Skip to main content
Powered by ShareScore

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.

1,202

datasets available to search

ShareScore release 0.9.0

Reset

Dataset results

1,202 results for “interests”

Learn how ShareScore rates datasets ↗
edi52/100

May to July 2018 regions of interest (ROIs) of tidal marsh and tidal forest plant species to be used as ground reference data in habitat mapping

We collected field data from sites distributed in habitats along the salinity axis of the Altamaha River estuary and the Duplin River to be used as ground reference data for habitat mapping. Regions of interest (ROIs) for tidal marsh (salt, brackish, tidal fresh) and tidal fresh forest vegetation species were generated near ground control points (GCP) by digitizing vegetation areas in ArcGIS 10.4 based on field maps.These observations will be used to create habitat maps from aerial photographs of the Altamaha River estuary, GA taken following Hurricane Irma to better understand how the storm surge affected tidal vegetation and to examine any shifts in vegetation type.

openCustomSep 2021View details →
zenodo48/100

Density Layers of selected Points of Interest from Open Street Map

<p>This dataset contains a raster layer of 100*100m resolution showing the density of selected amenities from Open Street Map. The amenities are selected as points of interest, where electric vehicles owners are likely to stop for a moment and recharge their vehicles. This dataset covers Europe and was obtained with the Overpass API. This dataset can be used to identify possible charging location for electric vehicles or any other purpose requiring to quantify the number of amenities in an area.</p> <p>&nbsp;</p> <p>This dataset shows densities of a selection of Points of Interest in Europe from Open Street Map [1].</p> <p>Included countries are:</p> <p>&nbsp;</p> <p><em><strong>country_codes</strong> = [&#39;AT&#39;, &#39;BE&#39;, &#39;BG&#39;, &#39;HR&#39;, &#39;CY&#39;, &#39;CZ&#39;, &#39;DK&#39;, &#39;EE&#39;, &#39;FI&#39;, &#39;FR&#39;, &#39;DE&#39;, &#39;GR&#39;, &#39;HU&#39;, &#39;IE&#39;, &#39;IT&#39;,&#39;LV&#39;, &#39;LT&#39;, &#39;LU&#39;, &#39;MT&#39;, &#39;NL&#39;, &#39;PL&#39;, &#39;PT&#39;, &#39;RO&#39;, &#39;SK&#39;, &#39;SI&#39;, &#39;ES&#39;, &#39;SE&#39;, &#39;AL&#39;, &#39;AD&#39;, &#39;AM&#39;, &#39;BY&#39;, &#39;BA&#39;, &#39;FO&#39;, &#39;GE&#39;, &#39;GI&#39;, &#39;IS&#39;, &#39;IM&#39;, &#39;XK&#39;, &#39;LI&#39;, &#39;MK&#39;, &#39;MD&#39;, &#39;MC&#39;, &#39;ME&#39;, &#39;NO&#39;, &#39;SM&#39;, &#39;RS&#39;, &#39;CH&#39;, &#39;TR&#39;, &#39;UA&#39;, &#39;GB&#39;, &#39;VA&#39;]</em></p> <p>&nbsp;</p> <p>The requests of Points of Interest have been performed with the Overpass API [2] (free of charge).