Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
3,172
datasets available to search
ShareScore release 0.9.0
Dataset results
3,172 results for “Publications”
A comparison of different methods of identifying publications related to the United Nations Sustainable Development Goals: Case Study of SDG 13: Climate Action
<p>This data set pertains to the following research article: Purnell, P.J. (2022) <em>A comparison of different methods of identifying publications related to the United Nations Sustainable Development Goals: Case Study of SDG 13 – Climate Action</em>. arXiv:2201.02006</p>
data set of scopus about technology and halal meat supply chain publications
<p>This is the dataset of papers related to the topics of technology and halal meat supply chain collected from Scopus. The duration of year was 2008-2022</p>
Differential equity in access to public and private coastal infrastructure in the Southeastern United States
<p>Despite the ubiquity of coastal infrastructure, it is unclear what factors drive its placement, particularly for water access infrastructure (WAI) that facilitates entry to coastal ecosystems such as docks, piers, and boat landings. The placement of WAI has both ecological and social dimensions, and certain segments of coastal populations may have differential access to water. In this study, we employed an environmental justice framework to assess how public and private WAI in South Carolina, USA is distributed with respect to race and income. Using publicly available data from state agencies and the US Census Bureau, we mapped the distribution of these structures across the 301 km of the South Carolina coast. Using spatially explicit analyses with high resolution, we found that census block groups with lower income contain more public WAI, but racial composition has no effect. On the other hand, private docks showed the opposite trends, as the abundance of docks is significantly, positively correlated with census block groups that have greater percentages of White residents, while income has no effect. Under a "need-based" model of equity, we argue that WAI are not equitably distributed in South Carolina and constitute an environmental justice issue. We contend that the racially unequal distribution of docks is likely a consequence of the legacy of Black land loss, especially of waterfront property, throughout the coastal Southeast over the past half-century. Knowledge of racially inequitable distribution of WAI can guide public policy to rectify this imbalance and support advocacy organizations working to promote public water access. Our work also points to the importance of considering race in ecological research, as the spatial distribution of coastal infrastructure both directly affects ecosystems through the structures themselves and regulates which groups access water and what activities they can engage in at those sites.</p>
Files for publication "Microseek: A Protein-Based Metagenomic Pipeline for Virus Diagnostic and Discovery"
<p><strong>Context</strong></p> <p>These files correspond to the article “Microseek: A Protein-Based Metagenomic Pipeline for Virus Diagnostic and Discovery” submitted to Genes.</p> <p> </p> <p><strong>File content</strong></p> <ul> <li>input_data-empty_matrices: 50M-read Tissues and Plasma matrices, no spike;</li> <li>input_data-matrices_spiked_known_viruses: 50M-read Tissues and Plasma matrices spiked with six known virus at d1, d10, d100;</li> <li>input_data-matrices_spiked_neo_viruses: 50M-read Tissues and Plasma matrices spiked with 3 Neopneumoviruses at d1 and d10;</li> <li>input_data-neo_viruses: Nucleotide and protein sequences of 3 Neopeumoviruses</li> <li>input_data-tick_sample: raw data of a Rhipicephalus tick sample known to be infected with the Cataloi Tick Quaranjavirus (CTQV)</li> <li>input_data-negative_control: raw data of the negative control (water)</li> <li>output_microseek: Microseek outputs, raw results and results after background filtration</li> </ul> <p> </p> <p><strong>File listing </strong></p> <pre><code class="language-bash">input_data-empty_matrices.tar.xz ├── plasma.fastq └── tissue.fastq input_data-matrices_spiked_known_viruses ├── d1 │ ├── spiked_plasma.fastq │ └── spiked_tissue.fastq ├── d10 │ ├── spiked_plasma.fastq │ └── spiked_tissue.fastq └── d100 ├── spiked_plasma.fastq └── spiked_tissue.fastq input_data-matrices_spiked_neo_viruses.tar.xz ├── d1 │ ├── plasma_spiked_with_neo1.fastq │ ├── plasma_spiked_with_neo2.fastq │ ├── plasma_spiked_with_neo3.fastq │ ├── tissue_spiked_with_neo1.fastq │ ├── tissue_spiked_with_neo2.fastq │ └── tissue_spiked_with_neo3.fastq └── d10 ├── plasma_spiked_with_neo1.fastq ├── plasma_spiked_with_neo2.fastq ├── plasma_spiked_with_neo3.fastq ├── tissue_spiked_with_neo1.fastq ├── tissue_spiked_with_neo2.fastq └── tissue_spiked_with_neo3.fastq input_data-neo_viruses.tar.xz ├── genes │ ├── neo_1.fasta │ ├── neo_2.fasta │ └── neo_3.fasta └── proteins ├── neo_1.fasta ├── neo_2.fasta └── neo_3.fasta input_data-tick_sample.tar.xz └── Cataloi_S1_R1_001.fastq.xz input_data-negative_control.tar.xz └── negative_control.fastq.xz output_microseek.tar.xz ├── empty_matrices │ ├── matrix_plasma │ └── matrix_tissue ├── matrices_spiked_known_viruses │ ├── filtered │ │ ├── d100_plasma │ │ ├── d100_tissue │ │ ├── d10_plasma │ │ ├── d10_tissue │ │ ├── d1_plasma │ │ └── d1_tissue │ └── non_filtered │ ├── d100_plasma │ ├── d100_tissue │ ├── d10_plasma │ ├── d10_tissue │ ├── d1_plasma │ └── d1_tissue ├── matrices_spiked_neo_viruses │ ├── filtered │ │ ├── plasma_spiked_with_neo1_at_d1 │ │ ├── plasma_spiked_with_neo1_at_d10 │ │ ├── plasma_spiked_with_neo2_at_d1 │ │ ├── plasma_spiked_with_neo2_at_d10 │ │ ├── plasma_spiked_with_neo3_at_d1 │ │ ├── plasma_spiked_with_neo3_at_d10 │ │ ├── tissue_spiked_with_neo1_at_d1 │ │ ├── tissue_spiked_with_neo1_at_d10 │ │ ├── tissue_spiked_with_neo2_at_d1 │ │ ├── tissue_spiked_with_neo2_at_d10 │ │ ├── tissue_spiked_with_neo3_at_d1 │ │ └── tissue_spiked_with_neo3_at_d10 │ └── non_filtered │ ├── plasma_spiked_with_neo1_at_d1 │ ├── plasma_spiked_with_neo1_at_d10 │ ├── plasma_spiked_with_neo2_at_d1 │ ├── plasma_spiked_with_neo2_at_d10 │ ├── plasma_spiked_with_neo3_at_d1 │ ├── plasma_spiked_with_neo3_at_d10 │ ├── tissue_spiked_with_neo1_at_d1 │ ├── tissue_spiked_with_neo1_at_d10 │ ├── tissue_spiked_with_neo2_at_d1 │ ├── tissue_spiked_with_neo2_at_d10 │ ├── tissue_spiked_with_neo3_at_d1 │ └── tissue_spiked_with_neo3_at_d10 ├── negative_control └── tick_sample </code></pre> <p> </p>
Publication rate of systematic reviews in the Lens.org database
<p><strong>Figure 2. </strong>The number of articles (document count) in the Lens.org database between 1990 and 2021 by publication year referring to the terms ‘systematic review*’, ‘systematically review*’ or ‘systematic literature review*’ in their titles, abstracts, keywords or indexed fields of study (see <a href="https://www.doi.org/10.5281/zenodo.6942304">https://www.doi.org/10.5281/zenodo.6942304</a> for raw data and exact search query).</p>
Supporting Data: Do spatial climate messages increase pro-environmental engagement? Evidence from a survey experiment on public transport
<p>Additional material for the paper:</p> <p>Victor von Loessl, Eva Weingärtner & Sonja Zitzelsberger (2022) Do spatial climate messages increase pro-environmental engagement? Evidence from a survey experiment on public transport, Journal of Environmental Economics and Policy, DOI: 10.1080/21606544.2022.2097960</p>
PreprintMatch: a tool for preprint publication detection applied to analyze global inequities in scientific publishing
<p>Dataset underlying the paper "PreprintMatch: a tool for preprint publication detection applied to analyze global inequities in scientific publishing." preprint-paper-matches.csv lists all matches found by our algorithm between bioRxiv/medRxiv and PubMed, and preprint_affiliations.csv lists all extracted affiliations from bioRxiv/medRxiv. The Rxivist data dump (https://zenodo.org/record/4738007) was used for all preprint data, and the scrips to download PubMed data are available on our GitHub repository, https://github.com/PeterEckmann1/preprint-match.</p> <p>The full database dump, with all data used in the study, is available on Google Drive at https://drive.google.com/file/d/1ZoafhYUP-DO4Hd_4A_v7mbQLjN3JPzJv/view?usp=sharing. The PostgreSQL database can be restored using the pg_restore command.</p>
