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Figure 9. from: Data sharing tools adopted by the European Biodiversity Observation Network Project - Research Ideas and Outcomes 2: e9390 (31 May 2016) https://doi.org/10.3897/rio.2.e9390
Figure 9. - Information flows between EU BON and LTER Europe, as envisaged on the 3rd EU BON Stakeholder Roundtable in Granada on 9-11 December 2015.
Figure 8. from: Data sharing tools adopted by the European Biodiversity Observation Network Project - Research Ideas and Outcomes 2: e9390 (31 May 2016) https://doi.org/10.3897/rio.2.e9390
Figure 8. - The patchiness of survey coverage in Europe illustrated by the distribution map of Plantago lanceolata taken from GBIF in 2016. This species is one of the commonest and most widespread in Europe, it should occur in almost all areas of this map, but in fact the data traces out the borders of countries and area who have published data on GBIF.
Figure 6. from: Data sharing tools adopted by the European Biodiversity Observation Network Project - Research Ideas and Outcomes 2: e9390 (31 May 2016) https://doi.org/10.3897/rio.2.e9390
Figure 6. - Individual Metacat instances can be connected to DataOne which replicates public files. Thus the data is still available if a single instance goes offline.https://search.dataone.org/#data/page/0
Figure 5. from: Data sharing tools adopted by the European Biodiversity Observation Network Project - Research Ideas and Outcomes 2: e9390 (31 May 2016) https://doi.org/10.3897/rio.2.e9390
Figure 5. - PPBio has installed a Metacat instance for their researchers to upload and make publicly available the results of work related to biodiversity in the Western Amazon.https://ppbiodata.inpa.gov.br/metacatui/
Figure 4. from: Data sharing tools adopted by the European Biodiversity Observation Network Project - Research Ideas and Outcomes 2: e9390 (31 May 2016) https://doi.org/10.3897/rio.2.e9390
Figure 4. - The public data repository provided by the Knowledge Network for Biocomplexity (KNB).https://knb.ecoinformatics.org/#data/page/0
Figure 3. from: Data sharing tools adopted by the European Biodiversity Observation Network Project - Research Ideas and Outcomes 2: e9390 (31 May 2016) https://doi.org/10.3897/rio.2.e9390
Figure 3. - The implementation of Darwin Core Archive in Plazi to transfer treatment data. Observation data described with Darwin Core terms.
Figure 1. from: Data sharing tools adopted by the European Biodiversity Observation Network Project - Research Ideas and Outcomes 2: e9390 (31 May 2016) https://doi.org/10.3897/rio.2.e9390
Figure 1. - ARPHA consists of two integrated workflows: in ARPHA-XML, the manuscript is written and processed via the ARPHA Writing Tool, and in ARPHA-DOC, the manuscript is submitted and processed as document file(s).
Data and literature repository for "Climate Futures are Political Futures: Integrating Political Development Into the Shared Socioeconomic Pathways (SSPs)"
<p>The datasets provided in the repository (listed in Table 1 of the manuscript):</p> <ul> <li>Governance (Andrijevic et al., 2020)*</li> <li>Government effectiveness (Andrijevic et al., 2020)*</li> <li>Violent conflict (Hegre et al., 2016)</li> <li>Rule of law (update to the Soergel et al., 2021)</li> </ul> <p>*Please note that these two variables can be found in the same data file.<br><br></p> <p>The indicators can also be retrieved through the <a href="https://ssp-extensions.apps.ece.iiasa.ac.at/">SSP Extensions Explorer.</a> <br><br><strong><br>For applications of the projections of political indicators in further analyses, please consult the following references: </strong> </p> <p>Brutschin, E., Pianta, S., Tavoni, M., Riahi, K., Bosetti, V., Marangoni, G., & Van Ruijven, B. J. <a href="https://iopscience.iop.org/article/10.1088/1748-9326/abf0ce/meta">A multidimensional feasibility evaluation of low-carbon scenarios.</a> <em>Environmental Research Letters </em>2021, <em>16</em>(6), 064069.