</p> <p>&nbsp;</p> <p>The codes included in each density are listed below :</p> <p>&nbsp;</p> <p><strong><em>&#39;highway&#39;</em></strong><em> = [&#39;&quot;highway&quot;=&quot;motorway&quot;&#39;, &#39;&quot;highway&quot;=&quot;rest_area&quot;&#39;];</em></p> <p><strong><em>&#39;parkings&#39;</em></strong><em> = [&#39;&quot;parking&quot;=&quot;surface&quot;&#39;, &#39;&quot;parking&quot;=&quot;multi-storey&quot;&#39;, &#39;&quot;parking&quot;=&quot;street_side&quot;&#39;, &#39;&quot;parking&quot;=&quot;underground&quot;&#39; , &#39;&quot;park_ride&quot;&#39; ];</em></p> <p><strong><em>&#39;school&#39;</em></strong><em> = [&#39;&quot;amenity&quot;=&quot;college&quot;&#39;, &#39;&quot;building&quot;=&quot;college&quot;&#39;, &#39;&quot;building&quot;=&quot;university&quot;&#39;, &#39;&quot;amenity&quot;=&quot;university&quot;&#39;, &#39;&quot;amenity&quot;=&quot;school&quot;&#39; , &#39;&quot;amenity&quot;=&quot;school&quot;&#39;, &#39;&quot;amenity&quot;=&quot;kindergarten&quot;&#39;, &#39;&quot;amenity&quot;=&quot;library&quot;&#39;];</em></p> <p><strong><em>&#39;health&#39;</em></strong><em>= [&#39;&quot;amenity&quot;=&quot;clinic&quot;&#39;, &#39;&quot;amenity&quot;=&quot;dentist&quot;&#39;, &#39;&quot;amenity&quot;=&quot;school&quot;&#39; , &#39;&quot;amenity&quot;=&quot;doctors&quot;&#39;, &#39;&quot;amenity&quot;=&quot;hospital&quot;&#39;, &#39;&quot;amenity&quot;=&quot;pharmacy&quot;&#39;,&#39;&quot;amenity&quot;=&quot;veterinary&quot;&#39;]; </em></p> <p><strong><em>&#39;cafe&#39;</em></strong><em>= [&#39;&quot;amenity&quot;=&quot;cafe&quot;&#39;,&#39;&quot;amenity&quot;=&quot;ice_cream&quot;&#39;, &#39;&quot;amenity&quot;=&quot;internet_cafe&quot;&#39;]; </em></p> <p><strong><em>&#39;supermarket&#39;</em></strong><em> = [&#39;&quot;shop&quot;=&quot;supermarket&quot;&#39;, &#39;&quot;shop&quot;=&quot;mall&quot;&#39;, &#39;&quot;shop&quot;= &quot;department_store&quot;&#39;, &#39;&quot;shop&quot;= &quot;convenience&quot;&#39;];</em></p> <p><strong><em>&#39;restaurant&#39;</em></strong><em>= [&#39;&quot;amenity&quot;=&quot;restaurant&quot;&#39;];</em></p> <p><strong><em>&#39;fastfood&#39;</em></strong><em> = [&#39;&quot;amenity&quot;=&quot;fast_food&quot;&#39;];</em></p> <p><strong><em>&#39;sport&#39;</em></strong><em>= [&#39;&quot;sport&quot;&#39;]; </em></p> <p><strong><em>&#39;hotel&#39;</em></strong><em> = [&#39;&quot;tourism&quot;=&quot;hotel&quot;&#39;, &#39;&quot;building&quot;=&quot;hotel&quot;&#39;, &#39;&quot;tourism&quot;=&quot;guest_house&quot;&#39;,&#39;&quot;tourism&quot;=&quot;apartment&quot;&#39;,&#39;&quot;tourism&quot;=&quot;hostel&quot;&#39;,&#39;&quot;tourism&quot;=&quot;motel&quot;&#39;,&#39;&quot;tourism&quot;=&quot;camp