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2,090 results for “competition”

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edi56/100

Altering pH changes competition dynamics between two crayfish species for both food and shelter resources

As climate change continues, alterations in abiotic variables within habitats will also change. One of the key variables for aquatic systems is pH. We were interested in how lowered pH altered the behavioral characteristics of two keystone species: Faxonius rusticus, a non-native crayfish in the upper midwest and Faxonius virilis, the native crayfish. We dosed size-matched individuals in separate tanks for four days and than placed these individuals in a flow through mesocosm to allow them to compete over food and shelter resources. Behavior was recorded from midnight to 4 am. Pairs of animals were exposed to pH levels varying from ambient (8.4) to 6.4. The experiment took place at the University of Michigan's Biological Station in northern Michigan in the United States.

openCC (other)Sep 2025View details →

edi52/100

Nitrogen addition alters plant competition directly more than indirectly through soil microbes.

Eutrophication, the excessive addition of nutrients to ecosystems, is a pervasive component of global environmental change that can alter community dynamics. Although nitrogen addition experiments have widely documented important declines in plant diversity and shifts in plant species composition, the underlying causes of these outcomes are widely debated. Nitrogen inputs may directly affect plant competition for light or soil water or may influence plant species indirectly by altering the composition of soil microbes. In a 28-year field nitrogen addition experiment, we tested whether nitrogen-induced changes to soil microbes could indirectly alter the outcome of competition between codominant foundation plant species. In the field, long-term addition of inorganic nitrogen slowed the competitive take-over of blue grama grass (Bouteloua gracilis) by black grama grass (B. eriopoda) and thereby stabilized the ecotone between two grassland ecosystems in central New Mexico, USA.

openCC (other)Aug 2025View details →

zenodo48/100

Data files for Competitive ability depends on mating system and ploidy level across Capsella species

The three data files associated with the article: Competitive ability depends on mating system and ploidy level across Capsella species. Annals Of Botany 2022: doi.org/10.1093/aob/mcac044 See README for details on each files

opencc-by-4.0Apr 2022View details →

zenodo48/100

Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions

This data set corresponds to the paper: Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions [1] (Experiment: Comprehensive reporting). The key research questions corresponding to this data set were: RQ1: What is the role of challenges for the field of biomedical image analysis (e.g. How many challenges conducted to date? In which fields? For which algorithm categories? Based on which modalities?) RQ2: What is common practice related to challenge design (e.g. choice of metric(s) and ranking methods, number of training/test images, annotation practice etc.)? Are there common standards? RQ3: Does common practice related to challenge reporting allow for reproducibility and adequate interpretation of results? To address these research questions, we aimed to capture all biomedical image analysis challenges that have been conducted up to 2016. To acquire the data, we analyzed the websites hosting/representing biomedical image analysis challenges, namely grand-challenge.org, dreamchallenges.org and kaggle.com as well as websites of main conferences in the field of biomedical image analysis, namely Medical Image Computing and Computer Assisted Intervention (MICCAI), International Symposium on Biomedical Imaging (ISBI), International Society for Optics and Photonics (SPIE) Medical Imaging, Cross Language Evaluation Forum (CLEF), International Conference on Pattern Recognition (ICPR), The American Association of Physicists in Medicine (AAPM), the Single Molecule Localization Microscopy Symposium (SMLMS) and the BioImage Informatics Conference (BII). This yielded a list of 150 challenges with 549 tasks. Next, a tool for instantiating the challenge parameter list introduced in [1] was used by some of the authors (engineers and medical student) to formalize all challenges that met our inclusion criteria as follows: (1) Initially, each challenge was independently formalized by two different observers. (2) The formalization results were automatically compared. In ambiguous cases, when the observers could not agree on the instantiation of a parameter - a third observer was consulted, and a decision was made. When refinements to the parameter list were made, the process was repeated for missing values. Based on the formalized challenge data set, a descriptive statistical analysis was performed to characterize common practice related to challenge design and reporting. [1] Maier-Hein, L., Eisenmann, M., Reinke, A., Onogur, S., Stankovic, M., Scholz, P., Arbel, T., Bogunovic, H., Bradley, A. P., Carass, A., Feldmann, C., Frangi, A. F., Full, P. M., van Ginneken, B., Hanbury, A., Honauer, K., Kozubek, M., Landman, B. A., März, K., Maier, O., Maier-Hein, K., Menze, B. H., Müller, H., Neher, P. F., Niessen, W., Rajpoot, N., Sharp, G. C., Sirinukunwattana, K., Speidel, S., Stock, C., Stoyanov, D., Aziz Taha, A., van der Sommen, F., Wang, C.-W., Weber, M.-A., Zheng, G., Jannin, P., Kopp-Schneider, A.: Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions. arXiv preprint arXiv:1806.02051 (2018).

