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670 results for “review study”
The data that support the findings of a review paper "From urban data to city-scale models: A review of traffic simulation case studies"
<p>This dataset contains the data that were used in a review paper "From urban data to city-scale models: A review of traffic simulation case studies". It contains the following files:</p> <ul> <li>keywords with counts.txt - list of keywords and their counts in the considered corpus of traffic simulation case studies. The data were used to produce Figure 2 and Figure 3 in the paper.</li> <li>Papers analysis.xlsx - Excel file containing the data on the reviewed studies. The document has the following sheets: <ul> <li> Appendix A - contains a table short reference, location, simulation period, spatial scale, simulated units and marked categories for a paper;</li> <li>Geography - contains data on geographical distribution of simulated areas between world regions and countries, these data were used to produce Figure 4 in the paper;</li> <li>Software tools - contains data on simulation tools used in the studies. </li> <li>Journals and conferences - contains data on where the reviewed papers were published.</li> </ul> </li> </ul>
Review of existing modelling studies focusing on specific soil-based ecosystem services (SES) and threats (ST) including climate change, management and land use change scenarios.
<p><span>We </span><span>reviewed existing modelling studies focusing on soil ecosystem services (SES) and soil threats (ST) including climate change, land use change and management scenarios. A publication has been submitted and is currently being reviewed. The title of the manuscript is: </span><span>Assessing and mapping soil ecosystem services and soil threats changes in agroecosystems through scenario-based approaches – a systematic review. </span></p> <p><span>Work was split between various authors. All Co-authors were working on either one or more SES or one ST. Excel sheets were prepared by INRA and BFW to ensure the comparability of results that members extracted from the papers found. Literature search was done in Scopus and Web of Science. The final list of related publications is reported here. <br></span></p>
MiRoR7-P1- Disagreements in risk of bias assessment for randomised controlled trials included in more than one Cochrane systematic reviews: a research on research study using cross-sectional design
<p>dataset referring to </p> <p><strong>Disagreements in risk of bias assessment for randomised controlled trials included in more than one Cochrane systematic reviews: a research on research study using cross-sectional design</strong></p> <p> </p> <p> </p> <p>Lorenzo Bertizzolo<sup>1</sup>, Patrick M Bossuyt<sup>2</sup>, Ignacio Atal<sup>1, 5</sup>, Philippe Ravaud<sup>1, 3-6</sup>, Agnès Dechartres<sup>7</sup></p> <p> </p> <p><sup>1</sup> INSERM, U1153 Epidemiology and Biostatistics Sorbonne Paris Cité Research Center (CRESS), Methods of therapeutic evaluation of chronic diseases Team (METHODS), Paris, F-75004 France; Paris Descartes University, Sorbonne Paris Cité, France.</p> <p><sup>2</sup> Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Netherlands.</p> <p><sup>3</sup> Centre d’Épidémiologie Clinique, Hôpital Hôtel Dieu, AP-HP (Assistance Publique des Hôpitaux de Paris), Paris, France.</p> <p><sup>4</sup> Faculté de Médecine, Université Paris Descartes, Sorbonne Paris Cité, Paris, France.</p> <p><sup>5</sup> Cochrane France, Paris, France</p> <p><sup>6</sup> Columbia University, Mailman School of Public Health, Department of Epidemiology, New York, USA</p> <p><sup>7</sup> Sorbonne Université, INSERM, Institut Pierre Louis de Santé Publique, Département Biostatistique, Santé Publique et Information Médicale, AP-HP, Hôpitaux Universitaires Pitié Salpêtrière – Charles Foix, Paris, France</p>
Fighting COVID-19 with computational tools: an AI guided review of 17,000 studies - The CSCoV database.