</p> <p>Gidden MJ, Brutschin E, Ganti G, Unlu G, Zakeri B, Fricko O<em>, et al. </em><a title="https://iopscience.iop.org/article/10.1088/1748-9326/acd8d5" href="https://iopscience.iop.org/article/10.1088/1748-9326/acd8d5">Fairness and feasibility in deep mitigation pathways with novel carbon dioxide removal considering institutional capacity to mitigate</a>. <em>Environmental Research Letters </em>2023, <strong>18</strong>(7)<strong>: </strong>074006. </p> <p>Hoch JM, de Bruin SP, Buhaug H, Von Uexkull N, van Beek R, Wanders N. <a title="https://iopscience.iop.org/article/10.1088/1748-9326/ac3db2" href="https://iopscience.iop.org/article/10.1088/1748-9326/ac3db2">Projecting armed conflict risk in Africa towards 2050 along the SSP-RCP scenarios: a machine learning approach</a>. <em>Environmental Research Letters </em>2021, <strong>16</strong>(12)<strong>: </strong>124068. </p> <p>Joshi DK, Hughes BB, Sisk TD. <a title="https://www.sciencedirect.com/science/article/abs/pii/S0305750X15000145" href="https://www.sciencedirect.com/science/article/abs/pii/S0305750X15000145">Improving governance for the Post-2015 Sustainable Development Goals: Scenario forecasting the next 50 years</a>. <em>World Development </em>2015, <strong>70: </strong>286-302. </p> <p>Moyer JD. <a title="https://www.sciencedirect.com/science/article/pii/S0305750X23000062" href="https://www.sciencedirect.com/science/article/pii/S0305750X23000062">Blessed are the peacemakers: The future burden of intrastate conflict on poverty</a>. <em>World Development </em>2023, <strong>165: </strong>106188. </p> <p>Moyer JD, Turner SD, Meisel CJ. <a title="https://journals.sagepub.com/doi/abs/10.1177/0022343320929740" href="https://journals.sagepub.com/doi/abs/10.1177/0022343320929740">What are the drivers of diplomacy? Introducing and testing new annual dyadic data measuring diplomatic exchange</a>. <em>Journal of Peace Research </em>2021, <strong>58</strong>(6)<strong>: </strong>1300-1310. </p> <p>Petrova, K, Olafsdottir, G, Hegre, H, Gilmore, EA (2023). <a title="https://iopscience.iop.org/article/10.1088/1748-9326/acb163" href="https://iopscience.iop.org/article/10.1088/1748-9326/acb163">The ‘conflict trap’ reduces economic growth in the shared socioeconomic pathways</a>. <em>Environmental Research Letters</em>, 2023, <strong>18</strong>(2), 024028. </p>
Illustrations from the Environmental Data Science Book: Shared under CC-BY 4.0 for reuse
<p>Illustrations as part of the <em>Environmental Data Science</em> book.</p> <p>When using any of the images, please include the following attribution with the specific DOI as listed on the particular Zenodo page:</p> <blockquote> <p>This illustration is created by Scriberia with The Turing Way community. Used under a CC-BY 4.0 licence. DOI: <a href="https://doi.org/10.5281/zenodo.7030142">10.5281/zenodo.7030142</a></p> </blockquote> <p>When using any of the images, please include the following attribution with the specific DOI as listed on the particular Zenodo page:</p> <p>You can cite all versions by using the DOI <a href="https://doi.org/10.5281/zenodo.7030142">10.5281/zenodo.7030142</a>. This DOI represents all versions, and will always resolve to the latest one.</p> <p><em>This work was supported by Wave 1 of The UKRI Strategic Priorities Fund under the EPSRC Grant EP/W006022/1, particularly the Environment & Sustainability theme within that grant & The Alan Turing Institute.</em></p>
Data from: The MRi-Share database: Brain imaging in a cross-sectional cohort of 1,870 university students
<p>We report on MRi-Share, a multi-modal brain MRI database acquired in a unique sample of 1,870 young healthy adults, aged 18 to 35 years, while undergoing university-level education. MRi-Share contains structural (T1 and FLAIR), diffusion (multispectral), susceptibility weighted (SWI), and resting-state functional imaging modalities. Here, we described the contents of these different neuroimaging datasets and the processing pipelines used to derive brain phenotypes, as well as how quality control was assessed. In addition, we present preliminary results on associations of some of these brain image-derived phenotypes at the whole brain level with both age and sex, in the subsample of 1,722 individuals aged less than 26 years. We demonstrate that the post-adolescence period is characterized by changes in both structural and microstructural brain phenotypes. Grey matter cortical thickness, surface area and volume were found to decrease with age, while white matter volume shows increase. Diffusivity, either radial or axial, was found to robustly decrease with age whereas fractional anisotropy only slightly increased. As for the neurite orientation dispersion and densities, both were found to increase with age. The isotropic volume fraction also showed a slight increase with age. These preliminary findings emphasize the complexity of changes in brain structure and function occurring in this critical period at the interface of late maturation and early aging.</p>
