Find research datasets worth reusing

opencc-by-4.0Sep 2018View details →

Bicycle trips collected using Cyclists Geo-C geo-game

This is an experimental dataset for the bicycle trips recorded using and geo-game called "Cyclist Geo-C". It contains the geometry of the trips recorded by 60 participants from three European Cities: Münster, Germany; Castelló, Spain; Valletta, Malta. This dataset was collected and analysed for the PhD Thesis "Mobile Services for Green Living" part of the European Joint Doctorate in Geoinformatics and the <a href="http://geo-c.eu/">Geo-C </a>Project.  The dataset is composed of three subsets. <ol> <li>There is a point dataset called "trips_od.geojson" which contained the point geometries where each trip started and ended with attributes for latitude, longitude, altitude, and precision coordinates. Each point also had the timestamp which indicates the time when the user started or ended the trip.</li> <li>There is a line dataset called "segments.geojson" which contained the geometries of the straight lines connecting two locations of the participant. Each segment started from an initial point "pi" recorded at a "ti” and ended at the next point recorded by the user "pf” at time “tf”. The time difference between "ti” and “tf” was at most five minutes while the length of the segment was at most one kilometre. Each segment also had the participant and trip identifier, and the segment's sequence number within the trip For each of the trip segments, we calculated the distance and speed using the recorded coordinates and timestamps from "pi" and "pf" points. \(trip\_segment = f(p_i,p_f)\) and \(segment\_speed = \frac{distance(p_i,p_f)}{\Delta time(p_i,p_f)}\). Then we classified the segments according to the calculated distance as: “walking segment” when the calculated speed was less than 5 km/h;  “cycling segment” when the calculated speed was between 5 and 50 km/h; or “non-cycling segment” when the calculated speed was more than 50 Km/h.</li> <li>There was another line dataset called “trips_tags.geojson ” which contained the geometries of each of the trip paths. A trip was a line (also called polyline by GIS users) defined by the ordered sequence of trip segments. It started from origin point "pi" of the trip’s first segment and ended at the destination point "pf" of the trip's last segment. Each trip also had the participant's identification, trip's identification, the number of segments, start and end times.</li> </ol> In addition to the experimental dataset recorded by participants, our analysis used a secondary dataset to define a comparable framework for the three cities. The secondary dataset consisted of the existing bicycle paths in the cities of Münster and Castelló as well as the planned bicycle paths around Valletta. For the city of Münster, the source of the bicycle paths was the <a href="http://www.openstreetmap.org">OpenStreetMap</a> (we downloaded the line elements with the tags “bicycle=yes” and "cycleway=yes”). For the city of Castelló, we obtained the bicycle paths from the city transport authority, including the city of Valletta, we created a digital version of the national bicycle network plan. We estimated the number of trips "bikepaths_trips.geojson" and the number of segments "bikepaths_segments.geojson" at each bike path. Also, we provide the areas where participants faced frictions during the experiment which corresponded to low cycling speeds "frictions.geojson". Finally, we provide a visual reference of the dataset in "frictions_cities.pdf".

opencc-by-4.0Jun 2019View details →

The Sincere Apology Corpus (SinA-C)

