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8,537 results for “OpenITI”
Open database on distributional information on European pollinators
<p>(abstract) This dataset was produced in the framework of the work package 1 (task 1) of the Horizon EU project Safeguard. We aimed to mobilise EU experts and data to compile and make available distributional data for bees, butterflies, moths and hoverflies. This will allow us to assess the magnitude, scale and extent of status and trends in pollinator distributions, diversity, abundance, communities and plant-pollinator networks.</p> <p>(method) Regarding distribution data for bees, UMons have been in contact with 23 bee taxonomists, 52 national champions and 5 museums. To date, we collected 52 bio-geographical databases of European bees from both restricted (i.e. databases shared under ad hoc agreement) and public (i.e. openly accessible databases) sources. Regarding distributional data for hoverflies, the starting point was the recently published in the IUCN Red List of hoverflies. To expand the number of species with precise distributional data on syrphid flies, UNSPMF further contacted taxonomists working with this species group : Gunilla Stahls from Finland; Jeroen van Steenis, Wouter van Steenis and Gerard Pennards from Netherlands; Grigory Popov from Ukraine; Santos Rojo from Spain; Axel Ssymank from Germany; Libor Mazanek from Czech Republic; Daniele Sommaggio from Italy. They provided additional data and conducted validation of the existing data, but also engaged additional experts who provided the data. For the butterflies and the moth, the data was collected by UFZ and come from an original initiative of the scientific expert on those two groups. As the publication of the row data of some databases (e.g. bees from The Netherlands) required the clustering of the spatial records to geographic grid squares (e.g. 10x10 km²), we simplified all the records in the present dataset.</p> <p>(dataset) We consider as a data, a record that includes the following information: the name of the species, the coordinates where the species was collected. Additional information were collected (e.g. collector, determinator, number of the individuals collected, sex, data owner and reference code) but were not displayed in the present dataset. The aggregation of bee databases include 4,837,731 row data for bees, 680,641 row data for hoverflies, 1,209,320 row data for butterflies and 6,862,835 row data for moths.</p>
Recordings Q&A and matchmaking sessions for call for proposals 'Open Science Infrastructure'
<p>On Thursday, July 11, and Tuesday, July 16, 2024, Open Science NL organised two online Q&A sessions combined with a matchmaking opportunity for the Open Science NL call 'Open Science Infrastructure'.</p> <p>These are the two recordings of the two Q&A sessions. The Open Science NL team has drafted a Frequently Asked Questions document addressing all the questions that came up during the meetings. This is added as a seperate text-file (PDF). The slides presented during both meetings are shared as well as a PDF.</p> <p>For more information about the call and how to apply, please go to: <a href="https://www.openscience.nl/en/calls/open-science-infrastructure" target="_blank" rel="noopener">https://www.openscience.nl/en/calls/open-science-infrastructure</a></p>
Mapping between zbMATH Open identifiers, DOIs, ORCIDs and arXiv identifiers
<p>The second version of the mapping between zbMATH Open identifiers for <a href="https://www.wikidata.org/w/index.php?title=Property:P1556&oldid=1755821772">authors</a> and <a href="https://www.wikidata.org/w/index.php?title=Property:P894&oldid=1766254659">documents</a> and <a href="https://www.wikidata.org/wiki/Property:P356">DOIs</a> and <a href="https://www.wikidata.org/wiki/Property:P496">ORCIDs</a> in CSV format.</p> <ul> <li>The file authors.csv contains the mapping between zbMATH Open author id and ORCIDs for 38 159 authors.</li> <li>The file documents.csv contains the mapping between zbMATH Open document id and DOI for 2 813 563 documents.</li> </ul> <p>Beginning from this version, we also provide the mapping between <a href="https://www.wikidata.org/w/index.php?title=Property:P894&oldid=1766254659">documents</a> and <a href="https://www.wikidata.org/w/index.php?title=Property:P818&oldid=2151126552">arXiv</a> in CSV format</p> <ul> <li>The file arxiv.csv contains the mapping between zbMATH Open document id and arXiv identifiers for 528 640 documents.</li> </ul> <p>See https://zbmath.org/about/ (section Full Text Links) for a live version of this dataset. That version is more current but less reproducible. Moreover, the dataset here is restricted to documents with a permanent zbMATH Open identifier in the form <code>Zbl d+.d+</code>.</p> <p> </p> <p> </p>
Interviews with editors of library science journals on transitioning to open access
