Find research datasets worth reusing

opencc-by-4.0Jan 2020View details →

European Procurement Markets as Bipartite Networks

EU Procurement Market Network Data Johannes Wachs January 2020 *In case you use this data, please reference:  <ul> <li>Wachs, J., Fazekas, M. & Kertész, J. Corruption risk in contracting markets: a network science perspective. Int J Data Sci Anal (2020). 10.1007/s41060-019-00204-1</li> <li>Available open access at: <a href="https://link.springer.com/article/10.1007%2Fs41060-019-00204-1">https://link.springer.com/article/10.1007%2Fs41060-019-00204-1</a></li> </ul> These 234 networks represent the annual national public procurement markets of 26 European countries from 2008-2016, inclusive. Data is sourced from Tenders Electronic Daily (TED), the official procurement portal of the European Union. Nodes with the suffix "_i" are issuers (sometimes referred to as buyers) of public contracts, for instance public hospitals, ministries, local governments. Nodes with the suffix "_w" are winners (sometimes called suppliers) of public contracts, generally private-sector firms. Identities have been statistically deduplicated, as described in the paper.  Each network is bipartite: edges only exist between issuers and winners. Edges represent contracting relationships and have two attributes:  <ul> <li>``count'' measures the volume of contracts between the issuer and winner in the given year. This attribute can be interpreted as a weight or strength of the relationship.</li> <li>``pctSingleBid'' describes the share of contracts between the issuer and winner awarded without competition, i.e. with the winner as single bidder or sole-supplier. Note: missing data on single-bidding is imputed. This is an elementary indicator of corruption risk of the contract. For more information consult the paper referenced above.</li> </ul> Ids of issuers and winners are consistent across time and within countries. Node ids have been randomly generated and do not correspond to any official statistics. The networks are stored in the GML format. For example: they can be read in directly by Gephi or by the Python NetworkX library with the following commands (using the 2010 Portuguese market as an example): <blockquote>     import networkx as nx     G=nx.read_gml('country_year_networks/PT_2010.gml') </blockquote>

Shared mobility opporTunities And challenges foR European citieS (STARS) - Work Package 2 - Tasks 2.1 - 2.3

These datasets contain data from the Work Package 2 (WP2) in the project STARS. The aims of this WP were:  1) To map existing car sharing services and quantitatively assess their relevance in their respective mobility contexts. 2) To define a classification scheme for such services to ease subsequent analyses. 3) To highlight which are the changes in social practices and media usages that are related to the diffusion of car sharing practices. 4) To assess which are the near and medium term development of such services following the trends and the planned implementation actions that are planned by different stakeholders. 5) To point out the main national and European policy barriers and opportunities for the growth of car-sharing. For more information on the project: <a href="http://stars-h2020.eu/">http://stars-h2020.eu/</a>

opencc-by-4.0Dec 2018View details →

Shared mobility opporTunities And challenges foR European citieS (STARS) - Work Package 4

These datasets contain data from the Work Package 4 (WP4) in the project STARS. For more information about the project: <a href="http://stars-h2020.eu/">http://stars-h2020.eu/</a> The aims of the WP 4 were:  To study the influence of factors related to individuals and to social settings that can be quantitatively measured; To uncover the role played by different mobility styles and mobility cultures in the diffusion of shared mobility practices; To assess the overall importance of individual, social, political, environmental and economic variables in driving the behavioural change towards shared mobility; To identify barriers and facilitators for a faster shift in life-styles that includes shared mobility.

