Find research datasets worth reusing

opencc-by-4.0Jul 2021View details →

Model fields supporting the publication "Integrated Assessment of the Risks to Ocean Acidification in the Northern High Latitudes: Regional Comparison of Exposure, Sensitivity and Adaptive Capacity of Pelagic Calcifiers"

These are the model outputs supporting the described manuscript. They include monthly averaged output of aragonite saturation state for each year during the 10-year hindcast. Also included is the particle tracking output, for both the Bering Sea and the Gulf of Alaska, as described in the manuscript.

openother-openJul 2021View details →

VlachosGroup/Pdn-CO-Dynamics: Initial release for publication

Lattice Kinetic Monte Carlo (KMC) Simulations for Subnanometer Pdn clusters Dynamics under a pressure of CO.

Authors with Publications in Open Access Journals

This dataset has the set of Brazilian authors with publications in open access journals. It presents information about place of professional performance, maximum degree, large area and area of expertise.

Tracking Data I/II of the publication "A graph-based cell tracking algorithm with few manually tunable parameters and automated segmentation error correction"

DATA belonging to the paper "A graph-based cell tracking algorithm with few manually tunable parameters and automated segmentation error correction" Katharina Löffler, Tim Scherr, Ralf Mikut doi: https://doi.org/10.1101/2021.03.16.435631 ----------------------------- To investigate the influence of different segmentation errors on the tracking performance we simulate errorneous segmentation data: - under-segmentation (referred to as "merge" in the folders), over-segmentation("split"), False Negatives ("remove"), combination of the aforementioned errors ("mixed") - percentages: 1,2,5,10,20 of errorneous masks per dataset - runs: 5 randomly initialized runs per combination - datasets: Fluo-N2DH-SIM+ and Fluo-N3DH-SIM+ each with two image sequences ---> in total 4 (error types) * 5 (percentage) * 5 (runs) * 2 (data sets) * 2 (image sequences) = 400 datasets The datasets can be recreated by running our code https://git.scc.kit.edu/KIT-Sch-GE/2021-cell-tracking ---------------------------- RESULTS We evuated the four tracking algorithms KIT-Sch-GE(1), KTH-SE, MU-Lux-CZ and our proposed algorithm on the aforementioned datasets and compare their performance using the CTC metrics DET, SEG and TRA. This repository contains all metrics as xls files and all tracking results as image sequences. xls files ----------- compare_all_trackers_on_synt_bm.csv Comparing the tracking algorithms MU-Lux-CZ, KTH-SE, KIT-Sch-GE(1) and the proposed tracking algorithm on synthetically degraded segmentation data Fluo-N2DH-SIM+ and Fluo-N3DH-SIM+ (Cell Tracking Challenge datasets). Reported scores are DET, SEG and TRA from the Cell Tracking Challenge (Fig8 and Fig9 and Supplementary Figures 3 and 4 are created from this data) compare_postprocessing_on_synth_bm.csv Comparing the different post-processing strategies of the proposed tracking algorithm algorithm on synthetically degraded segmentation data Fluo-N2DH-SIM+ and Fluo-N3DH-SIM+ (Cell Tracking Challenge datasets). Reported scores are DET, SEG and TRA from the Cell Tracking Challenge (Fig7 and Fig8 and Supplementary Figures 1 and 2 are created from this data) PLEASE NOTE: the folder compare_postprocessing_synth_bm  is provided in the repository 10.5281/zenodo.5227610 due to size restrictions. folders (decompressed approximately 90GB of data!) ----------- tracking_data     compare_all_synth_bm     Contains all tracking results for each tracking algorithm on the synthetically degraded datasets ()     compare_all_synth_bm_no_error     Contains the tracking results for each tracking algorithm provided with the perfect ground truth segmentation data     compare_postprocessing_synth_bm [will be stored in 10.5281/zenodo.5227610 due to size restrictions]     Contains all tracking resuls for each postprocessing configuration of the proposed cell tracking algorithm     the leaf folders are names run_xPOSTPROCESSING where x is the run number and POSTPROCESSING the postprocessing key     Postprocessing keys: ("no untangle" or "no masks" is indicated by an overline in the paper)     all ("untangle + masks" in the paper)     nd ("no untangle + masks")     nd_ns-l ("no untangle + no masks")     ns-l ("untangle + no masks")

FDup deduplication software data benchmark: 10Mi OpenAIRE Publications Dump

This dataset is a random subset of publications extracted from the OpenAIRE Research Graph (<a href="http://doi.org/10.5281/zenodo.4707307">http://doi.org/10.5281/zenodo.4707307</a>). The dataset contains ~10Mi JSON publications records.  The file is a zip archive containing gz files, each with one JSON per line. Each JSON is compliant to the schema available at <a href="http://doi.org/10.5281/zenodo.4723403">http://doi.org/10.5281/zenodo.4723403</a>. Learn more about the OpenAIRE Research Graph at <a href="https://graph.openaire.eu/">https://graph.openaire.eu</a>.