_site&quot;&#39;]; </em></p> <p><strong><em>&#39;pubs&#39;</em></strong><em> = [&#39;&quot;amenity&quot;=&quot;bar&quot;&#39;,&#39;&quot;amenity&quot;=&quot;pub&quot;&#39;, &#39;&quot;amenity&quot;=&quot;biergarten&quot;&#39;];</em></p> <p><em>&#39;theatre&#39;= [&#39;&quot;amenity&quot;=&quot;theatre&quot;&#39;, &#39;&quot;amenity&quot;=&quot;cinema&quot;&#39;, &#39;&quot;amenity&quot;=&quot;music_venue&quot;&#39;, &#39;&quot;leisure&quot;=&quot;stadium&quot;&#39; ]; </em></p> <p><strong><em>&#39;night&#39;</em></strong><em> = [&#39;&quot;amenity&quot;=&quot;nightclub&quot;&#39;, &#39;&quot;amenity&quot;=&quot;casino&quot;&#39;,&#39;&quot;amenity&quot;=&quot;gambling&quot;&#39;,&#39;&quot;amenity&quot;=&quot;stripclub&quot;&#39;]; </em></p> <p><strong><em>&#39;socio&#39;</em></strong><em>= [&#39;&quot;amenity&quot;=&quot;arts_centre&quot;&#39;, &#39;&quot;amenity&quot;=&quot;community_centre&quot;&#39;, &#39;&quot;amenity&quot;=&quot;social_centre&quot;&#39;, &#39;&quot;amenity&quot;=&quot;music_school&quot;&#39;, &#39;&quot;amenity&quot;=&quot;language_school&quot;&#39;]; </em></p> <p><strong><em>&#39;shop&#39;</em></strong><em> = [&#39;&quot;shop&quot;&#39;];</em></p> <p><strong><em>&#39;tourism&#39;</em></strong><em> = [&#39;&quot;amenity&quot;=&quot;exhibition_centre&quot;&#39;, &#39;&quot;tourism&quot;=&quot;attraction&quot;&#39;,&#39;&quot;tourism&quot;=&quot;viewpoint&quot;&#39;,&#39;&quot;tourism&quot;=&quot;aquarium &quot;&#39;,&#39;&quot;leisure&quot;=&quot;beach_resort &quot;&#39;,&#39;&quot;tourism&quot;=&quot;gallery&quot;&#39;,&#39;&quot;tourism&quot;=&quot;museum&quot;&#39;,&#39;&quot;tourism&quot;=&quot;theme_park&quot;&#39;,&#39;&quot;tourism&quot;=&quot;zoo&quot;&#39;,&#39;&quot;tourism&quot;=&quot;artwork&quot;&#39;];</em></p> <p>&nbsp;</p> <p>The pixel values are the sum of the number of POIs of each type located in the pixel.</p> <p>&nbsp;</p> <p><em>Limitations of the dataset</em></p> <p>- The dataset provides densities of only a selection of points of interests, regardless of its type. The complete list of amenity codes can be found on the OSM Wiki [3].</p> <p>- Ways are only considered through their centre points.</p> <p>&nbsp;</p> <p>[1] &ldquo;Open Street Map.&rdquo; <a href="https://www.openstreetmap.org/">https://www.openstreetmap.org/</a> (accessed Sep. 05, 2023).</p> <p>[2] &ldquo;Overpass API.&rdquo; <a href="https://wiki.openstreetmap.org/wiki/Overpass_API">https://wiki.openstreetmap.org/wiki/Overpass_API</a>&nbsp; (accessed Sep. 05, 2023).</p> <p>[3] &ldquo;Open Street Map Wiki.&rdquo; <a href="https://wiki.openstreetmap.org/wiki/Key:amenity#Sustenance">https://wiki.openstreetmap.org/wiki/Key:amenity#Sustenance</a> (accessed Sep. 05, 2023).</p>