Dataset for Surface Enhanced Raman Spectroscopy for quantitative analysis: results of a large-scale European multi-instrument interlaboratory study

This dataset contains all the spectra used in "Surface Enhanced Raman Spectroscopy for quantitative analysis: results of a large-scale European multi-instrument interlaboratory study". Data are available in 2 different formats: - a compressed archive with 1 folder ("Dataset”) cointaining all the 3516 TXT files (1 file = 1 spectrum) uploaded by all participants (all spectra of the Interlaboratory study); - 1 single CSV file (“ILSspectra.csv”) with all the 3516 spectra uploaded by all participants in the form of a table. The data are structured as follow, with each row being 1 spectrum, preceded by metadata: "labcode", "substrate", "laser", "method", "sample", "type", "conc", "batch", "replica". Note that for those spectra starting after 400 cm-1 and/or ending before 2000 cm-1 missing values were expressed as NAs.

opencc-by-4.0Feb 2020View details →

Climate simulation over the European Alps for the period 1902-2010 produced with the model MAR

This directory contains the netcdf files produced with the MAR model (http://mar.cnrs.fr/; https://gitlab.com/Mar-Group) applied over the European Alps, for the period 1902-2010, based on a spatial resolution of 7km. This data is a downscaling of the ERA20C reanalysis. The list of variables available is described in the file variables.txt, and further information can be found in the file readme.txt

opencc-by-4.0Feb 2020View details →

Provisioning forest and conservation science with European tree species distribution models under climate change

Estimating shifts in the current range of forest tree species is crucial for formulating adaptive management strategies such as assisted migration. Ecological niche models have been the most widely used tools to estimate the potential climatic suitability of species worldwide. The reliability of such estimations depends on the model algorithm and the input data such as climate and species occurrence. We developed a dataset of the potential distribution of seven ecologically and economically important tree species of Europe in terms of their climatic suitability with an ensemble approach while accounting for uncertainty due to model algorithms. The distribution models shall be the basis for follow-up studies in forest and conservation science.

Datasets of "Whole genome sequencing of European autochthonous and commercial pig breeds provides selection signatures of adaptation of genetic resources to different breeding and production systems"

Results of the FST and HP analyses.

opencc-by-4.0Mar 2020View details →

ENTSO-E PECD (European Climate Database) from MAF 2019 in CSV and Feather formats

ENTSO-E has published the PECD dataset with the Mid-term Adequacy Forecast (MAF) 2019: https://www.entsoe.eu/outlooks/midterm/#download The downloadable archive contains 3 large Microsoft Excel (~350 MB each). Each file contains the hourly data for all the considered weather years (1982-2016) for all the MAF regions (grouped in tabs). Here we provide the same data but in a more open and user-friendly format. Single files Data saved in CSV and <a href="https://blog.rstudio.com/2016/03/29/feather/">Feather format</a> (using R package feather 0.35). Each file contains the hourly data in a wide tabular format with area, day, month, hour and year (1982-2016). The files are: <ul> <li>PECD-MAF2019-wide-PV.csv (and .feather)</li> <li>PECD-MAF2019-wide-WindOffshore.csv (and .feather)</li> <li>PECD-MAF2019-wide-WindOnshore.csv (and .feather)</li> </ul> Split by year We provide here three archives each one containing a file per year. The files are: <ul> <li>PECD-MAF2019-wide-PV.single_years.tar.bz2</li> <li>PECD-MAF2019-wide-WindOffShore.single_years.tar.bz2</li> <li>PECD-MAF2019-wide-WindOnshore.single_years.tar.bz2</li> </ul>

opencc-by-4.0Mar 2020View details →

CES in European forest

The dataset contains the results from a Pan-european Survey dealing with Cultural Ecosystem Services in European forests. The survey has focused on forest owners and managers, who were asked about the current status of CES in the properties they owned/managed. The file also contain the factors elicited from 2 Principal component analyisis. One made over the presence absence of CES in the forest; and another made over the potential CES in the forest. Additionally, the file also contains the results from a Hierarchical Cluster Analysis, in which the factors from the above-mentioned PCAS were used to classify forest owners in groups.