<p>CSCoV (Computational Studies about COVID-19) is a dataset containing COVID-19 related studies extracted from PubMed, bioRxiv, medRxiv, and arXiv, together with article and author related metrics obtained from Semantic Scholar (plus page views from bioRxiv and medRxiv). Using machine learning, the articles are categorized in six topics (Pharmacology, Genomics, Epidemiology, Healthcare, Clinical Medicine, Clinical Imaging) and prioritized. The database is periodically updated.</p> <ul> <li>Publication: TBA</li> <li>Files included in this release: <ul> <li>cscov_09_2021.png: dataset statistics for the current CSCoV release.</li> <li>cscov_09_2021.tsv: CSCoV database.</li> <li>schema.json: metadata.</li> <li>cscov_09_2021.tar.gz: Doc2Vec and DeepWalk features used for the DL model</li> </ul> </li> <li> <p>Source code: <a href="https://github.com/SFB-KAUST/covid-review">https://github.com/SFB-KAUST/covid-review</a></p> </li> </ul>
Data for Few studies of wild animal performance account for parasite infections: a systematic review
<p>Data from a systematic review across eight scientific journals publishing primarily studies in animal behaviour and physiology over a 5-year period to assess the proportion of studies which acknowledge, treat or control for parasite infection in their study design and/or analyses. Wild animals have parasites. This inconvenient truth has far-reaching implications for biologists measuring animal performance traits: infection with parasites can alter host behaviour and physiology in profound and sometimes counterintuitive ways. Yet, to what extent do studies on wild animals take individual infection status into account? We explored whether parasite inclusion differed between studies that are experimental versus observational, conducted in the field vs the laboratory and measure behavioural vs physiological traits. We also investigated the importance of other factors such as the journal, the year of publication, the trait category (e.g. locomotion, reproduction) measured, the vertebrate taxonomic group investigated, and the host climatic zone of origin. Our results show that parasite inclusion was generally lacking across recent studies on wild vertebrates. In over 680 filtered papers, we found that only 21.9% acknowledged the potential effects of infections on animal performance in the text, and only 5.1% of studies treated animals for infection (i.e. parasite control) or considered infection status in the statistical analyses (i.e. parasite analysis). Parasite inclusion, control and analysis were higher in laboratory compared to field studies and higher for physiological studies compared to behavioural studies but did not differ among journals, performance trait categories and taxonomic groups. Overall, our literature review suggests that parasites are sorely under-acknowledged by researchers in recent years despite growing evidence that infections can modify animal performance. Given the ubiquity of parasites in the environment, we encourage scientists to consider individual infection status when assessing performance of wild animals. We also suggest ways for researchers to implement such practices in both experimental and observational studies. </p>
Data Extraction table summarizing studies in the scoping review on co-creation of patient education materials
<p>Data extraction table for scoping review on best practices for co-creating patient-facing educational materials</p>
Data from Comparative effectiveness of common therapies for Wilson disease: A systematic review and meta‐analysis of controlled studies
<p>This dataset contains three text files in RIS format. They represent the screening process during study selection for "Comparative effectiveness of common therapies for Wilson disease: A systematic review and meta‐analysis of controlled studies" (<a href="https://doi.org/10.1111/liv.14179">https://doi.org/10.1111/liv.14179</a>). The file DOKU_All TiAb-Screening_20200116_cap contains all 3453 records (merged from original and update search) that were subjected to title-abstract screening. The file DOKU_All FT-Screening_20200116_cap contains all 174 records that were subjected to full-text screening. The file DOKU_All Included_20200116_cap contains all 26 records that were included into the final review.</p> <p>In addition, a PRISMA flow diagram (Fig. 1 in the paper) is available in TIF format.</p>
SmartUpLab- Co-Creation in sustainable mobility research - Systematic Reviews and Case Studies
<p>The current dataset presents the results of systematic reviews and case studies about co-creation tools best practice for sustainable mobility, carried out in the context of the research project SmartUpLab (funded by EFRE).</p>
Figure 1 in Aeshna affinis Vander Linden, 1820 (Odonata: Aeshnidae) in the Iberian Peninsula: A review of past and recent records, and a larval biometric study
Figure 1. Body length (A), prementum (B), supracoxal armature of prothorax (C), lateral spines on segments 6 to 9 of the abdomen and ovipositor (D), extremity of abdomen: cerci, paraprocts, and epiproct (E). / Longitud corporal (A), prementón (B), armadura supracoxal del protórax (c), espinas laterales de los segmentos abdominals 6 a 9 y ovipositor (D), extremo final del abdomen: cercos, paraproctos y epiprocto (E).
Figure 1 in Review Of Bryophyte Functional Traits In Ecological Studies
Figure 1. Example of two bryophyte species Radula complanata (L.) Dumort., 1831) and Dicranum viride (Lindberg, 1863) with different life strategies (D. viride: perennial stayer; Radula complanata: perennial shuttle species) and life forms (D. viride: cushion; R. complamata: turf), which share the same substrate affinity trait: bark (BernhardtRömermann et al. 2018). Photo: Anna PastareSkutele.
Figure 2 in Review Of Bryophyte Functional Traits In Ecological Studies
Figure 2. Bryophyte species complex on log in black alder swamp forest habitat. Photo: Anna PastareSkutele.
