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13,499 results for “researcher”
Pilot 1 - Research Data
<p>Three main aims inform the collection and generation of data in Pilot 1: [1] achieving the pilots' research objectives, as outlined in the previous section, and [2] managing and monitoring the pilots' implementation and [3] informing technical developments in the ARETE WWL app. Anonymised student information has been collected in the form of pre and post intervention standardised tests of reading and spelling competence, in order to compare and evaluate the students’ progress with or without the use of the interactive AR content toolkit. Only the students code, month and year of birth and assessment outcomes will be shared outside the school environment for analysis. The anonymised paper NARA II and VERNON test forms will be stored by participating schools. In addition parents of the students in the intervention and control groups have been requested to complete an anonymised online ‘ProfilED’ Case History form, which is sent directly to WWL for data analysis. The sender's email was not logged nor is there any identifying information on the form. The information gathered in this form is essential for the analysis of Pilot 1 test outcomes as it can identify if certain developmental patterns or comorbid issues enhance or detract from AR intervention outcomes. This data has been securely stored on a server, PC and on an external hard drive (stored in a safe off site).</p> <p>Pilot 1 collects only personal information (name, surname, contact information) from the participating teachers, in the form of consent forms (necessary to obtain the participants’ consent to participate in the ARETE research activities). These consent forms have been collected by European Schoolnet (EUN) and stored on EUN’s secure servers. All personal data collected within the project activities will be anonymised upon completion of the project, apart from data that need to be kept for the full audit period.</p> <p>In accordance with the data minimization principle, no personal information from the participating students or their parents/legal guardians will be transferred to EUN or to other members of the ARETE consortium for the purpose of Pilot 1. The only personal information collected from students and their parents/legal guardians has been for the purpose of acquiring consent/assent, and these forms have been collected at the level of each participating school. EUN has established a Memorandum of Understanding with each participating school in Pilots 1, in order to ensure that: [1] the heads of the participating schools are appropriately informed about the research carried out in the context of the ARETE project and have provided their agreement for the school to participate in research and [2] that the schools have all the necessary permissions from the parents/legal guardians of the pupils participating in the ARETE research or, in the case such permissions do not exist at the school level, ensure that the schools collect all necessary consent forms from the participating students. This measure is meant to reduce the transfer of sensitive personal information between organisations unless absolutely necessary.</p>
Pilot 3 - Research Data
<p>Data collected for the Pilot 3 have been used for the following main purposes:</p> <ul> <li>to develop the contents of the PBIS-AR application (task 5.1 “Analysis of PBIS Requirements for ARETE” of WP5 “Interactive AR for PBIS”)</li> <li>to develop the contents of the PBIS behavioral research lessons (task 5.2 “Analysis of PBIS Requirements for ARETE” of WP5”Interactive AR for PBIS”)</li> <li>to investigate the use of AR as a tool for PBIS, evaluating the incremental value of integrating AR contents within PBIS in promoting school-wide and class-wide positive behaviours (task 6.3 of WP6”Pilots’ Implementation Deployment and Evaluation”).</li> </ul> <p> </p> <p>All collected data can and will be used to realize publications in academic and popular psychological journals, as well as for poster and oral presentation at conferences. The data will consist of:</p> <p>(1) quantitative data: questionnaire and survey data that will be collected through an online and paper-based survey procedure at one or more time points during the pilot (for specifics, see Annex G “06.2022 - ARETE P3 - Assessment Strategy” of D5.3 “WP5 - D5.3: Analysis of PBIS Requirement for ARETE - Update D5.1”) .</p>
Supporting Data Ferguson, Camenzind, et al., "Measurement-induced induced population switching", Phys. Rev. Research 5, 023028 (2023)
<p>This repository contains data for the publication "Measurement-induced population switching", Phys. Rev. Research 5, 023028 (2023) by Ferguson, Camenzind, <em>et al</em>.</p> <p><strong>Abstract</strong></p> <p>Quantum information processing is a key technology in the ongoing second quantum revolution, with a wide variety of hardware platforms competing toward its realization. An indispensable component of such hardware is a measurement device, i.e., a quantum detector that is used to determine the outcome of a computation. The act of measurement in quantum mechanics, however, is naturally invasive as the measurement apparatus becomes entangled with the system that it observes. This always leads to a disturbance in the observed system, a phenomenon called quantum measurement backaction, which should solely lead to the collapse of the quantum wave function and the physical realization of the measurement postulate of quantum mechanics. Here we demonstrate that backaction can fundamentally change the quantum system through the detection process. For quantum information processing, this means that the readout alters the system in such a way that a faulty measurement outcome is obtained. Specifically, we report a backaction-induced population switching, where the bare presence of weak, nonprojective measurements by an adjacent charge sensor inverts the electronic charge configuration of a semiconductor double quantum dot system. The transition region grows with measurement strength and is suppressed by temperature, in excellent agreement with our coherent quantum backaction model. Our result exposes backaction channels that appear at the interplay between the detector and the system environments, and opens new avenues for controlling and mitigating backaction effects in future quantum technologies.</p>
A dataset of metadata for UK academic institutional repositories, including a census of research software contained.