Shared mobility opporTunities And challenges foR European citieS (STARS) - Work Package 5, Task 5.1

These datasets contain information about car sharing members and non-members collected through a survey carried out as part of the Work Package 5 (WP5) activities in the STARS project. The data were gathered in three European countries (Italy, Germany and Belgium) and contain information about travel habits, car ownership level and sociodemographic characteristics of the respondents. The data collected were used to: 1) Define the maximum portion of travel demand that can be served by car sharing and how this will impact the demand for other travel means. 2) Define a “rupture scenario”, where the benefits of car sharing are maximised. 3) Quantify the gap between the business as usual scenario and the rupture scenario, and the related impacts. For more information about the project, please refer to <a href="http://stars-h2020.eu/">http://stars-h2020.eu/</a>

opencc-by-nc-4.0Nov 2019View details →

Supplementary data for Kvist et. al. 2020 "Draft genome of the European medicinal leech Hirudo medicinalis (Annelida: Clitellata: Hirudiniformes) with emphasis on anticoagulants"

anticoagulant_prots.tar.gz: Proteins sequence, alignment, exon structure, and tree files for identified anticoagulant proteins plus putative anticoagulant proteins from the Hirudo medicinalis ROM11733 v1 assembly Himedicinalis_ROM11733_annotation.tar.gz: InterProScan, UniProtKB, MAKER, RepeatModeller, Rfam, and tRNAscan-SE annotation files for the Hirudo medicinalis ROM11733 v1 assembly PhymmBL_tax_assign.tar.gz: PhymmBL files of the tree rounds of taxnonomic assignment

opencc-by-4.0Sep 2019View details →

Macroscopic and histological image dataset of the European plaice (Pleuronectes platessa) ovaries

