Find research datasets worth reusing

Fig. 5 in Freier Zugang zu den Informationen der Artenvielfalt - Wie werde ich Teil der Global Biodiversity Information Facility (GBIF)?

Fig. 5: Das Suchportal des Botanik-Knotens von GBIF-Deutschland, einer der mehreren im Internet verfügbaren Zugangspunkte zu den Daten des GBIF-Netzwerks.

Fig. 2 in Freier Zugang zu den Informationen der Artenvielfalt - Wie werde ich Teil der Global Biodiversity Information Facility (GBIF)?

Fig. 2:Tatenflüsse über das Internet im GBIF-Netzwerk zwischen Nutzer, Suchportal und Datenlieferant.

Fig. 3 in Freier Zugang zu den Informationen der Artenvielfalt - Wie werde ich Teil der Global Biodiversity Information Facility (GBIF)?

Fig. 3: Die Zuordnung der Daten aus dem relationalen Datenschema der Sammlungsdatenbank zu den ABCD-Elementen wird im Mapping festgelegt und ist in einer komfortablen Oberfläche mit dem Internet- Browser möglich.

Fig. 1 in Freier Zugang zu den Informationen der Artenvielfalt - Wie werde ich Teil der Global Biodiversity Information Facility (GBIF)?

Fig. 1: Die Wrapper-Software umgibt die bestehenden Sammlungsdatenbanken mit einer zusätzlichen Abstraktionsschicht und bietet so eine definierte Schnittstelle zwischen den existierenden Datenbanksystemen und den GBIF-Suchportalen.

Fig.1 in Die Global Biodiversity Information Facility (GBIF) - Struktur, Aufgaben und Ziele

Fig.1: Das Knotensystem GBIF Deutschland und seine Anbindung an GBIF International. Die Daten fliessen aus den Teilprojekten in die Datenbanksysteme der einzelnen Knoten, denen ein BioCASE-Wrapper aufgesetzt ist, der auf dem ABCD-Datenmodell basiert. Damit ist es möglich, alle angebundenen Daten über das Datenportal von GBIF International im Internet abzurufen bzw. verfügbar zu machen. GBIF International stellt ausserdem die Wrapper-Software DiGIR, welche auf dem Darwin Core 2 aufbaut, zur Verfügung. Einzelne Teilprojekte, wie z.B. DIG mit BIODAT im Knoten Evertebraten I, setzen eigene Datenbanklösungen ein und fungieren daher als direkte GBIF Datenprovider. Die Angaben entsprechen dem Stand Anfang April 2005.

opencc-by-4.0Nov 2023View details →

Supporting information for "Illuminating the nanostructure of diffuse interfaces: Recent advances and future directions in reflectometry techniques"

This deposition contains the data and analysis (Jupyter notebooks) detailed in Illuminating the nanostructure of diffuse interfaces: Recent advances and future directions in reflectometry techniques. All Jupyter notebooks have also been converted into PDF files for ease of viewing. All data and code (notebooks) required to reproduce the analysis can be found within the "supporting_data_analysis.zip" archive. This archive contains two sub-directories:<ul><li>insituAnalysis<ul><li>Jupyter notebook outlining how to perform the `on-the-fly' analysis.</li><li>Data directory containing all temporally sliced neutron reflectometry data.</li></ul></li><li>MaxEnt<ul><li>Jupyter notebook outlining how to perform the maximum entropy modelling approach for polymer volume fraction profiles.</li><li>Data directory containing relevant neutron reflectometry data and PCHIP spline modelling by Gresham et al. (<a href="www.doi.org/10.1107/S160057672100251X">10.1107/S160057672100251X</a>).</li><li>Code available on the <a href="https://github.com/refnx/refnx-models/tree/master/MaxEntVFP">refnx-models GitHub repo</a>.</li></ul></li></ul>

opencc-by-4.0Nov 2023View details →

EduQuick: A Dataset for Assessing Summarization of Informal Educational Content for Social Media

The presented dataset is a curated collection of model-generated text for educational TikTok content, abbreviated as EduQuick. This dataset is the result of evaluating and selecting high-quality content generated by the GPT-4 model following an empirical study. It aims to provide engaging and informative summaries suitable for TikTok's educational audience.