<p>A dataset of metadata for UK academic institutional repositories, including a census of research software contained.</p> <table> <tbody> <tr> <td><strong>URL</strong></td> <td>The OAI url</td> </tr> <tr> <td><strong>id</strong></td> <td>CORE Identifier</td> </tr> <tr> <td><strong>openDoarId</strong></td> <td>Open DOAR identifier</td> </tr> <tr> <td><strong>name</strong></td> <td>Name of repository</td> </tr> <tr> <td><strong>Russell_member</strong></td> <td>If the university is a member of the Russell Group of research intensive universities</td> </tr> <tr> <td><strong>RSE_group</strong></td> <td>If an RSE group is present (based on Soc of RSE data)</td> </tr> <tr> <td><strong>email</strong></td> <td>Redacted</td> </tr> <tr> <td><strong>uri</strong></td> <td>Not used</td> </tr> <tr> <td><strong>uni_sld</strong></td> <td>Second level domain (the part of the url between . And .ac.uk</td> </tr> <tr> <td><strong>homepageUrl</strong></td> <td>University website</td> </tr> <tr> <td><strong>source</strong></td> <td>Not used</td> </tr> <tr> <td><strong>ris_software</strong></td> <td>the Research Information System software used</td> </tr> <tr> <td><strong>ris_software_enum</strong></td> <td>Resolve ris_software into similar types (e.g. Eprints 3, EPrints3.3.16 both equal eprints)</td> </tr> <tr> <td><strong>metadataFormat</strong></td> <td>the protocol used for metadata</td> </tr> <tr> <td><strong>createdDate</strong></td> <td>Repository creation date</td> </tr> <tr> <td><strong>location</strong></td> <td>location of university</td> </tr> <tr> <td><strong>logo</strong></td> <td>University logo (resolves in error)</td> </tr> <tr> <td><strong>type</strong></td> <td>Only = Repository for this dataset. Can be = journal etc.</td> </tr> <tr> <td><strong>stats</strong></td> <td>Not used</td> </tr> <tr> <td><strong>contains_software_set</strong></td> <td>Whether the OAI-PMH software set is present in the repository.</td> </tr> <tr> <td><strong>Num_sw_records</strong></td> <td>The response of the OAI-PMH query for software (erroneous as discussed in paper)</td> </tr> <tr> <td><strong>Error</strong></td> <td>The category of error returned by the experiment’s OAI-PMH queries (see paper)</td> </tr> <tr> <td><strong>Manual_Num_sw_records</strong></td> <td>The true amount of software contained in the repository as found by a manual exhaustive search of each university website</td> </tr> <tr> <td><strong>Category</strong></td> <td>Whether the repository (a) contains software; (b) can contain software, but doesn’t yet; (c) has no separate type of research output called software or similar</td> </tr> </tbody> </table> <p> </p>
Making Social Science Research Transparent [Webinar recording]
<p>High-quality data have the potential to be reused in many ways. Archiving and publishing your data properly is at the core of making your data FAIR and will enable both your future self as well as others to get the most out of your data. Recently, more and more scientific journals are implementing open data policies, leading to researchers' dilemmas about where, when and how to publish the data. Consequently, the way that social science research is conducted and disseminated is gradually changing. A crucial element of that change is research transparency. Introduction to the topic took place in the first part of the event.</p> <p>In the second part, panellists presented in-depth the processes, policies and tools implemented for facilitating transparent research in the social sciences. They discussed the processes that need to be in place for an open research cycle, the role of data archives and repositories in sharing research data and materials, tools for reproducing research findings in practice, collaborations between archives and social science journals, and implementing Transparency and Openness Promotion Guidelines in different social science disciplines.</p> <p>The video is available on<a href="https://www.youtube.com/watch?v=B-phrIMETGk"> the CESSDA Training YouTube channel</a>.</p>
Research Data Management and data protection in the Social Sciences [Workshop recording]