opencc-by-4.0Jun 2018View details →

zenodo48/100

"ICDAR2023 Competition on Detection and Recognition of Greek Letters on Papyri" Dataset

<h1>Dataset description of the “ICDAR2023 Competition on Detection and Recognition of Greek Letters on Papyri”</h1> Prof. Dr. Isabelle Marthot-Santaniello, Dr. Olga Serbaeva 2024.09.16 <h2>Introduction</h2> The present dataset stems from the ICDAR2023 Competition on Detection and Recognition of Greek Letters on Papyri (original links to the competition are provided in the file “1b.CompetitionLinks.”) The aim of this competition was to investigate the performance of glyph detection and recognition in a very challenging type of historical document: Greek papyri. The detection and recognition of Greek letters on papyri is a preliminary step for computational analysis of handwriting that can lead to major steps forward in our understanding of this important source of information on Antiquity. Such detection and recognition can be done manually by trained papyrologists. It is, however, a time-consuming task that would need automatising.  We provide here the documents related to two different tasks: localisation and classification. The document images are provided by several institutions and are representative of the diversity of book hands on papyri (a millennium time span, various script styles, provenance, states of preservation, means of digitization and resolution). <h2>How the dataset was constructed</h2> In the frame of <a href="https://d-scribes.philhist.unibas.ch/en/case-studies/iliad-208/" target="_blank" rel="noopener">D-Scribes project</a> lead by Prof. Dr. Isabelle Marthot-Santaniello, 2018-2023, around 150 papyri fragments containing Iliad were manually annotated at a letter-level in <a href="https://github.com/readsoftware/read" target="_blank" rel="noopener">READ</a>. The editions were taken, for the major part, from <a href="papyri.info" target="_blank" rel="noopener">papyri.info</a>, and were simplified, i.e. the accents, editorial marks, and other additional information were removed to be as close as possible to what is to be found on papyri. When the text was not available on papyri.info, the relevant passage was extracted from the <a href="https://github.com/PerseusDL/canonical-greekLit/blob/master/data/tlg0012/tlg001/tlg0012.tlg001.perseus-grc2.xml" target="_blank" rel="noopener">Homer Iliad of Perseus</a>. From those, 150 plus papyri fragments, 185 surfaces (sides of fragments) belonging to 136 different manuscript identified by their Trismegistos numbers, (further TMs) were selected to serve as a material for Competition. These 185 surfaces were separated into the “training set” and the “test set” provided for the competition as a set of images and corresponding data in JSON format. Details on the competition summarised in "ICDAR 2023 Competition on Detection and Recognition of Greek Letters on Papyri", by Mathias Seuret, Isabelle Marthot-Santaniello, Stephen A. White, Olga Serbaeva Saraogi, Selaudin Agolli, Guillaume Carrière, Dalia Rodriguez-Salas, and Vincent Christlein; edited by G. A. Fink et al. (Eds.): ICDAR 2023, LNCS 14188, pp. 498–507, 2023. https://doi.org/10.1007/978-3-031-41679-8_29. After the competition ended, the decision was taken to release manually annotated dataset for the “test set” as well. Please find the description of each included document below. <h2> Dataset Structure</h2> “1. CompetitionOverview.xlsx” contains the metadata of the used images in Excel file, state 2024.09.19. Here is the structure of the Excel file:   <table> <tbody> <tr> <td> Excel columns </td> <td> Name </td> <td> Content </td> <td> Notes </td> </tr> <tr> <td> A </td> <td> TM </td> <td> Trismegistos