cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.23721/100/1478804
title: HTTP DATASET CSIC 2010

description: The HTTP dataset CSIC 2010 contains the generated traffic targeted to an eCommerce web application developed at our department. In this web application, users can buy items using a shopping cart and register by providing some personal information. As it is a web application in Spanish, the data set contains some Latin characters.
The dataset is generated automatically and contains 36,000 normal requests and more than 25,000 anomalous requests. The HTTP requests are labeled as normal or anomalous and the dataset includes attacks such as SQL injection, buffer overflow, information gathering, files disclosure, CRLF injection, XSS, server side include, parameter tampering and so on. This dataset has been successfully used for web detection in previous works [4, 5, 6, 7, 8, 9].

The traffic is generated following the next steps: 

First, real data are collected for all the parameters of the web application. All the data (names, surnames, addresses, etc.) are extracted from real databases. These values are stored in two databases: one for the normal values and other for the anomalous ones. Additionally, all the public available pages of the web application are listed. 
Next, normal and anomalous requests are generated for every web page. In the case that normal requests have parameters, the parameter values are filled out with data taken from the normal database randomly. The process is analogous for anomalous requests, where the values of the parameters are taken from the anomalous database.

Three types of anomalous requests were considered: 

1) Static attacks try to request hidden (or non-existent) resources. These requests include obsolete files, session ID in URL rewrite, configuration files, default files, etc. 

2) Dynamic attacks modify valid request arguments: SQL injection, CRLF injection, cross-site scripting, buffer overflows, etc. 

3) Unintentional illegal requests. These requests do not have malicious intention, however they do not follow the normal behavior of the web application and do not have the same structure as normal parameter values (for example, a telephone number composed of letters). 

The attacks were generated with the help of tools such as Paros [10] and W3AF[11].

The WAFs where this dataset was used [4,5,6,7] follow the anomaly approach, i.e. the normal behavior of the web application is defined and the behavior apart from that are considered anomalous. Therefore, in this approach only normal traffic is needed for the training phase.

The dataset is divided into three different subsets. One subset for the training phase, which has only normal traffic. And two subsets for the test phase, one with normal traffic and the other one with malicious traffic. ;
DOI: 10.13145/bacdive144947.20211221.6
title: Bacillus cereus

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive144948.20211221.6
title: Bacillus pumilus

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive144949.20211221.6
title: Brevibacillus brevis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive144950.20211221.6
title: Bacillus pumilus

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive144951.20211221.6
title: Erysipelothrix rhusiopathiae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive144952.20211221.6
title: Abiotrophia defectiva

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive144953.20211221.6
title: Neisseria meningitidis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive144954.20211221.6
title: Neisseria meningitidis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.17632/3bksddznyg.1
title: Data Extraction of Nano Silica as a potential filler in nanocomposites from Rice Husk Ash with Ballmill and Coprecipitation Methods

description: This article consists of data from the extraction of nano silica from rice husk ash (RHA) by ball mill and coprecipitation methods. RHA is an agricultural waste that is widely found in Indonesia. The extracted RHA can be used as a filler in nanocomposites. Calcining RHA did silica extraction from rice husk ash at 500oC for 5 hours. After calcining RHA in the Ball Mill for 10 hours with a rotation of 250 rpm. Furthermore, RHA was mixed with 5 M HCl in a ratio of 1:4, stirred, and heated with a Magnetic Stirrer at 70 oC for 4 hours at a speed of 400 rpm. Then mixed again with NH4OH M in a ratio of 1:4, stirred, and heated with a Magnetic Stirrer at a temperature of 70 oC for 4 hours at a speed of 400 rpm. The resulting RHA was further characterized by Scanning Electron Microscope (SEM), Fourier-transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD). The resulting data shows that nano silica from RHA is optimal and can be used as a filler in nanocomposites.
DOI: 10.26050/wdcc/c6sspawawm
title: CMIP6_supplemental ScenarioMIP AWI AWI-CM-1-1-MR

description: Project: CMIP6 Supplemental Data - The project is aligned to the CMIP6 project. It includes datasets of variables, which result from CMIP6 MIPs, but are not part of the CMIP6 MIP tables. Summary: These data include supplemental datasets for 'CMIP6.ScenarioMIP.AWI.AWI-CM-1-1-MR' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The AWI-CM 1.1 MR climate model, released in 2018, includes the following components: atmos: ECHAM6.3.04p1 (T127L95 native atmosphere T127 gaussian grid; 384 x 192 longitude/latitude; 95 levels; top level 80 km), land: JSBACH 3.20, ocean: FESOM 1.4 (unstructured grid in the horizontal with 830305 wet nodes; 46 levels; top grid cell 0-5 m), seaIce: FESOM 1.4. The model was run by the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany (AWI) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 25 km, seaIce: 25 km. Individuals using the data must abide by terms of use for CMIP6 data (https://pcmdi.llnl.gov/CMIP6/TermsOfUse). The original license restrictions on these datasets were recorded as global attributes in the data files, but these may have been subsequently updated.
DOI: 10.6084/m9.figshare.19354835.v3
title: Dentists’ Perceptions on the present and future dental practice during the COVID-19 Pandemic

