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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).
Pan-European temperature distribution at depth - GeoDH project
<p>The dataset includes two shapefiles showing the temperature distribution at depth in Europe, specifically areas with temperatures exceeding 50°C at 1000m depth and 90°C at 2000m depth.<br><br>This dataset was developed for assessing the potential of Geothermal District Heating in Europe as part of the <strong>GeoDH project</strong> (<a href="http://geodh.eu/" target="_new" rel="noopener">http://geodh.eu/</a>). Please note that this represents the<strong> state of the art as of 2014</strong> and that geological, technological, and regulatory developments may have occurred since its creation, and users should verify if more recent data is available for their purposes.</p>
Fig. 8 in The "Spaghetti Project": the final identification guide to European Terebellidae (sensu lato) (Annelida, Terebelliformia)
Fig. 8. Diversity of Trichobranchidae, SEM. A. Terebellides gentili Lavesque, Hutchings, Daffe, Nygren & Londoño-Mesa, 2019, anterior end, lateral view (MNHN-IA-TYPE 1873). B. Terebellides lilasae Lavesque, Hutchings, Daffe, Nygren & Londoño-Mesa, 2019, branchia, lateral view (MNHN- IA-TYPE 1881). C. Trichobranchus glacialis Malmgren, 1866, anterior end, lateral view (SMA-BR- Tricho-05). D. Octobranchus lingulatus (Grube, 1863), anterior end, lateral view (MNHN-IA-PNT 94). E. Terebellides resomari Lavesque, Hutchings, Daffe, Nygren & Londoño-Mesa, 2019, geniculate chaetae (paratype MNHN-IA-TYPE 1892). F. Terebellides lilasae, thoracic uncini (SMA-ARC- Terebellides-VOG8-1). Abbreviations: Br = Branchiae; Bt = Buccal tentacles; Gc = Geniculate chaetae; Ll = Lateral lobes.
Fig. 7 in The "Spaghetti Project": the final identification guide to European Terebellidae (sensu lato) (Annelida, Terebelliformia)
Fig. 7. Diversity of Trichobranchidae. A. Terebellides lilasae Lavesque, Hutchings, Daffe, Nygren & Londoño-Mesa, 2019, entire specimen, lateral view (MNHN-IA-TYPE 1879). B. Terebellides lilasae, anterior end, lateral view, methyl green staining (MNHN-IA-TYPE 1879). C. Trichobranchus glacialis Malmgren, 1866, anterior end, lateral view (MNHN-IA-PNT 96). D. Terebellides sp., thoracic acicular uncini (SMA-BR-Terebellides-KER1). Abbreviations: Br = Branchiae; glr = glandular region; Pp = Posterior process.
Fig. 6 in The "Spaghetti Project": the final identification guide to European Terebellidae (sensu lato) (Annelida, Terebelliformia)
Fig. 6. Diversity of Terebellidae Johnston, 1846 (s.s.), SEM. A. Pista sauriauiLavesque, Daffe, Londoño- Mesa & Hutchings, 2021, anterior end, lateral view (paratype MNHN-IA-TYPE 2036). B. Paramphitrite dragovabeci Lavesque, Daffe, Londoño-Mesa & Hutchings, 2021, anterior end, lateral view (paratype MNHN-IA-TYPE 2030). C. Lanice kellyslateri Lavesque, Daffe, Londoño-Mesa & Hutchings, 2021, anterior end, lateral view (paratype MNHN-IA-TYPE 2028). D. Eupolymnia meissnerae Lavesque, Daffe, Londoño-Mesa & Hutchings, 2021, anterior end, ventro-lateral view (paratype MNHN-IA-TYPE 2025). E. Lanice kellyslateri, thoracic uncini (paratype MNHN-IA-TYPE 2028). F. Paramphitrite dragovabeci, uncini SG XIV (paratype MNHN-IA-TYPE 2030). G. Eupolymnia meissnerae, uncini SG VIII (paratype MNHN-IA-TYPE 2025). Abbreviations: Gp = genital papillae; Ll = lateral lobes; Ul = upper lip. Numbers referring to segments.