number is internationally used for papyri identification </td> <td> With READ item name in (). </td> </tr> <tr> <td> B </td> <td> Papyri.info link </td> <td> link </td> <td>   </td> </tr> <tr> <td> C </td> <td> Fragments' Owning Institution (from <a href="http://papyri.info">papyri.info</a>) </td> <td> Institution’s name </td> <td> Institution that physically stores the papyri </td> </tr> <tr> <td> D </td> <td> Availability (of metadata, <a href="http://papyri.info">papyri.info</a>) </td> <td> link </td> <td> Metadata reuse clarification </td> </tr> <tr> <td> E </td> <td> text ID (READ) </td> <td> Number from READ SQL database that was used to link the images and the editions. </td> <td> Serves to locate the attached images and understand the JSON structure. </td> </tr> <tr> <td> F </td> <td> Test/Training </td> <td>   </td> <td> I.e. the image was originally included in the training or in the test set of the dataset. </td> </tr> <tr> <td> G </td> <td> Image Name (for orientation) </td> <td>   </td> <td> As in READ </td> </tr> <tr> <td> H </td> <td> Cedopal link </td> <td> link </td> <td> Contains additional metadata and includes the links to all available online images. </td> </tr> <tr> <td> I </td> <td> License from the Institution webpage. </td> <td> Either license or usage summary. </td> <td> If no precise licence has been given, the summary of the reuse rights is provided with a link to the regulations in column K </td> </tr> <tr> <td> J </td> <td> Image URL </td> <td> link </td> <td> Not all images are available online. Please contact the owning institution directly if the image is not available. </td> </tr> <tr> <td> K </td> <td> Information on the image usage from the institution </td> <td> link </td> <td> In case of any doubt, please contact the owning institution directly. </td> </tr> <tr> <td> L </td> <td> Notes </td> <td>   </td> <td>   </td> </tr> </tbody> </table> For the purpose of an easy overview, the items with special problems, i.e. images not online or missing links, have been marked in red. 2. There are three data subsets: 2a. “Training file”  (containing 150 papyri images separated into 108 texts and HomerCompTraining.json). The images are those of papyri containing Iliad of Homer in JPG-format. These were processed in READ, namely, each visible letter on a given papyri was linked to the edition of the Iliad, through this process, each linked letter of the edition was linked to its coordinates in pixels on the HTML-surface of the image. All that information is provided in the JSON-file. The JSON file contains the “annotations” (b-boxes of each letter/sign), “categories” (Greek letters), “images” (Image IDs), and “licenses”. The links between image and bboxes is defined via the “id” in the “images” part (for example,  "id": 6109). This same id is encoded as “"image_id": 6109” in the “annotations”. Alternatively, “text_id” which can be found in the “images” URL and in the file-names provided here and containing images, can be used for data linking. Let us now describe the content of each part of the JSON file: Each “annotation” contains “area" characterised as “bbox" with coordinates,  “category_id”, that allows to identify which Greek letter in categories is represented by the number; “id”, which is a unique number of the cliplet, i.e. area;  “image_id”, that links cliplet to the surface of the image having the same id;  “iscrowd" and “seg_id" are useful to find the information back in READ database;  and, finally, “tags”. In tags, “BaseType" was used to annotate quality as described below. “FootMarkType”, ft1, etc., was used for clustering tests, but played no role for the Competition. “BaseType” ot bt-tags were assigned to the letters