Data to accompany the publication "Combined biophysical and genetic modelling approaches reveal complementary information about population connectivity of New Zealand green-lipped mussels"
<p>Data to accompany the publication "Combined biophysical and genetic modelling approaches reveal complementary information about population connectivity of New Zealand green-lipped mussels". </p> <p>migrationmatrix14.txt contains the particle tracking matrix, with the total number of particles that migrated from row i to column j (out of a total of 2217864 particles released per population).</p> <p>mussel_microsat_Genepop.txt contains the microsatellite data for each population in Genepop format.</p>
Data for the publication "Control of electronic topology in a strongly correlated electron system"
<p>Data sets of the figures in the publication "Control of electronic topology in a strongly correlated electron system"</p>
Hash data files for "Hashes are not suitable to verify fixity of the public archived web"
<p>This work investigates the fixity of a set of archived webpages, or mementos. We conducted a study on 16,627 mementos from 17 public web archives. We replayed and downloaded the mementos 39 times using a headless browser over a period of 442 days and generated a hash for each memento after each download, resulting in 39 hashes per memento. The hashes were generated by creating Merkle trees to represent hashes at each level of the memento. A hash was generated for each resource used to construct the full webpage and then the hashes were combined to generate an overall hash for the composite memento.</p> <p>There are 39 data files, one for each download. </p> <p>The mementos downloaded come from the dataset at <a href="https://github.com/oduwsdl/mementos-fixity/">https://github.com/oduwsdl/mementos-fixity/</a></p>
Public Acceptance of Regional Redistribution in Germany: A Survey Experiment on the Perceived Deservingness of Regions
<p>Codebook and data that support the findings of the study "Public Acceptance of Regional Redistribution in Germany: A Survey Experiment on the Perceived Deservingness of Regions" by Jan Gniza and Matthias Wrede. Published in the <em>Journal of Social Policy</em>. For further information on data collection see sheet "Cover" in the codebook.</p>
Dataset for FlexSNG project - publication CET2022 vol 92
<p>Dataset (dataset 1.0) for FlexSNG; Refer to Article Development of a bubbling circulating fluidized-bed reactor for biomass and waste gasification (CET 2022 vol.92)</p>
The Application of Machine Learning for Classification on Blood Pressure Variability. A New Approach for an Old Idea - Professor Kelvin Tsoi (The Chinese University of Hong Kong, School of Public Health and Primary Care)
<p>This video is the eighth talk from our Future Blood Testing Network Plus Launch that took place on the 23/11/2021.</p> <p>The Application of Machine Learning for Classification on Blood Pressure Variability. A New Approach for an Old Idea - Professor Kelvin Tsoi (The Chinese University of Hong Kong, School of Public Health and Primary Care)</p> <p>Bio: Professor Kelvin Tsoi is an Epidemiologist specialized in Digital Health. His research interests focus on digital innovation in chronic disease management, including mobile and telecare application for hypertension management, technological implementation and social engagement for cognitive screening, artificial intelligent application on electronic health records. He also works as the traditional epidemiologist on evidence-based medicine and population cohort studies. He obtained his Bachler Degree from Department of Statistics and Doctor of Philosophy from School of Public Health in the Chinese University of Hong Kong. He further received post-doctoral training in the Division of Gastroenterology and Hepatology, Department of Medicine and Therapeutics. He was also appointed as a Director of CUHK JC Bowel Cancer Education Centre to promote colorectal cancer screening. In 2011, he worked as a research scientist in Hospital Authority. He led projects covering a wide range of service areas on chronic diseases, such as service demand projection for schizophrenia and dementia. The experience of database management enhanced his understanding of the HA database structures. In 2013, he was invited to join the interdisciplinary team for Big Data research and worked closely with a team of engineers and data scientists. Currently, Professor Tsoi is an Associate Professor in JC School of Public Health and Primary Care, SH big Data Decision Analytics Research Centre and JC Institute of Ageing.