Macroscopic and histological image dataset of the European plaice (Pleuronectes platessa) ovaries    Authors:   Carine Sauger1, Jérôme Quinquis1, Kristell Kellner2, Clothilde Heude-Berthelin2, Mélanie Lepoittevin2, Nicolas Elie3, Laurent Dubroca1   Affiliations:   1 : Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER). Laboratoire Ressources Halieutiques de Port-en-Bessin, Avenue du Général de Gaulle, 14520, Port-en-Bessin-Huppain, Calvados 2 : Biologie des Organismes et Ecosystèmes Aquatiques (FRE 2030 BOREA). Université de Caen Normandie, Esplanade de la Paix, CS 14032, Caen, Calvados 3 : Centre de Microscopie Appliquée à la Biologie (SF 4206 ICORE, CMABIO3). Université de Caen Normandie, Esplanade de la Paix, CS 14032, Caen, Calvados   Contents: This dataset was established during a 6 month long Master’s degree internship (February to July 2019), under the IFREMER (Institut Français de Recherche pour l'Exploitation de la Mer) project MATO (MATurité Objective des poissons par l’histologie quantitative), with the collaboration of two research facilities from the University of Caen-Normandie : BOREA (Biologie des Organismes et Ecosystèmes Aquatiques) and CMABIO3 (Centre de Microscopie Appliquée à la Biologie). This dataset contains the macroscopic and the histological images of the ovaries of 151 European plaices (female, Pleuronectes platessa) collected along the French Coast of the English Channel (ICES area 27.7.d) in 2017, 2018 and 2019.   Images: <ul> <li> Full_Ovaries_Data.zip: archive in zip format of 151 pictures (.JPG; 8Mo-9Mo; sRGB; 6016x4000 pixels) of both ovaries from 151 female plaice dissected during this study. Each photo was taken by the same person with a Nikon camera (D3200), in the same room with identical lightening methods (no flash). For each picture, both ovaries were set on a blue background, with a 0.50€ coin for size calibration. The upper most ovary is the dorsal gonad of the fish while the lower one is the ventral gonad. The name of the picture is the same as the fish’s ID number. </li> </ul>   <ul> <li> Stereology_Readings_Data.zip: archive in zip format of two directories containing the images </li> </ul> <ul> <li> <ul> <li> Interagent_Calibration: the ovarian histological slides were digitized using an Aperio slide scanner (Scan Scope Console software, v.10.2.0.2352, Leica Biosystems), x20 lens. The pictures (.svs: Aperio single-file pyramidal tiled TIFF, with non-standard metadata and compression) are of the 20 histological slides used for the stereological count. 20 slides of 20 fish (with one slide per fish) were analyzed for the intercalibration analysis. The slides used were from the central position of the ventral ovary (V2). </li> <li> Ovary_Slides: the ovarian histological slides were digitized using an Aperio slide scanner (Scan Scope Console software, v.10.2.0.2352, Leica Biosystems), x20 lens. The pictures (Aperio single-file pyramidal tiled TIFF, with non-standard metadata and compression) in this dataset are the 226 histological slides read during this study. With a total of 151 fish dissected, 151 ovarian histological slides of the median position of the ventral ovary were read. Among the remaining slides, 90 were read to analyze the homogeneous distribution of the different cell types. These 90 slides belong to 15 fish, with three histological samples taken in the anterior (1), median (2) and posterior (3) sections of the dorsal (D) and ventral (V) ovaries. </li> </ul> </li> </ul> Data frames: <ul> <li> Intergaent_read_me.txt : a text file (.txt) listing the acronyms used in the Interagent.csv file, as well as their meaning. </li> <li> Interagent.csv: a text data file (.csv) with the output of two stereological readings, done by three agents for 15 slides, and by two agents for 20 slides. Between the first and second reading, a reading protocol was set up to help in the determination of the different structures. This protocol allowed the three agents to calibrate themselves with a determination key. This key was necessary for the identification of specific complex structures. The information contained in this table is as follows: <ul> <li> agent: code id for the three agents that did the calibration exercise (A, B and C) </li> <li> num_fish: fish number for this study. Here we have 20 different fish </li> <li> fish_id: identification number of the fish. This id number is identical to the name given to the pictures of the full ovaries (Full_Ovaries_Data) </li> <li> scan_id: identification number of the digitized histological slide that was used for the stereological count (Stereology_Readings_Data / Interagent_Calibration) </li> <li> total_points: total number of identified structures for the stereological sampling grid of a slide </li> <li> cell_type: abbreviation of the structure identified (reading protocol available here: https://archimer.ifremer.fr/doc/00501/61235/). In this study, we have 20 different structures </li> <li> hit_points: number of time a structure has been counted on a single slide </li> <li> Fract_estim: percentage (%) of times a structure was counted on a single slide = (100 / total_point) * hit_points </li> <li> reading: reading number. In this study, we have two readings, the first (1) and the second (2) </li> </ul> </li> </ul>   <ul> <li> Macros_read_me.txt : a text file (.txt) listing the acronyms used in the Macros.csv file, as well as their meaning. </li> <li> Macros.csv: a text data file (.csv) containing macroscopic parameters measurements for all 151 fish that have been used during this study. The information contained in this table is as follows: <ul> <li> num_fish: fish number for this study. Here we have 151 different female fish </li> <li> fish_id: identification number of the fish. This id number is identical to the name given to the pictures of the full ovaries (Full_Ovaries_Data) </li> <li> gon_pos: gonad position, with D being the dorsal gonad of the individual, and V being the ventral gonad. </li> <li> date: the date the fish was caught (dd/mm/yyyy) </li> <li> L_fish: total length of the fish (cm) </li> <li> W_fish: total weight of the fish (g) </li> <li> mat_estim: visually estimated maturity, after observation of the fish’s gonad with the naked eye, following the WKMATCH (ICES, 2012) scale </li> <li> age: estimated age (in years) of the fish, after analysis of the fish’s otolith. The IFREMER laboratory executed this analysis in Boulogne-sur-Mer (FRANCE) </li> <li> W_gon: gonad weight (g) </li> <li> Kurtosis*: kurtosis parameter </li> <li> Skewness*: skewness coefficient </li> <li> gon_area*: gonad area (mm²) </li> <li> L_gon*: gonad length (mm) </li> <li> width_gon*: maximum gonad width (mm) </li> <li> width_mid_L_gon*: width at mid-length of the gonad (mm) </li> <li> mean_col_index*: the mean color value of the different hues found on the ovary </li> <li> std_dev*: standard deviation of the mean_col_index </li> <li> modal*: modal value or the most frequently occurring color value within the selected ovary </li> </ul> </li> </ul> *: values determined after image analysis of the Full_Ovaries_Data with the ImageJ software (v. 1.50J)   <ul> <li> Stereology_read_me.txt : a text file (.txt) listing the acronyms used in the Stereology.csv file, as well as their meaning. </li> <li> Stereology.csv: a text data file (.csv) of the stereology count results of 226 slides read during this study. Among these slides, 90 were read to test the homogeneity distribution of different cell types found throughout each ovary (15 fish with 6 histological sections : a median, an anterior and a posterior histological section, for both ovaries), 20 slides were read by two agents for calibration purposes, and 15 of these 20 slides were also read by a third agent for calibration purposes. Finally, 151 median histological slides of the ventral ovary were also read. The information contained in this table is as follows: <ul> <li> agent: code id for the 3 agents that did the calibration exercise (A, B and C) </li> <li> num_fish: fish number for this study. Here we have a total of 151 fish </li> <li> fish_id: identification number of the fish. This id number is identical to the name given to the pictures of the full ovaries (Full_Ovaries_Data) </li> <li> scan_id: identification number of the digitized histological slide that was used for the stereological count (Stereology_Readings_Data / Ovary_Slides) </li> <li> reading: reading data to test the homogeneity of cell distributions throughout the ovaries (homogeneity), reading data of the 20 slides read for the inter-agent calibration, and reading data of all the slides (median) </li> <li> cell_type: abbreviation of the structure identified (reading protocol available here: https://archimer.ifremer.fr/doc/00501/61235/). In this study, we have 20 different structures </li> <li> point_id: identification number of the point inside the stereological sampling grid placed over the ovarian histology slide </li> <li> coord_x: x coordinate of the sampling point </li> <li> coord_y: y coordinate of the sampling point </li> </ul> </li> </ul>   Contact : For questions, please contact: <a href="mailto:carine.sauger@gmail.com">carine.sauger@gmail.com</a> or <a href="mailto:laurent.dubroca@ifremer.fr">laurent.dubroca@ifremer.fr</a>

