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Dataset with the results of the e-infrastructures Austria National Survey about Research Data

This is the dataset accompanying the report with the results of our national survey regarding the management of research data

opencc-by-4.0May 2016View details →

zenodo44/100

Linguistic Atlas Projects - Atlanta Survey Project - Version 1

Director: William A. Kretzschmar, Jr. Status of work: Field work complete in 2003. Direct CD recordings; some full transcriptions have been completed. Areas covered: Fulton and DeKalb counties in the Atlanta, GA, metropolitan area. Subjects: 18 speakers selected by random phone sampling, with later in-person interviews. African American and nonAfrican American subjects, stratified by gender and occupational status. Nature of recordings: Guided conversational interview expected to last one hour, adapted from Western States interview. Fixed format elicitation in which speakers read words from cards. Archives: Original materials are archived in the Special Collections repository of the Library, University of Georgia, Athens, Georgia 30602. For access to original materials, contact the Linguistic Atlas Project office.

opencc-by-4.0Jan 2017View details →

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OpenAIRE FP7 Post-Grant Pilot - Survey of Beneficiaries

The OpenAIRE FP7 Post-grant OA Pilot was launched by the European Commission (EC) for the period May 30th, 2015 to April 30th, 2017 in the context of the OpenAIRE2020 project. The survey of the Pilot's beneficiaries was comprised of 21 multiple choice and open text questions. It was distributed to the 547 recipients of pilot funding by email and received a total of 322 responses (59% response rate).  The results were analysed by Research Consulting, on behalf of the OpenAIRE consortium.

opencc-by-4.0Feb 2017View details →

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Results from the RDM Survey - LEARN project (December 2016)

Data obtained from the open survey developed by the LEARN project (http://www.learn-rdm.eu/) as a self-assessment tool to assist institutions discover how ready they are for managing research data. This dataset replaces the first one published at http://doi.org/10.5281/zenodo.61903. The survey is based on the issues posed to institutions by the LERU Roadmap for Research Data published at the end of 2013, and available at: http://www.learn-rdm.eu/material/leru_roadmap_for_research_data The survey has thirteen questions addressing the main elements to be taken into account in developing an institutional strategy for research data management. Each question has three possible answers representing green, yellow or red light. The more ‘green light’ responses recorded, the readier an institution probably is for managing its research data. The survey is available in English at http://learn-rdm.eu/en/rdm-readiness-survey/ and in Spanish at http://learn-rdm.eu/encuesta-rdm/

opencc-by-4.0Feb 2017View details →

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OpenAIRE Open Peer Review Survey 2016

This data set contains: - Full data files of a 2016 survey of attitudes to Open Peer Review in xls and csv formats - Survey questions (pdf) - Readme file (txt) Between 8 September and 7 October 2016, OpenAIRE held a survey designed to aid the development of appropriate OPR approaches by providing evidence about the attitudes of authors, editors and reviewers towards OPR, their reservations and needs, as well as to gauging current levels of experience and reservation with different types of OPR. A supplementary aim was to collect feedback on a provisional definition of OPR as created during another strand of work. The survey aimed to aid the development of appropriate OPR approaches by providing evidence about the attitudes of authors, editors and reviewers towards OPR, their reservations and needs, as well as to gauge current levels of experience and reservations with different types of OPR. The survey was conducted via an openly accessible online questionnaire (using the scientific survey platform SoSci, www.soscisurvey.de). It received a total of 3062 complete responses (a further 635 responses were discarded as incomplete). The survey was open to all wishing to take part and distributed via social media, scholarly communications mailing lists, publisher newsletters and, in one case, a publisher internal mailing list (Copernicus Publications). Acknowledgement: This work is funded by the European Commission H2020 project OpenAIRE2020 (Grant agreement: 643410, Call: H2020-EINFRA-2014-1) Contact: Dr Tony Ross-Hellauer, University of Göttingen, State and University Library, ross-hellauer@sub.uni-goettingen.de

opencc-by-4.0Mar 2017View details →

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OpenUP survey on researchers' current perceptions and practices in peer review, impact measurement and dissemination of research results

OpenUP project (http://openup-h2020.eu/) conducted a survey to capture current perceptions and practices in peer review, dissemination of research results and impact measurement among European researchers. The survey was coducted between 20 January and 23 February 2017. It consisted of four sections. The first section asked a series of questions on the respondents’ scientific discipline, career stage, gender and other characteristics. The following sections asked a series of questions on peer review practices, dissemination of research results and impact measurement/use of altmetrics. The questionnaire was collaboratively prepared by the OpenUP consortium. The survey was implemented via surveygizmo tool (https://www.surveygizmo.com/). Invitations to participate were sent to a random sample of researchers from arXiv, Pubmed and RePEc. The OpenUP team mined researchers’ contact details from these platforms. The OpenUP project team made efforts to further boost the repondent sample for certain underrepresented areas through the DARIAH website, THESIS network, EURODOC, AIMS portal, the Parthenos community and other channels. The survey targeted researchers from the EU-28, Switzerland and Norway. The goal was to get around 1,000 responses. In total, there were 976 completed response and completion rate was 72.4%. The attached documents include the questionnaire and the dataset. In the dataset (cvs file) the top row contains numbered questions that correspond to the numberring in the questionnaire (word file). The data was exported as an excel file, anonymised by creating respondent IDs and IP data were deleted. The file was then converted to CSV.

