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41,236 results for “Reviews”
A 31-Year Bibliometric Review of Team Effectiveness Research: Evolution, Trends, and Future Directions (DATA).
<p>This dataset is derived from a comprehensive study of team effectiveness over three decades, utilizing bibliometric techniques to examine scholarly publications across multiple databases. The repository includes bibliometric data from 6,051 publications related to team effectiveness, featuring metadata such as authors, titles, publication years, citations, and keywords.</p> <h3>Repository Structure:</h3> <p>The data shared in this repository is organized as follows:</p> <ul> <li><strong>Bibliometrix database.xlsx:</strong> This excel file contains information on 6051 publications in the field of Team Effectiveness downloaded from the Scopus and Web of Science databases using specific search terms and inclusion criteria detailed in our associated paper (see our publication for more information on the methodology). The file contains the necessary headers for direct use in the Biblioshiny interface of the bibliometrix library for R.</li> <li><strong>List of stop words.txt:</strong> This file contains keywords, separated by commas, that we have decided to eliminate from our analyses due to their potential to introduce bias in the results.</li> <li><strong>List of synonyms.txt:</strong> This file contains groups of semantically synonymous keywords, separated by semicolons. Each line represents a group of synonyms, with the first keyword being the one that Bibliometrix will use to replace all other keywords in that line.</li> <li><strong>Appendix [A-H].pdf:</strong> List of appendices that complement the results of the study carried out.</li> </ul> <h3>Recommended Usage:</h3> <div> <div> <div> <div> <p>This dataset is ideal for researchers interested in conducting new analyses of research trends, co-authorship network analysis, and thematic evolution in the field of team effectiveness. For example, researchers can narrow the scope to focus exclusively on team effectiveness in educational contexts. Our publication provides all the necessary details to replicate or extend our methodology. For any queries related to the data, please contact <strong>Yeray Barrios-Fleitas</strong> at <em><a rel="noreferrer">y.d.c.barriosfleitas@utwente.nl</a></em>.</p> </div> </div> </div> </div> <div> </div> <h3>License and Citation:</h3> <p>The data are distributed under the CC BY license. Please cite any use of this dataset using the following format:<br>Barrios Fleitas, Y., Marcella A.M.G., Eysink, T.H., & Rensink , A. (2025). A 31-Year Bibliometric Review of Team Effectiveness Research: Evolution, Trends, and Future Directions. ZENODO, <a href="https://doi.org/10.5281/zenodo.12082529" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.12082529</a></p>
Circularity3 DDOMP - Project tracksheets: scholarly publications, non-peer-reviewed digital outputs, dataset log, and software log.
<p>Project tracking sheets for the Circularity3 project. </p> <p>The following tracking sheets are provided:</p> <ol> <li>Scholarly Publications </li> <li>Non-peer-reviewed digital outputs</li> <li>Dataset log </li> <li>Software log </li> </ol> <p>For further specifications and explanations of the tracking sheets refer to the Circularity3 DDOMP here: https://doi.org/10.5281/zenodo.11047951</p> <p> </p> <p>This tracking sheets reference widely the PARSEC research teams tracking sheets, to whom we are very grateful for their transparent and insightful documentation.</p> <p>Stall, Shelley, Specht, Alison, Corrêa, Pedro Luiz Pizzigatti, David, Romain, Edmunds, Rorie, Mabile, Laurence, Machicao, Jeaneth, Miyairi, Nobuko, Murayama, Yasuhiro, O'Brien, Margaret, Wyborn, Lesley, & Vellenich, Danton Ferreira. (2023). PARSEC Data and Digital Output Management Plan and Workbook. Zenodo. <a href="https://doi.org/10.5281/zenodo.3891426">https://doi.org/10.5281/zenodo.3891426</a></p>
Identification of biomarkers for the early detection of non-small cell lung cancer: a systematic review and meta-analysis
<p>We sought to identify the best biomarkers for the early diagnosis of LC, using a systematic review of seven databases. We identified 79 articles that focused on the identification and assessment of diagnostic biomarkers and then performed a meta-analysis. This work has been submitted for publication.</p>
Screened literature for mapping review of environmental problem shifting (EPS)