opennotspecifiedJan 2020View details →

FIGURES 1–6. Thremma sardoum Costa 1884, final instar larva. 1 in Discriminatory matrix for the larvae of the European Thremma species (Trichoptera: Thremmatidae)

FIGURES 1–6. Thremma sardoum Costa 1884, final instar larva. 1, head, frontal (a = antenna; small white and black numbers = setal positions). 2, head and pronotum, dorsal (small white and black numbers = setal positions; yellow oval = group of frontoclypeal setae #1–3; c = lateral constriction; p = pronotum). 3, head, ventral (small white number = setal position). 4, detail of pennate ventral head seta # 8. 5, mandibles, ventral (a = apex; c = central section; e = median straight edge; s = semicircular edge; arrow = setal tuft). 6, mesonotum, dorsal (ms = mesonotum; sa1–sa3 = sclerites of setal areas 1–3; dotted oval = small sclerite sometimes separated from sclerite sa2; arrow = incomplete suture in center of sclerite sa3). Scale bars: 0.5 mm (except Figs 4, 5: 0.1 mm).

opennotspecifiedJan 2020View details →

FIGURES 12–17. Thremma sardoum Costa 1884, final instar larva. 12 in Discriminatory matrix for the larvae of the European Thremma species (Trichoptera: Thremmatidae)

FIGURES 12–17. Thremma sardoum Costa 1884, final instar larva. 12, prothorax, right ventrolateral (ae = anterolateral extension of prosternite; h = head; p = pronotum; pe = posterolateral extension of prosternite; ph = prosternal horn; pt = protuberance). 13, ventral protuberance of abdominal segment I, ventral (m = row of muscle attachment spots; sf = posterior spinule field; vs = ventral sclerite; dashed lines = mesal margins of ventral sclerites). 14, metathorax and abdominal segments I–III, right lateral (dg = dorsal gills; ls = lateral seta; sa3 = setal area 3; sf = posterior spinule field; vs = ventral sclerite; arrow = white patch within spinule field on lateral protuberance). 15, abdominal segment IX, dorsal (arrows = short lateral sclerite setae). 16, tip of abdomen, right lateral (ls = lateral sclerite of anal proleg; ac = anal claw). 17, case, ventral. Scale bars: 0.5 mm.