<p>This online workshop organized by The Austrian Social Science Data Archive (AUSSDA) focused on the Research Data Management basics, Data Management Plans and common data protection issues in the Social Sciences.</p> <p>The first part of the workshop was dedicated to RDM basics and Data Management Plans (DMPs). In many projects, DMPs are mandatory deliverables that need to be submitted at the beginning of a project and are updated throughout the project life cycle. During the workshop, it was explained which aspect funders expect to be part of DMPs in Social Sciences and how researchers can benefit from (writing) these documents.</p> <p>In the second part of the workshop, data protection issues that are common in Social Sciences were addressed and how they can be handled. In particular, differences in the curation of quantitative and qualitative data need in order to comply with data protection regulations in general and AUSSDA deposit guidelines in particular. Presentation on how AUSSDA scans quantitative data for potential data protection violations using STATA and gives participants the opportunity to test the code on their own data and devices.</p> <p>The video is available on<a href="https://www.youtube.com/watch?v=DhiL9J-Iwqg"> the CESSDA Training YouTube channel</a>.</p> <p> </p>
Joint Research Agenda and Research Opportunities
<p>This dataset includes the opinions of different sectoral researchers regarding the importance of the assembled 144 research topics in the open data domain. The survey was conducted in March 2022.</p>
Pilot 4 - Research Data
<p>Pilot 4: Teaching with eXtended Reality – Evaluating the MirageXR Authoring Tool</p> <p>Pilot 4 aims to accelerate the uptake of AR in education, by providing an authoring tool and learning management system to teachers. We believe that introduction at scale requires to put tailored authoring tools in the hands of teachers to support the production of bespoke AR learning experiences for the mainstream as well as for the Long Tail. The MirageXR platform is user-friendly and does not require any prior AR experience. Participation is on a voluntary basis, as a choice under free will.</p> <p><strong>Target Group</strong> are teachers who:</p> <ul> <li>have a good level of English language (B2 in Reading and B1 in Writing + Speaking)</li> <li>are pre-service or in-service teachers</li> <li>are willing to participate</li> <li>have an AR-compatible iOS or Android phone or tablet</li> </ul> <p>With this pilot study (ARETE Pilot 4), we seek to evaluate quantitatively and qualitatively, in which ways and how well our authoring toolkit supports teachers in designing XR learning experiences. The ARETE Project Pilot 4 is evaluating novel AR interactive technologies for teaching. The data we gather from this project would help design and develop more effective and efficient digital education solutions and contribute to improving XR Open Educational Resources.</p> <p>In pilot 4, data are collected (1) via online surveys, (2) in interviews, (3) from work products, and (4) from system interaction log files. These data are collected to validate the MirageXR toolkit applied in the pilot and to evaluate the teachers’ experiences during the pilot with regards to their user experience (technical perspective) and to their opinions on the potential role of interactive AR toolkits in teaching and learning processes (pedagogical perspective). The data collected in pilot 4 for these purposes will further be used for scientific publications, e.g., in scientific journals and at conference</p> <p> </p>
CaRCC Research Computing and Data (RCD) Workforce Survey Data 2021 - Part 2
<p>Data sets to accompany "Compensation of Academic Research Computing and Data Professionals"</p> <p>Paper citation: Christina Maimone, Carrie Brown, Kimberly Grasch, Chris Reidy, and Ashley Stauffer. 2023. Compensation of Academic Research Computing and Data Professionals. In Proceedings of Practice and Experience in Advanced Research Computing (PEARC23). ACM, New York, NY, USA, 8 pages. https://doi.org/10.1145/3569951.3593599</p> <p>Survey questions: Maimone, Christina, Yockel, Scott, Middelkoop, Timothy, Alameda, Jay, Stauffer, Ashley, & Neeser, Amy. (2021). CaRCC Research Computing and Data (RCD) Workforce 2021 Census Questions (1.0). Zenodo. https://doi.org/10.5281/zenodo.5914431</p>
UTHSC Publication Research Category (ANZSRC 2020) Co-Occurrence