Supporting information for the paper "High peak current lightning and the production of Elves"

Supporting data for the paper "High peak current lightning and the production of Elves" by I. Bjørge-Engeland et al.

opencc-by-4.0Nov 2023View details →

Data for SI-Hg D2 validation report for the calibration of elemental mercury gas generators including information on repeatability, reproducibility and uncertainty evaluation at emission and ambient levels extended to the sub ng/m3 level

In deliverable 2 of the SI-Hg project the first validation results of the SI-Hg calibration protocol are reported. Within the SI-Hg project a protocol for the metrological calibration of elemental mercury gas generators used in the field was developed. For the validation the output of two different mercury gas generators was calibrated according to the protocol. As metrological reference standard the primary mercury gas standard from the Van Swinden Laboratory (VSL) was used. The measurements described in the protocol could be performed during the validation and the data was processed using a script to determine the output of the candidate generator and the uncertainty of the mercury concentration. Based on the validation measurements and data processing several improvements for the calibration protocol were identified and were used to improve the calibration protocol. In this repository data obtained during the validation is published. The files of the following comparisons between reference generator and candidate generator can be found in this repository:<ul><li>VSL vs VSL<ul><li>m1<ul><li>09022022 calibration mercury gas generator VSL vs VSL m1</li><li>VSL_vs_VSL_m1</li></ul></li><li>m2 <ul><li>05072022 calibration mercury gas generator VSL vs VSL m2</li><li>VSL_vs_VSL_m2</li></ul></li><li>m3<ul><li>07072022 calibration mercury gas generator VSL vs VSL m3</li><li>VSL_vs_VSL_m3</li></ul></li></ul></li><li>VSL vs PSA before modification<ul><li>m1<ul><li>15032022 calibration mercury gas generator VSL vs PSA fixed m1</li><li>single_point_VSL_vs_PSA_fixed_m1_4</li><li>single_point_VSL_vs_PSA_fixed_m1_6</li><li>single_point_VSL_vs_PSA_fixed_m1_8</li><li>single_point_VSL_vs_PSA_fixed_m1_12</li></ul></li><li>m2<ul><li>28032022 calibration mercury gas generator VSL vs PSA fixed m2</li><li>single_point_VSL_vs_PSA_fixed_m2_4</li><li>single_point_VSL_vs_PSA_fixed_m2_6</li><li>single_point_VSL_vs_PSA_fixed_m2_8</li><li>single_point_VSL_vs_PSA_fixed_m2_12</li></ul></li><li>m3 <ul><li>06042022 calibration mercury gas generator VSL vs PSA fixed m3</li><li>single_point_VSL_vs_PSA_fixed_m3_4</li><li>single_point_VSL_vs_PSA_fixed_m3_6</li><li>single_point_VSL_vs_PSA_fixed_m3_8</li><li>single_point_VSL_vs_PSA_fixed_m3_12</li></ul></li><li>m4 <ul><li>12042022 calibration mercury gas generator VSL vs PSA fixed m4</li><li>single_point_VSL_vs_PSA_fixed_m4_4</li><li>single_point_VSL_vs_PSA_fixed_m4_6</li><li>single_point_VSL_vs_PSA_fixed_m4_8</li><li>single_point_VSL_vs_PSA_fixed_m4_12</li></ul></li><li>less tubing <ul><li>14042022 calibration mercury gas generator VSL vs PSA fixed less tubing</li><li>single_point_VSL_vs_PSA_fixed_less_tubing</li></ul></li><li>less tubing and air as complementary gas <ul><li>19042022 calibration mercury gas generator VSL vs PSA fixed less tubing in air</li><li>single_point_VSL_vs_PSA_fixed_less_tubing_air</li></ul></li></ul></li><li>VSL vs PSA after modification<ul><li>m1 air as complementary gas <ul><li>Calibration PSA fixed mercury gas generator air m1 20230324</li><li>PSA_fixed_air_m1_9</li><li>PSA_fixed_air_m1_11</li><li>PSA_fixed_air_m1_14</li></ul></li><li>m2 air as complementary gas <ul><li>Calibration PSA fixed mercury gas generator air m2 20230327</li><li>PSA_fixed_air_m2_9</li><li>PSA_fixed_air_m2_11</li><li>PSA_fixed_air_m2_14</li></ul></li><li>m3 air as complementary gas <ul><li>Calibration PSA fixed mercury gas generator air m3 20230329</li><li>PSA_fixed_air_m3_9</li><li>PSA_fixed_air_m3_11</li><li>PSA_fixed_air_m3_14</li></ul></li><li>m4 air as complementary gas <ul><li>Calibration PSA fixed mercury gas generator air m4 20230907</li><li>PSA_fixed_air_m4_9</li><li>PSA_fixed_air_m4_11</li><li>PSA_fixed_air_m4_14</li></ul></li><li>m5 air as complemantary gas <ul><li>Calibration PSA fixed mercury gas generator air m5 20230911</li><li>PSA_fixed_air_m5_9</li><li>PSA_fixed_air_m5_11</li><li>PSA_fixed_air_m5_14</li></ul></li><li>m1 nitrogen (N2) as complementary gas<ul><li>Calibration PSA fixed mercury gas generator nitrogen m1 20230330</li><li>PSA_fixed_N2_m1_9</li><li>PSA_fixed_N2_m1_11</li><li>PSA_fixed_N2_m1_14</li></ul></li><li>m2 N2 as complementary gas <ul><li>Calibration PSA fixed mercury gas generator nitrogen m2 20230331</li><li>PSA_fixed_N2_m2_9</li><li>PSA_fixed_N2_m2_11</li><li>PSA_fixed_N2_m2_14</li></ul></li><li>m3 N2 as complementary gas <ul><li>Calibration PSA fixed mercury gas generator nitrogen m3 20230405</li><li>PSA_fixed_N2_m3_9</li><li>PSA_fixed_N2_m3_11</li><li>PSA_fixed_N2_m3_14</li></ul></li><li>measurement at TUV<ul><li>PSA_Fixed_at_TUV</li></ul></li></ul></li></ul>