opencc-by-4.0Sep 2023View details →
zenodo48/100

Deliverable T2.2 soil threats and soil ecosystem services of interest in SERENA.xlsx

<p>The internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales. &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</p> <p>In T2.2 we discussed the definitions of soil threats (ST) and soil-based ecosystem services (SES) to be further analysed in SERENA. In this process we kept information from the literature review and the results of the national prioritisation of ST and SES. This dataset description is an Excel with sheets of literature search and national prioritisation from the participating countries. Please read metadata at the fist sheet. Furthermore, the last sheet shows the results of our discussion on definitions that we had to clarify before the prioritisation.&nbsp;</p>

opencc-by-4.0Oct 2024View details →
zenodo44/100

Undirected Node Attributed Social Network Graph of Twitter Users interested in plastic pollution - created in the framework of the PlasticTwist project

<p>This dataset has been created in the framework of the Plastic Twist project (<a href="https://ptwist.eu/">Ptwist</a>) and more specifically using the Ptwist crowdsourcing application (<a href="https://crowdsourcing.plastictwist.com/">crowdsourcing.plastictwist.com/</a>). We are sharing the edge list and specific node attributes (hashtags) of Twitter users posting about plastic pollution. The dataset can be used for community detection,clustering, node importance, influence maximization tasks, etc. Each user is represented by a unique integer which has nothing to do with the official Twitter user ID. The dataset contains three (3) files:&nbsp;</p> <ul> <li>ptwist.edgelist: A list containing all the&nbsp;1,362,863 edges between the users. When loaded they create an undirected graph of 800K+ users.</li> <li>node_attributes.txt: This file contains information about the hashtags used by each user. (e.g.&nbsp;&quot;652003&quot;: [&quot;SingleUsePlastic&quot;] -&gt; user 6529003 has used the hashtag SingleUsePlastic)&nbsp;</li> <li>annotated_graph: A pickle file which, when loaded, returns a&nbsp;<a href="https://networkx.github.io/">NetworkX</a>&nbsp;node attributed undirected graph.</li> </ul> <p>&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Jan 2020View details →
zenodo44/100

Land use and land cover samples for specific regions of interest in the Brazilian Cerrado agricultural belt

<p>Land use and land cover samples for specific regions of interest in the Brazilian Cerrado agricultural belt in 2019/2020. Total of samples: 957. The process to collect them is described in Chaves, M., &amp; Sanches, I. (2023). Improving crop mapping in Brazil's Cerrado from a data cubes-derived Sentinel-2 temporal analysis.&nbsp;Remote Sensing Applications: Society and Environment, 32, 101014.&nbsp;<a href="https://www.sciencedirect.com/science/article/pii/S2352938523000964">https://www.sciencedirect.com/science/article/pii/S2352938523000964</a> and Chaves, M., Soares, A., Mataveli, G., Sánchez, A., &amp; Sanches, I. (2023).&nbsp;A semi-automated workflow for LULC mapping via Sentinel-2 data cubes and spectral indices.&nbsp;Automation, 4(1), 94-109.&nbsp;<a href="https://www.mdpi.com/2673-4052/4/1/7">https://www.mdpi.com/2673-4052/4/1/7</a>.</p>

opencc-by-4.0Nov 2023View details →
zenodo44/100

Research Data Alliance Interest Group Professionalising Data Stewardship Career Tracks Survey Dataset

<p>This is the final dataset resulting from the data steward Career Tracks survey that the Reseach Data Alliance (RDA) Interest Group Professionalising Data Stewardship carried out in 2022. Data stewards were defined as professionals who aim at guaranteeing that data is appropriately treated in all stages of the research cycle (i.e., design, collection, processing, analysis, preservation, data sharing and reuse); we invited responses from participants who either now or in the past carried out data stewardship functions, regardless of their job title. The survey asked respondents about their job titles, the organizational context in which they work(ed) including contract types and domains, their educational background, and how they perceive their professional future.&nbsp;</p><p>This dataset publication includes:</p><ol><li>Survey response data in CSV format. The file includes data from 241 respondents who consented to participate in the survey and share the data via a repsoitory, who indicated that they either currently work or have worked in the past in a data stewardship role, and who responded to at least one further question.</li><li>Thematic analysis of the qualitative questions Q11 and Q12 in PDF format.</li></ol>