opencc-by-4.0Apr 2017View details →

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Final Results from the RDM Survey - LEARN project (June 2017)

Data obtained from the open survey developed by the LEARN project (http://www.learn-rdm.eu/) as a self-assessment tool to assist institutions discover how ready they are for managing research data. This dataset replaces the previous ones published at http://doi.org/10.5281/zenodo.61903 and http://doi.org/10.5281/zenodo.290635. The survey is based on the issues posed to institutions by the LERU Roadmap for Research Data published at the end of 2013, and available at: http://www.learn-rdm.eu/material/leru_roadmap_for_research_data The survey has thirteen questions addressing the main elements to be taken into account in developing an institutional strategy for research data management. Each question has three possible answers representing green, yellow or red light. The more ‘green light’ responses recorded, the readier an institution probably is for managing its research data. The survey is available in English at http://learn-rdm.eu/en/rdm-readiness-survey/ and in Spanish at http://learn-rdm.eu/encuesta-rdm/

opencc-by-4.0Jun 2017View details →

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Audio Commons WP2 - Responses to user survey (Deliverable 2.1)

These are the responses gathered from the user survey described in Deliverable 2.1 of the Audio Commons project. The survey contained 24 questions asking creatives working in music industry about various subjects like demographics, workflows they use and metadata they would like to use when searching for new audio content on the Web. The file formResponses.csv contains the actual responses, column names in the first row, fields separated by commas and enclosed in double quotes if needed (e.g., a comma was in the value). The Timestamp column contains the response timestamp, in DD/MM/YYYY hh:mm:ss format. Each other column is named as one of the survey questions and contain the corresponding responses. For the relevant context, please check the Audio Commons web page (http://www.audiocommons.org/) and specifically Deliverable 2.1.

opencc-by-4.0Jul 2017View details →

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Archaeological Survey of India Collections: Burma Circle, 1907-13. Photo 1004/2 : 1907-1913 (.jpg format)

This is a digitized collections of photos held by the British Library (catalog record photo 1004/2). These photos were taken by the Archeological Survey of India (Burma Circle) between 1907-1913. The digitization was conducted by the photography lab of the British Library as part of the Pyu epigraphy sub-project (PI, Nathan W. Hill of SOAS University of London) of the ERC synergy grant "Beyond Boundaries: Religion, Region, Language and the State" (Identifier: ASIA 609823). The original photographs are under crown copyright, which means that sufficient time has past for them to be distributed to the public. Here is the record from the BL-- <ul> <li>Title: Archaeological Survey of India Collections: Burma Circle, 1907-13. Photographer(s): Archaeological Survey of India </li> <li>Collection Area: Visual Arts</li> <li>Reference: Photo 1004/2</li> <li>Creation Date: 1907-1913</li> <li>Extent and Access: Extent: 321 items Conditions of Use: Appointment Required to view these records. Please consult Asian and African Studies Print Room staff.</li> <li>Language: Not applicable</li> <li>Contents and Scope: Contents: Blue half-leather album, 385x322mm, containing prints mounted on pages interleaved with tissue. The photographs were taken by the Archaeological Survey, Burma, between 1907-13, and listed in the annual Report of the Superintendent... Copies of each year's report precede the photographs for that year, as follows: Year Photo no 1907-08 510-609 1908-09 610-750 1909-10 751-859 1910-11 860-962 1911-12 963-1053 1912-13 1054-1182 The photographs, including views of Burmese architecture, sculpture and relics, were taken under the direction of the Superintendent, a post held at the time by Taw Sein Ko. Process = Collodio-chloride and gelatine silver prints Photographers = Archaeological Survey of India., ; </li> <li>History: Immediate Source of Acquisition: Official Deposit </li> </ul>

opencc-by-4.0Jul 2017View details →

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Paper Survey Table - Smart Mobility - role of mobile games