description: This is the questionaire and interview guide used to collect data pertaining to the present study.
DOI: 10.6084/m9.figshare.9228176
title: G-RUN : Global Runoff Reconstruction

description: An updated and extended version of the dataset (referred as G-RUN ENSEMBLE) is available at https://figshare.com/articles/dataset/G-RUN_ENSEMBLE/12794075<br><br>-------------------------------------------------------------------------------------------------<br>The dataset contains a gridded global reconstruction of monthly runoff timeseries. In-situ streamflow observations from the GSIM dataset are used to train a machine learning algorithm that predicts monthly runoff rates based on antecedent precipitation and temperature from the Global Soil Wetness Project Phase 3 (GSWP3) meteorological forcing dataset. We thank Prof. Dr. Hyungjun Kim for developing the GSWP3 dataset and providing us with early access to the data. The data are provided in NetCDFv4 format at monthly resolution covering the period 1902-2014. <br>The GRUN reconstruction ("GRUN_v1_GSWP3_WGS84_05_1902_2014.nc" file) is provided on a 0.5 degrees (WGS84) grid in units of mm/day. The runoff time series correspond to the ensemble mean of 50 reconstructions obtained by training the machine learning model with different subsets of data. The individual ensemble members of the reconstruction are provided in the "Realizations_GRUN_v1_GSWP3_WGS84_05_1902_2014.zip" file.<br>When using this dataset, please cite: Ghiggi, G., Humphrey, V., Seneviratne, S. I., Gudmundsson (2019), GRUN: An observations-based global gridded runoff dataset from 1902 to 2014, Earth Syst. Sci. Data, 2019, DOI: https://doi.org/10.5194/essd-2019-32<br> The complete collection of in-situ streamflow observations from the GSIM archive can be found at: - https://doi.pangaea.de/10.1594/PANGAEA.887477 - https://doi.pangaea.de/10.1594/PANGAEA.887470 <br>For further information on the GSIM dataset see: - https://doi.org/10.5194/essd-10-765-2018 - https://doi.org/10.5194/essd-10-787-2018 <br>For further information on GSWP3, see: - https://doi.org/10.20783/DIAS.501 - https://hyungjun.github.io/GSWP3.DataDescription - http://hydro.iis.u-tokyo.ac.jp/GSWP3/exp1.html
DOI: 10.18434/m31824
title: Cell-scaffold contact
DOI: 10.21223/p3/cvryso
title: Dataset for: Participatory mapping for long-term monitoring and red listing of cultivated potato populations in Huancavelica, Peru

description: Biodiversity sustains a wide variety of genetic traits that are very valuable for the potato's adaption to changing environments and successful cultivation in the future. It is assumed that several factors are threatening biodiversity in the Andes. Without robust baselines and indicators used for reliable time lines, it is impossible to assess diversity loss or increase. Long-term studies in situ are necessary to distinguish short term fluctuation from general tendencies caused by environmental and socio-cultural shifts and to understand ongoing evolutionary principles within the potato genepool. Powerful tools are needed that facilitate the management, evolution and exchange of mainly oral transmitted traditional knowledge. Participatory mapping is such a tool where cognitive spatial knowledge is transformed into maps at grassroots level by trained community members. Local knowledge can be documented in context with social, political, biotic and abiotic factors and if accompanied with comprehensive capacity building and the application of robust indicators will strengthen the cross-generation knowledge exchange and sensitization towards land use shifts, resource dynamics affected by climate and societal related factors and pressure. Most local farmers practice traditional small scale agriculture with focus on potato production, partly organized in sectoral fellow systems. Because of the high biological diversity, coexistence of wild potato species and the extensive local knowledge owned by the potato farmers, communities of this study site contribute to generate knowledge on dynamics of potato diversity in situ and complement the diversity hotspot network ‘Chirapaq Ñan’ for long-term in situ monitoring of cultivated potato. This dataset contributes to i) elaborate robust baseline to assess spatial and temporal dynamics and distribution ranges of potato diversity within and among fields, families and altitudinal belts, ii) elaborate on the application of utilized diversity indexes for red listing of potato landraces and cultivar types. The dataset contains parcel and community maps, geographic distribution of cultivated potato populations, red listing of potato landraces and cultivar types and supplementary files (surveys, protocols) used for this study.
DOI: 10.21223/p3/vraxfd
title: Dataset for: Participatory mapping for long-term monitoring and red listing of cultivated potato populations in Pasco, Peru