opencc-by-4.0Jul 2024View details →

data sets supporting information about rime-splintering experiments

The uploaded data are related to the publication: ' Secondary Ice Production - No Evidence of Efficient Rime-Splintering Mechanism during Dry and Wet Rimer Growth' by Seidel et al. in the journal Atmospheric Chemistry and Physics. Droplet size distributions can be found in DSD.csv. Information on the individual secondary ice production experiments are provided by SIP_experiments_valid.csv. The descriptive information of the parameters can be found in the respective read_me file.

restrictedcc-by-4.0Dec 2023View details →

Research data and related information to the paper Asrat, Z. et al. 2023/24

Many mountain-restricted animal species, including Canis simensis, Tachyoryctes macrocephalus, Tragelaphus buxtoni, and Tragelaphus scriptus, can be found in the Ericaceous vegetation of the Bale Mountains, which is a biodiversity hotspot (Miehe and Miehe, 1994; Girma et al. 2018). Currently it's under pressure from a rising human population, it is characterized by fire-resistant woody trees or branched shrubs of Erica (Erica trimera and Erica arborea) (Wesche et al., 2000; Gil-Romera et al., 2019). We postulate that the current change in the distribution of Erica plants is due to anthropogenic disturbances rather than seed scarcity, in addition to the Erica distribution edge. In order to determine their effects on the composition of Ericaceous vegetation and the regeneration of soil seed banks, we collected data considering aspects, altitude, and disturbance of the environment. Our data includes list of plant species and corresponding families' , including growth habits and lifestyle. We identified species from stand vegetation and germination test plots, and our data contained plant cover, families, and related abundance data to show the major environmental constraints on Erica growth above tree-line. Along with the vegetation data, we ranked anthropogenic disturbance by site observation, and the study plots floor covers, altitude, and aspect are included for testing variability. For every site, the density of Erica seeds and the Erica cover are arranged in columns and tested for significant factor. Pleas read the journal article for more information.