This table (CSV File) compiles the papers reviewed for the survey paper "Smart Mobility, the role of Mobile Games" presented at the 8th Serious Games Development & Applications (SGDA 2017) conference. It compiles 140 documents read and described to understand the role of mobile games in the promotion of smart mobility, especially based on urban cycling.  The images provide relevant insights of the survey and support the analysis of the survey paper they are briefly described as follows:  Chart 1: Number of papers classified by publisher and type of publication reported. Chart 2: Number of participants classified by type of publication reported. Chart 3: Number of papers classified by the method reported and the number of citations. Chart 4: Number of papers reporting cycling classified by type of motivation used for gamification strategies Chart 5: Number of papers reporting cycling classified by device and location technology reported The following is a short explanation of each of the columns of the table and its contents, self-explanatory titles are omitted. <ul> <li>Database: source or publisher of the paper</li> <li>Type: description of the kind of publication between conference paper, book chapter, or journal paper. </li> <li>Oldest Reference: year of publication of the oldest reference cited in the paper.</li> <li>Newest Reference: year of publication of the newest reference cited in the paper.</li> <li>Citation: Classification of the number of citations that the paper has. Values: none, 1-5, 5-10, +10.</li> <li>Participants: Classification of the number of participants that the paper reports. Values: none, 1-5, 5-10, +10. </li> <li>Method Description: Short description of the method reported by the paper.</li> <li>Reported Method: Classification of the reported method of the paper in three main categories. Design, Experiment / Test, Literature review, Survey.</li> <li>Gamification - Motivation: Classification of the sources of motivation reported. Values: Intrinsic Motivation, Extrinsic Motivation, Mixed.</li> <li>Gamification - Negative Issues: Filled when the paper is reporting the analysis of negative consequences of using gamification:</li> <li>Gamification: Classification of the kind of technique reported. Values: Gamified, not Gamified</li> <li>Device and Location Usage: Classification of the use of mobile devices, wearables and location technologies. Values: No device, Device enabled, Mobile and location enabled, Device and location enabled.</li> <li>App Name: The name of the application reported by the paper when it exists.</li> </ul>

opencc-by-4.0Dec 2016View details →

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Archaeological Survey of India Collections: Burma Circle, 1913-1916. Photo 1004/3 : 1913-1916 (.jpg format)

This is a digitized collections of photos held by the British Library (catalog record photo 1004/3). These photos were taken by the Archeological Survey of India (Burma Circle) between 1913-1916. The digitization was conducted by the photography lab of the British Library as part of the Pyu epigraphy sub-project (PI, Nathan W. Hill of SOAS University of London) of the ERC synergy grant "Beyond Boundaries: Religion, Region, Language and the State" (Identifier: ASIA 609823). The original photographs are under crown copyright, which means that sufficient time has past for them to be distributed to the public. Here is the record from the BL-- <ul> <li>Title: Archaeological Survey of India Collections: Burma Circle, 1913-16. Photographer(s): Archaeological Survey of India </li> <li>Collection Area: Visual Arts</li> <li>Reference: Photo 1004/3</li> <li>Creation Date: 1913-1916</li> <li>Extent and Access: Extent: 265 items Conditions of Use: Appointment Required to view these records. Please consult Asian and African Studies Print Room staff.</li> <li>Language: Not applicable</li> <li>Contents and Scope: Contents: Blue half-leather album, 385x322mm, containing prints mounted on pages interleaved with tissue. The photographs were taken by the Archaeological Survey, Burma, between 1913-16, and listed in the annual Report of the Superintendent... Copies of each year's report precede the photographs for that year, as follows: Year Photo no 1913-14 1183-1317 1914-15 1318-1490 1915-16 1491-1593 The photographs, including views of Burmese architecture, sculpture and relics, were taken under the direction of the Superintendent, a post held at the time by Taw Sein Ko. Process = Gelatine silver prints Photographers = Archaeological Survey of India., ; </li> <li>History: Immediate Source of Acquisition: Official Deposit </li> </ul>

opencc-by-4.0Jul 2017View details →

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Archaeological Survey of India Collections: Burma Circle, 1916-22. Photo 1004/4 : 1916-22 (.jpg format)