description: Biodiversity sustains a wide variety of genetic traits that are very valuable for the potato's adaption to changing environments and successful cultivation in the future. It is assumed that several factors are threatening biodiversity in the Andes. Without robust baselines and indicators used for reliable time lines, it is impossible to assess diversity loss or increase. Long-term studies in situ are necessary to distinguish short term fluctuation from general tendencies caused by environmental and socio-cultural shifts and to understand ongoing evolutionary principles within the potato genepool. Powerful tools are needed that facilitate the management, evolution and exchange of mainly oral transmitted traditional knowledge. Participatory mapping is such a tool where cognitive spatial knowledge is transformed into maps at grassroots level by trained community members. Local knowledge can be documented in context with social, political, biotic and abiotic factors and if accompanied with comprehensive capacity building and the application of robust indicators will strengthen the cross-generation knowledge exchange and sensitization towards land use shifts, resource dynamics affected by climate and societal related factors and pressure. Most local farmers practice traditional small scale agriculture with focus on potato production, partly organized in sectoral fellow systems. Because of the high biological diversity, coexistence of wild potato species and the extensive local knowledge owned by the potato farmers, communities of this study site contribute to generate knowledge on dynamics of potato diversity in situ and complement the diversity hotspot network ‘Chirapaq Ñan’ for long-term in situ monitoring of cultivated potato. This dataset contributes to i) elaborate robust baseline to assess spatial and temporal dynamics and distribution ranges of potato diversity within and among fields, families and altitudinal belts, ii) elaborate on the application of utilized diversity indexes for red listing of potato landraces and cultivar types. The dataset contains parcel and community maps, geographic distribution of cultivated potato populations, red listing of potato landraces and cultivar types and supplementary files (surveys, protocols) used for this study.
DOI: 10.5281/zenodo.3266930
title: Brain Invaders calibration-less P300-based BCI with modulation of flash duration Dataset (bi2015a)

description: <strong>Summary:</strong>

This dataset contains electroencephalographic (EEG) recordings of 50 subjects playing to a visual P300 Brain-Computer Interface (BCI) videogame named <em>Brain </em><em>Invaders</em>. The interface uses the oddball paradigm on a grid of 36 symbols (1 Target, 35 Non-Target) that are flashed pseudo-randomly to elicit the P300 response. EEG data were recorded using 32 active wet electrodes with three conditions: flash duration 50ms, 80ms or 110ms. The experiment took place at GIPSA-lab, Grenoble, France, in 2015. A full description of the experiment is available at https://hal.archives-ouvertes.fr/hal-02172347. Python code for manipulating the data is available at https://github.com/plcrodrigues/py.BI.EEG.2015a-GIPSA. The ID of this dataset is <em>bi2015a.</em>

 

<strong>Full description of the experiment and dataset: </strong>https://hal.archives-ouvertes.fr/hal-02172347

 

<strong><em>Investigators</em>:</strong> Eng. Louis Korczowski, B. Sc. Martine Cederhout

 

<strong><em>Technical</em></strong> <strong><em>Support</em></strong>: Eng. Anton Andreev, Eng. Grégoire Cattan, Eng. Pedro. L. C. Rodrigues, M. Sc. Violette Gautheret

 

<strong><em>Scientific Supervisor:</em></strong> Ph.D. Marco Congedo

 

<strong>ID of the dataset: </strong><em>bi2015a</em>
DOI: 10.5281/zenodo.3830794
title: Sparktope example LPs

description: This dataset consists of the main examples from the Sparktope compiler. These examples are pre-compiled and ready to pass to a solver. The filename format is <em>polytope</em>-<em>objective</em>.lp.gz where <em>polytope</em> is compiled from a .spk program and <em>objective</em> is compiled from a .in input description. These are the (relatively) easy versions of the examples with some extra constraints forcing the input variables. More challenging instances (that should still have the same optimal solutions) can be produced with e.g. "grep -v force <em>forced</em>.lp &gt; <em>unforced</em>.lp"
DOI: 10.5281/zenodo.5606502
title: Automatic exhaustive calculations of large material space by Korringa-Kohn-Rostoker coherent approximation method --- Applied to equiatomic quaternary high entropy alloys