<p>This data visualization is a bibliometric analysis of University of Tennessee Health Science Center publications for the years 2018-2020. It was created for senior University leadership for the purposes of strategic planning and identifying research areas of strength.</p> <p>Bibliographic data was supplied by Dimensions by Digital Science. The chord graph was created in Tableau and demonstrates relationship pairs of Fields of Research (ANZSRC 2020) categories. Each publication record may be associated with 1+ categories. The graph highlights the frequency of category pairings within a single publication record. I.e. publications categorized as "Immunology" are most commonly also categorized with "Medical Microbiology," indicating overlap in this area of research.</p> <p>This graph was created using instructions from Marc Reid's datavis.blog entry "Creating a Chord Diagram with Tableau Prep and Desktop" (<a href="https://datavis.blog/2020/07/02/creating-chord-diagram-in-tableau/">https://datavis.blog/2020/07/02/creating-chord-diagram-in-tableau/</a>).</p> <p>The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.</p>
How to Ensure Researchers Share Their FAIR Data: Practical Tips and Tools [Online Workshop, Recording]
<p>The online hands-on workshop was aimed at trainers and support staff covering critical elements of data sharing and available tools and resources for supporting Open Science including:<br> • Open Science resources and Data Management Planning<br> • Consent and Ethical considerations<br> • Legislation and Licence frameworks<br> The objectives of the workshop were i) to raise awareness of key tools and resources available for Open Science training ii) to enable a platform to exchange ideas regarding key training topics and iii)n to provide training materials and worksheets for future reuse.<br> The workshop consisted of presentations, demos, a roundtable discussion on ethical considerations, a showcase of licence frameworks at different European archives and an exercise with all participants fostering an exchange of experiences focused on learnt lessons.</p> <p>The video is available on<a href="https://www.youtube.com/watch?v=uztTCRFRZHg"> the CESSDA Training YouTube channel</a>.</p>
Data of Chinese treatment group for the research work "Disentangling material, social, and cognitive determinants of human behavior and belief".
<p>This repository contains data files of Chinese treatment group for the research work "Disentangling material, social, and cognitive determinants of human behavior and belief".</p>
A mapping of keywords from published papers on alien squirrels to biological invasion research themes
<p><strong>Context</strong></p> <p>This dataset was used to produce the worldl and the graphs in the editorial to the research topic <a href="https://www.frontiersin.org/research-topics/29270/ecology-impact-and-management-of-squirrel-invasions"><em>Ecology, impact and management of squirrel invasions</em></a> (La Morgia et al. 2023).</p> <p><strong>Contents of the dataset</strong></p> <p>The dataset contains the keywords of papers since 2000 harvested with a Web of Science search (performed on 29/05/2023) using the advanced search string TS=(invasive squirrel) OR TI=(invasive squirrel) OR AB=(invasive squirrel). We screened the search results, excluding papers irrelevant to alien squirrels, for example, papers on computer science or physiology, medical or other aspects without any bearing to conservation science. To do this, we checked the abstract and keywords of the papers. Out of the 401 initial papers, after this first screening, we kept 217 in this dataset. The keywords of these papers were manually assigned to alien squirrel research topics by the authors of this dataset (using an own categorisation) and then mapped to the seven broad themes of invasive alien species research of <a href="https://doi.org/10.1007/s10530-023-03067-7">Stevenson et al. (2023)</a>: </p> <ol> <li>Ecosystems: topics which discuss a specific region, or biome, or focused on a particular species strongly associated with one ecosystem type;</li> <li>Monitoring: topics regarding all aspects of monitoring, including detection, identification, and distributional mapping;</li> <li>Management and decision-making: topics discussing the management and socio-political aspects of invasion science, such as prevention, control, and policy;</li> <li>Interactions: topics discussing the interactions with native species, or the effects of those interactions</li> <li>Assessing change: topics focused on studying and analysing temporal and ecological change;</li> <li>Traits: topics that explored the characteristics of alien squirrels;</li> <li>Invasion mechanisms: topics discussing dispersal pathways and drivers of spread.