to mark the quality of preservation:  bt-1: well-preserved letter that should allows easy identification for both human eyes and the Computer-vision; bt-2: Partially preserved letter that might also have some background damage (holes, additional ink, etc), but remains readable, and has one interpretation. bt-3: Letters damaged to such an extant that they cannot be identified without reading an edition. These are treated as traces of ink. bt-4: The letters that have some damage, but this damage is of such kind that it makes possible multiple interpretations. For example, missing/defaced horizontal stroke makes alpha indistinguishable from damaged delta or lambda. Each “category” contains  “id”, this is a number references also in “annotations” and it allows to identify which Greek letter was in the bbox;  ”name”, for example, “χ”;  and “supercategory”, i.e. “Greek”. Each “image” contains the following sub fields:  “bln_id" is an internal READ number of the html surface;  "date_captured": null - is another READ field;  "file_name": “./images/homer2/txt1/P.Corn.Inv.MSS.A.101.XIII.jpg", allows to link easy image and text, i.e. for the image in question the JPG will be in the file called “txt1”, it is very similar by structure and function to "img_url": "./images/homer2/txt1/P.Corn.Inv.MSS.A.101.XIII.jpg";  each image has “height" and “width" expressed in pixels.  Each image has “id”, and this id is referenced in the “annotations” under “image_id”.  Finally, each image contains a link to “license”, expressed as a number.  Each “licence” lists a license as it was found during the time of competition, i.e. in February 2023. 2b. “Test file”  contains 34 papyri image sides separated into 31 TMs and HomerCompTesting.json The JSON file here only allows to connect the images with the “categories”, “images”, “licenses”, but without the “annotations”. The structure and logic is otherwise the same like in “Training” JSON. 2c. “Answers file”  Containing the “annotations” and other information for the 34 papyri of the “Testing” dataset. The structure and logic is the same like in “Training” JSON. 3. “Additional files”  Containing lists of duplicate segments id (multiple possible readings or tags), respectively 6 items for “Training”, 17 for “Testing” and 15 for “Answers”. 4. “Dataset Description” This same description included for completeness. <h2>References</h2> The Dataset was reused or mentioned in a number of publications (state September 2024) Mohammed, H., Jampour, M. (2024). "From Detection to Modelling: An End-to-End Paleographic System for Analysing Historical Handwriting Styles". In: Sfikas, G., Retsinas, G. (eds) Document Analysis Systems. DAS 2024. Lecture Notes in Computer Science, vol 14994. Springer, Cham, pp. 363–376. https://doi.org/10.1007/978-3-031-70442-0_22 De Gregorio, G., Perrin, S., Pena, R.C.G., Marthot-Santaniello, I., Mouchère, H. (2024). "NeuroPapyri: A Deep Attention Embedding Network for Handwritten Papyri Retrieval". In: Mouchère, H., Zhu, A. (eds) Document Analysis and Recognition – ICDAR 2024 Workshops. ICDAR 2024. Lecture Notes in Computer Science, vol 14936. Springer, Cham, pp. 71–86. https://doi.org/10.1007/978-3-031-70642-4_5 <div> Vu, M. T., Beurton-Aimar, M. "PapyTwin net: a Twin network for Greek letters detection on ancient Papyri". HIP '23: 7th International Workshop on Historical Document Imaging and Processing, San Jose, CA, USA, August 2023. https://doi.org/10.1145/3604951.3605522 https://dl.acm.org/doi/fullHtml/10.1145/3604951.3605522 Turnbull, R., Mannix, E. "Detecting and recognizing characters in Greek papyri with YOLOv8, DeiT and SimCLR". (Preprint). arXiv:2401.12513 https://doi.org/10.48550/arXiv.2401.12513 </div>