opencc-by-4.0Nov 2023View details →
zenodo44/100

COSI-Article matrix: linking ISCB Communities of Special Interest to Wikipedia

<p>Wikipedia is regarded as one of the most important channels for the public communication of science; English Wikipedia has around 1,500 articles relating to computational biology, which are frequently accessed as an educational resource. Joint efforts between the International Society for Computational Biology (ISCB) and the Computational Biology taskforce of WikiProject Molecular Biology (a group of expert Wikipedia editors) have considerably improved computational biology representation on Wikipedia in recent years. However, there is still an urgent need for further quality improvement, primarily while comparing to related scientific fields such as genetics and medicine. Facilitating the involvement of members from ISCB COSIs (Communities of Special Interest) would improve a vital open educational resource in computational biology, additionally allowing COSIs to provide a quality educational resource particular to their subfield.</p> <p>This first version of the COSI-Article matrix is a binary matrix identifying relevant ISCB COSIs for all Wikipedia articles relating to computational biology, defining a domain-specific open educational resource for each COSI. In addition, quality and importance ratings for each article allow identification of areas where domain experts could improve computational biology representation.</p>

opencc-by-4.0Jan 2022View details →
zenodo44/100

Data repository for the publication "Economic Interests Cloud Hazard Reductions in the European Regulation of Substances of Very High Concern"

<p>This repository contains the data and scripts associated with the article &ldquo;Economic Interests Cloud Hazard Reductions in the European Regulation of Substances of Very High Concern&ldquo;, written by Jessica Coria, Erik Kristiansson and Mikael Gustavsson.</p>

opencc-by-4.0Sep 2022View details →
zenodo44/100

Edward FitzGerald Life and Letters – Analysis of other interests and views

<p>These files form part of an archive of research material relating to the Life and Letters of Edward FitzGerald.&nbsp; The data have been compiled by independent researchers W H (Bill) Martin and Sandra Mason;&nbsp; their contact details are below.&nbsp; The files comprise a number of searchable listings of information contained in FitzGerald&rsquo;s letters. The information formed input to a book on Edward FitzGerald which is referenced below.</p> <p>This section of the archive contains a number of databases which analyse the letters in terms of their comments on FitzGerald&rsquo;s interests and activities, and his views on a variety of topics.&nbsp; The databases cover current affairs (<em>efgctaffairs</em>), religion (<em>efgreligion</em>), travel (<em>efgtravel</em>), leisure activities (<em>efgactivities</em>), nature and countryside (<em>efgnature</em>), food and drink (<em>efgfood</em>), and personal matters (<em>efgcharacter</em>).&nbsp; They also show the dating of the letters, the people to whom FitzGerald wrote, and his location at the time of writing.&nbsp; The letters are those contained in the collection published by A M Terhune and A B Terhune in 1980 &ndash; see reference below.&nbsp; An&nbsp;explanatory README text file contains tables showing the fields included in the databases and giving definitions of them and of the codings used where relevant.&nbsp;</p>

opencc-by-4.0Feb 2019View details →
zenodo44/100

QSPR models for bioconcentration factor (BCF): Are they able to predict data of industrial interest?

<p>This dataset is described and studied in the article&nbsp;</p> <p>&quot;QSPR models for bioconcentration factor (BCF): Are they able to predict data of industrial interest?&quot;</p> <p>published in <em>SAR and QSAR Environmental Research</em> (Taylor&amp;Francis).</p> <p>Files description:</p> <p>SI_BCFtrainset.xlsx: a collection of 1129 chemical structures and CAS identifiers with their logBCF values extracted from various literature sources.</p> <p>SI_BCFtestset.xlsx: a collection of 204 chemical structures for which the logBCF is considered of lower reliability and used as an external test set.</p> <p>SI_FullDataset_rawdata.csv: the raw data composed of 15372 entries with the following columns:&nbsp;CASRN, Tissue, Duration [d], Test organism, Exposure type, Steady state, RESPONSE, RESPONSE UNIT, Media&nbsp;type, TakenFrom, TITLE, AUTHOR, YEAR, SOURCE, SMILES</p> <p>SI_ExcludedOutliers34.csv: 34 chemical structures that have been identified as suspicious during analysis.</p> <p>&nbsp;</p>

opencc-by-4.0Dec 2018View details →
zenodo44/100

Dataset for the article "Reduced order model approaches for predicting the magnetic polarizability tensor for multiple parameters of interest"