Supplementary information for Yamada et al. (2023): Natural history notes of the rare enigmatic ant Opamyrma hungvuong: A first glimpse of their preying behavior on centipedes (Hymenoptera: Formicidae: Leptanillinae)

Supprementary figure and videos (with original unedited source videos of behavior of Opamyrma hungvuong) for: Aiki Yamada, An Van Dang & Katsuyuki Eguchi (2023). Natural history notes of the rare enigmatic ant Opamyrma hungvuong: A first glimpse of their preying behavior on centipedes (Hymenoptera: Formicidae: Leptanillinae). Asian Myrmecology 16: e016009

opencc-by-4.0Aug 2023View details →

Online trust in Information Society. Four representative database and questionnaire (Hungary, Romania, Poland, Czech Republic

This data collection was conducted by the Institute of the Information Society of the University of Public Service - Ludovika, and covered four Central European countries: the Czech Republic, Hungary, Poland, and Romania, with the aim of examining the characteristics of the use of information technology by the adult population in the region, mainly for communication purposes. A telephone survey was conducted in October and November 2019, and the results are representative of the population over 18 years of age in the four countries, categorized by age, gender, education, type of settlement and region. The data set contains: <ul> <li>Questionnaires in the original languages (Hungarian, Czech, Romanian and Polish), and all questionnaires in English language, too.</li> <li>The four databases with variables in English</li> <li>Merged database of four databases</li> <li>Code table about variables </li> </ul>

Data for: Understanding consumers to inform market interventions for Singapore's shark fin trade

<ol> <li>Sharks, rays and their cartilaginous relatives (Class Chondricthyes, herein 'sharks') are amongst the world's most threatened species groups, primarily due to overfishing, which in turn is driven by complex market forces including demand for fins. Understanding the high-value shark fin market is a global priority for conserving shark and rays, yet the preferences of shark fin consumers are not well understood. This gap hinders the design of evidence-based consumer-focused conservation interventions. </li> <li>Using an online discrete choice experiment, we explored preferences for price, quality, size, menu types (as a proxy for exclusivity) and source of fins (with varying degrees of sustainability) among 300 shark fin consumers in Singapore: a global entrepot for shark fin trade. </li> <li>Overall, consumers preferred lower-priuced fins sourced from responsible fisheries or produced using novel lab-cultured techniques. We also identified four consumer segments, each with distinct psychographics characteristics and consumption behaviors. </li> <li>These preferences and profiles could be leveraged to inform new regulatory and market-based interventions regarding the sale and consumption of shark fins, and incentivize responsible fisheries and lab-cultured innovation for delivering conservation and sustainability goals. </li> <li>In addition, message framing around health benefits, shark endangerment and counterfeiting could reinforce existing beliefs amongst consumers in Singapore and drive behavioral shifts to ensure that market demand remains within the limits of sustainable supply. </li> </ol> This dataset includes all the responses collected from the online discrete choice experiment which was implemented by a market survey company, as well as the goodness-of-fit chi-square analyses. These data were also used to plot the figures in the manuscript and the Supplemental Information. Password for excel sheet titled 'Final CEOE data' is 35433. Please refer to the published manuscript for more detailed information. The authors received financial support from Silverstrand Capital awarded to Wildlife Conservation Society for the research, authorship, and publication of this work.