opencc-by-nc-4.0Sep 2024View details →

zenodo48/100

Priority effects can be explained by competitive traits

Code (updated after review) Traits - Trait values that were measurent and calculated from the individuals grown alone (updated after review). See version 2 for other files

opencc-by-4.0Jan 2024View details →

zenodo48/100

Replication files for: Strongmen Cry Too: The Effect of Aerial Bombing on Voting for The Incumbent in Competitive Autocracies

The NATO bombing of Yugoslavia, which lasted from March 24, 1999 until June 10, 1999, was the largest air campaign in Europe since the bombing of Britain and Germany in World War II. The air raids lasted for 78 days and hit 108 out of 160 municipalities, excluding Kosovo and Montenegro. The bombing was spread out and largely aimed at military barracks, industrial facilities, transportation networks, and communication lines. This repo provides a novel dataset with information on over 1,000 targets in the Federal Republic of Yugoslavia, including the date, location, target type, and fatalities. Included is also R code for the replication of my article "Strongmen Cry Too: The Effect of Aerial Bombing on Voting for The Incumbent in Competitive Autocracies" that was accepted for publication at Journal of Peace Research.

opencc-by-4.0May 2021View details →

zenodo48/100

Blind Prediction Competition - Sera.ta - Seismic Response of Masonry Cross Vaults: Shaking table tests and numerical validations

Masonry vaults play a much relevant role in the seismic response of heritage masonry buildings, ranging from housing to the greatest cathedrals. Acting as both a ceiling and a structural horizontal diaphragm with significant mass, their mechanical behaviour affects the overall seismic response of buildings, in terms of strength, stiffness, and ductility. Moreover, local damage and collapse of vaults may produce significant losses in terms of cultural assets and casualties. In spite of the importance of this topic, the evaluation of the complex three-dimensional behaviour of vaults is still an important challenge for researchers. The main objectives of the present research project are: 1)    to better understand the seismic behaviour of masonry cross vaults by means of shaking table tests on both full-scale and small-scale models; 2)    to assess the capability of different modelling/analysis approaches to predict the seismic response of these masonry structures. In particular, three sets of shaking table tests are planned: a.    Tests on a 1:1 scale model of a brick unreinforced masonry cross vault:  to investigate the behaviour of brick masonry cross vaults under different seismic inputs, in terms of damage, displacement capacity and peak acceleration. b.    Tests on a 1:1 scale model of a brick reinforced masonry cross vault: to evaluate the effectiveness of reinforcing techniques to repair the vaults tested in a). In addition to the experimental tests, a blind prediction competition is performed to assess the efficacy of different modelling strategies and analysis techniques. The final aims are to improve the safety assessment procedures proposed for historic masonry buildings in Eurocode 8.3 and to provide better seismic assessment techniques and strengthening measures.

opencc-by-4.0Feb 2023View details →

edi48/100

Data from: Competition among eggs shifts to cooperation along a sperm supply gradient in an external fertilizer

Purple sea urchin, Strongylocentrotus purpuratus, are broadcast spawners. Empirical and theoretical exploration of this trade-off in broadcast spawners has focused heavily on the role of sperm availability. In contrast, the particular manner in which egg concentrations alter both fertilization and polyspermy remains less explored. These data are from a laboratory experiment with a factorial design (six sperm concentrations x four egg concentrations replicated across multiple male-female pairs), to measure fertilization and polyspermy of purple sea urchins. Data were used to evaluate the impact of egg concentration on fertilization, and to explicitly test for random versus nonlinear sperm-egg collision rates. A new dynamic model was developed that expands upon existing models. Observations of fertilization and polyspermy were also used to parameterize and compare the performance of existing models that included random or or nonlinear collision parameters by utilizing several different basic model forms. For more information, see paper with published results or data set methods. Results for these data are pulished in Okamoto. D. K. 2016 Competition among eggs shifts to cooperation along a sperm supply gradient in an external fertilizer. The American Naturalist. 187:5, E129-E142. DOI: 10.1086/685813

openCC (other)Oct 2022View details →

zenodo44/100

Adele 3D seismic survey segy format used in the FORCE 2020 machine learning competition for fault identification