<p>Datasets to accompany the article &quot;Reduced order model approaches for predicting the magnetic polarizability tensor for multiple parameters of interest&quot;. Written by J. Elgy and P. D. Ledger (Keele University, 2023).</p> <p>The datasets include data files, meshes, and source code for generating figures from the paper. This requires the open source MPT-Calculator software available at <a href="https://github.com/MPT-Calculator/MPT-Calculator%7D">https://github.com/MPT-Calculator/MPT-Calculator</a> (InitialRelease branch).</p> <p>The authors gratefully acknowledge the financial support received from EPSRC in the form of grant EP/V009028/1</p> <p>&nbsp;</p>

opencc-by-4.0Jul 2023View details →
zenodo44/100

A gonad photographs dataset for fish of commercial interest

<p>This dataset was established during a one year project under the IFREMER (Institut Fran&ccedil;ais de Recherche pour l&rsquo;Exploitation de la Mer) for the harmonisation of maturity data acquisition methods for bony fish of commercial interest, with the help of scientific campaign CGFS, EVHOE, IBTS and ACCOBIOM (Auber et al., 2021,&nbsp;Laffargue et al.,1987, Le Roy et al., 1988).</p> <p>This dataset contains 4133 standardised gonad&rsquo;s macroscopic photos of 61&nbsp;species of fish of commercial interests collected along the European coastal water and the Caribbean Sea. The scale used throughout this project is the&nbsp; ICES maturity scale &ldquo;WKASMSF&rdquo; (ICES, 2018). To have more details about the photography process used for photos in this database, check the &ldquo;Fish gonads&rsquo; photography protocol&rdquo; from Le Meleder et al. (2022).</p> <p>This dataset is associated with a GitHub page hosting tools to generate maturity identification forms for fish of commercial interest. To have more detail about identification forms files and have the latest update, check the GitHub page &ldquo;MaturityScaleTools&rdquo; (<a href="https://github.com/LM-Anna/MaturityScaleTools">LM-Anna/MaturityScaleTools: Maturity scale tools to identify visual maturity phases (github.com)</a>).</p> <p>This dataset is meant to be enriched with time. Photos may be added to complete the missing maturity phases for every species of the world. To have more details about the dataset or to add new photos, please contact annalemeleder@orange.fr or <a href="mailto:laurent.dubroca@ifremer.fr">laurent.dubroca@ifremer.fr</a>.</p> <p>&nbsp;</p> <p><strong>Images:</strong></p> <ul> <li> <p><strong>Photo_MATURITY.zip</strong> : archive in zip format of&nbsp; 4133 macroscopic photographs of gonads (.JPG; 2Mo-6Mo; sRGB; 1080p). Each photo was taken with the same camera (OLYMPUS / Tough F2.0), on the same white background, with homogeneous lighting to avoid glints from overexposure. Since there are no duplicated photos&rsquo; names because all photos were taken with the same camera, names correspond to the one generated by the camera. Photos are sorted under three levels of directories :</p> <ul> <li> <p><strong>First level :<em> species&rsquo; scientific name</em></strong> (Example : <em>Dicentrarchus labrax</em>) : there are currently 61&nbsp;different species listed</p> </li> <li> <p><strong>Second level :<em> F or M</em> </strong>: the sex, with F from females and M for male</p> </li> <li> <p><strong>Third level : <em>A, B, C, D, E or F</em> </strong>: the maturity phases of the ICES 2018 scale. In each folder are assigned the corresponding gonadic photos.