description: Calculated data of equiatomic quaternary solid solution phase (high-entropy alloys) on local magnetic moment, total magnetization, magnetic phase transition temperature and residual resistivity. The data was added on October 28.
DOI: 10.5683/sp2/0qdtjx
title: Risk of Any Hypoglycemia with new antihyperglycemic agents in patients with type 2 diabetes: a systematic review and meta-analysis

description: supplementary appendix for a systematic review and meta-analysis
DOI: 10.13145/bacdive144955.20211221.6
title: Neisseria meningitidis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.34740/kaggle/dsv/4285601
title: AutoXGB
DOI: 10.6084/m9.figshare.21269862
title: Supplementary Material for: Responsiveness to Direct Verbal Suggestions and Dissociation Independently Predict Symptoms Associated with Environmental Factors

description: Symptoms associated with environmental factors (SAEF; also known as idiopathic environmental intolerance) include the presentation of various common symptoms that are causally attributed to normally benign environmental triggers, such as electromagnetic fields, odors, and chemicals. SAEF are typically conceptualized as psychogenic in origin, and multiple models have proposed that dissociation and responsiveness to suggestions may contribute to the manifestation or expression of these symptoms. This preregistered study sought to characterize these variables’ independent and interactive predictive utility. Participants (<i>N</i> = 294) completed psychometric measures of dissociative tendencies, trauma, SAEF, and a behavioral scale indexing responsiveness to direct verbal suggestions. Moderation analyses were used to evaluate predictions derived from different models regarding whether these variables would uniquely and interactively predict individual differences in the reporting of SAEF. Responsiveness to verbal suggestions individually predicted SAEF, but no clear evidence was observed for an interaction with dissociation or trauma. Dissociation similarly individually predicted SAEF with additional evidence that this association was moderated by trauma such that the positive association between dissociation and SAEF was only significant in those with moderate-to-high trauma exposure. These results align with the proposal that environmental factors may function as suggestions that trigger involuntary symptoms in some individuals. Our findings further suggest that among individuals with a history of trauma exposure, those with dissociative tendencies may be at an increased risk of experiencing SAEF.
DOI: 10.13145/bacdive144956.20211221.6
title: Actinomyces naeslundii

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive144957.20211221.6
title: Sphingomonas parapaucimobilis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive144958.20211221.6
title: Enterococcus cecorum

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive144959.20211221.6
title: Streptococcus acidominimus

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive144960.20211221.6
title: Streptococcus salivarius

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive144961.20211221.6
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive144962.20211221.6
title: Streptococcus gordonii

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.5281/zenodo.7046702
title: Reconstruction of Mediterranean sea-level changes and contributions for 1960-2018

description: <strong>Data supporting the paper:</strong> <strong>Calafat, F. M., Frederikse, T., and Horsburgh, K. (2022). The Sources of Sea-Level Changes in the Mediterranean Sea since 1960, Journal of Geophysical Research Oceans, under review.</strong> Please cite the paper above when using this data set. This new version of the data set has been published to support the paper above and includes more data than the previous version as well as several improvements and refinements. Version 2.3 has been created to include regional estimates of rates due to the inverse barometer effect. <em>Data description:</em> <strong>Bayesian_estimates_Mediterranean_sea_level.nc:</strong> this file contains gridded estimates of relative sea-level changes and their instantaneous rates for 1960-2018 in the Mediterranean Sea, separated into the individual contributions of: Sterodynamic changes (i.e., ocean dynamics and thermal expansion). Contemporary GRD (i.e., changes in Earth gravity, Earth rotation, and solid-earth deformation due to land-mass changes). GIA (i.e., glacial isostatic adjustment). Short-term variability (interannual to decadal). Inverse barometer effect. <strong>data_input.mat:</strong> this file contains all of the data needed to run the Bayesian hierarchical model. This includes the observational data from tide gauges and satellite altimetry as well as the ensemble-mean and ensemble covariance matrices for the sea-level fingerprints associated with contemporary GRD effects and GIA. The Bayesian estimates have been obtained using a spatiotemporal Bayesian hierarchical model (see paper). This work has been carried out within the framework of the EuroSea project funded by European Union’s Horizon 2020 research and innovation programme under grant agreement No 862626.
DOI: 10.13145/bacdive144963.20211221.6
title: Streptococcus gordonii

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive144964.20211221.6
title: Streptococcus gordonii

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive144965.20211221.6
title: Streptococcus gordonii

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive144966.20211221.6
title: Stenotrophomonas maltophilia

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive144967.20211221.6
title: Lactobacillus paracasei

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive144968.20211221.6
title: Bacillus cereus

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.