Fig. 3 in The "Spaghetti Project": the final identification guide to European Terebellidae (sensu lato) (Annelida, Terebelliformia)
Fig. 3. Diversity of Telothelepodidae Nogueira, Fitzhugh & Hutchings, 2013 and Thelepodidae Hessle, 1917. A. Parathelepus collaris (Southern, 1914), anterior end, frontal view (AM W.53063). B. Parathelepus collaris, anterior end, ventral view (NHMUK ANEA 1983.1696). C. Thelepus japonicus Marenzeller, 1884, anterior end, lateral view (AM W.53073). D. Thelepus corsicanus Lavesque, Londoño-Mesa, Daffe & Hutchings, 2020, anterior end, frontal view (AM W.53068). E. Streblosoma cabiochi Lavesque, Londoño-Mesa, Daffe & Hutchings, 2020, anterior end, dorsal view (MNHN-IA- TYPE 2000). F. Thelepus japonicus, anterior end, ventral view (MNHN-IA-PNT 117). Abbreviations: Br = Branchiae; Bt = Buccal tentacles; Gp = genital papillae; Ll = Lower lip; Ul = Upper lip.
Fig. 5 in The "Spaghetti Project": the final identification guide to European Terebellidae (sensu lato) (Annelida, Terebelliformia)
Fig. 5. Diversity of Terebellidae Johnston, 1846 (s.s.). A. Eupolymnia lacazei Lavesque, Daffe, Londoño-Mesa & Hutchings, 2021, live specimen (paratype MNHN-IA-TYPE 2023). B. Eupolymnia gili Lavesque, Daffe, Londoño-Mesa & Hutchings, 2021, anterior end, lateral view (holotype MNHN- IA-TYPE 2020). C. Amphitrite edwardsii (Quatrefages, 1866), anterior end, lateral view (MNHN-IA- PNT 126). D. Terebella banksyi Lavesque, Daffe, Londoño-Mesa & Hutchings, 2021, anterior end, lateral view (holotype MNHN-IA-TYPE 2037). E. Paramphitrite dragovabeci Lavesque, Daffe, Londoño-Mesa & Hutchings, 2021, notochaeta, SG XI (paratype MNHN-IA-TYPE 2030). F. Terebella cf. lapidaria Linnaeus, 1767, notochaetae, SG IX (MNHN-IA-PNT 131). G. Terebella lapidaria, notochaetae, posterior segments (MNHN-IA-PNT 131). Abbreviations: Bs = branchial stem; Ey = eyes; Gp = genital papillae; Ll = lateral lobes; Np = nephridial papillae. Numbers referring to segments.
Fig. 2 in The "Spaghetti Project": the final identification guide to European Terebellidae (sensu lato) (Annelida, Terebelliformia)
Fig. 2. Diversity of Polycirridae Malmgren, 1866. A. Amaeana gremarei Lavesque, Hutchings, Daffe & Londoño-Mesa, 2020, anterior end, lateral view (MNHN-IA-TYPE 2006). B. Polycirrus gujanensis Lavesque, Hutchings, Daffe & Londoño-Mesa, 2020, anterior end, ventral view (MNHN-IA-TYPE 2013). C. Amaeana gremarei, anterior end, ventral view (AM W.53111). D. Polycirrus idex Lavesque, Hutchings, Daffe & Londoño-Mesa, 2020, anterior end, ventral view (AM W.53127). E. Polycirrus glasbyi Lavesque, Hutchings, Daffe & Londoño-Mesa, 2020, notochaetae SG V (AM W.53118). F. Polycirrus catalanensis Lavesque, Hutchings, Daffe & Londoño-Mesa, 2020, abdominal uncini (AM W.53113). G. Polycirrus glasbyi, thoracic uncini (AM W.53118). Abbreviations: Bt = buccal tentacles; Gp = genital papilla; Ll = lower lip; Ne = neuropodia; Ul = upper lip; Vp = ventral pads.