Supplemental data for: A scoping review of studies on ruscism
<p><span>The supplementary materials accompanying the paper: "A scoping review of studies on ruscism". These materials include: raw data from citation databases, table for quantitative analysis of imported bibliographic data, key topics and content analysis of publications, python code. These supplementary materials are intended to enhance the usability of the research data, allowing for in-depth secondary analyses and aiding scholars in conducting related studies.</span></p>
Coding frame and dataset for the study: Land-use governance: The interplay of social, market, and policy drivers – A global systematic review
<p>This file entails the coding frame and dataset used to conduct the systematic literature review "Land-use governance: The interplay of social, market, and policy drivers – A global systematic review".</p> <p>This study was first published as Chapter 2 of the PhD Dissertation "From soil to society - Rethinking governance for multifunctional land use and management" (Elsa L. Dingkuhn, 2025), and in a modified form in the journal Earth System Governance (Dingkuhn et al. 2025).</p> <p>The file consists of three sheets:<br>- Coding frame: Includes coding instructions and definitions used to extract and categorize the data.<br>- Variables: A list of dataset variables with explanations.<br>- List of included studies: The 81 studies from which the data was sourced.<br>- Data_List of observations: The dataset itself, consisting of 718 observations extracted from the included studies.</p>
Selected articles from the scoping review of biomarker discovery studies for the EU project on "Personalised Medicine Trials" (PERMIT)
<p>This dataset provides the data extracted for the scoping review of the literature on biomarker discovery studies for patient stratification using machine learning analysis of omics data, as part of the EU project on “Personalised Medicine Trials” (PERMIT). It covers the references for all articles selected as part of the scoping review, as well as information on the study type and methodology, the outcome measures, the validation type, and representative sentences extracted from each article on the main results and key findings of the corresponding biomarker study.</p>
Dataset underpinning "Understanding health behaviours in context: A systematic review and meta-analysis of Ecological Momentary Assessment studies of five key health behaviours"
<p>This is the dataset underpinning the article "Understanding health behaviours in context: A systematic review and meta-analysis of Ecological Momentary Assessment studies of five key health behaviours": https://pubmed.ncbi.nlm.nih.gov/35975950/</p>
Selected articles from the scoping review on the study designs for clinical trials applied to personalised medicine
<p>The dataset provides the data extracted for the scoping review of the literature on the study designs for clinical trials applied to personalised medicine, as part of the EU project on “Personalised Medicine Trials” (PERMIT).</p> <p>The dataset reports the references for all articles selected as part of the scoping review, as well as information on the general study characteristics and definition, methodology, statistical considerations, and examples of each study design referred to in each included paper.</p>
Dataset of the study "Exploring the Notion of Risk in Reviewer Recommendation"
<p><strong>Note: Please find the dockerized version of this replication package in the following link:</strong></p> <p><a href="https://figshare.com/articles/dataset/Replication_Package_of_the_study_Exploring_the_Notion_of_Risk_in_Reviewer_Recommendation_/20673255">https://figshare.com/articles/dataset/Replication_Package_of_the_study_Exploring_the_Notion_of_Risk_in_Reviewer_Recommendation_/20673255</a></p> <p> </p> <p>This repository contains the necessary data for replicating the necessary information to replicate the study of "Exploring the Notion of Risk in Reviewer Recommendation." This code extends the RelationalGit package (https://github.com/CESEL/RelationalGit) from the study of E. Mirsaeedi and P. C. Rigby [1] and adds some functionality that is needed to incorporate the concept of the fix-inducing likelihood of a project.</p> <p>In addition to our dataset, this repository also have the supporting materials for our study. The supporting materials are in the "ICSME_online_materials_ICSME.pdf" and contains the following items:</p> <ul> <li>Table 1 contains the detail of the dataset and some related statistics for each of the studied projects. </li> <li>Table 2 have risk measures that were used in our defect prediction model. We use Commit Guru Tool to extracts the data from the GitHub repositories and then use this data to train our defect prediction model.</li> <li>Figure 1 illustrates the distribution of predicted defect probability of different projects. This distribution shows how defect probability of different periods are similar to the adjacent periods. </li> </ul> <p><strong>References:</strong></p> <p>[1] E. Mirsaeedi and P. C. Rigby, ‘Mitigating turnover with code review recommendation: Balancing expertise, workload, and knowledge distribution’, στο <em>Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering</em>, 2020.</p> <p> </p>
Figs 5–7 in A mini-review of advances in the study of the evolution of Perdix species
Figs 5–7. Morphological comparison on three species of Perdix (Pictures from http://image.baidu.com/).
Figs 1–4 in A mini-review of advances in the study of the evolution of Perdix species
Figs 1–4. Phylogenies trees of Perdix. 1. Monophyletic group consisting of Perdix, Meleagrididae, and Tetraoninae in the supertree (Eo et al., 2009). 2. Based on morphological and zoogeographical data (Zheng, 1978). 3. Based on C-mos + Cyt b + ND2 (Bao et al., 2010). 4. Based on Cyt b + ND2 (Bao et al., 2010).
Dataset related to article: QUALITY ASSESSMENT OF THE MRI-RADIOMICS STUDIES FOR MGMT PROMOTER METHYLATION PREDICTION IN GLIOMA: A SYSTEMATIC REVIEW AND META-ANALYSIS
<p><strong><span>This table contains the raw data used to generate the heatmap illustrated in Fig 2. Each row of the table shows the distribution of the scores achieved by the studies for a domain. Colors from red to green denote progressive increase from minimum to maximum score obtainable for each domain.</span></strong></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.