This is a digitized collections of photos held by the British Library (catalog record photo 1004/4). These photos were taken by the Archeological Survey of India (Burma Circle) between 1916-22. The digitization was conducted by the photography lab of the British Library as part of the Pyu epigraphy sub-project (PI, Nathan W. Hill of SOAS University of London) of the ERC synergy grant "Beyond Boundaries: Religion, Region, Language and the State" (Identifier: ASIA 609823). The original photographs are under crown copyright, which means that sufficient time has past for them to be distributed to the public. Here is the record from the BL-- <ul> <li>Title: Archaeological Survey of India Collections: Burma Circle, 1916-22. Photographer(s): Archaeological Survey of India </li> <li>Collection Area: Visual Arts</li> <li>Reference: Photo 1004/4</li> <li>Creation Date: 1916-1922</li> <li>Extent and Access: Extent: 238 items Conditions of Use: Appointment Required to view these records. Please consult Asian and African Studies Print Room staff.</li> <li>Language: Not applicable</li> <li>Contents and Scope: Contents: Blue half-leather album, 385x335mm, containing prints mounted on pages interleaved with tissue. The photographs were taken by the Archaeological Survey, Burma, between 1916-22 (except for 1917-18 and 1918-19), and listed in the annual Report of the Superintendent ... Copies of each year's report precede the photographs for that year, as follows: Year Photo no 1916-17 1594-1743 1917-18 No prints 1918-19 No prints 1919-20 1991-2094 1920-21 2095-2203 1921-22 2204-2280 The photographs, including views of Burmese architecture, sculpture and relics, were taken under the direction of the Superintendent, a post held until 1919 by Taw Sein Ko, and thereafter by his successor Charles Duroiselle. Process = Gelatine silver prints Photographers = Archaeological Survey of India., ; </li> <li>History: Immediate Source of Acquisition: Official Deposit </li> </ul>

opencc-by-4.0Aug 2017View details →

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Data repository of multi-temporal high-resolution data products of ecosystem structure derived from country-wide airborne laser scanning surveys of the Netherlands