This repository contains the Sincere Apology Corpus (SinA-C). SinA-C is an English speech corpus of acted apologies in various prosodic styles created with the purpose of investigating the attributes of the human voice which convey sincerity. Thirty-two speakers were recorded in a studio at the Columbia Computer Music Center inside a sound-proof recording booth. Audio was recorded with an AKG C414 dynamic microphone. The digital audio workstation Logic Pro 9 was used to collect the audio signals. Recordings were captured at 44.1 kHz and 16 bit in AIFF format and later converted to mono WAV files. Speakers <ul> <li>Gender: 15 male and 17 female</li> <li>Age: 20-60 years old (mean: 29.8 years; std; 9.9 years)</li> <li>Background: 27 American born English native speakers, and 5 from other nationalities (all fluent in spoken English). 24 speakers were professional actors, and the remaining 12 were artists</li> </ul> Recordings Speakers were given a description of the study, a set of 6 sentences (apologies; see Table 1) and a short definition for a set of 4 prosodic styles (see Table 2) to adopt when uttering each sentence (the recordings are not spontaneous, but rather acted). The sentences used were the following: <ul> <li>Sorry.</li> <li>I am sorry for everything I have done to you. </li> <li>I cannot tell you how sorry I am for everything I did.</li> <li>Please allow me to apologise for everything I did to you. I was inappropriate and lacked respect.</li> <li>It was never my intention to offend you, for this I am very sorry. </li> <li>I am sorry but I am going to have to decline your generous offer. Thank you for considering me.</li> </ul> The prosodic styles intended to be adopted when uttering each of the sentences were: <ul> <li>monotonic;</li> <li>pitch prominence (labelled as `Stress');</li> <li>fast speaking rate;</li> <li>slow speaking rate.</li> </ul> Annotations The SinA-C audio recordings were labelled in terms of the sincerity perceived by listeners (`How sincere was the apology you just heard?') on a 5-point Likert scale ranging from 0 (Not Sincere) to 4 (Very Sincere) by 22 volunteers (13 male and 9 female; age range: 18-22; μ 19.5 std 1.0).  Of the 22 annotators, all reported to have normal hearing, and all were English speakers (6 reported to be bilingual with at least one other language). Raw annotations were standardised to zero mean and unit standard deviation on a per-subject basis in order to eliminate potential individual rating biases. We then computed the mean across all subjects for each utterance. This resulted in a set of ratings ranging from [-1.51, 1.72] (mean -0.002 std 0.60) which are used as the gold-standard for regression experiments. We also converted these ratings to binary labels. Average ratings larger than 0 were labelled as `Sincere` (S), and those smaller of equal to 0 were labelled as `Not Sincere` (NS). This resulted in 478 instances labelled as S and 438 as NS. These labels are the gold-standard for classification tasks. SinA-C Baseline The Baseline for the dataset is described in detail in the INTERSPEECH 2019 publication "Sincerity in Acted Speech: Presenting the Sincere Apology Corpus and Results" [1]. This article presents both classification and regression baseline results. The modelling experiments included both a 3-fold Speaker Independent Nest Cross Validation (SICV) schema as well as Speaker Independent folds (C-SIF) (train, validation, test). C-SIF is provided by the original database baseline from the INTERSPEECH 2016 COMputation PARalinguistics challengE (COMPARE) [2]. For reproducibility, speaker distributions across the two partitioning strategies are provided with the corpus package. The audio descriptors include conventional and state-of-the-art features extracted from the audio files. We used Support Vector Machines (SVM) for classification tests and linear Support Vector Regression (SVR) for the regression ones. In both cases we used linear kernels and both SVM and SVR were implemented using the open-source machine learning toolkit Scikit-Learn. During the development phase, we trained various models (using the training set) with different complexity parameters (C ∈ 10-7, 10-6, 10-5, 10-4, 10-3, 10-2, 10-1, 1), and evaluated their performance on the validation set. After determining the optimal value for C, we concatenated the training and validation sets, re-trained the model with this enlarged training set, and evaluated the performance on the test set. Further detail on the baseline development are given in [1]. Comments SinA-C was initially gathered between 2015-2016 at the Columbia University Computer Music Centre (CCMC) in New York City, United States of America. The dataset was also included in the INTERSPEECH 2016 COMPARE challenge [2], and prior to that in 2015 a subset of the dataset was also exhibited as part of a graduate-school art exhibition. Citing this corpus When using the data set for your own research, and within publications, please cite this repository and [1]. Bibliography [1] Baird, A., Coutinho, E., Hirschberg, J., & Schuller, B. W. (2019). Sincerity in Acted Speech: Presenting the Sincere Apology Corpus and Results. In Interspeech 2019, in press. [2] Schuller, B. W., Steidl, S., Batliner, A., Hirschberg, J., Burgoon, J. K., Baird, A., Elkins, A. C., Zhang, Y., Coutinho, E., & Evanini, K. (2016). The INTERSPEECH 2016 Computational Paralinguistics Challenge: Deception, Sincerity & Native Language. In Interspeech 2016, 2001-2005.

opencc-by-4.0Aug 2024View details →

EFSA Project on the use of NAMs to explore the immunotoxicity of PFAS (Annexes B, C, D1, E, G, I, K, M, O)