</p> </li> </ul> </li> </ul> <p>&nbsp;</p> <p><strong>Data frames:</strong></p> <ul> <li> <p><strong>photo_mat.xlsx</strong> (13 columns / 4133 rows): data table (Excel format) listing all photos in the Photo_MATURITY database, as well as the data associated with the photos. The data table is presented as followed, for each photo :</p> <ul> <li> <p>Name : Name of the photo</p> </li> <li> <p>Type : Type of gonad photo (INT = inside without organs, INT ORG = inside with organs, EXT = outside, EXT OUV = outside and open, FLUANT = fluent)</p> </li> <li> <p>sppeng : English vernacular name of the species or species group established for identification forms</p> </li> <li> <p>Species : Scientific name of the species or species group established for identification guides</p> </li> <li> <p>Sex : Sex of the fish (M = male, F = female)</p> </li> <li> <p>phase ID :&nbsp; visually estimated maturity phase (ICES WKASMSF scale : A, B, C, D, E or F)</p> </li> <li> <p>Link : Link to the photo, to change depending on your path to the downloaded dataset&nbsp; =LIEN_HYPERTEXTE(&laquo; (Your path to the dataset)\Photo_MATURITE\&laquo; &amp;H<sub>n</sub>&amp; &raquo;\&laquo; &amp;E<sub>n</sub>&amp; &raquo;\&laquo; &amp;F<sub>n</sub>&amp; &raquo;\&laquo; &amp;A<sub>n</sub>&amp; &raquo;.JPG &raquo;)*</p> </li> <li> <p>spplatTRUE : Scientific name of the species without taking species groups into account</p> </li> <li> <p>sppengTRUE : English vernacular name of the species without taking species groups into account</p> </li> <li> <p>Date : Date the photo was added to the dataset (the year correspond to the year the photo was took)</p> </li> <li> <p>Campaign : Survey during which the photo was taken</p> </li> <li> <p>Area : Geographical area (ICES or not) where the scientific survey occurred (Caribbean sea = Caribbean waters area, IVb-c = ICES area for the IBTS campaign, NA = unknown area, VIId = ICES area for NourManche campaign, VIId/VIIe = ICES area for CGFS campaign, VIIg/VIIj/VIIh/VIIIa-b = ICES area for EVHOE campaign)</p> </li> <li> <p>Commentary : Comments about the photo.</p> </li> </ul> </li> </ul> <p>&nbsp;</p> <p><strong>CAUTION</strong> : When using this database, please make sure to modify the link to the photos in the &ldquo;Link&rdquo; column with the link where you downloaded the Photo_MATURITY.zip file, and to check if it works by clicking it.</p> <p>&nbsp;</p> <p>*<sub>n</sub> = row number</p>

opencc-by-4.0Sep 2022View details →
zenodo40/100

Fig. 3 in New and interesting Surirella taxa (Surirellaceae, Bacillariophyta) from the Congo Basin (DR Congo)

Fig. 3. Surirella ebalensis sp. nov., type material from sample CCA 2070, Lomami River, DR Congo, SEM. External view. A–B. Detail of the girdle showing a part of a girdle with ligula (arrow) and the neighbouring interrupted band. C. Detail of the valve mantle with the draped silica spines (arrow) and the silica plaques (arrow) near the edge of the mantle and the valvocopula. D. Detail of the girdle band near the pole. Scale bars = 2 µm.

opencc-by-3.0Aug 2015View details →
zenodo40/100

Fig. 1 in New and interesting Surirella taxa (Surirellaceae, Bacillariophyta) from the Congo Basin (DR Congo)

Fig. 1. Surirella ebalensis sp. nov., from the holotype slide BR 4398, Lomami River, DR Congo, LM (DIC). A–C. Valve representing the holotype, different foci of the same valve. D–E. Different foci of the same valve. F. Girdle view. Scale bar = 10 µm.