This data repository contains a set of multi-temporal data products of ecosystem structure derived from four national ALS surveys of the Netherlands (AHN1–AHN4) (folders: 1_AHN1, 2_AHN2, 3_AHN3, and 4_AHN4). Four sets of 25 LiDAR-derived vegetation metrics representing ecosystem height, cover, and structural variability are provided at 10 m spatial resolution, providing valuable data sources for a wide range of ecological research and field beyond. A preview of all generated LiDAR metrics are also provided (folder: 5_Maps). All 25 LiDAR metrics were calculated using Laserfarm workflow  (<a href="https://laserfarm.readthedocs.io/en/latest/">https://laserfarm.readthedocs.io/en/latest/</a>) (building on the user-extendable features from the “Laserchicken” software: <a href="https://laserchicken.readthedocs.io/en/latest/#features">https://laserchicken.readthedocs.io/en/latest/#features</a>). All metrics are calculated with the normalized point cloud. More details on metric calculation are provided on GitHub (Laserchicken: <a href="https://github.com/eEcoLiDAR/laserchicken">https://github.com/eEcoLiDAR/laserchicken</a> and Laserfarm: <a href="https://github.com/eEcoLiDAR/Laserfarm">https://github.com/eEcoLiDAR/Laserfarm</a>), as well as on the “Laserchicken” documentation page (<a href="https://laserchicken.readthedocs.io/en/latest/">https://laserchicken.readthedocs.io/en/latest/</a>). We also provided masks to minimize the influence of water surfaces, buildings and roads, powerlines and NA values in the data products (folder: 6_Masks).  To supplement the generated data products, we also provided a set of raster layers that contains point/pulse density of each AHN survey and the DTM and DSM raster layers for each AHN dataset (folder: 7_Auxiliary_data). To test the robustness of the LiDAR metrics, we also compared the metrics generated from different pulse densities across different habitat types (folder: 8_Sensitivity_analysis). Two use cases demonstrated the utility of the presented data products: (use case 1) monitoring forest structural change across time using multi-temporal ALS data and (use case 2) comparison of vegetation structural difference within Natura 2000 sites. The used data are also provided (folder: 9_Use_case). Note that all the raster layers are provided at 10 m resolution under the local Dutch coordinate system “RD_new” (EPSG: 28992, NAP:5709). To gain more insights of the pre-classification accuracy of the AHN datasets, we also conducted a preliminary assessment of the effect of terrain filtering on vegetation change detection across AHN datasets (i.e. AHN2–AHN4). The data used in this analysis are made available (folder: 10_Ground_classification). An overview of all the folders in the repository: 1.     AHN1 2.     AHN2 3.     AHN3 4.     AHN4 5.     Maps Those folders contain four sets of 25 LiDAR metrics at 10 m resolution generated from each AHN dataset. The file names and their corresponding LiDAR metrics can be found in Table 1. An additional folder (5_Maps) contains the maps (.pdf format) of all 25 metrics for each AHN dataset. 6. Masks <ul> <li>ahn3_10m_mask_building_road_water.tif</li> <li>ahn4_10m_mask_building_road_water.tif</li> <li>ahn4_10m_mask_powerline.tif</li> <li>ahn1_10m_NA_mask.tif</li> <li>ahn2_10m_NA_mask.tif</li> <li>ahn3_10m_NA_mask.tif</li> <li>ahn4_10m_NA_mask.tif</li> </ul>   It contains two mask layers of water surfaces, buildings and roads for both AHN3 and AHN4 data products based on the Dutch cadaster data (TOP10NL) from 2018 (corresponding to AHN3) and 2021 (corresponding to AHN4) (<a href="https://www.kadaster.nl/zakelijk/producten/geo-informatie/topnl">https://www.kadaster.nl/zakelijk/producten/geo-informatie/topnl</a>). In the masks, water surfaces, buildings and roads were merged into one class with pixel value assigned to 1 and the rest has the pixel value of 0. There is also a powerline mask generated from the AHN4 dataset at 10 m resolution, where pixels containing powerlines were assigned a value of 1 and the rest as NoData. We provide those masks to minimize the inaccuracies of the data products caused by human infrastructures and water surfaces. We also provided a mask for each AHN dataset where NA value occurs — areas with no vegetation points (“unclassified” class in the AHN datasets). Pixels with NA value were assigned with a value of 1 and the rest as 0. 7. Auxiliary data (1) Point_density <ul> <li>ahn1_10m_point_density.tif</li> <li>ahn2_10m_point_density.tif</li> <li>ahn3_10m_point_density.tif</li> <li>ahn4_10m_point_density.tif</li> </ul> (2) Pulse_density <ul> <li>ahn3_10m_pulse_density.tif</li> <li>ahn4_10m_pulse_density.tif</li> </ul> (3) Flighttime <ul> <li>ahn3_10m_flighttime.tif</li> <li>ahn4_10m_flighttime.tif</li> </ul> (4) DTM_DSM <ul> <li>ahn2_10m_dtm.tif</li> <li>ahn2_10m_dsm.tif</li> <li>ahn3_10m_dtm.tif</li> <li>ahn3_10m_dsm.tif</li> <li>ahn4_10m_dtm.tif</li> <li>ahn4_10m_dsm.tif</li> </ul> It contains four raster layers representing the point density of each AHN dataset, two raster layers for pulse density of the AHN3 and AHN4, two raster layers for flight timestamp of the AHN3 and AHN4, and six DTM and DSM layers for AHN2–AHN4. All raster layers are provide at 10 m resolution. 8. Sensitivity analysis <ul> <li>Dunes</li> <li>Marsh</li> <li>Grassland</li> <li>Shrubland</li> <li>Woodland</li> <li>Code</li> <li>Figure</li> </ul> It contains the 25 metrics generated from point clouds with the original and down-sampled pulse densities (original pulse density of the AHN4, pulse density of the AHN3, ½ of the pulse density of the AHN3, and ¼ of the pulse density of AHN3) for each habitat type (i.e. dunes, marsh, grassland, shrubland, and woodland). We also provided the code and the figures generated from this analysis. 9. Use_case (1) Multi-temporal_AHN <ul> <li>Data</li> <li>Usecase_multi-temporal_AHN.R</li> </ul> It contains the input data for the use case data processing (i.e. Data folder), including the shapefile of the area (i.e. shp folder), and extracted pixel value from six selected LiDAR metrics from AHN1–AHN5 (i.e. Metrics folder), and the selected LiDAR metrics of the area (e.g. Hp95 folder), and the R code for data processing (i.e. Usecase_multi-temporal_AHN.R). (2) Natura2000 <ul> <li>Data</li> <li>Natura2000_end2021_HABITATCLASS.csv</li> <li>Natura2000_NL_habitat_grouped.csv</li> <li>Usecase_Natura2000.R</li> </ul> It contains a folder of the input data used for the use case (i.e. Data folder), including the shapefile (i.e. shp folder) of the Natura 2000 sites in the Netherlands (i.e. Nature2000_NL_RDnew.shp) and the 100 random sample plots from each habitat type (e.g. woodland_points.shp), and the LiDAR metrics from AHN4 used for demonstrating the vegetation  structure within each habitat type (i.e. AHN4_metrics folder). The table “Natura2000_end2021_HABITATCLASS.csv” is the original attribute table of Natura 2000 sites, including information related to the description of habitat classes (column “DESCRIPTION”), the code corresponding to the habitat class (column “HABITATCODE”), the code for the specific site (column “SITECODE”), and the percentage of the cover of a specific habitat class in one site (column “PERCENTAGECOVER”). The table “Natura2000_NL_habitat_grouped.csv” contains two subtabs, one (i.e. “Habitatclass”) is the copy of the original attribute table of Natura 2000 sites in the Netherlands, and the other one (i.e. “Habitat_class_summary”) is the grouped habitat type based on the dominant habitat class (i.e. class with the highest percentage cover) in each site. Different colors indicate different habitat types, corresponding to the colors in the first tab (“Habitatclass”) where the dominant habitat class was highlighted for each site. 10. Ground classification <ul> <li>Raw_point_cloud</li> <li>Computed_metrics </li> <li>Plottings_and_code</li> <li>ArcGIS_project</li> </ul> It contains four subfolders: (1) The original point cloud for each sample area (AHN2–AHN4) (subfolder: Raw_point_cloud); (2) The 25 LiDAR metrics computed from the original point clouds with pre-classification of AHN and from the new terrain filtering method across AHN2–AHN4 (subfolder: Computed_metrics); (3) Generated violin plots for the comparison of vegetation change detection and the python code employed (subfolder: Plottings_and_code); (4) an ArcGIS project which the shapefiles of the study area and sample plots are provided (subfolder: ArcGIS_project). Code availability Jupyter Notebooks for processing AHN datasets: <a href="https://github.com/ShiYifang/AHN">https://github.com/ShiYifang/AHN</a> Laserfarm workflow repository: <a href="https://github.com/eEcoLiDAR/Laserfarm">https://github.com/eEcoLiDAR/Laserfarm</a> Laserchicken software repository: <a href="https://github.com/eEcoLiDAR/laserchicken">https://github.com/eEcoLiDAR/laserchicken</a> Code for downloading AHN dataset: <a href="https://github.com/ShiYifang/AHN/tree/main/AHN_downloading">https://github.com/ShiYifang/AHN/tree/main/AHN_downloading</a> Code for generating masks for AHN datasets: <a href="https://github.com/ShiYifang/AHN/tree/main/AHN_masks">https://github.com/ShiYifang/AHN/tree/main/AHN_masks</a> Code for demonstration of ecological use cases: <a href="https://github.com/ShiYifang/AHN/tree/main/Use_case">https://github.com/ShiYifang/AHN/tree/main/Use_case</a>