In vitro raw data, RIN values and RNA concentrations, DNA quality assessment, RNAseq outputs and analysis of EFSA Project on the use of NAMs to explore the immunotoxicity of PFAS (OC/EFSA/SCER/2021/13).

openbsd-3-clauseSep 2024View details →

Efficient Detection of Test Interference in C Projects (Artifact)

This record provides research artifacts for the article "Efficient Detection of Test Interference in C Projects", accepted and to be presented at <a href="https://conf.researchr.org/home/ase-2024">ASE 2024</a>. Please refer to the README.md in the tgz file for details about the artifact and how it relates to the manuscript describing our study. Please also see our related Zenodo record with the container images used in the study: <a href="https://doi.org/10.5281/zenodo.7935821" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.7935821</a>.

opencc-by-4.0Dec 2020View details →

Stable isotope ratios of C, N and S in Southern Ocean sea stars (1985-2017)

Sea stars (Echinodermata: Asteroidea) are a key component of Southern Ocean benthos, with 16% of the known sea star species living there. In temperate marine environments, sea stars commonly play an important role in food webs, acting as keystone species. However, trophic ecology and functional role of Southern Ocean sea stars are still poorly known, notably due to the scarcity of large-scale studies. Here, we report 24332 trophic marker (stable isotopes and elemental contents of C, N and S of tegument and/or tube feet) and biometric (arm length, disk radius, arm to disk ratio) measurements in 2456 specimens of sea stars. Samples were collected between 12/01/1985 and 08/10/2017 in numerous locations along the Antarctic littoral and Subantarctic islands. The spatial scope of the dataset covers a significant portion of the Southern Ocean (Latitude: 47.717° South to 86.273° South ; longitude: 127.767° West to 162.201° East ; depth: 6 to 5338 m). The dataset contains 133 distinct taxa, including 72 currently accepted species spanning 51 genera, 20 families and multiple feeding guilds / functional groups (suspension feeders, sediment feeders, omnivores, predators of mobile or sessile prey). For 505 specimens, mitochondrial CO1 genes were sequenced to confirm and/or refine taxonomic identifications, and those sequences are already publicly available through the Barcode of Life Data System. This number will grow in the future, as molecular analyses are still in progress. Overall, thanks to its large taxonomic, spatial, and temporal extent, as well as its integrative nature (combining genetic, morphological and ecological data), this dataset can be of wide interest to Southern Ocean ecologists, invertebrate zoologists, benthic ecologists, and environmental managers dealing with associated areas.

opencc-zeroMay 2020View details →

Corpus des Deutschen Bundesrechts (C-DBR)