</li> </ol> <p><strong>Dataset description</strong></p> <p>Every row (N = 1275) in the comma-separated .csv represents one original keyword with reference to the paper in which that keyword appears and mapped to the research topics on invasive squirrels and the broad themes in invasion biology research. The .csv contains the following fields:</p> <ul> <li>ID: a unique ID assigned to the combination of an original keyword and the corresponding paper harvested from the WoS search</li> <li>original_keyword: the original keywords associated with the paper (WoS search)</li> <li>keyword_topic: categorization of original keywords into topics related to invasive squirrel research by La Morgia et al. (2023)</li> <li>mapped_category: mapping to one of the seven broad themes of invasive alien species research of <a href="https://doi.org/10.1007/s10530-023-03067-7">Stevenson et al. (2023)</a> as listed and described above</li> <li>authors: author(s) of the paper (WoS search)</li> <li>year: publication year of paper (WoS search)</li> <li>title: title of the paper (WoS search)</li> <li>journal: full journal name (WoS search)</li> <li>doi: full doi of the paper (WoS search)</li> </ul> <p><strong>Potential applications of the dataset</strong></p> <p>This dataset can be used to reproduce the graphs in La Morgia et al. (2023) or to perform more in-depth review or analysis of the literature on alien squirrel invasions. For more information and graph code, we refer to <a href="https://github.com/Vale-LaMo/squirrels">this GitHub repository</a>.</p>
A high-throughput 3D X-ray histology facility for biomedical research and preclinical applications - Underlying Data
<p><strong>Video files and logs</strong></p> <p>Single-slice and thick-slice roll* source videos are included. Each video is accompanied by a .txt log that contains information about the source file, slice thickness, and a brief description of the visualization mode.</p> <p>List of files:</p> <ul> <li>20211019-23h59m_20xAvgInt.mp4</li> <li>20211019-23h59m_20xAvgInt.txt</li> <li>20211019-23h59m_20xMaxInt.mp4</li> <li>20211019-23h59m_20xMaxInt.txt</li> <li>20211019-23h59m_20xStDev.mp4</li> <li>20211019-23h59m_20xStDev.txt</li> <li>20211019-23h59m_XYSliceRoll.mp4</li> <li>20211019-23h59m_XYSliceRoll.txt</li> <li>20211019-23h59m_XZSliceRoll.mp4</li> <li>20211019-23h59m_XZSliceRoll.txt</li> <li>20211019-23h59m_YZSliceRoll.mp4</li> <li>20211019-23h59m_YZSliceRoll.txt</li> </ul> <p>* <em>Thick-slice rolling is a 2D thick-slice viewing that allows rolling of a pre-selected number of slices (n) along the z-axis of the 3D data. A single thick-slice roll forwards is accomplished by translating the thick-slice by one single slice forwards; that is moving forward by one (+1) slice from the first and nth element and reapplying the criteria or operations to the new slice sub-stack.</em></p> <p><strong>Volume XRH data</strong><br> These are processed raw volume file saved in .raw and/or .tiff format, which are resliced to a histology-relevant orientation and/or have been enhanced using noise reduction (3D median filter) and/or ct-artefact removal techniques (e.g. cBC identifies a bandpass filter used to remove intensity variations originating from the histology cassette).