<p>Final literature sample used in manuscript. (506 publications). </p><p>Version 2 after revision. </p><p>Columns from the Scopus API:</p><ul><li>DOI, ISSN, ISBN</li><li>Subjabbr: Abbreviation of Scopus subject area</li><li>Publication year</li><li>Pubname: The name of the journal</li><li>Authkeywords: The article keywords</li><li>Title: The document title</li></ul><p> </p><p>Columns from our classification:</p><ul><li>Articletype: Classification into empirical, review and conceptual-theoretical.</li><li>Documenttype: The type of publication: journal article, book chapter, reports.</li><li>Counter: Marks the 13 studies that find no shifting or positive environmental impacts only.</li><li>Miti measures: The type of mitigation option.</li><li>Split measures: The subtype of mitigation. Only coded for <i>CDR</i>; <i>Solar, hydro and wind power</i> and <i>Other</i>.</li><li>Methods: The method(s) used in empirical papers</li><li>Impacts: The environmental impact.</li><li>Split impacts: The environmental impact specified for subtypes of mitigation.</li></ul>
Review of redshift values of bright AGNs with hard spectra in 4LAC catalog v3
<p>Review of redshift values of bright AGNs with hard spectra in 4LAC catalog</p> <p>FITS table and description file (pdf)</p>
Dataset for Machine Learning Assisted Citation Screening for Systematic Reviews
<p>The work "Machine Learning Assisted Citation Screening for Systematic Reviews" explored the problem of citation screening automation using machine-learning (ML) with an aim to accelerate the process of generating <a href="https://en.wikipedia.org/wiki/Systematic_review#:~:text=Systematic%20reviews%20are%20a%20type,synthesize%20findings%20qualitatively%20or%20quantitatively." rel="nofollow">systematic reviews</a>. Manual process of citation screening involve two reviewers manually screening the searched studies using a predefined inclusion criteria. If the study passes the "inclusion" criteria, it is included for further analysis or is excluded. As apparant through manual screening process, the work considered citation screening as a binary classification problem whereby any ML classifier could be trained to separate the searched studies into these two classes (include and exclude).</p> <p> </p> <p>A physiotherapy citation screening dataset was used to test automation approaches and the dataset includes the studies identified for citation screening in an update to the systematic review by Hilfiker <em>et al.</em> The dataset included titles and abstracts (citations) from 31,279 (deduplicated: 25,540) studies identified during the search phase of this SR. These studies were already manually assessed for relevance and labelled by two reviewers into two mutually exclusive labels. The uploaded file consists of 25,540 data samples, with each data sample separated by a new line. It is a tab separated file and the data in it is structured as shown below. This dataset was manually labelled into include and exclude by Hilfiker <em>et al.</em></p> <p> </p> <table> <tbody> <tr> <td><strong>Title</strong></td> <td><strong>PMID</strong></td> <td><strong>Abstract </strong></td> <td><strong>Class</strong></td> <td><strong>MeSH terms (separated by a pipe)</strong></td> </tr> <tr> <td>Structured exercise improves physical functioning in women with stages I and II breast cancer: results of a randomized controlled trial. </td> <td>11157015</td> <td>Abstract PURPOSE: Self-directed and supervised exercise were compared with usual care in a clinical trial designed to evaluate the effect of structured exercise on physical functioning and other dimensions of health-related quality of life in women with stages I and II breast cancer. PATIENTS AND METHODS: One hundred twenty-three women with stages I and II breast cancer completed baseline evaluations of generic and disease- and site-specific health-related quality of life, aerobic capacity, and body weight. Participants were randomly allocated to one of three intervention groups: usual care (control group), self-directed exercise, or supervised exercise. Quality of life, aerobic capacity, and body weight measures were repeated at 26 weeks...</td> <td>include or exclude</td> <td>Clinical Trial | Comparative Study | Randomized Controlled Trial | Research Support, Non-U.S. Gov't | Antineoplastic Combined Chemotherapy Protocols | Breast Neoplasms | Breast Neoplasms | Breast Neoplasms | Chemotherapy, Adjuvant | Exercise | Female | Humans | Middle Aged | Neoplasm Staging | Quality of Life | Radiotherapy, Adjuvant</td> </tr> </tbody> </table> <p> </p> <p>If you use this dataset in your research, please cite our papers.</p>
A Systematic Review and Meta-Analysis of Mindfulness-Based (Baduanjin) Exercise for the Rehabilitation of Stroke Patients
<p><span>A Systematic Review and Meta-Analysis of Mindfulness-Based (Baduanjin) Exercise for the Rehabilitation of Stroke Patients</span></p>
Data inputs and results from AI-supported title and abstract screening "Lack of evidence regarding markers identifying acute heart failure in patients with COPD: an AI-supported systematic review"
<p>These comma-separated data files were used to conduct the AI supported screening of [Lack of Evidence Regarding Markers Identifying Acute Heart Failure in Patients with COPD: An AI-supported Systematic Review (working title)], following the methodology described in the publication (URL/doi to be uploaded).</p> <p>These files provide insight into the AI-supported screening process and the choices made by the human reviewer.</p>