Überblick Das Corpus des deutschen Bundesrechts (C-DBR) ist eine möglichst vollständige Sammlung der konsolidierten Fassungen aller Gesetze und Verordnungen auf Bundesebene. Der Datensatz nutzt als seine Datenquelle das amtliche Internetangebot <a href="http://www.gesetze-im-internet.de">www.gesetze-im-internet.de</a> des Bundesministeriums der Justiz und wertet dieses vollständig aus. Bitte lesen Sie zuerst das beiliegende Codebook! Es enthält wichtige Informationen zur korrekten Nutzung des Datensatzes. Es hilft auch bei der Entscheidung, welche Variante für Sie am besten geeignet ist. In der Regel empfehle ich für quantitative Forschung die CSV-Dateien und für traditionelle Forschung die PDF-Sammlung. Um das Gesetzgebungsverfahren näher zu beleuchten können Sie zusätzlich auf folgende Datensätze zurückgreifen (jeweils mit Links auf vergleichbare Datensätze anderer Autor:innen): <ul> <li><a href="http://doi.org/10.5281/zenodo.4643065">Corpus der Drucksachen des Deutschen Bundestages (CDRS-BT)</a></li> <li><a href="http://doi.org/10.5281/zenodo.4542661">Corpus der Plenarprotokolle des Deutschen Bundestages (CPP-BT)</a></li> </ul>   Aktualisierung Dieser Datensatz wird ca. alle 3 Monate aktualisiert. Benachrichtigungen über neue und aktualisierte Datensätze veröffentliche ich immer zeitnah auf Mastodon unter <a href="https://fediscience.org/@seanfobbe">@seanfobbe@fediscience.org</a>   NEU in Version 2025-10-02 <ul> <li>Vollständige Aktualisierung der Daten</li> </ul>   Eckdaten Stichtag:  2. Oktober 2025 Umfang: 6838 Bundesgesetze und -verordnungen der Bundesrepublik Deutschland Formate: CSV, PDF, EPUB, TXT und XML   Features <ul> <li>Einfache Nutzung für statistische Analysen mit CSV-Dateien</li> <li>Bis zu 42 Variablen in den CSV-Varianten</li> <li>Fortlaufende Aktualisierung</li> <li>Urheberrechtsfreiheit</li> <li>Sowohl für traditionelle Rechtsanwender als auch für Legal Tech-Anwendungen geeignete Formate (CSV, PDF, EPUB, TXT und XML)</li> <li>Umfangreicher Compilation Report um den Erstellungs-Prozess zu erläutern</li> <li>Hochauflösende Diagramme und deskriptive Tabellen für alle Zwecke</li> <li>Diagramme in PDF (Druck) und PNG (Web) verfügbar, Tabellen als menschen- und maschinenlesbares CSV</li> <li>Vollständiges tabellarisches Verzeichnis aller Rechtsakte und der vom BMJV gebrauchten Abkürzungen</li> <li>Netzwerk-Strukturen für alle Rechtsakte und Visualisierungen für über 1000 Rechtsakte (experimentell)</li> <li><a href="../doi/10.5281/zenodo.4072934">Veröffentlichung des Source Codes</a></li> </ul>   Source Code und Compilation Report Der gesamte Erstellungs-Prozess ist vollautomatisiert und detailliert dokumentiert. Mit jeder Kompilierung des vollständigen Datensatzes wird auch ein umfangreicher Compilation Report in einem attraktiv designten PDF-Format erstellt (ähnlich dem Codebook). Zudem werden Robustness Checks auf Vollständigkeit und Plausibilität durchgeführt und in einem separaten Bericht dokumentiert. Der Compilation Report enthält den Code für die vollständige Pipeline, dokumentiert relevante Rechenergebnisse, gibt sekundengenaue Zeitstempel an und ist mit einem klickbaren Inhaltsverzeichnis versehen. Er ist zusammen mit dem Source Code hinterlegt. Wenn Sie sich für Details des Erstellungs-Prozesses interessieren, lesen Sie diesen bitte zuerst. Der vollständige Source Code — sowohl für die Erstellung des Datensatzes, als auch für das Codebook — ist öffentlich