Text-fig. 10. Langtonia bisulcata REID et CHANDLER. a, b, e–g: Holotype, V. 22984, from micro-CT data. a: Dorsiventral view surface rendering. b: Dorsiventral view translucent volume rendering showing outline of locule cast. c: Equatorial transverse fracture showing paired dorsal infolds and locules with shape of a ε in cross section, reflected light, V. 22993. d: Digital transverse section from micro-CT data, of fruit with two well developed ε-shaped locules, V. 22985. e–g: Successive digital transverse sections with one well developed ε-shaped locule and infolds of the abortive locule visible in (g) (arrows). h–j: Physical transverse thin sections of specimen from middle Eocene Clarno Formation, Oregon, USA with well-preserved mesocarp including longitudinal canals in (j) (arrows), USNM 424875; Scale bars 0.5 cm in (a, b), 2.5 mm in (c–g), 5 mm in (h), 2 mm in (i), 1 mm in (j); (a, b) share same scale bar; (c, d) share same scale bar; (e, f, g) share same scale bar. in Mastixioid Fruits (Cornales) From The Early Eocene London Clay Flora: Morphology, Anatomy And Nomenclatural Revision
Text-fig. 10. Langtonia bisulcata REID et CHANDLER. a, b, e–g: Holotype, V. 22984, from micro-CT data. a: Dorsiventral view surface rendering. b: Dorsiventral view translucent volume rendering showing outline of locule cast. c: Equatorial transverse fracture showing paired dorsal infolds and locules with shape of a ε in cross section, reflected light, V. 22993. d: Digital transverse section from micro-CT data, of fruit with two well developed ε-shaped locules, V. 22985. e–g: Successive digital transverse sections with one well developed ε-shaped locule and infolds of the abortive locule visible in (g) (arrows). h–j: Physical transverse thin sections of specimen from middle Eocene Clarno Formation, Oregon, USA with well-preserved mesocarp including longitudinal canals in (j) (arrows), USNM 424875; Scale bars 0.5 cm in (a, b), 2.5 mm in (c–g), 5 mm in (h), 2 mm in (i), 1 mm in (j); (a, b) share same scale bar; (c, d) share same scale bar; (e, f, g) share same scale bar.
Text-fig. 8. Lanfrancia subglobosa E.REID et M.CHANDLER. a–c, e–g: Holotype V. 23014. a: reflected light. b, c: Surface renderings from micro-CT data. a, b: Lateral views with dorsal surface of locule facing forward and locule casts protruding in upper part. c: Apical view. d: Fruit showing two locule casts the dorsal surfaces of which face to the left and the right, V. 30417(1). e–g: Successive digital transverse sections showing four u to v to c-shaped locules from micro-CT data. h: Physical transverse section of specimen in (d). i–k: Physical transverse section, V. 30419 from Herne Bay, blue lines in K indicating limits of fibre layer lining the locule. l: Detail from (h), showing sclerenchyma composing the septa and central axis. m: Transverse section, enlargement from (i), showing anatomy of tissues adjacent to the dorsal infold. Blue lines indicate limits of the fibre layer lining the locule. n: Part of (m) recut, tangential section transecting the dorsal infold (central), both limbs of the locule cast, and peripheral parts of the pericarp on either side. o: Detail from (n), showing anatomy of the infold. Scale bars 5 mm in (a–h) (a–g share the same bar), 3 mm in (i), 1 mm in (j–m), 0.5 mm in (n), 0.2 mm in (o). in Mastixioid Fruits (Cornales) From The Early Eocene London Clay Flora: Morphology, Anatomy And Nomenclatural Revision
Text-fig. 8. Lanfrancia subglobosa E.REID et M.CHANDLER. a–c, e–g: Holotype V. 23014. a: reflected light. b, c: Surface renderings from micro-CT data. a, b: Lateral views with dorsal surface of locule facing forward and locule casts protruding in upper part. c: Apical view. d: Fruit showing two locule casts the dorsal surfaces of which face to the left and the right, V. 30417(1). e–g: Successive digital transverse sections showing four u to v to c-shaped locules from micro-CT data. h: Physical transverse section of specimen in (d). i–k: Physical transverse section, V. 30419 from Herne Bay, blue lines in K indicating limits of fibre layer lining the locule. l: Detail from (h), showing sclerenchyma composing the septa and central axis. m: Transverse section, enlargement from (i), showing anatomy of tissues adjacent to the dorsal infold. Blue lines indicate limits of the fibre layer lining the locule. n: Part of (m) recut, tangential section transecting the dorsal infold (central), both limbs of the locule cast, and peripheral parts of the pericarp on either side. o: Detail from (n), showing anatomy of the infold. Scale bars 5 mm in (a–h) (a–g share the same bar), 3 mm in (i), 1 mm in (j–m), 0.5 mm in (n), 0.2 mm in (o).