Data set for "Distributed and specific encoding of sensory, motor and decision information in the mouse neocortex during goal-directed behavior"

Data set for: Oryshchuk A, Sourmpis C, Weverbergh J, Asri R, Esmaeili V, Modirshanechi A, Gerstner W, Petersen CCH, Crochet S (2024) Distributed and specific encoding of sensory, motor and decision information in the mouse neocortex during goal-directed behavior. Cell Reports 43: 113618. https://doi.org/10.1016/j.celrep.2023.113618   There are 2 files in this upload:   1. The file named "2024_Oryshchuk_CellReports.pdf" is the Open Access pdf of the online publication in Cell Reports.   2. The file named " Oryshchuk _data_code.zip" (~1.8 GB) is a zipped version of a folder "Oryshchuk _data_code" (~2.3 GB), which contains the preprocessed data analyzed in the study along with the Matlab and Python codes used to generate the published figures. To access the data and codes, first unzip the file. ·       The subfolder “Atlas” contains templates from the Allen Mouse Brain Reference Altas of anatomical brain sections used to map the location of the silicon probes (Supplementary Figure S1). ·       The subfolder “Clustering-master” contains the Matlab codes used for the clustering on neuronal activity (Figure 1). The output is the data structure ‘Data_Clustering.mat’ file already provided in the folder ‘Data’. ·       The subfolder “Code” contains the main Matlab codes used to analyze the data and plot the figures. The ouput from the clustering and decoding analyses are provided in the ‘Data’ folder, thus the Matlab codes can be run independently, without running the ‘clustering’ or ‘decoding’ codes first. ·       The subfolder “Data” contains the Matlab  data structures containing the electrophysiological and behavioral data from whisker rewarded (‘DataWR.mat’) and non-rewarded (‘DataWnonR.mat’) mice, the behavioral data for optogenetic inactivation in rewarded mice, the clustering results (‘Data_Clustering.mat’) and a subfolder containing the results from the decoding analyses (“Decoding”). ·       The subfolder “decoding” contains the Python codes used for the decoding analyses. The required configuration can be found in the file ‘requirements.txt’. To run the codes, follow instructions from the ‘README.md’ file. ·       The subfolder “Figures” will be populated with figures saved in .png and .eps formats as well as a ‘Methods.txt’ files when running the main Matlab codes. ·       The subfolder “Functions” contains subfunctions used by the main Matlab codes to analyze the data and plot the figures. ·       The subfolder “Results” will be populated with Matlab data structures as well as a ‘.xlsx’ files when running the main Matlab codes. When running the code, you need to set the Matlab file path to be "Oryshchuk _data_code". In addition, you should add the folder "Oryshchuk_data_code" with subfolders to the Matlab path. Some parts of the code rely upon previous results, and need to be executed sequentially in the order of the figure panels in the journal publication. Please note that some of the code can take several hours to execute.

Fig. 6 in New information on ornithopod dinosaurs from the Late Jurassic of Portugal

Fig. 6. Dorsal vertebrae Ankylopollexia indet. from the Lourinhã municipality, Portugal, Lourinhã Formation, Kimmeridgian–Tithonian. A. Partial neural arch, ML 864 in anterior (A1), posterior (A2), lateral (A3), and dorsal (A4) views. B, C. Dorsal vertebrae, ML 452a, complete (B) and ML 452b, incomplete (C) specimens, in anterior (B1, C1), posterior (B2, C2), lateral (B3, C3), dorsal (B4, C4), and ventral (digitally modified) (B5, C5) views.

Fig. 4 in New information on ornithopod dinosaurs from the Late Jurassic of Portugal

Fig. 4. Limb bones of Dryosauridae indet. from the Lourinhã municipality, Portugal, Lourinhã Formation, Kimmeridgian–Tithonian. A, B. Femur, ML 2055 (A), ML 563 (B), in anterior (A1, B1), lateral (A2, B2), medial (A3, B3), posterior (A4, B4), distal (A5, B5), and proximal (A6, B6) views. C, D. Tibia, ML 2055 associated to femur ML 2055 (C), ML 505 (D), in anterior (C1, D1), lateral (C2, D2), posterior (C3, D3), medial (C4, D4), proximal (D5), and distal (C5, D6) views.