einsehbar und dauerhaft erreichbar im wissenschaftlichen Archiv des CERN unter diesem Link hinterlegt: <a href="https://doi.org/10.5281/zenodo.8402568">https://zenodo.org/doi/10.5281/zenodo.4072934</a>   Kryptographische Signaturen Die Integrität und Echtheit der einzelnen Archive des Datensatzes sind durch eine Zwei-Phasen-Signatur sichergestellt. In Phase I werden während der Kompilierung für jedes ZIP-Archiv, das Codebook und die Robustness Checks Hash-Werte in zwei verschiedenen Verfahren (SHA2-256 und SHA3-512) berechnet und in einer CSV-Datei dokumentiert. In Phase II werden diese CSV-Datei und der Compilation Report mit meinem persönlichen geheimen GPG-Schlüssel signiert. Dieses Verfahren stellt sicher, dass die Kompilierung von jedermann durchgeführt werden kann, insbesondere im Rahmen von Replikationen, die persönliche Gewähr für Ergebnisse aber dennoch vorhanden ist. Die während der Kompilierung des Datensatzes erstellte CSV-Datei mit den Hash-Prüfsummen ist mit meiner persönlichen GPG-Signatur versehen. Der mit dieser Version korrespondierende Public Key ist sowohl mit dem Datensatz als auch mit dem Source Code hinterlegt. Er hat folgende Kenndaten: Name: Sean Fobbe (fobbe-data@posteo.de) Fingerabdruck: FE6F B888 F0E5 656C 1D25 3B9A 50C4 1384 F44A 4E42   Kein Urheberrecht: Public Domain An den Normtexten und Metadaten besteht gem. § 5 Abs. 1 UrhG kein Urheberrecht, da sie amtliche Werke sind. § 5 UrhG ist auf amtliche Datenbanken analog anzuwenden (BGH, Beschluss vom 28.09.2006 - I ZR 261/03, "Sächsischer Ausschreibungsdienst"). Alle eigenen Beiträge (z.B. durch Zusammenstellung und Anpassung der Metadaten) und damit den gesamten Datensatz stelle ich gemäß einer <a href="https://creativecommons.org/publicdomain/zero/1.0/legalcode">CC0 1.0 Universal Public Domain License</a> vollständig urheberrechtsfrei.   Disclaimer Dieser Datensatz ist eine private wissenschaftliche Initiative und steht in keiner Verbindung zu Behörden, Gerichten oder anderen öffentlichen Stellen der Bundesrepublik Deutschland.   Alternativen [Ab 10.06.2019, nur XML] Beckedorf, Janis/Coupette, Corinna/Hartung, Dirk. 2020. "gesetze-im-internet: A daily archive of https://www.gesetze-im-internet.de". GitHub. <a href="https://github.com/QuantLaw/gesetze-im-internet">https://github.com/QuantLaw/gesetze-im-internet</a> [Änderungsgesetze] Wehrmeyer, Stefan/Semsrott, Arne/Filter, Johannes. 2021. "OffeneGesetze.de ist eine zivilgesellschaftliche, ehrenamtliche Plattform für amtliche Gesetzesblätter". Open Knowledge Foundation. <a href="https://offenegesetze.de/">https://offenegesetze.de/</a> [Alte Rechtsakte] Open Knowledge Foundation. 2013. "Bundesgit". GitHub. <a href="https://github.com/bundestag/gesetze">https://github.com/bundestag/gesetze</a>   Weitere Open Access Veröffentlichungen (Fobbe) Website — <a href="https://www.seanfobbe.de">www.seanfobbe.de</a> Open Data  —  <a href="../communities/sean-fobbe-data/">zenodo.org/communities/sean-fobbe-data/</a> Source Code  —  <a href="../communities/sean-fobbe-code/">zenodo.org/communities/sean-fobbe-code/</a> Volltexte regulärer Publikationen  —  <a href="../communities/sean-fobbe-publications/">zenodo.org/communities/sean-fobbe-publications/</a>   Kontakt Fehler gefunden? Anregungen? Kommentieren Sie gerne im <a href="https://codeberg.org/seanfobbe/c-dbr/issues">Issue Tracker</a> oder kontaktieren Sie mich über <a href="https://www.seanfobbe.de">www.seanfobbe.de</a>