Data for publication "Switzerland's PM10 and PM2.5 environmental increments show the importance of non-exhaust emissions"

Data for publication "Switzerland's PM10 and PM2.5 environmental increments show the importance of non-exhaust emissions". Please see README.md for information.

opencc-zeroMar 2013View details →

FIG. 20. — Tectulipora tuberculata n in ERRATUM volume 34 (4), 2012: 693-738. Date of publication: December 28, 2012. Description of a bryozoan fauna from mud mounds of the Lebanza Formation (Lower Devonian) in the Arauz area (Pisuerga-Carrión Province, Cantabrian Zone, NW Spain)

FIG. 20. — Tectulipora tuberculata n. sp: A, B, tangential section showing superstructure, holotype SMF 21.361; C, mid tangential section showing autozooecial chambers, apertures and wide keels, SMF 21.378; D, tangential section showing autozooecial apertures, holotype SMF 21.361; E, tangential section of reverse surface showing microacanthostyles and nodes, paratype SMF 21.377; F, tangential section of obverse surface showing granulated skeleton of axial wall, paratype SMF 21.371; G, longitudinal section, paratype SMF 21.362; H, transverse section of conical colony at its base, paratype SMF 21.369.Scale bars:A, B, G, H, 1 mm; C, 0.5 mm; D, 0.2 mm; E, F, 0.1 mm.

Public resources about PHYVV and TMV detection in Jalapeño pepper plants using CNNs

This repository contains a dataset of Jalapeño pepper leaves which where divided into three classes labeles as "healthy", "PHYVV-infected" and "TMV-infected. In addition, the folder labeled as model contains all the information of the artificial intelligence model that was utilized to classify between the aforementioned classes.

Dataset part one to the publication "CAL-1 as Cellular Model System to Study CCR7-Guided Human Dendritic Cell Migration"

This study was supported in parts by research funding from the Swiss National Science Foundation (grant number 310030_189144), the Thurgauische Stiftung für Wissenschaft und Forschung, and the State Secretariat for Education, Research and Innovation to DFL.

Survey Data: Public Engagement with Science: A Survey for India Alliance Grantees

Lately, the Indian research ecosystem has seen an upward trend in scientists showing interest in communicating their science and engaging with non-scientific audiences; however, the number and variety of science communication or public engagement activities undertaken formally by scientists remains low in the country. There could be many contributing factors for this trend. To explore this further, the science funding public charity in India, DBT/Wellcome Trust India Alliance (India Alliance), in a first of its kind of study by a funding agency in India, surveyed its 243 research grantees in November 2020 requesting their views on public engagement with science in India through an online survey. The survey included both quantitative as well as open-ended questions to assess the understanding of, participation in, and attitude of India Alliance Fellows/Grantees towards public engagement with research, identify the enablers, challenges, and barriers to public engagement for India Alliance Fellows/Grantees, understand the specific needs (training/capacity-building, funding, etc.) and develop recommendations for India Alliance as well as for the larger scientific ecosystem in the country. The survey showed that India Alliance grantees are largely motivated to engage with the public about science or their research but lack professional recognition and incentives, training and structural support to undertake public engagement activities. A shareable survey was designed using Microsoft Forms. The survey employed a mixed methods strategy and included 24 closed-ended questions (multiple choice and Likert scale) and nine qualitative questions, similar to open-ended questions. The questions were modelled on a similar survey carried out by Wellcome in 2016 to gather views of researchers on public engagement in Asia and Africa. The survey was shared by email with 243 Indian researchers in receipt of India Alliance fellowships or grants, out of which 137 (male – 78; female – 59) responded to the survey. Of these, 90 respondents were basic science researchers, 22 were clinical researchers, and 25 were public health researchers. A majority, i.e. 81% of the respondents indicated working as an independent researcher for more than 4 years (time post-PhD). Furthermore, 58% of the respondents were based at research institutions, 18% at higher education institutions, and 17% at central, state and private universities; these organisations geographically represent around 31 cities of India (9 respondents chose to not reveal their host institution in the survey). Periodic reminders were sent by email to the fellows to complete the survey. Three fellows who received funding from India Alliance for their public engagement projects were contacted via email after the survey for their views (in 50-150 words) on the public engagement funding programme of India Alliance. They were informed that their input is intended to be included in a report of the survey results, and they can choose to either stay anonymous or be credited. The data was collected from 27 November 2020 until 28 April 2021. Following the end of the survey, the data automatically mapped on Microsoft Excel was cleaned for duplication and errors. Microsoft Excel tools were used to analyse and visualise the data. The study did not undergo a formal ethical clearance process as the primary objective of the study was to gather insights of grantees to inform India Alliance’s public engagement support mechanisms.  At the start of the survey, the objectives of the survey were clearly stated and the respondents were informed that the anonymized data of the survey may be communicated in the future. Participation in the survey was entirely voluntary.