Fig. 8 in New information on ornithopod dinosaurs from the Late Jurassic of Portugal

Fig. 8. Ankylopollexian appendicular skeleton from the Lourinhã municipality, Portugal, Lourinhã Formation, Kimmeridgian–Tithonian. Coracoid ML 2206 (A), scapula ML 2042 (B), in lateral (A1, B1) and medial (A2, B2) views.

Fig. 7 in New information on ornithopod dinosaurs from the Late Jurassic of Portugal

Fig. 7. Comparative dorsal vertebrae table of selected Ankylopollexians from the Late Jurassic and Early Cretaceous. A, B. Ankylopollexia indet. Lourinhã municipality, Portugal, Lourinhã Formation, Kimmeridgian–Tithonian. A. ML 452 in lateral view (A1, A2). B. ML 864 in right lateral view. C. "Uteodon" SHN.LPP 015 in left lateral view; Praia da corva, Torres Vedras Municipality, Portugal, Lourinhã Formation (Kimmeridgian–Tithonian). D. "Uteodon" aphanoecetes CM 11337 in left lateral view; East end of Carnegie Quarry at Dinosaur National Monument, Uintah County, Utah (USA), Morrison Formation (Kimmeridgian–Tithonian). E. Camptosaurus dispar (unnumbered specimen) in left lateral view; Bone Cabin Quarry, Wyoming USA), Morrison Formation (Kimmeridgian–Tithonian). F. "Cumnoria" prestwichii OUM. J.3303 in lateral view; Oxford, UK, Kimmeridge Clay Formation (Kimmeridgian–Tithonian). G. Hippodraco scutodens UMNH VP 20208 in left lateral view; Andrew's Site, Grand County, Utah; Upper Yellow Cat Memberof the Cedar Mountain Formation (upper Barremian–lowermost Aptian). H. Iguanacolossus fortis UMNH VP 20205 in right lateral view; Don's Ridge, Grand County, Utah, Lower Yellow Cat Member, Cedar Mountain Formation (?lower Barremian). I. Mantellisaurus atherfieldensis IRSNB 1551 in left lateral view; Isle of Wight, Wessex Formation (Barremian). J. Barilium dawsoni NHMUK R798 in left lateral view; Shornden, East Sussex, UK, Wadhurst Clay Formation (Valanginian). K. Hypselospinus fittoni NHMUK R604 in lateral view; Shornden Quarry, Hastings, UK, Wadhurst Clay Formation (Valanginian). L. Iguanodon bernissartensis IRSNB "Individu S" in left lateral view; Bernissart, Belgium, Sainte Barbe Clays Formation Barremian). Abbreviations: dia, diapophysis; par, parapophysis. Scale bars 100 mm. Re-drawn from: C, Escaso 2014: fig. 6.5; D, Carpenter and Wilson 2008: fig. 11; E, Carpenter and Galton 2018: fig. 22D; F, Galton and Powell 1980: fig. 4; G, McDonald 2010b: fig. 27; H, McDonald 2010b: fig. 10;, Norman 1980: fig. 37; J, Norman 2011: fig. 4; K, Norman 2015: fig. 22; L, Norman 1980: fig. 31).

Fig. 3 in New information on ornithopod dinosaurs from the Late Jurassic of Portugal

Fig. 3. Axial skeleton elements of Dryosauridae indet. (A, B) from the Lourinhã municipality, Portugal, Lourinhã Formation, Kimmeridgian–Tithonian compared with of Dryosaurus altus (C), Camptosaurus ("Uteodon") aphanoecetes (D), and Mantellisaurus atherfieldensis (E). Dorsal vertebrae: ML 2321a (A) and ML 2321b (B), in dorsal (A1, B1), anterior (A2, B2), lateral (A3, A6, B3, B6), posterior (A4, B4), and ventral (A5, B5) views. Dorsal neural arches: YPM 1876 (C), CM 11337 (D), IRSNB 1551 (E), in dorsal view.