Adele seismic 3D  survey segy format used in the FORCE 2020 machine learning competition for fault identification. Dataset is courtesy of GEOSCIENCE Australia who need to be acknowledged in each publication

opencc-by-4.0Nov 2020View details →

zenodo44/100

Resilient farm demographics withstand, adapt, or transform in the face of competitive pressure, technological change, and the expected lifestyles of future generations

Farm demographics has been recognized as an important driver of structural change in European agriculture. Focus groups and computer simulations on farm demographic change were used to better understand its role for the case study regions of the Altmark in the eastern part of Germany and Flanders in the northern part of Belgium. According to these analyses, many potential agricultural entrants are deterred by what they view as a poor quality of life that farming offers. This applies to farm successors as well as hired workers. For higher attractiveness of agriculture, policy objectives should address the social image of farming as well as revitalize rural areas. Increasingly critical is the demand for skilled hired labour. However, policies dealing with farm demographic change ignore these needs and focus almost exclusively on farm succession. Particularly, the direct payment system, including additional support for small farms and young farmers, must be re-evaluated for its effectiveness. The analyses provide evidence that this system constrains European agricultural development more than assists it; ultimately preventing farms from adapting and transforming.

opencc-by-4.0Feb 2020View details →

zenodo44/100

Data from: Synergistic effects of grass competition and insect herbivory on the weed Rumex obtusifolius in an inundative biocontrol approach

Data are from a field experiment to test for synergistic interactions between grass competition and herbivory on Rumex obtusifolius, a prominent weed in temperate grasslands worldwide.Rumex obtusifolius was grown in the presence and absence of competition from the grass Lolium perenne and subjected to herbivory through targeted inoculation with root-boring Pyropteron spp.To explore whether the interactive effects of competition and herbivory were size-dependent, R. obtusifolius was planted covering a large range of plant sizes found in managed grasslands.The experimental layout followed a split-split plot design. Main-level factor was L. perenne competition, split-level factor was herbivory application, split-split-level factor was initial root mass of R. obtusifolius. Main-plots were arranged according to a randomized complete block design on the site (8 blocks, each containing a L. perenne competition and a no competition treatment).

opencc-by-4.0Oct 2023View details →

zenodo44/100

45 Vulnerability Discoverability Timelines from the 2019 Collegiate Penetration Testing Competition

Description This is a collection of manually curated timelines from the 2019 Collegiate Penetration Testing Competition (CPTC). Collection and annotation are described in detail in this publication: <ul> <li>Benjamin S. Meyers, Sultan Fahad Almassari, Brandon N. Keller, and Andrew Meneely. Examining Penetration Tester Behavior in the Collegiate Penetration Testing Competition. Forthcoming at Transactions on Software Engineering and Methodology. https://dl.acm.org/doi/10.1145/3514040</li> </ul> Included Files <ul> <li>2019_cptc_timelines.csv: Completed timelines for ten teams from the 2019 CPTC nationals competition.</li> <li>2019_cptc_timeline_columns.csv: Descriptions of the columns in 2019_cptc_timelines.csv.</li> <li>2019_cptc_vulnerabilities.csv: Brief vulnerability descriptions and CWE mappings.</li> </ul> Other Resources <ul> <li>Complete Splunk log data dumps are available <a href="http://mirrors.rit.edu/cptc/2019/mirrors/nationals/">here</a>. These must be ingested and viewed with a Splunk instance.</li> <li>To request access to the CPTC team reports, please contact Brock Wagehoft (<a href="mailto:bew1127@rit.edu">email</a>).</li> </ul> Contact Please contact Benjamin S. Meyers (<a href="mailto:bsm9339@rit.edu">email</a>) with questions about this data and its collection. Acknowledgments Collection of this data has been sponsored in part by the National Science Foundation grant 1922169, and by a Department of Defense DARPA SBIR program (grant 140D63-19-C-0018).

opencc-by-4.0Dec 2021View details →

zenodo44/100

Factors determining distributions of rainforest Drosophila shift from interspecific competition to high temperature with decreasing elevation (original datasets)