</p> <p>List of volume files:</p> <ul> <li><strong>32220_20200703_XRH_2504_OLK_DEMO02019-FFPE_1620x1959x164x16bit.raw</strong> <ul> <li>sample: Human lung adenocarcinoma</li> <li>histology-relevant resliced volume (2x2x2 3D medial filter applied)</li> <li>import as 1620 x 1959 x 164 x 16-bit, big-endian; voxel edge size (mm): 0.0160042 isotropic</li> </ul> </li> <li><strong>cBC_32220_20200703_XRH_2504_OLK_DEMO02019-FFPE_1588x1674x164x16bit.raw</strong> <ul> <li>sample: Human lung adenocarcinoma</li> <li>cassette artefacts background correction (bandpass) of volume 32220_20200703_XRH_2504_OLK_DEMO02019-FFPE_1620x1959x164x16bit.raw</li> <li>import as 1620 x 1959 x 164 x 16-bit, big-endian; voxel edge size (mm): 0.0160042 isotropic</li> </ul> </li> <li><strong>Med3D_HPass_2111_20190606_MEDX_2234_EH_HN2_recon_2000x1952x501x32bit.raw</strong> <ul> <li>sample: Human head and neck tumour</li> <li>histology-relevant resliced volume (1x1x1 3D medial filter applied)</li> <li>import as 2000 x 1952 x 501 x 32-bit, big-endian; voxel edge size (mm): 0.00999782 isotropic</li> </ul> </li> </ul> <p><strong>Conventional Histology and correlative imaging</strong></p> <ul> <li><strong>HN2_Level001_MEDX080_Manual_BW_Series4.tif</strong> <ul> <li>H&E histology slice of the human head and neck tumour sample shown in "Med3D_HPass_2111_20190606_MEDX_2234_EH_HN2_recon_2000x1952x501x32bit.raw"</li> </ul> </li> <li><strong>HN2_Level001_MEDX080_Manual_BW</strong> <ul> <li>manual landmark selection used for registering the conventional histology slice onto the μCT slice</li> </ul> </li> <li><strong>HN2_MEDX_rotated_0080.tif</strong> <ul> <li>Slice 80 from volume "Med3D_HPass_2111_20190606_MEDX_2234_EH_HN2_recon_2000x1952x501x32bit.raw" that corresponds to histological slice "HN2_Level001_MEDX080_Manual_BW"</li> </ul> </li> </ul>
CS3MESH4EOSC Final Event Science Mesh - Unlocking Open Science and Collaborative Research Landscape
<p>The recap video of CS3MESH4EOSC final event. The CS3MESH4EOSC final event, took place on 22 June 2023, at the EGI Conference in Poznan (Poland), showcased how the Science Mesh is contributing to an easier and more robust open science across Europe, thanks to novel approaches for data sharing and synchronisation.</p> <p><strong>The first half of the event</strong> will count with live demonstrations, where each data service from the Science Mesh will be presented from a user-perspective point of view. Event attendees will get practical information on how they can join the Science Mesh as a researcher, a software developer or a service provider. The event will also bring together representatives of Science Mesh use cases, who will explain how Science Mesh is making a difference in their lives, thanks to easier data sharing and synchronisation. A panel discussion with representatives of different sectors, from research to industry and education, will discuss the most urgent trends & priorities for cross-border science collaboration between different sciences.</p> <p><strong>The second half of the event</strong> will be focused on the technical novelties within the Science technical foundation. A series of demonstrations will be presented, followed by a panel discussion, with representatives of CS3MESH4EOSC members that are part of the EOSC Task Forces, on how the Science Mesh contributes to EOSC’s success and the overall EOSC Strategic Research and Innovation Agenda (SRIA).</p>
RESEARCH DATA IN PALEOBOTANICAL: DATASET OF THE THIN PETROGRAPHIC SLIDES AT FOSSIL WOODS
<p>Objective: The study aims to disseminate and analyze the collection of fossil wood stored in the collection of thin slides sections of the paleobotany collection of the Department of Paleontology and Stratigraphy of the Institute of Geosciences of a University in southern Brazil. Thin sheets of petrified wood are described, while research data used for research in Geosciences, specifically, seeks to compose a model for the use of this type of sheet in paleobotany, allowing to visualize its representativeness in studies published in 40 years, will be obtained the anatomical characteristics of fossil woods and aiming to define their systematic affinities as a specific typology of research data in Geosciences.