</p> <p>Further details on this event can be found at: https://futurebloodtesting.org/event/23-11-21-future-blood-testing-network-launch/</p> <p>This video is an output from the Future Blood Testing Network which is funded by EPSRC under Grant Number EP/W000652/1</p> <p>YouTube Link: https://youtu.be/liLVKA-JHiI</p>
PURE: a Dataset of Public Requirements Documents
<p>Please cite this dataset as <strong>Ferrari, A., Spagnolo, G. O., & Gnesi, S. (2017, September). PURE: A dataset of public requirements documents. In <em>2017 IEEE 25th International Requirements Engineering Conference (RE) </em>(pp. 502-505). IEEE.</strong></p> <p><a href="https://ieeexplore.ieee.org/abstract/document/8049173">https://ieeexplore.ieee.org/abstract/document/8049173</a></p> <p>This dataset presents PURE (PUblic REquirements dataset), a dataset of 79 publicly available natural language requirements documents collected from the Web. The dataset includes 34,268 sentences and can be used for natural language processing tasks that are typical in requirements engineering, such as model synthesis, abstraction identification and document structure assessment. It can be further annotated to work as a benchmark for other tasks, such as ambiguity detection, requirements categorisation and identification of equivalent re-quirements. In the associated paper, we present the dataset and we compare its language with generic English texts, showing the peculiarities of the requirements jargon, made of a restricted vocabulary of domain-specific acronyms and words, and long sentences. We also present the common XML format to which we have manually ported a subset of the documents, with the goal of facilitating replication of NLP experiments. The XML documents are also available for download.</p> <p>The paper associated to the dataset can be found here: </p> <p>https://ieeexplore.ieee.org/document/8049173/</p> <p>More info about the dataset is available here: </p> <p>http://nlreqdataset.isti.cnr.it</p> <p>Preprint of the paper available at ResearchGate:</p> <p>https://goo.gl/HxJD7X</p> <p>The dataset includes:</p> <p>- all the documents in PDF format</p> <p>- a subset of 19 documents in XML format</p> <p>- the .xsd schema of the XML files</p> <p>The dataset has been created by gathering data from web sources and we are not aware of license agreements or intellectual property rights on the requirements. The curator took utmost diligence in minimizing the risks of copyright infringement by using non-recent data that is less likely to be critical, by sampling a subset of the original requirements collection, and by qualitatively analyzing the requirements. In case of copyright infringement, please contact the dataset curator (Alessio Ferrari, alessio.ferrari@cnr.it, alessio.ferrari@ucd.ie) to discuss the possibility of removal of that dataset [see <a href="https://support.zenodo.org/help/en-gb/13-policies/140-what-is-your-take-down-procedure" target="_blank" rel="noopener">Zenodo's policies</a>].</p>
Data and code related to publication "Migration pulsedness alters patterns of allele fixation and local adaptation in a mainland-island model" - Aubree et al. 2021
<p>Those data sets and codes are related to the manuscript "Migration pulsedness alters patterns of allele fixation and local adaptation in a mainland-island model" available on BioRXiv.</p> <p>All the information that are necessary to use those data sets and codes are contained in the file "readme.txt".</p>
Can Public Transport Improve Accessibility for the Poor Over the Long Term? Empirical Evidence in Paris, 1968-2010