opencc-by-nc-sa-4.0Sep 2021View details →

Datasets and Software for publication "Distinct RPA domains promote recruitment and the helicase-nuclease activities of Dna2"

- Magnetic tweezers and mass photometry datasets for the publication "Distinct RPA domains promote recruitment and the helicase-nuclease activities of Dna2, Nature Communications 2021" - costum written Matlab Software for Helicase Analysis

Dataset for Evolution of Cooperation in Costly Institutions: Red Queen and Black Queen Dynamics in Heterogenous Public Goods

This dataset contains the Matlab codes used in "Evolution of Cooperation in Costly Institutions: Red Queen and Black Queen Dynamics in Heterogenous Public Goods". The zip file contains Matlab codes used in simulation and numerical solutions of the replicator dynamics. The zip file "Figures" contains the Matlab code and data used to produce figures in this study.

openmit-licenseOct 2021View details →

Data for publication "Fast and Accurate Distance-based Phylogenetic Placement using Divide and Conquer" (APPLES-2)

Data and scripts used in the paper "Fast and Accurate Distance-based Phylogenetic Placement using Divide and Conquer"

opencc-by-4.0Apr 2021View details →

Dataset for "Radiation environment at the surface and subsurface of the Moon: Model development and validation" publication in Journal of Geophysical Research: Planets

data set used for plots in manuscript "Radiation environment at the surface and subsurface of the Moon: Model development and validation" submitted to GRL

opencc-by-4.0Oct 2021View details →

Data for paper publication 'Important role of stratospheric injection height for the distribution and radiative forcing of smoke aerosol from the 2019/2020 Australian wildfires'

This repository contains version 2.0 data from the aerosol-climate simulations performed with the ECHAM6.3-HAM2.3 model and aerosol lidar profiles, as presented in the paper publication by Heinold et al.: Important role of stratospheric injection height for the distribution and radiative forcing of smoke aerosol from the 2019/2020 Australian wildfires, submitted to Atmos. Chem. Phys. For details, please refer to the enclosed data description (README) file.

opencc-by-4.0Oct 2021View details →

Data in support of the publication "First Detection and Thermal Characterization of Terminator CO2 Ice Clouds with ExoMars/NOMAD" on Geophysical Research Letters

This archive contains the data underlying the 3 Figures in the main manuscript, including the vertical profiles of retrieved aerosols, vertical profiles of CO2 saturation ratio and spatial distribution of the retrieved clouds.

opencc-by-4.0Sep 2023View details →

Public spendings on housing in Hungary, 1990-2026

This database summarises central government expenditures on housing in Hungary, from the official Budget Acts and Closing Accounts Acts and other sources (e.g. Hungarian Central Statistical Office). The aim of the database was to determine how much money the government has spent on housing since 1990 and how much of this expenditure was socially targeted, i.e. how much was used to reduce housing poverty. The database organises publicly available central budget data into a machine-readable database. Thus, it is also making the government’s management of public funds more transparent. The database was created for <a href="https://www.habitat.hu/">Habitat for Humanity Hungary</a>’s Annual Report on Housing Poverty 2021 (<a href="https://habitat.hu/sites/wp-content/uploads/2021/12/Habitat_EvesJelentes_2021_final.pdf">Hungarian</a> / <a href="https://habitat.hu/sites/lakhatasi-jelentes-2021/wp-content/uploads/sites/10/2022/09/Habitat_AnnualReport_2021_EN_FINAL.pdf">English</a>), updated for the 2025 report. Further methodological details are included in the 2021 annual report. File list <ul> <li>description.rtf - Detailed description of the database (in Hungarian and English).</li> <li>lakaskiadasok_values_long.csv - Values of the detailed budget expenditures. Data for each year are in the rows of the table. Budget expenditures were grouped. Data sources are also included in this table. Expenditures are presented in both current and 2025 prices. </li> <li>lakaskiadasok_values_wide.csv - Values of the detailed budget expenditures. Data for each year are in the columns of the table. Budget expenditures were grouped. Data sources are also included in this table. Expenditures are presented in both current and 2025 prices. </li> <li>lakaskiadasok_variables.csv - Description of the variables of the detailed budget expenditures, both in English and in Hungarian. </li> <li>lakastamogatasok_values.csv - Values of the database on the ‘Housing subsidies’ budget line and the data source of each cell. Expenditures are presented in both current and 2024 prices.</li> <li>lakastamogatasok_variables.csv - Description of the variables on the expenditures of the ‘Housing subsidies’ budget line, both in English and Hungarian. </li> <li>price_deflator.csv - Value of the consumer price index used for the conversion to 2025 prices (2025=100).</li> </ul> The dataset and its description is fully bilingual (Hungarian and English).