Data Used in [~Re] Setting Inventory Levels in a Bike Sharing Network
<p>Data used to reproduce the publication "Setting an Inventory Levels in a Bike Sharing Network" by Datner et al.</p> <p>This data correspond to the scenarios generated from the parameters given by the authors.</p>
FAIR Data sharing à la FBM : garantie d'une recherche plus transparente et reproductible
<p>Nouveaux services développés à la FBM UNIL/CHUV pour répondre aux principes FAIR/ Open Research Data</p>
Gravitational lensing: towards combining the multi-messengers (data sharing)
<div> <div># Gravitational lensing: towards combining the multi-messengers (data sharing)</div> <br> <div>This repository contains the data and code to plot Fig. 1 and Fig. 4 from the article titled - "Gravitational lensing : towards combining the multi messengers". The two folders included here are described below.</div> <br> <div>## 1. delta-psi</div> <br> <div>- This folder contains the data and code to plot Fig. 1 in the paper.</div> <div>- To generate plot for Fig. 1, run python plot_fig1.py</div> <div>- It computes the y-axis ($\delta \Delta \psi$ : uncertainty in the determination of the relative Fermat potential) for each combination of image pairs (x-axis), for 3 mock lenses, for each of the 4 configuration which are stored in "PLpert_fig_data"</div> <br> <div>## 2. grb-gw-lensing</div> <br> <div>- This folder contains the data and code to plot Fig. 4 in the paper.</div> <div>- data-gererator.ipynb generates the data for the plot. This data is stored in "ler_data" folder. Parameters for the GRB-GW lensing system are stored there.</div> <div>- grb-gw-lensing-plot.ipynb generates the plot for Fig. 4 (stored as 'combined-final.png'). It uses the data generated by data-gererator.ipynb. This plot shows, i) detectable lensed GRBs and the associated detectable lensed GW events, and ii) detectable lensed GW events and their</div> <div>associated detectable lensed GRBs.</div> </div>
Data set for Plos One Article "Force sharing and other collaborative strategies in a dyadic force perception task"
<p>Data set for Plos One Article :</p> <p>Tatti, F., Baud-Bovy G. (2018) "Force sharing and other collaborative strategies in a dyadic force perception task". doi: 10.1371/journal.pone.0192754</p> <p>This study investigates how people might interact to extract information from the forces experienced while holding an object together. More specifically, the dyads (i.e. pairs formed two persons) participating to the study had to identify the direction of a small force applied to a jointly held object by a haptic device. This study included a condition where each participant responded independently and another one where the two participants had to agree upon a single negotiated response.</p> <p>The dataset (data.csv) contains the force produced by the haptic device and the average and standard deviation of the interaction force for all trials together with the responses of the participants. We also included the initial and final position of the haptic device and total distance traveled for each trial.</p> <p>The data are in comma separated text format and its description in a PDF document (readme.pdf).</p>
Open Research Data in Medicine - Polish scientists' attitudes towards data sharing
<p>The survey on the attitudes and beliefs of research staff has been carried out at selected Polish medical universities. The purpose of the questionnaire was to collect respondents' opinions on opening research data created during their scientific work. The research was aimed at preparing the necessary educational, technical and legal support for scientists after launching the Polish Medical Platform, when Polish scientists will be asked to deposit their data in local repositories.</p>
Handschriftencensus data for Network of Shared Manuscript Transmission
<p>List of nodes and edges to create networks of shared manuscripts transmission with the data from <em>Handschriftencensus</em> (http://handschriftencensus.de)</p> <p>The files can be uploaded directly to <em>Gephi</em> and can be easily adapted to use in other softwares for network analysis. </p> <p>Reading the<em> Gephi</em> documentation should be enough to understand the fields used.</p>
Data supporting the "Health Libraries Sharing Game"
<p>This dataset provides the necessary files to reproduce the "Health libraries sharing game". This game was created for the workshop "Health libraries: sharing through gaming" held in Basel on Wednesday the 19th of June 2019, as part of the EAHIL conference.</p> <p>Inspired by the game "Bucket of Doom", this game aims to help health librarians address challenging professional situations (based on real situations experienced by the authors). The players will have to be creative to overcome each challenge. </p> <p>The game is composed of cards that include possible situations to resolve, some tools, as well as resources available to solve those questions. The cards are accompanied by a "How to play" file explaining the rules of the game and a "Name sheet" file with the combination of funny names that participants can choose at the beginning of the game. The README.txt file describes the files and the content of the different folders of the dataset.</p> <p>Please consult the following article for further information about the creation of the game:</p> <p>Gómez-Sánchez, A., Kerdelhue, G., Isabel-Gómez, R., González-Cantalejo, M., Iriarte, P., & Muller, F. (2019). Health libraries: sharing through gaming. Journal of EAHIL, 15(3), 8-11. https://doi.org/10.32384/jeahil15329 </p>
Data for: "Considering unique, shared, and dominant brain activation in the VWFA and LOC: A comparison of separate and combined word and picture naming"
<p>FMRI data underlying analyses for Experiments 1 and 2 in "Considering unique, shared, and dominant brain activation in the VWFA and LOC: A comparison of separate and combined word and picture naming".</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.