Fig. 1 in The "Spaghetti Project": the final identification guide to European Terebellidae (sensu lato) (Annelida, Terebelliformia)
Fig. 1. Schematic illustrations of different uncini morphologies, in lateral view (following Nogueira et al. 2010). A. Terebellides sp., SG IX (SMA-BR-Terebellides-KER1). B. Polycirrus catalanensis Lavesque, Hutchings, Daffe & Londoño-Mesa, 2020, SG XX (holotype MNHN-IA-TYPE 2007). C. Pista sauriaui Lavesque, Daffe, Londoño-Mesa & Hutchings, 2021, SG V (paratype MNHN-IA- TYPE 2036). D. Lomia ramzega Lavesque, Bonifácio, Londoño-Mesa, Le Garrec & Grall, 2017, SG XII (paratype MNHN-IA-TYPE 1791). E. Streblosoma cabiochi Lavesque, Londoño-Mesa, Daffe & Hutchings, 2020, SG VI (holotype MNHN-IA-TYPE 2000). F. Thelepus japonicus Marenzeller, 1884, SG XVII (MNHN-IA-PNT 117). Abbreviations: Af = anterior filament; Ba = base; Ca = capitium; Cext = coma-shape extension; Cr = crest; Db = dorsal button; He = heel; Lh = long handle; Mf = main fang; Oc = occipitium; Pr = prow.
Fig. 4 in The "Spaghetti Project": the final identification guide to European Terebellidae (sensu lato) (Annelida, Terebelliformia)
Fig. 4. Diversity of Telothelepodidae Nogueira, Fitzhugh & Hutchings, 2013 and Thelepodidae Hessle, 1917, SEM. A. Parathelepus collaris (Southern, 1914), anterior end, frontal view (AM W.53063). B. Thelepus corsicanus Lavesque, Londoño-Mesa, Daffe & Hutchings, 2020, anterior end, latero-frontal view (AM W.53069). C. Streblosoma cabiochi Lavesque, Londoño-Mesa, Daffe & Hutchings, 2020, anterior end, lateral view (AM W.53066). D. Thelepus corsicanus, thoracic notochaetae (AM W.53069). E. Parathelepus collaris, abdominal uncini, (AM W.53063). F. Thelepus japonicus Marenzeller, 1884, abdominal uncini, SG48. (SMA-NL-Thele08). Abbreviations: Br = Branchiae; Bt = Buccal tentacles; Lc = lateral crest; Ll = Lower lip; Vl = Ventral lobe of SG I.
ECLIPS 1.1 - European CLimate Index ProjectionS database
<p>Based on the available bias corrected regional climate model results, which were created under the CORDEX project we calculated several climate indices both for past and future. (http://cordex.org/data-access/bias-adjusted-rcm-data/)</p> <p>This database contains ascii files for climate index maps with a horizontal resolution of 0.11 degree ( on a regular grid ) for Europe.</p> <p>Five GCM-RCM pairs for RCP4.5 and RCP8.5 scenarios are available for three future periods: 2041-2060, 2061-2080, 2081-2100 and one past period :1961-1990</p> <p>Additionally multi-model mean maps are available for the period 1961-1990 as a reference.</p> <p>The attached document gives information about the calculated indices and climate models ( Research paper is in prep.)</p> <p>21 zip files covers the database: 5-5 for each RCP scenarios (1 for each model) + 1 for the past period.</p> <p>File name conventions: <GCM name> <RCP scenario> <RCM name> <Index name> <period></p> <p>(GCM and RCM names are following the CORDEX name conventions)</p> <p> </p> <p>Contact: dobor.laura@gmail.com</p> <p> </p> <p> </p>
European Market Place - FLEXICIENCY project
<p>The FLEXICIENCY project aims to demonstrate how, inside the European Union, the implementation of novel services dedicated to energy market can be boosted by the introduction of a Market Place that allows the exchange of data, services and tools among the operators. The video gives a general overview of the project and the potential benefits of its implementation.</p>
SECURES-Met - A European wide meteorological data set suitable for electricity modelling (supply and demand) for historical climate and climate change projections