opencc-by-3.0Aug 2015View details →
zenodo40/100

Fig. 9 in New and interesting Surirella taxa (Surirellaceae, Bacillariophyta) from the Congo Basin (DR Congo)

Fig. 9. Surirella congolensis sp. nov., type material from sample CCA 2071, Lomami River, DR Congo, SEM. Internal view. A–B. Head pole showing the continuous raphe (arrow). C–D. Foot pole showing the interruption of the raphe and the straight slightly expanded terminal raphe endings. E–F. Detail of the alar canals. Scale bars: B–C = 2 µm; A, D = 1 µm.

opencc-by-3.0Aug 2015View details →
zenodo40/100

Fig. 8 in New and interesting Surirella taxa (Surirellaceae, Bacillariophyta) from the Congo Basin (DR Congo)

Fig. 8. Surirella congolensis sp. nov., type material from sample CCA 2071, Lomami River, DR Congo, SEM. External view. A. Overview. B–C. Detail of foot pole showing the straight not expanded raphe endings (arrow). D. Detail of the apical pole showing the slightly curved raphe endings (arrow). E–F. Detail of the biseriate striae and the open fenestrae with the fenestral bars. Scale bars: A–B = 2 µm; C–F = 1 µm.

opencc-by-3.0Aug 2015View details →
zenodo40/100

Fig. 2 in New and interesting Surirella taxa (Surirellaceae, Bacillariophyta) from the Congo Basin (DR Congo)

Fig. 2. Surirella ebalensis sp. nov., type material from sample CCA 2070, Lomami River, DR Congo, SEM. External view. B, C, F = detail of the raphe keel with blunt spines orientated towards the valve face and which are draped over a large part of the indented mantle side. A. Overview. B–C. Detail of the valve ornamented with silica granules and blunt spines. D. Detail of the apical pole, showing the curved raphe endings. E–F. Detail of the foot pole showing the straight raphe endings. F. Short spherical shaped silica elements near the pole (arrow). Scale bars: A = 10 µm; B = 4 µm; C, F = 2 µm; D–E = 1 µm.

opencc-by-3.0Aug 2015View details →
zenodo40/100

Fig. 4 in New and interesting Surirella taxa (Surirellaceae, Bacillariophyta) from the Congo Basin (DR Congo)

Fig. 4. Surirella ebalensis sp. nov., type material from sample CCA 2070, Lomami River, DR Congo, SEM. External view. Details of the various types of spines on the valve face and the keel. A–B. Detail of the valve surface with the biseriate striae (arrow) becoming sometimes uniseriate near the axial area. C–D. Section of the valve face showing the simple perforation of the silica wall at the areolae. Scale bars: A–B = 2 µm; C–D = 1 µm.

opencc-by-3.0Aug 2015View details →
zenodo40/100

Fig. 5 in New and interesting Surirella taxa (Surirellaceae, Bacillariophyta) from the Congo Basin (DR Congo)

Fig. 5. Surirella ebalensis sp. nov., type material from sample CCA 2070, Lomami River, DR Congo, SEM. Internal view. A. Detail of the multiseriate striae, and the perforation of the elongated granules without rimmed margin (arrow). B, D. Detail of the continuous raphe near the apical pole with a reduced helictoglossa (arrow). C. Detail of the straight not expanded raphe endings at the foot pole and their reduced helictoglossae (arrows). Scale bars: B = 2 µm; A, C–D = 1 µm.

opencc-by-3.0Aug 2015View details →
zenodo40/100

Figure 1 Galumna sandormahunkai n in New and interesting species of the generaGalumna andPergalumna (Acari, Oribatida, Galumnidae) from the Montagne d'Ambre National Park, Madagascar

Figure 1 Galumna sandormahunkai n. sp., adult: a – dorsal view; b – ventral view (gnathosoma and legs omitted). Scale bar 100 μm.

opencc-by-4.0Jan 2020View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record