opencc-by-4.0Oct 2024View details →

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Dataset for: A revised and expanded deep radiostratigraphy of the Greenland Ice Sheet from airborne radar sounding surveys between 1993–2019

Version 5 changes the variable names in the NetCDF file so that are more readable by xarray. The NetCDF v4 file (Greenland_radiostratigraphy_v2.nc) contains both the gridded depths of synthetic isochrones (i.e., at ages of interest that were not necessarily directly observed) and the age at regular normalized depths (10–80%) in the ice sheet. For each campaign that was traced, there is an HDF5-compliant .mat MATLAB file (Greenland_radiostratigraphy_v2_X_Y, where X is the year the campaign was flown and Y is the aircraft that was used) that contains the original traced and dated reflections for each traced segment in that campaign. If using Python instead of MATLAB, the mat73 package and its loadmat function can be used to load these files. An example Jupyter notebook is included that illustrates how to access the full contents of .mat file using Python and this package. There is also a zipped (.zip) archive for each campaign that contains GeoPackage (.gpkg) files for each traced segment of that campaign. Because of format restrictions, these GeoPackages only include the traced reflections' depths, with the ages in the metadata.

opencc-by-4.0Nov 2024View details →

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Cleaned spawner survey data

This dataset is a version of the New Salmon Escapement Database (NuSEDS) downloaded from Open Data Canada on January 21, 2025 at <a href="https://open.canada.ca/data/en/dataset/c48669a3-045b-400d-b730-48aafe8c5ee6">https://open.canada.ca/data/en/dataset/c48669a3-045b-400d-b730-48aafe8c5ee6</a>. These data have been cleaned and matched to Conservation Units (CUs) by staff at the Pacific Salmon Foundation.  Details of the data cleaning procedure are outlined in the Pacific Salmon Explorer Technical Report (Appendix 2) available online at <a href="https://www.salmonexplorer.ca/methods/appendix-2.html">https://www.salmonexplorer.ca/methods/appendix-2.html</a>. The entire cleaning procedure is available online at <a href="https://bookdown.org/salmonwatersheds/1_nuseds_collation_atkinson/1_nuseds_collation.html">a_nuseds_collation</a> and corresponding code <a href="https://github.com/salmonwatersheds/salmon_data_demise/blob/main/code/a_nuseds_collation.Rmd">a_nuseds_collation.Rmd</a>. The procedure to match the cleaned data to CUs is available online at <a href="https://bookdown.org/salmonwatersheds/2_nuseds_cuid_pse_atkinson/2_nuseds_cuid_pse.html">b_nuseds_cuid_pse</a> and corresponding code <a href="https://github.com/salmonwatersheds/salmon_data_demise/blob/main/code/b_nuseds_cuid_pse.Rmd">b_nuseds_cuid_pse.Rmd</a>.  This revised dataset (v3, 2025-04-15) includes observed counts of zero. This is the dataset used in <a href="https://doi.org/10.1139/cjfas-2024-0387">Atkinson et al. 2025. Monitoring for fisheries or for fish? Declines in monitoring of salmon spawners continue despite a conservation crisis</a>, published in the CJFAS. The definition of the fields/columns is available at: <a href="https://github.com/salmonwatersheds/population-indicators/blob/f33058a4aaa0e5fc30354588b5dab469cc9d2a4a/spawner-surveys/output/METADATA_2_nuseds_cuid_streamid.csv">METADATA_2_nuseds_cuid_streamid.csv</a>

opencc-by-4.0Nov 2024View details →

zenodo44/100

PARESv3 : PArish REgistry Survey − Historical Census Table Dataset (19th, 20th centuries) − France