opencc-by-4.0Mar 2023View details →

Supplemental data files: Beyond the reference: gene expression variation and transcriptional response to RNAi in C. elegans

This dataset holds all non-GEO-hosted supplemental data files for manuscript "Beyond the reference: gene expression variation and transcriptional response to RNAi in C. elegans". Please see the linked preprint/publication for full details. The PDF _guide_to_datafiles.pdf gives details on the format and content of each of the included files.

opencc-by-4.0Mar 2023View details →

Molecular and functional properties of human Plasmodium falciparum CSP C-terminus antibodies

AIRR Community-compliant information comprising all antibodies described in EMBO Mol Med 15:e17454 [DOI:10.15252/emmm.202317454].

opencc-by-4.0Jun 2023View details →

Macroscopic, histological and stereological image dataset of the Striped red mullet (Mullus surmuletus) ovaries from the Bay of Biscay (ICES area 27.7.g,j & 27.8.a-c) stock

Contents: This dataset can be completed with the : Macroscopic, histological and stereological image dataset of the Striped red mullet (Mullus surmuletus) ovaries from the English Channel (ICES area 27.7.d) stock, which can also be found on the Zenodo repository. This dataset contains the macroscopic and histological images of the ovaries of 103 Striped red mullet (female, Mullus surmuletus, Linnaeus 1758) collected from the Bay of Biscay stock (ICES areas 27.7.j,g & 27.8.a-c) in November 2020 (n=9), May 2021 (n=11), June 2021(n=7), July 2021 (n=15), September (n=15), October 2021 (n=3), November 2021 (n=27) and February 2022 (n=15).   Images: <ul> <li>Macroscopic_pictures.zip: archive in zip format of 290 pictures (.JPG; 2Mo-8Mo; JPG; 350pp) from 103 female Striped red mullets dissected during this study. Each photo was taken with a digital camera (no flash). For each individual, up to three pictures were taken when possible (Le Meleder et al., 2022) with : <ul> <li>one picture of the entire fish with its abdominal cavity open with the ovaries in view</li> <li>one picture of the whole fish with the ovaries outside of the abdominal cavity</li> <li>one picture of the ovaries</li> <li>the name of the picture is the same as the fish’s ID number.</li> </ul> </li> </ul> <ul> <li>Histology_slides.zip: archive in zip format containing the ovarian histological slides digitized using an Olympus V120 slide scanner, x20 lens. The pictures (.vsi from the OlympusVSI format) are of the 264 histological slides acquired during this study. Data was split for smaller size downloads : <ul> <li>Histology_slides_1of3 : histological sections for individuals numbered 062 to 094</li> <li>Histology_slides_2of3 : histological sections for individuals numbered 100 to 250</li> <li>Histology_slides_3of3 : histological sections for individuals numbered 290 to 304</li> </ul> </li> </ul>   Data: <ul> <li>Readings.zip: archive in zip format containing the stereology reading results of the ovarian histological slides. In this folder, three directories are available. <ul> <li>Calibration : Reading results of 4 different agents, with the first and last readings, as well as the Qupath scripts used.</li> <li>Homogeneity : Reading results for 84 histological slides used to check the cellular homogeneity inter- and intra-gonad. These 84 slides belong to 14 fish, with three histological samples taken in the anterior (1), median (2) and posterior (3) sections of the left (G) and right (D) ovaries. A QuPath folder is also present, containing the scripts used.</li> <li>Total : Reading results for 103 ovarian histological slides of the median position of either the left or right ovary. One median slide was read per sampled fish. A QuPath folder is also present, containing the scripts used.</li> </ul> </li> </ul> <ul> <li>Macro_MULL_read_me.txt : a text file (.txt) listing the acronyms used in the Macro_MULL.xlsx file, as well as their meaning.</li> <li>Macro_MULL.xlsx : Excel file (.xlsx) containing measurements of macroscopic parameters for all 103 fish sampled during this study. The information contained in this table is as follows: <ul> <li>Fish_id: identification of the fish. This id is identical to the name given to the pictures of the full ovaries (Macroscopic_pictures_Data)</li> <li>ICES _Division: International Council for the Exploration of the Sea (ICES) division where the fish was sampled in the Food and agricultural Organization of the United nations (FAO) fishing area 27</li> <li>ICES_statistical_rectangle : Statistical rectangle where the fish was sampled within the FAO fishing area 27</li> <li>Date: date the fish was caught (dd/mm/yyyy)</li> <li>Total_fish_length: total length of the fish (cm)</li> <li>Ungutted_fish_weight: total weight of the fish (g)</li> <li>Otolith_ID: unique identification number given to each sampled fish through the Imagine (Ellebode et al., 2022) software used by IFREMER</li> <li>Parasite: presence (Y) or absence (N) of parasite in or on the fish</li> <li>age: age (in years) of the fish after analysis of the fish’s otolith. The IFREMER laboratory of Boulogne-sur-Mer (FRANCE) executed this analysis</li> <li>Visual_maturity : visually estimated maturity, after observation macroscopic criteria of the fish’s gonad with the naked eye, following the WKASMSF (ICES, 2018) scale</li> <li>Liver_weight: liver weight (g)</li> <li>Droite_gonad_weight : gonad weight (g) of right ovary</li> <li>Gauche_gonad_weight : gonad weight (g) of left ovary</li> <li>Sections: number of cross sections sampled for the individual</li> </ul> </li> </ul> <ul> <li>Stereo_MULL_read_me.txt : a text file (.txt) listing the acronyms used in the Stereo_MULL.csv file, as well as their meaning.</li> <li>Stereo_MULL.csv : a text data file (.csv) of the stereology count results of 173 slides read during this study. Among these slides, 84 were read to test the homogeneity distribution of different cell types found throughout each ovary (14 fish with 6 histological sections : a median, an anterior and a posterior histological section, for both ovaries), slides were read by multiple agents for calibration purposes (see Calibration folder for reading results of the 4 agents). Finally, 103 median histological ovarian slides were read. The information contained in this table is as follows: <ul> <li>cell_type: structure identified for one sample point (for the abbreviations, see Heude-Berthelin et al. 2023)</li> <li>idpt: identification number of the sampling point</li> <li>id: unique complex identification number of the sampling point generated by combining the x and y coordinates</li> <li>x: x coordinate of the sampling point</li> <li>y: y coordinate of the sampling point</li> <li>reading: Indicates if the reading data was used to test cellular homogeneity (Homogeneity) or to the sexual maturity phase</li> <li>slideid: identification number of the digitized histological slide that was used for the stereological count. Shares the same 12 first characters with Fish_id</li> </ul> </li> </ul>