Bibliographic Dataset for the Systematic Literature Review on Industry 5.0 Concepts and Enabling Technologies, Towards an Enhanced Conservation Practice
<p>This database contains all the bibliographic information found after applying the Search Strategy used for the Industry 5.0 Concepts and Enabling Technologies, Towards an Enhanced Conservation Practice: Systematic Literature Review. The following electronic databases were searched:</p> <ul> <li>Scopus.</li> </ul> <p>A total of 907 records were found. The search was conducted on 16/02/2024.</p> <p>The information is presented in .ris, .bib, and .csv format.</p>
A scoping review on bovine tuberculosis highlights the need for novel data streams and analytical approaches to curb zoonotic diseases
<p>The following data and scripts are part of the manuscript titled 'A scoping review on bovine tuberculosis highlights the need for novel data streams and analytical approaches to curb zoonotic diseases' which is currently going through the peer-review process and has already been published as a preprint. Please read the README.txt file for information on the files uploaded.</p>
CGM Scoping Review Data Repository
<p>This dataset represents the data extracted as part of a CGM-based biological feedback scoping review.</p>
A scoping review of the ethics frameworks describing issues related to the use of extended reality
<p>This is the dataset used for the scoping review of D2.1, which required an overview and assessment of relevant ethics frameworks, codes of conduct, guidelines regarding extended reality technologies. The specific objective is to map, review, and assess existing frameworks in terms of relevant foundational principles, ethical issues addressed, proposals to address these ethical issues, and the commonalities/differences identified between the documents.</p>
Clinical evidence for high-risk CE-marked medical devices for glucose management: a systematic review and meta-analysis
<p><strong><span>Aims: </span></strong><span>High-risk medical devices are increasingly used in diabetes management, but<span><span> there are no specific European recommendations on how they should be evaluated. Within</span></span> the Coordinating Research and Evidence for Medical Devices (CORE-MD) project, we conducted a systematic review and meta-analysis evaluating CE-marked high-risk devices for glucose management. </span></p> <p><strong><span>Materials and Methods: </span></strong><span>We<span> identified interventional and observational studies evaluating the </span>efficacy and safety of 8 automated insulin delivery (AID) systems, 2 implantable insulin pumps, and 3 implantable continuous glucose monitoring (CGM) devices.<span> </span></span><span>We meta-analysed randomized controlled trials (RCTs) comparing AID systems with other treatments.</span></p> <p><strong><span>Results:</span></strong><span> 99 studies published from 2009–2022 were included, comprising 83 on AID systems, 6 on insulin pumps, and 10 on CGM; 43% reported industry funding;30% were pre-market; 45% had a comparator group. 33% were RCTs, 25% non-randomized trials, and 41% observational studies. Median sample size was 52 (interquartile range 25–111), age 37.8 years (17–45.5), and study duration 13 weeks (4.5–26). AID systems lowered HbA1c by 0.3 percentage points (absolute mean difference [MD]=-0.3; 9 RCTs; I<sup>2</sup>=85%) and increased time in target range for sensor glucose level by 10.5 percentage points (MD=10.5; 14 RCTs; I<sup>2</sup>=89%). 69% of studies reported on at least one safety outcome.</span></p> <p><strong><span>Conclusions:</span></strong><span> High-risk devices for glucose monitoring or insulin dosing, in particular AID systems, improve glucose control safely but evidence on diabetes-related end organ damage is lacking due to short study durations. Methodological heterogeneity highlights the need for d<span><span>eveloping standards for future pre- and post-market investigations of diabetes-specific high-risk medical devices.</span></span></span></p>
Understanding the Publish-Review-Curate (PRC) Model of Scholarly Communication - Data and Code
<p>Summary data for the number of articles submitted to publish-review-curate platforms as of August 2024 (Figure 1) [Update 14 Nov 2024: Added JMIRx. Data still from August 2024]</p> <p>Summary data for the number of articles reviewed by review platforms (Figure 2)</p> <p>Analysis code to produce Figures 1 and 2</p> <p>Code to extract articles for inclusion in data</p>
TripAdvisor Restaurant Reviews