FIGURE 4 in A further review of European Magelonidae (Annelida), including redescriptions of Magelona equilamellae and Magelona filiformis

FIGURE 4. Rose Bengal stained specimens of Magelona equilamellae from Ebro Delta, Catalonia, (A, D) Stn AT 5–2, 2008; (B, C, E) Stn AT 9–2, 2008: (A) anterior region (dorsal view, showing LH palp); (B) prostomium (antero-dorsal view, LH palp attached); (C) mid-palp region; (D) pygidium (ventro-lateral view, methyl green stained); (E) sediment covered, layered tube.

FIGURE 5 in A further review of European Magelonidae (Annelida), including redescriptions of Magelona equilamellae and Magelona filiformis

FIGURE 5. Scanning Electron Microscope images of Magelona equilamellae from Ebro Delta, Catalonia, (A–E) Stn AT 4–2, 2011 (specimen 3); (F) Stn AT 4–2, 2011 (specimen 1): (A) prostomium and first four chaetigers (dorso-lateral view); (B) LH parapodia of chaetigers 1–5 (lateral view); (C) RH parapodia of chaetigers 5–7 (lateral view); (D) RH parapodia of chaetigers 8–11; (E) RH parapodia of chaetigers 10–11; (F) tridentate abdominal hooded hooks from chaetiger 11 (lateral view, hoods broken). (No) Notopodium; (Ne) Neuropodium.

FIGURE 1 in A further review of European Magelonidae (Annelida), including redescriptions of Magelona equilamellae and Magelona filiformis

FIGURE 1. Magelona equilamellae, larger syntype (SMF 4675): (A) anterior (dorsal view); (B) prostomium (dorsal view, RH palp and tip of LH palp visible, both incomplete); (C–E, G, J, L, N, O, P) parapodia of chaetigers 1–3, 4, 6, 7, 8, 9 and 11 respectively (anterior views); (F, H, K) neuropodial lamellae of chaetigers 3, 4 and 6 respectively (ventral views); (I) notopodia of chaetiger 5 (anterior view, neuropodia damaged on both sides); (M) neuropodial lamella of chaetiger 7 (dorsal view); (Q) notopodial lamella of chaetiger 20 (anterior view); (R, S) tridentate abdominal hooded hooks (oblique lateral and lateral view respectively).

FIGURE 3 in A further review of European Magelonidae (Annelida), including redescriptions of Magelona equilamellae and Magelona filiformis

FIGURE 3. Magelona equilamellae from Ebro Delta, Catalonia, east coast of Spain reported in Capaccioni-Azzati (1987; 1989), (A, B) Stn I–1 AH; (C, D) Stn E–3 AH: (A) anterior, showing pigment band of the posterior thorax between chaetigers 5–7 (dorso-lateral view); (B) prostomium and first three chaetigers (lateral view); (C, D) anterior (dorso-lateral and ventro-lateral views respectively, left hand palp retained).

opennotspecifiedMay 2020View details →

FIGURE 3. A–M, except J in The millipede family Polyxenidae (Diplopoda, Polyxenida) in the faunas of the Crimean Peninsula and Caucasus, with notes on other European Polyxenidae

FIGURE 3. A–M, except J: Propolyxenus argentifer (Verhoeff, 1921) comb. n. Topotype, adult male. A. Head; B. Collum; Tergites showing pattern of trichome insertions: C. Tergite 2, D. Tergite 4; E. Tergite 10; F. Pattern of insertions of dorso-medial fan of trichomes on telson; G. right gnathochilarium; H. Left antenna showing proportions of articles; I. Article VII sensilla; K. Article VI sensilla; L. leg 8; M. Hooked caudal trichome. J. P. argentifer adult male, Russia, Utrish Nature Reserve, Article VII sensilla. Scale bars: A–E = 200 µm; F, G, M = 50 µm; I, J, K = 10 µm; H, L = 100 µm.