This repository provides the data for the manuscript "Factors determining distributions of rainforest Drosophila shift from interspecific competition to high temperature with decreasing elevation" We investigated thermal tolerances and interspecific competition as causes of species turnover in the nine most abundant species of Drosophila along elevational gradients in the Australian Wet Tropics. Specifically, we 1) analyzed the distribution patterns of the studies Drosophila species; 2) fitted thermal performance curves; 3) tested the correlation between multiple thermal traits and distribution patterns; 4) fitted the Beverton-Holt model to describe the single-generation intra- and inter-specific competition effect; 5) examined the long-term effect of competition and temperature on the population size of a pair of Drosophila species. More details are provided in the README file.

opencc-by-4.0Mar 2022View details →

zenodo44/100

Datasets and Supporting Materials for the IPIN 2021 Competition Track 3 (Smartphone-based, off-site)

This package contains the datasets and supplementary materials used in the IPIN 2021 Competition. Contents: <ul> <li>IPIN2021_Track03_TechnicalAnnex_V1-02.pdf: Technical annex describing the competition</li> <li>01-Logfiles: This folder contains a subfolder with the 105 training logfiles,  80 of them single floor indoors, 10 in outdoor areas, 10 of them in the indoor auditorium with floor-trasitio and 5 of them  in floor-transition zones, a subfolder with the 20 validation logfiles, and a subfolder with the 3 blind evaluation logfile as provided to competitors.</li> <li>02-Supplementary_Materials: This folder contains the matlab/octave parser, the raster maps, the files for the matlab tools and the trajectory visualization.</li> <li>03-Evaluation: This folder contains the scripts used to calculate the competition  metric, the 75th percentile on the 82 evaluation points. It requires the  Matlab Mapping Toolbox.  The ground truth is also provided as 3 csv files.  Since the results must be provided with a 2Hz freq. starting from  apptimestamp 0, the GT files include the closest timestamp matching the timing provided by competitors for the 3 evaluation logfiles. It contains samples of reported estimations and the corresponding results.</li> </ul> Please, cite the following works when using the datasets included in this package: <ul> <li>Torres-Sospedra, J.; et al.  Datasets and Supporting Materials for the IPIN 2021 Competition Track 3 (Smartphone-based, off-site). http://dx.doi.org/10.5281/zenodo.5948678</li> </ul>

opencc-by-4.0Dec 2021View details →

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Party control, intra-party competition and the substantive focus of women's parliamentary questions: evidence from Belgium (replication data)

Replication data for B. de Vet & R. Devroe, (2022). Party Control, Intraparty Competition, and the Substantive Focus of Women's Parliamentary Questions: Evidence from Belgium. Politics & Gender, 1-25. doi:10.1017/S1743923X21000490

opencc-by-4.0Oct 2022View details →

zenodo44/100

ICDAR'15 SMARTPHONE DOCUMENT CAPTURE AND OCR COMPETITION (SmartDoc) - Challenge 1 (original version)