<h2><strong>Description</strong></h2> <p>This dataset contains restaurant reviews from TripAdvisor for five European cities, capturing detailed information on users, restaurants (items), and reviews. It offers a comprehensive view of user experiences, opinions, and restaurant attributes.</p> <h3><strong>Data Structure</strong></h3> <h4><strong>User Information</strong></h4> <ul> <li><code>userId</code>: Unique identifier for each user (hashed).</li> <li><code>name</code>: Display name or username.</li> <li><code>location</code>: User's location (city and country).</li> </ul> <h4><strong>Restaurant Information (Items)</strong></h4> <ul> <li><code>itemId</code>: Unique identifier for each restaurant.</li> <li><code>name</code>: Restaurant name.</li> <li><code>city</code>: City where the restaurant is located.</li> <li><code>priceInterval</code>: Price range.</li> <li><code>url</code>: Link to the restaurant’s TripAdvisor review page.</li> <li><code>rating</code>: Average rating score for the restaurant.</li> <li><code>type</code>: List of cuisine types (e.g., <code>[Spanish, Mediterranean]</code>).</li> </ul> <h4><strong>Review Information</strong></h4> <ul> <li><code>reviewId</code>: Unique identifier for each review.</li> <li><code>userId</code>: Corresponding user who wrote the review.</li> <li><code>itemId</code>: Restaurant associated with the review.</li> <li><code>title</code>: Title of the review summarizing the user’s impression.</li> <li><code>text</code>: Full text of the review describing the user’s experience.</li> <li><code>date</code>: Date when the review was posted.</li> <li><code>rating</code>: Numerical score (typically from 0 to 50, where 50 represents the highest satisfaction).</li> <li><code>language</code>: Language of the review.</li> <li><code>images</code>: List of URLs pointing to images uploaded by the user (if available).</li> <li><code>url</code>: Link to the full review on TripAdvisor.</li> </ul> <h2><strong>Code example</strong></h2> <pre><code>import pandas as pd city = "Barcelona" # Load restaurants items = pd.read_pickle(f"{city}/items.pkl") # Load users users = pd.read_pickle(f"{city}/users.pkl") # Load reviews reviews = pd.read_pickle(f"{city}/reviews.pkl")</code></pre>
Systematic review data on the role of urban planning in the context of sustainability transformations and human-nature connections
<p>This data publication belongs to the following research paper:<br>Harms, P., Hofer, M. & Artmann, M. Planning cities with nature for sustainability transformations — a systematic review. Urban Transform 6, 9 (2024). <br>https://doi.org/10.1186/s42854-024-00066-2 </p> <p>We conducted a systematic literature review according to the PRISMA Statement 2020 (Page et al. 2021). The list shows the steps performed and the names of the corresponding datasets available here:</p> <p>Step A - Identification of Records<br>A_01_PRISMA-protocoll.pdf<br>A_02_searchstring.txt<br>A_03_recordsidentified.ris</p> <p>Step B - Screening of Records<br>B_01_recordsscreened-title-keywords.ris<br>B_02_recordsscreened-abstract.ris<br>B_03_recordsscreened-fulltext.ris<br>B_04_studiesincluded.ris<br>B_05_screeningdecisions-overview.xlsx</p> <p>Step C - Qualitative Analysis<br>C_01_codingscheme.xlsx</p> <p> </p>
Transforming towards what? A review of futures thinking applied in the quest for navigating sustainability transformations
<p>This is the dataset used for the review article "Transforming towards what? A review of futures thinking applied in the quest for navigating sustainability transformations". The spreadsheet contains the bibliographic records and the data used and organized for its analysis. </p>
Reproduction package for paper "How far are we from reproducible research on code smell detection? A systematic literature review"
<p>Checklist and data extracted from publications analyzed for "How far are we from reproducible research on code smell detection? A systematic literature review" paper, together with processing scripts and calculations of Cohen's Kappa.</p> <p>Paper that describes details of the data is available here: https://doi.org/10.1016/j.infsof.2021.106783</p>
Mixed methods systematic review and metasummary about barriers and facilitators for the implementation of cotrimoxazole and isoniazid - preventive therapies for people living with HIV.
<p>This is the minimal data set underlying the findings of our systematic review and metasummary:</p> <p>We uploaded the following data extracted from the studies included in our review:</p> <p>- Systematic Review protocol, also published in PROSPERO (CRD42019137778).</p> <p>- detailed description of studies included in our review.</p> <p>- barriers identified in the review (metasummary).</p> <p>- facilitators identified in the review.</p>
Data and Material for 'Less is More: Supporting Developers in Vulnerability Detection during Code Review'
<p>Data and Material supporting the paper 'Less is More: Supporting Developers in Vulnerability Detection during Code Review'.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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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.