<h2>PARES Dataset v3</h2> PARES (PArish REcord Survey) contains 535 images of handwritten census tables for years ranging from around 1650 A.D. until 1850 A.D..They come from two French cities, Vic-sur-Seille (French department of Moselle) and Echevronne (French department of Côte d'Or). While they mention very ancient times, the documents are handwritten transcriptions of even older documents and are quite recent, copied from original documents during the 1950's and 1960's for demographic studies led by the INED in France (Institut National des études démographiques − National Institute for Demographic Studies). These copies were made by only a few different writers. In this updated version of the dataset, each table row has been carefully annotated and transcribed. Please note that for each row transcription, we have specified the attribute to which each value corresponds. We published a paper, <a href="https://link.springer.com/article/10.1007/s10032-025-00531-z">The PARES Database: Information Extraction over Historical Parish Records,</a> in which we better describe the dataset and the tasks it's possible to run on it.

opencc-by-4.0Dec 2023View details →

zenodo44/100

CBS - Charging Behavior Survey

Two online surveys, one for BEV, and one for truck drivers, were set up and yielded a total of 348 responses, which are all included in this data set. For the BEV survey, stickers with QR codes linking to the respective online survey were attached to 56 charging stations in Munich and its surroundings. The truck survey was sent to professional truck drivers known to the Chair of Automotive Technology of the Technical University of Munich. The data repository available contains three data file types, all in CSV format:<ol><li>The surveys' complete results are provided in both German (original) and English (translated) language (bev_survey_ger.csv, bev_survey_eng.csv, truck_survey_ger.csv, truck_survey_eng.csv).</li><li>Question encodings are given by bev_question_encoding.csv and truck_question_encoding.csv. These encoding files contain the original question texts, their English translations, the corresponding column name mapping to column names in the survey data CSV, and the data type per question.</li><li>bev_response_translation.csv and truck_response_translation.csv comprise all original response options and their English translations.</li></ol>Additionally, we provide two Python files for an easy import of the data sets. The data was collected from December 2022 to February 2023.