opencc-by-4.0Aug 2023View details →

Dataset for publication "Enhancing C≥2 product selectivity in electrochemical CO2 reduction by controlling the microstructure of gas diffusion electrodes"

Data used for publication: Broad topic: electrochemical reduction of CO2 using gas diffusion electrodes and neutral electrolyte Data is devided in subfolders named after the figure of the paper. Raw data, processed data, and Origin/Power Point files are all contained in the subfolders  A subfolder corresponding to a sample contains: data from a potentiostat, gas and liquid chromatograms, recording of flow, pressure and temperature, tables of calculated Faradaic efficiency (FE), png image of the FE vs t, zipped raw files. .json file was created using a yadg scheme (https://dgbowl.github.io/yadg/master/index.html), and data was processed by a dgpost scheme (<a href="https://pypi.org/project/dgpost/">https://dgbowl.github.io/dgpost/master/index.html</a>)

Nitrogen and carbon concentrations and stable isotope ratios (δ¹⁵N and δ¹³C) in European moss samples, 2005-2006

This dataset contains nitrogen (N) and carbon (C) concentrations and stable isotope ratios (δ¹⁵N and δ¹³C) measured in moss samples collected across Europe within the framework of the ICP Vegetation programme (International Cooperative Programme on Effects of Air Pollution on Natural Vegetation and Crops, UNECE LRTAP Convention). Moss surveys are conducted every five years and the data presented here correspond specifically to the first sampling campaign, carried out in 2005/2006. During the 2005/2006 European moss survey, approximately 3,000 moss samples were collected at non-urban and semi-natural sites across 16 European countries following a standardized biomonitoring protocol. The dataset used in this study comprises a subset of 1,022 moss samples (approximately 35 % of the total survey), provided by 12 European countries, which were selected for the determination of nitrogen and carbon concentrations and their corresponding stable isotope signatures (δ¹⁵N and δ¹³C). Moss samples collected by each participating country were sent to the Integrated Environmental Quality Laboratory (LICA), Institute for Biodiversity and Environment (BIOMA - University of Navarra), where all chemical and isotopic analyses were subsequently performed under uniform analytical conditions. In addition, this dataset incorporates moss data from Sweden, Croatia and Macedonia for the same sampling year, which were not included in the official ICP Vegetation 2005/2006 dataset. The European moss biomonitoring network was established to provide a complementary, high spatial resolution and time-integrated measure of atmospheric deposition of nitrogen and other pollutants within terrestrial ecosystems. The approach is based on the ability of ectohydric mosses to accumulate nutrients and trace elements directly from wet and dry atmospheric deposition, enabling dense spatial sampling across large geographical areas. This biomonitoring framework supports the assessment of spatial patterns of atmos

openOpenSep 2021View details →

Soil enzyme activities and soil chemistry near and away from alder collected at sites along the Sagavanirktok River, BNZ LTER sites UP3a-c, and sites near BNZ LTER site WDI6, collected June and July 2019

This dataset contains the data and R code associated with Heslop et al. 2021 "Soil Enzymes Illustrate the Effects of Alder Nitrogen Fixation on Soil Carbon Processes in Arctic and Boreal Ecosystems" published in Ecosphere. Activities of acid phosphatase, beta-glucosidase, and phenoloxidase, as well as %N, C, P, and Mo, 15N and 13C natural abundance, resin extractable P, and SOM chemsitry using FTIR spectroscopy were measured for soils taken under alder (Alnus viridis ssp. fruticosa) canopies and 5 m away. Samples were collected in the Arctic at sites near Sagwon Bluffs and the Lupine-Sagavanirktok river confluence as well as in the boreal forest at BNZ LTER sites UP3a-c and at sites located near BNZ LTER site WDI6.

openCustomJan 2020View details →

Measurements of Coarse Woody Debris %C and %N at the Coweeta LTER Terrestrial Gradient Sites, Coweeta Hydrological Laboratory, Otto, NC.