<p>This dataset allows to reproduce the results of the paper "Can Public Transport Improve Accessibility for the Poor Over the Long Term? Empirical Evidence in Paris, 1968-2010", by Vincent Viguié, Charlotte Liotta, Basile Pfeiffer, and Nicolas Coulombel, submitted to the Journal of Transport Geography and available at SSRN: <a href="https://ssrn.com/abstract=4049765">https://ssrn.com/abstract=4049765</a> or <a href="https://dx.doi.org/10.2139/ssrn.4049765">http://dx.doi.org/10.2139/ssrn.4049765</a>.</p> <p>Files MODUS_private_cars.csv and MODUS_public_transport.csv correspond to the average transport time between municipalities by public transit for the Census years between 1968 and 20109, and by car for the year 2010. MODUS is a model calibrated by the public regional road and transport authority (DRIEAT Île de France) to simulate road traffic and transit in the region. More details can be found in the research paper.</p> <p>Files COM_RES_csp_1968_2010.csv and COM_EMP_csp_1968_2010.csv correspond to the number of employed workers, by place of residence or employment, at the municipality (communes) level, with stable geographical boundaries over time. They are derived from the detailed census of the French population carried out by the INSEE, the French national statistical institute. More details can be found in the research paper.</p>
Relevant data for publication 'Atmospheric phosphorus deposition amplifies carbon sinks in simulations of a tropical forest in Central Africa' Goll et al.
<p>Plotting scripts and processed output from ORCHIDEE-CNP. The version of ORCHIDEE is available here: https://doi.org/10.14768/391825ae-d257-4365-9820-30ea1940914c</p>
Factors associated with child abuse in children and adolescents in a Peruvian public hospital
<p>The study's objective was to determine the factors associated with the type of child and adolescent abuse of the MAMIS program, Hipólito Unanue hospital, Tacna-Peru region, 2019-2021. It had a quantitative, retrospective, cross-sectional, correlational approach in which 174 child abuse cases in children and adolescents were examined. It was found that the predominant personal factors were located in the ages of 12-17 years (57.4%), secondary level (51.15%), female sex (56.9%), and do not consume alcohol and/or drugs (88.5%). The family factors that stood out were the type of single parenteral family (48.28%), the age of both parents was 30-59 years (58.5%), the divorced, marital status (37.3%), secondary level (68.9%), the occupation of the independent parents (64.9%), there is no history of the parents having suffered violence (91.3%), there are no problems of addiction or alcohol consumption and/or drugs (95.40%), and at the same time there are no psychiatric disorders (95.4%). The types of child abuse that prevails is the psychological type (93.68%), followed by the type of neglect or abandonment (38.51%), the physical type (37.93%), and sexual abuse (27.0%). It is concluded that there is a significant relationship, with a confidence level of 95%, between personal factors such as the age of the minor with psychological abuse and sexual abuse<strong>; </strong>the sex of the minor with physical abuse and sexual abuse; the consumption of alcohol and/or drugs with the physical abuse of children and adolescents.</p>
REMODEL. WP6. Sensory Systems and Mechatronic Tools. T6-2. Development and optimization of sensory system components. Data related to IMM2021 publication
<p>The datasets contain data related to the experiments presented in the publication:</p> <p>Costanzo, M., Pirozzi, S., “Optical Force/Tactile Sensors for Robotic Applications” (2021) IEEE Instrumentation and Measurement Magazine, 24 (5), art. no. 9491003, pp. 28-35. DOI: 10.1109/MIM.2021.9491003</p>
X-ray scattering Datasets of gold and silver nanoparticle composites, relating to the publication "Gold and silver dichroic nanocomposite in the quest for 3D printing the Lycurgus cup"
<p>Wide-range X-ray scattering datasets and analyses for all samples described in the 2020 publication "Gold and silver dichroic nanocomposite in the quest for 3D printing the Lycurgus cup". These datasets are composed by combining multiple small-angle x-ray scattering and wide-angle x-ray scattering curves into a single dataset. They have been analyzed using McSAS to extract polydispersities and volume fractions. They have been collected using the MOUSE project (instrument and methodology). </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.