<br> Methods: The methodology involves interviewing a paleobotany specialist and using different techniques applied in metric studies to map their scientific production. Thus, a dataset of (20) thin slides sections of petrified fossil wood used in the study Stressing environmental conditions in the “petrified forest” from the Mata Sequence in the Triassic context of the Paraná Basin published by the Journal of South American Earth Sciences, according to (DOI: 10.1016/j.jsames.2023.104415). According to the methodology used, these thin petrified wood sheets have the potential to identify paleoclimatic signatures based on the anatomical characteristics of fossil wood. In addition to this case study, which represents a collection of more than (2.000) thousand blades of fossil wood and about 40 years of research, this paleobotany collection of the Department is reused in methodology classes. It comprises a database of research physicists that provides information about anatomical features, systematic affinities, paleoclimatic conditions, and paleoenvironmental insights.<br> Potential for reuse: Its reuse, registration, storage, identification, and preservation of thin sections as a type of research data used by paleobotany aims to improve the methodology associated with the organization of a physical database of the institution. The research data, and blades of fossil wood, are being digitized, and soon, all will be available under the CC BY 4.0 license in the ZENODO repository, according to the sample described here in this data paper. (DOI Zenodo) and may be reused by optical and electronic scanning microscopy software.</p> <p> </p>
Rapid Review Dataset for Seeking Enlightenment: Incorporating Evidence-Based Practice Techniques in a Research Software Engineering Team
<p>A collection of evidence briefings produced through a rapid literature review protocol the Department of Software Engineering and Research at Sandia National Laboratories. These briefings are described in our research paper, "Seeking Enlightenment: Incorporating Evidence-Based Practice Techniques in a Research Software Engineering Team", which was accepted for publication at the 1st Annual Conference of the United States Research Software Engineer Association (US-RSE'23).</p> <p>Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. SAND2023-06549O.</p>
M4Raw: A multi-contrast, multi-repetition, multi-channel MRI k-space dataset for low-field MRI research [V1.6]
<p>V1.6 release notes:</p> <ul> <li>The test subset is released, which contains T1w (6 repetitions/subject), T2w (6 repetitions/subject), and FLAIR (4 repetitions/subject) data from 25 new subjects. These data have passed motion inspection, but one should note that due to the doubled repetition numbers, the average inter-contrast motions are around twice larger than those in the training and validation subsets. To facilitate users, we release the ground truth images as well, but please do not use them during hyperparameter tuning.</li> </ul> <p>V1.5 release notes:</p> <ul> <li>T1w Gradient echo (GRE) data for all 183 subjects are released. Note that the phase encoding direction for GRE data is in the AP direction, different from other contrasts. These GRE data were not checked for motions.</li> <li>A few incorrect records of patient_id were corrected in the H5 files.</li> <li>Scans 2022062708 and 2022062709 were removed due to duplication. Two new scans were added to replace them.</li> </ul> <p>V1.1 release notes:</p> <ul> <li>Please refer to https://www.nature.com/articles/s41597-023-02181-4 for details.</li> </ul>
Research Excellence Framework (REF) 2021 enhanced submissions dataset
<p>An enhanced version of the public <a href="https://results2021.ref.ac.uk/">REF 2021 submissions dataset</a>, produced by Jisc, which contains metadata for all outputs submitted to the exercise. Metadata has been cleaned and new fields have been added to increase the potential for analytical purposes, e.g. by identifying where the publisher exists as an imprint of a larger parent company.</p> <p>For its own analytical purposes, Jisc focused on long-form output types (books and parts of books), but cleaning measures were performed on the entire dataset, uploaded here.</p>
Aventa AV-7 ETH Zurich Research Wind Turbine SCADA and high frequency Structural Health Monitoring (SHM) data
