire [10])</li> <li><strong>Short procedure conducted to receive data</strong>: Online questionnaire</li> </ol> </li> </ol> <p><strong>Data collection details</strong></p> <ol> <li>All data was collected, processed, and archived in accordance with the General Data Protection Regulation (GDPR) and the FAIR (Findable, Accessible, Interoperable, Reusable) principles under the supervision of the Principal Investigator.</li> <li>The principal researcher and a team of experts (supervisors) in the field of health psychology and eHealth (University of Twente, The Netherlands) reviewed the scientific quality of the research. The studies were piloted and tested before starting the collection of the data. For the survey study, the researchers monitored the data collection weekly to ensure it was running smoothly.</li> <li>The ethical review board, Centrale Ethische Toetsingscommissie of the University Medical Center Groningen, The Netherlands (CTc), granted approval for this research (Registration number: 202000623).</li> <li>Participants digitally signed informed consent for participating in the study.</li> </ol> <p><strong>Terms of use</strong></p> <ol> <li>Interested persons can send a data request by contacting the principal investigator (Prof. dr. Mariët Hagedoorn, University Medical Center Groningen, the Netherlands <a href="mailto:mariet.hageboorn@umcg.nl">mariet.hageboorn@umcg.nl</a>).</li> <li>Interested persons must provide the research plan (including the research question, methodology, and analysis plan) when requesting for the data.</li> <li>The principal investigator reviews the research plan on its quality and fit with the data and informs the interested person(s).</li> <li>(Pseudo)anonymous data of those participants who agreed on the reuse of their data is available on request for 15 years from the time of completion of the PhD project.</li> <li>Data will be available in Excel or SPSS format alongside the variable codebook after the completion of this PhD project and publication of the study results.</li> </ol> <p><strong>References</strong></p> <p>1. Wagman P, Håkansson C. Introducing the Occupational Balance Questionnaire (OBQ). Scand J Occup Ther 2014;21(3):227–231. PMID:24649971</p> <p>2. Schaufeli WB, Desart S, De Witte H. Burnout assessment tool (Bat)—development, validity, and reliability. Int J Environ Res Public Health 2020;17(24):1–21. PMID:33352940</p> <p>3. Watson D, Clark LA, Tellegen A. Development and Validation of Brief Measures of Positive and Negative Affect: The PANAS Scales. J Pers Soc Psychol 1988;54(6):1063–1070. PMID:3397865</p> <p>4. Pavot W, Diener E, Colvin CR, Sandvik E. Further Validation of the Satisfaction With Life Scale; Evidence for the Cross-Method Convergence of Well-Being Measures. J Pers Assess 1991;57(1):149–161. PMID:1920028</p> <p>5. Tarlow BJ, Wisniewski SR, Belle SH, Rubert M, Ory MG, Gallagher-Thompson D. Positive aspects of caregiving: Contributions of the REACH project to the development of new measures for Alzheimer’s caregiving. Res Aging 2004;26(4):429–453. [doi: 10.1177/0164027504264493]</p> <p>6. Hendrick SS, Dicke A, Hendrick C. The relationship assessment scale. J Soc Pers Relat 1998;15(1):137–142. [doi: 10.1177/0265407598151009]</p> <p>7. Berg CA, Schindler I, Maharajh S. Adolescents’ and Mothers’ Perceptions of the Cognitive and Relational Functions of Collaboration and Adjustment in Dealing With Type 1 Diabetes. J Fam Psychol 2008;22(6):865–874. PMID:19102607</p> <p>8. Laugwitz B, Held T, Schrepp M. Construction and evaluation of a user experience questionnaire. Lect Notes Comput Sci (including Subser Lect Notes Artif Intell Lect Notes Bioinformatics) 2008;5298 LNCS:63–76. [doi: 10.1007/978-3-540-89350-9_6]</p> <p>9. Lewis JR. Psychometric evaluation of an after-scenario questionnaire for computer usability studies. ACM SIGCHI Bull 1991;23(1):78–81. [doi: 10.1145/122672.122692]</p> <p>10. Meschtscherjakov A, Gärtner M, Mirnig A, Rödel C, Tscheligi M. The Persuasive Potential Questionnaire (PPQ): Challenges, drawbacks, and lessons learned. Lect Notes Comput Sci (including Subser Lect Notes Artif Intell Lect Notes Bioinformatics) 2016;9638:162–175. [doi: 10.1007/978-3-319-31510-2_14]</p> <p> </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.