CHALLENGE 1: SMARTPHONE DOCUMENT CAPTURE COMPETITION Smartphones are replacing personal scanners. They are portable, connected, powerful and affordable. They are on their way to become the new entry point in business processing applications like document archival, ID scanning, check digitization, just to name a few. In order keep our workflows streamlined, we need to make those new capture device as reliable as batch scanners. We believe an efficient capture process should be able to: <ol> <li>detect and segment the relevant document object during the preview phase;</li> <li>assess the quality of the capture conditions and help the user improve them;</li> <li>optionally, trigger the capture at the perfect moment;</li> <li>and produce a high-quality, controlled output based on the high resolution captured image.</li> </ol> This competition is focused on the first step of this process: efficiently detect and segment document regions, as illustrated by following video showing the ideal output for the preview phase of some acquisition session: <a href="https://youtu.be/WNsI0R_rpO0">Click here to watch the video.</a> This video shows the ideal document object detection &lrm;(ie the ground truth, as a red frame)&lrm;. For this challenge, the input consists in a set of videoclips containing a document from a predefined set, and the output should be an xml file containing the quadrilateral coordinates in which we can find the document per each frame of the video. Click <a href="https://sites.google.com/site/icdar15smartdoc/challenge-1/challenge1dataset">here</a> for detailed information about the dataset.    Licence for the dataset of challenge 1 (page outline detection in preview frames) : This work is licensed under a Creative Commons Attribution 4.0 International License <<a href="https://www.google.com/url?q=http://creativecommons.org/licenses/by/4.0/&sa=D&ust=1524734857667000&usg=AFQjCNEt4YXnUv2nXCFwkeOuBDqxDpvknQ">http://creativecommons.org/licenses/by/4.0/</a>>. Author attribution should be given by citing the following conference paper: Jean-Christophe Burie, Joseph Chazalon, Mickaël Coustaty, Sébastien Eskenazi, Muhammad Muzzamil Luqman, Maroua Mehri, Nibal Nayef, Jean-Marc OGIER, Sophea Prum and Marçal Rusinol: “ICDAR2015 Competition on Smartphone Document Capture and OCR (SmartDoc)”, In 13th International Conference on Document Analysis and Recognition (ICDAR), 2015. If you use this dataset, please send us a short email at <icdar.smartdoc (at) gmail.com> to tell us why it was useful to you, and whether you have results or publications we can reference on our website. Thank you!

opencc-by-4.0Aug 2015View details →

zenodo44/100

Dataset for ICFHR2018 Competition on Automated Text Recognition on a READ Dataset

The main idea of this dataset is to analyse the impact of training data. How many training data specific to the document, you are transcribing, is necessary?    general data: This is a collection of heterogeneous documents to train an initial system. For each text line there is an image file of that line, a file with the ground truth text and an information file containing an automatically generated surrounding polygon. specific data: The specific data contains documents related to the test data. For the specific systems only the images of the train list may be used. The file are of the same type as the general data. test data: The test data contains only the images and the information files. More Information, some published results and an evaluation procedure at https://scriptnet.iit.demokritos.gr/competitions/10/

opencc-by-4.0Sep 2018View details →

zenodo44/100

ScriptNet: ICDAR 2017 Competition on Baseline Detection in Archival Documents (cBAD)

This dataset contains the training and test set for the ICDAR 2017 Competition on Baseline Detection in Archival Documents (cBAD). A newly created freely available real world dataset consisting of 2035 annotated document page images that are collected from 9 different archives and form the basis of cBAD. Two competition tracks test different characteristics of the methods submitted. Track A [Simple Documents] is published with annotated text regions and tests therefore a method's quality of text line segmentation. The more challenging Track B [Complex Documents] provides only the page area. Hence, baseline detection algorithms need to correctly locate text lines in the presence of marginalia, tables, and noise. The dataset comprises images with additional PAGE XMLs. The PAGE XMLs contain text regions and baseline annotations. Competition Website: https://scriptnet.iit.demokritos.gr/competitions/5/ Version 3 is the version of the cBad competition Version 4 contains also the page region and in case of a double-page the page split as separator.

opencc-by-sa-4.0Jan 2017View details →

zenodo44/100

H2020 PrimeFish National Level Competitiveness Iceland Norway Spain Vietnam Newfoundland

The data set contains data on individual indicators of national seafood competitiveness. Data are collected as part of the EU H2020 project PrimeFish (grant no 635761). The analysis follows the general framework of the annual World Economic Forum Competitiveness Report. Indicators are taken from three sources; directly from the World Economic Forum report, survey among national experts and hard data such as stock sizes and wages. All data are numeric, and on a 1-7 scale. Data were collected from the World Economic Forum 2017 competitiveness report and surveys and hard data collected in 2017.   Indicators are grouped in several catergories, that again are grouped in higher level categories, ultimately yielding a single competitiveness indicator for the seafood sector.

opencc-by-4.0Feb 2019View 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