Coarse woody debris (CWD) plays a critical role in nutrient retention and cycling, including the cycling and retention of carbon and nitrogen. However, comparison studies of CWD in different forest types and elevation gradients in the southern Appalachian Mountains are lacking. We measured CWD in five different forest communities/elevations at Coweeta Hydrologic Lab. A subsample of CWD in each plot was measured for percent C and percent N, as well as for cations.

openCC (other)Sep 2022View details →

Wood alpha-cellulose stable C and O isotope ratios from New Hampshire and Vermont

To quantify the effects of tree height and canopy position on delta13C and delta18O of wood cellulose, we sampled 399 trees and saplings of eight species at nine forest stands across New Hampshire and Vermont, along with nearby saplings growing in the open. Samples were collected in 2017-18, and we analyzed the combined alpha-cellulose from growth rings formed in 2013-2017 for each tree. Carbon data are published in: Vadeboncoeur, M., K. Jennings, A. Ouimette, and H. Asbjornsen. (2020) Correcting tree-ring d13C time series for tree-size effects in eight temperate tree species. Tree Physiology. https://doi.org/10.1093/treephys/tpz138

Meteorology and soil moisture data collected at multiple frequencies from the C-CALI NPP site automated monitoring stations: Jornada Basin LTER, 2013 - ongoing

This dataset contains summary data collected at the Jornada Basin LTER program's C-CALI NPP site weather station and associated soil substation at several temporal scales. Precipitation data are collected at 1-second frequency during rain events, air temperature and wind at 5-minute frequency, and all sensors are measured at 30-minute, hourly and daily frequencies. Observed values include average/maximum/minimum air temperature, relative humidity, and wind speed; average wind direction; total precipitation; soil moisture, temperature and conductivity. These are measured and calculated based on 1-second scan rate of all sensors located at an automated weather station, and a nearby soil substation, installed at the site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximately 2.5m. Soil sensors are installed at approximately 10, 20 and 30cm depths.

Meteorology and soil moisture data collected at multiple frequencies from the C-GRAV NPP site automated monitoring stations: Jornada Basin LTER, 2013 - ongoing

This dataset contains summary data collected at the Jornada Basin LTER program's C-GRAV NPP site weather station and associated soil substation at several temporal scales. Precipitation data are collected at 1-second frequency during rain events, air temperature and wind at 5-minute frequency, and all sensors are measured at 30-minute, hourly and daily frequencies. Observed values include average/maximum/minimum air temperature, relative humidity, and wind speed; average wind direction; total precipitation; soil moisture, temperature and conductivity. These are measured and calculated based on 1-second scan rate of all sensors located at an automated weather station, and a nearby soil substation, installed at the site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximately 2.5m. Soil sensors are installed at approximately 10, 20 and 30cm depths.

Meteorology and soil moisture data collected at multiple frequencies from the C-SAND NPP site automated monitoring stations: Jornada Basin LTER, 2013 - ongoing

This dataset contains summary data collected at the Jornada Basin LTER program's C-SAND NPP site weather station and associated soil substation at several temporal scales. Precipitation data are collected at 1-second frequency during rain events, air temperature and wind at 5-minute frequency, and all sensors are measured at 30-minute, hourly and daily frequencies. Observed values include average/maximum/minimum air temperature, relative humidity, and wind speed; average wind direction; total precipitation; average and total solar incoming and reflectance; average albedo; average net radiation; soil moisture, temperature and conductivity. These are measured and calculated based on 1-second scan rate of all sensors located at an automated weather station, and a nearby soil substation, installed at the site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, air temperature and relative humidity at approximately 2.5m, and solar at approximately 3m. Soil sensors are installed at approximately 10, 20 and 30cm depths.