opengpl-3.0-or-laterOct 2023View details →

zenodo44/100

National Open Access Monitor Survey: Organisational Identity: Responses Dataset

This dataset contains the response data from the 'National Open Access Monitor Survey: Organisational Identity which was carried out between 9th October and 9th November 2023 under the National Open Access Monitor Project: <a href="https://zenodo.org/doi/10.5281/zenodo.8420404">https://zenodo.org/doi/10.5281/zenodo.8420404</a>This survey was run to:<ul><li>compile a complete list of Irish research performing organisations (RPO) and research funding organisations (RFO) to be represented by the National Open Access Monitor.</li><li>ensure each organisation/entity is categorised correctly as an RPO or an RFO (or both), as applicable.</li><li>identify if an organisation/entity is publicly funded.</li><li>identify formally affiliated organisations/entities where all research outputs of one organisation/entity should also be included in the research outputs of another organisation/entity.</li><li>capture the persistent identifiers for RPOs, RFOs and publishers, to enable identification of relevant research outputs for the National Open Access Monitor.</li></ul>To note: <ul><li>Respondents' email addresses have been redacted.</li><li>Responses have been pseudonymised to the level of stakeholder-group e.g. Contributor A, Research Funding Organisation A, where requested by the participant in the participant consent form: <a href="https://doi.org/10.5281/zenodo.7589770">https://doi.org/10.5281/zenodo.7589770</a>.</li><li>Respondents were notified of the limits of pseudonymisation for this survey. Due to the nature and purpose of this survey on Organisational Identity, the identity of the organisation/entity could not be pseudonymised. Participants were advised only to participate if they were happy to do so under these conditions.</li><li>Survey responses were deleted by request of certain respondents. These responses are not included in these files.</li><li>Survey respondents were enabled to update their submissions. These changes are captured in the NationalOpenAccessMonitorSurvey.OrganisationalIdentity.MasterChangeFile.</li></ul>There are four files within in this dataset:- Results.NationalOpenAccessMonitorSurvey.OrganisationalIdentity.README - this PDF details the changes made to the raw data, as specified in the bullet points above and a description of the files within the dataset.- Results.NationalOpenAccessMonitorSurvey.OrganisationalIdentity.Pseudonymised.101123 - this is the original raw data, in csv format, as downloaded from the Online Surveys platform and subsequently pseudonymised and redacted.- NationalOpenAccessMonitorSurvey.OrganisationalIdentity.MasterChangeFile.101123 - this is a change file, in csv format, which documents the changes which participants requested to be made to their submissions after they were received.- Results.NationalOpenAccessMonitorSurvey.OrganisationalIdentity.Pseudonymised.Updated.101123 -  this is the original raw data, pseudonymised and redacted, with the requested changes implemented.Notes for data use:<ul><li>The "affiliated organisations/entities" section of the survey was insufficiently described in the survey text. One-to-one follow-up and support was provided to clarify to respondents that questions 12 and 13 of the survey intended to identify where all research outputs of one organisation/entity should appear on that organisation's/entities' own RPO or RFO dashboard within the National Open Access Monitor, and also on the dashboard of another organisation/entity.  </li><li>Survey respondents were notified in the introduction section to the "affiliated organisations/entities" section that "only where all entities agree there is a formal relationship in place that should be reflected in the Monitor will the link be implemented". Therefore, for the National Open Access Monitor project, only where both parties have asserted that all research outputs of one organisation/entity should also appear on the dashboard of another organisation/entity, will it be considered validated and implemented. </li><li>The geographic scope of the National Open Access Monitor Project is the Republic of Ireland. Where respondent's RPO or RFO organisations/entities are based outside the Republic of Ireland, or where respondents stated affiliations with overseas organisations/entities, they will not be actioned or implemented. To note: the survey invited responses from international publishers to enable filtering functionality by publisher within the National Open Access Monitor, these responses are not out of scope.  </li></ul>-----------------------The context for the survey is detailed in the National Open Access Monitor Project Plan: <a href="https://doi.org/10.5281/zenodo.7331431">https://doi.org/10.5281/zenodo.7331431</a>, the National Open Access Monitor Advisory Group Meeting Minutes, 18th September 2023: <a href="https://zenodo.org/doi/10.5281/zenodo.8405472">https://zenodo.org/doi/10.5281/zenodo.8405472</a> and the Developing the National Open Access Monitor, Ireland: Stakeholder Webinar, 22nd September 2023: <a href="https://zenodo.org/doi/10.5281/zenodo.8370578">https://zenodo.org/doi/10.5281/zenodo.8370578.</a>This project is managed by <a href="http://www.irel.ie/">IReL </a>and has received funding from Ireland's National Open Research Forum under the NORF Open Research Fund. <a href="https://norf.ie/funding/">https://norf.ie/funding/ </a><a href="https://norf.ie/orf-projects-announcement/">https://norf.ie/orf-projects-announcement/</a>

opencc-by-4.0Nov 2023View details →

zenodo44/100

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

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

opencc-by-4.0Nov 2023View details →

zenodo44/100

Data: "Using butterfly survey data to model habitat associations in urban developments", JEJ Cooper et al., (2023)

This data package has been used to examine the responses of UK butterfly species   to different features of the urban environment. 'JC_WCBSmodel.Rdata' presents the butterfly abundance data, and supporting information about   species and sites. This data can be fed through the script '04_model_builder.R', to   produce the models reported in the research article. '00_functions.R' is a script   containing functions which support the modelling process, which is loaded as part of   the 04_model_builder script.     Summaries of the resulting models are an output of that script -   'Butterfly_GAM_Outputs.xlsx'. These are represented graphically in the manuscript,   using scripts '06_01_Map'.R:'06_03_Cross_Validation'. '06_04_Model_Metric.R'   is a further summary of the .xlsx file, found in the Supplementary Materials.   '06_05_graphic_4_twitter.R' produces a condensed version of the figure resulting   from the script '06_02_Metric_Summary.R'   Dataset descriptions are found in the attached readme.txt ........................................................................................ We would also greatly appreciate if you could fill out <a href="https://forms.gle/DCc58VXpdmqnTmTk8" target="_blank" rel="noopener">this very short form</a> to tell us how you intend to use these data. Thanks in advance!

opencc-by-4.0Oct 2023View details →

ScienceDex guides

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

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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

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Archaeological Survey of India Collections: Burma Circle, 1916-22. Photo 1004/4 : 1916-22 (.jpg format)

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Cleaned spawner survey data

PARESv3 : PArish REgistry Survey − Historical Census Table Dataset (19th, 20th centuries) − France

CBS - Charging Behavior Survey

National Open Access Monitor Survey: Organisational Identity: Responses Dataset

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

Data: "Using butterfly survey data to model habitat associations in urban developments", JEJ Cooper et al., (2023)

Understand access before you commit

Allen Brain Atlas

Annotated Behaviour and Observability Dataset (ABODe)

DANDI Archive for NWB datasets

International Brain Laboratory public data

OpenNeuro

Your academic CV and NIH biosketch