<p><strong>General description of wind turbine: </strong>The ETH owned wind turbine is Aventa AV-7, manufactured by Aventa AG in Switzerland and was commissioned in December 2002. The turbine is operated via a belt-driven generator and a frequency converter with a variable speed drive. The rated power of the Aventa AV-7 is 7 kW, beginning production at a wind speed of 2 m/s and having a cut-off speed of 14 m/s. The rotor diameter is 12.8 m with 3 rotor blades, and a hub height is 18m. The maximum rotational speed of the turbine is 63 rpm. The tower is a tubular steel-reinforced concrete structure, supported on concrete foundation, while the blades are made of glassfiber with a tubular steel main-spar. The turbine is regulated via a variable-speed and variable pitch control system.</p> <p><strong>Location of site: </strong>The wind turbine is located in Taggenberg, about 5 km from the city centre of Winterthur, Switzerland. This site is easily accessible by public transport and on foot with direct road access right next to the turbine. This prime location reduces the cost of site visits and allows for frequent personal monitoring of the site when test equipment is installed. The coordinates of the site are: 47°31'12.2"N 8°40'55.7"E.</p> <p><strong>Control and measurement systems and signals: </strong>The turbine is regulated via a variable-speed and collective variable pitch control system.</p> <p><strong>SHM Motivation: </strong>Designed and commissioned in 2002, the Aventa wind turbine in Winterthur is soon reaching its end of design lifetime. In order to assess the various techniques of predicting the remaining useful lifetime, a Structural Health Monitoring (SHM) campaign was implemented by ETH Zurich. The monitoring campaign started in 2020, and is still ongoing. In addition, the setup is used as a research platform on topics such as system identification, operational modal analysis, faults/damage detection and classification. We analyze the influence of operational and environmental conditions on the modal parameters and to further infer Performance Indicators (PIs) for assessing structural behavior in terms of deterioration processes.</p> <p><strong>Data Description: </strong>The tower and nacelle have been instrumented with 11 accelerometers distributed along the length of the tower, nacelle main frame, main bearing and generator. Two full bridge strain gauges are installed on the concrete tower based measuring fore-aft and side-side strain (and can be converted to bending moments) – all acceleration and strain signals sampled at 200Hz. Temperature and humidity are measured at the tower base – 1Hz data. In additional we are collecting operational performance data (SCADA), namely: wind speed, nacelle yaw orientation, rotor RPM, power output and turbine status – SCADA signals are sampled at 10Hz. See appendix for further details of the sensors layout.</p> <p>The measurements/instrumentation setup, type and layout is provided in the pdf files.</p> <p><strong>The data:</strong> the data is provided in zip files corresponding to four use-cases as follows:</p> <ul> <li>Normal operation data for system identification</li> <li>Aerodynamic imbalance on one blade</li> <li>Rotor icing event</li> <li>Failure of the flexible coupling of the linear drive of the collective pitch system</li> </ul> <p>The data for each of the four uses-cases is organized in zip files. The content of each zip file is as follows:</p> <ul> <li>Time-series data in HDF5 format</li> <li>Metadata: <ul> <li>Turbine specification (Aventa-AV-7.json and Aventa-AV-7.yaml)</li> <li>Sensor specification (Aventa_sensors.json )</li> <li>Unstructured description of the Aventa Turbine and the installed sensors (Aventa_Sensors_Specs.xlsx)</li> </ul> </li> <li>Semantic artifacts: <ul> <li>WindIO Wind Turbine YAML schema describing turbine specifications (IEAontology_schema.yaml)</li> <li>Sensor specification JSON schema (sensors_schema.json)</li> </ul> </li> <li>Media: Pictures of leading edge roughness and a clip of wind turbine operation</li> <li>Code: Jupyter notebook containing example code to load metadata from JSON and data from HDF5 files (example.ipynb)</li> </ul> <p>Additional data is available upon request, please contact:</p> <ul> <li>Prof. Dr. Eleni Chatzi (chatzi@ibk.baug.ethz.ch)</li> <li>Dr. Imad Abdallah (ai@rtdt.ai , abdallah@ibk.baug.ethz.ch)</li> </ul> <p>For further details or questions, please contact:</p> <p>Prof. Dr. Eleni Chatzi<br> Chair of Structural Mechanics & Monitoring</p> <p>ETH Zürich<br> <a href="http://www.chatzi.ibk.ethz.ch/">http://www.chatzi.ibk.ethz.ch/</a></p>
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