<p>For the modelling of electricity production and demand, meteorological conditions are becoming more relevant due to the increasing contribution from renewable electricity production. But the requirements on meteorological data sets for electricity modelling are quite high. One challenge is the high temporal resolution, since a typical time step for modelling electricity production and demand is one hour. On the other side the European electricity market is highly connected, so that a pure country based modelling does not make sense and at least the whole European Union area has to be considered. Additionally, the spatial resolution of the data set must be able to represent the thermal conditions, which requires high spatial resolution at least in mountainous regions. All these requirements lead to huge data amounts for historic observations and even more for climate change projections for the whole 21st century. Thus, we have developed an aggregated European wide data set that has a temporal resolution of one hour, covers the whole EU area, has a reasonable size but is considering the high spatial variability. This meteorological data set for Europe for the historical period and climate change projections fulfills all relevant criteria for energy modelling. It has a hourly temporal resolution, considers local effects up to a spatial resolution of 1 km and has a suitable size, as all variables are aggregated to NUTS regions. Additionally meteorological information from wind speed and river run-off is directly converted into power productions, using state of the art methods and the current information on the location of power plants. Within the research project SECURES (https://www.secures.at/) this data set has been widely used for energy modelling.</p> <p> </p> <p>The SECURES-Met dataset provides variables visible in the table.</p> <table> <tbody><tr> <th>Variable</th> <th>Short name</th> <th>Unit</th> <th>Aggregation methods</th> <th>Temporal resolution</th> </tr> </tbody><tbody> <tr> <th>Temperature (2m)</th> <td>T2M</td> <td> <p>°C</p> <p>°C</p> </td> <td> <p>spatial mean</p> <p>population weighted mean (recommended)</p> </td> <td>hourly</td> </tr> <tr> <th>Radiation</th> <td> <p>GLO (mean global radiation)</p> <p>BNI (direct normal irradiation)</p> </td> <td> <p>Wm-2</p> <p>Wm-2</p> </td> <td> <p>spatial mean</p> <p>population weighted mean (recommended)</p> </td> <td>hourly</td> </tr> <tr> <th><strong>Potential Wind Power </strong></th> <td>WP</td> <td>1</td> <td>normalized with potentially available area</td> <td>hourly</td> </tr> <tr> <th><strong>Hydro Power Potential</strong></th> <td> <p>HYD-RES (reservoir)</p> <p>HYD-ROR (run-of-river)</p> </td> <td> <p>MW</p> <p>1</p> </td> <td> <p>summed power production</p> <p>summed power production normalized with average daily production</p> </td> <td>daily</td> </tr> </tbody> </table> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p>SECURES-Met is available in a tabular csv format for the historical period (1981-2020, Hydro only until 2010) created from ERA5 and ERA5-Land and two future emission scenarios (<strong>RCP 4.5 </strong>and <strong>RCP 8.5</strong>, both 1951-2100, wind power starting from 1981, hydro power from 1971) created from one CMIP5 EUROCORDEX model (GCM: ICHEC-EC-EARTH, RCM: KNMI-RACMO22E, ensemble run: r12i1p1) on the <strong>spatial aggregation level</strong></p> <ul> <li>NUTS0 (country-wide),</li> <li>NUTS2 (province-wide),</li> <li>NUTS3 (Austria only),</li> <li>and EEZ (Exclusive Economic Zones, offshore only).</li> </ul> <p>The data is divided into the historical (Historical.zip) and the two emission scenarios (Future_RCP45.zip and Future_RCP85.zip), a README file, which describes, how the files are organized, and a folder (Meta.zip), which has information and shape files of the different NUTS levels. As <strong>population weighted</strong> temperature and radiation represent values in geographical areas more relevant for solar power, it is highly relevant to use population weighted files. Spatial mean should be used for reference only.</p> <p>The project SECURES, in which this dataset was produced, was funded by the Climate and Energy Fund (Klima- und Energiefonds) under project number KR19AC0K17532.</p>
Technical Solutions for Increasing DER and EV Hosting Capacity in Distribution Grids in the Czech Republic in Terms of European Project Interflex
<p>dataset for scientific paper</p>
Supplementary material 3: List of tested and analyzed data sharing tools (non-exhaustive) 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
List of tested and analyzed data sharing tools (non-exhaustive)
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.