opencc-by-4.0May 2019View details →

Public domain but paywalled: an overview of the papers of 1923

On 2019-01-01, for the first time in 20 years the USA has seen an expansion of the public domain: all works published in 1923 have returned to it. In this dataset we briefly explore the scholarly works published in 1923, as indexed by CrossRef, and their availability. In the Unpaywall dump of 2018-09-24, 73,484 DOIs are known for publications of 1923 (*1923.dois.txt). For all of these, we extracted availability status according to Unpaywall as of May 2019 using our previous methods (Leva 2017), finding only 10,767 open access works (*dois.oa.txt) and the rest presumably toll-access (*dois.notoa.txt). A breakdown by DOI prefix and therefore publisher (*dois.prefixes.ods) shows that the 20 biggest providers (with over ~1000 works each) typically have an OA rate of 4–8 %: most notable are Springer (10.1007) with over 9700 restricted works and JSTOR (10.2307) with over 6900. Marginally better does CUP (10.1017) with 16 %, while Wiley (10.1002) reaches 14 % mostly by assigning a DOI to thousands of "mastheads" (frontispices) which typically have no meaningful content. About 40 % of works are available for Nature (10.1038), almost exclusively with items from its "News" section, and for BMJ (10.1136). The Smithsonian is the only provider with a majority of OA works (66 %), thanks to the Biodiversity Heritage Library (BHL) which provides over 1400 works on the Internet Archive. Our list does not distinguish between "gold" and "green" open access: a portion of the available works is provided by open archives rather than the publishers. Moreover, some works are freely available and not detected as such (or vice versa) due to Unpaywall's unavoidable limitations. As illustrated by the Hirtle chart (Hirtle, 2019), works published before 1924 are nearly automatically in the public domain in USA, although exceptions may exist for works first published outside USA. Therefore, nearly all of the toll-access works found above represent an enclosure of the public domain and potentially a case of copyfraud if false statements of copyright ownership are attached. Similar considerations may be extended to works first published outside of the USA, which may be considered simultaneously published in the USA (within 30 days) due to the very nature of international journals (which were necessarily distributed in the USA and the mailing of which could benefit, in the 1920s, of a transatlantic crossing taking less than a week). We conclude that there is a significant opportunity for academic institutions, libraries and open archives to legally and easily expand access to tens of thousands of historical papers, as long as the publishers choose not to.

opencc-by-4.0Oct 2022View details →

Data for replication of the publication: Probabilistic leak localization in water distribution networks using a hybrid data-driven and model-based approach

20 to 30% of drinking water produced is lost due to leaks in water distribution pipes. In times of water scarcity, losing so much treated water comes at a significant cost, both environmentally and economically. In this paper, we propose a hybrid leak localization approach combining both model-based and data-driven modeling. Pressure heads of leak scenarios are simulated using a hydraulic model, and then used to train a machine-learning based leak localization model. A key element of our approach is that discrepancies between simulated and measured pressures are accounted for using a dynamically calculated bias correction, based on historical pressure measurements. Data of in-field leak experiments in operational water distribution networks were produced to evaluate our approach on realistic test data. Two problematic settings for leak localization were examined. In the first setting, an uncalibrated hydraulic model was used. In the second setting, an extended version of the water distribution network was considered, where large parts of the network were insensitive to leaks. Our results show that the leak localization model is able to reduce the leak search region in parts of the network where leaks induce detectable drops in pressure. When this is not the case, the model still localizes the leak but is able to indicate a higher level of uncertainty with respect to its leak predictions.