<p>These three files are related to qualitative, semi-structured interviews conducted in Fall 2023 with editors of Library and Information Science (LIS) journals on transitioning to open access. One subgroup consisted of participants who were editors at the time of an LIS journal when it transitioned (or flipped) to an open access model that does not charge a fee to either readers or authors (which this study refers to as equitable open access), and the other subgroup consisted of current editors (at the time) of LIS journals that have not yet transitioned (or unflipped) to an equitable open access model. Two of the files are the interview protocols for each group of flipped and unflipped editors, and the third file is the codebook the researchers used to analyze the interview transcripts. Interview transcripts are not being publicly shared to ensure confidentiality for interview participants.</p> <p>The interview protocols were created based on the findings of a prior research study:</p> <p>Borchardt, R., Dawson, D., & Schultz, T. (2024). Financial and other perceived barriers to transitioning to an equitable no-publishing fee open access model: A survey of LIS journal editors. College & Research Libraries, 85(1). <a href="https://doi.org/10.5860/crl.85.1.96">https://doi.org/10.5860/crl.85.1.96</a></p> <p>The codebook was created iteratively based on the researchers' review and analysis of the interview transcripts.</p>
Data and Statistical analysis for: "Predator in the pool? A quantitative evaluation of non-indexed open access journals in aquaculture research"
<p>Data and Statistical analysis for: "Predator in the pool? A quantitative evaluation of non-indexed open access journals in aquaculture research" published in <em>Frontiers in Marine Science</em></p>
Open Access levels of Dutch universities' output 2016-2017 (articles & reviews): green, gold, hybrid and bronze - May 2018
<p>Using Web of Science and Unpaywall data, we here provide an update of Open Access (OA) levels of Dutch universities, for 2016 and 2017.</p> <p>Our previous analysis (<a href="http://doi.org/10.5281/zenodo.1133759">10.5281/zenodo.1133759</a> and <a href="http://doi.org/10.7287/peerj.preprints.3520v1">10.7287/peerj.preprints.3520v1</a>) looked at OA classification as included in Web of Science (gold and green OA, based on Unpaywall data), and supplemented that with a breakdown of gold OA into pure gold, hybrid and bronze, taken from Unpaywall data (formerly OADOI) directly. Here, we improve on this by running all DOIs retrieved from WoS through Unpaywall data (using their web interface that allows batch checking of up to 10,000 DOIs at a time). Unlike WoS, Unpaywall data itself includes author-submitted versions in their green OA classification, resulting in more complete green OA levels. </p> <p>In addition, since our initial analysis of December 2017, Unpaywall data has considerably expanded its coverage of institutional repositories (IRs) (see <a href="https://unpaywall.org/sources">https://unpaywall.org/sources</a>). This now includes coverage of the IRs from all Dutch universities. </p> <p>Taken together, the current data show higher levels of green open access, including author-submitted versions, compared to our previous analysis. </p> <p>In this update, we include output (articles and reviews) from 2016 and 2017 for all 14 universities in the Netherlands. </p> <p>The following categories are distinguished (description taken from Piwowar at al., 2018, doi: <a href="https://doi.org/10.7717/peerj.4375">10.7717/peerj.4375</a>)</p> <ul> <li><strong>Pure gold</strong>: Published in an open-access journal (as defined by the DOAJ)</li> <li><strong>Hybrid</strong>: Free under an open license in a toll-access journal</li> <li><strong>Bronze</strong>: Free to read on the publisher page, but without a license</li> <li><strong>Green: </strong>Available from an institutional or disciplinary repository (including PubMedCentral)</li> </ul> <p>Data for Dutch universities were collected from Web of Science using the organization-enhanced field. Only articles and reviews were included. DOIs were extracted from the Web of Science export, run through the Unpaywall data <a href="https://unpaywall.org/products/simple-query-tool">Simple Query Tool</a>. From the resulting data from Unpaywall, OA classification was done using a simple formula in Excel (to be replaced by an R script in a future update). The Excel template used is included in this dataset, as is the OADOI API output for each Dutch university's article subset, and the lists of DOIs derived from Web of Science. The dataset also includes summarized data and three charts generated from these data, showing levels of different types of OA for 2016, 2017 and the two years compared. </p> <p>----------------------------------------------------------------------------------------------------------------------------------------------------------------------------</p>
Method Classification of Open Access INTACT Molecular Interaction data.
<p>Simple classification data derived from open access papers indexed in the INTACT database (https://www.ebi.ac.uk/intact/downloads) based on PSI-MI25 codes for interaction detection methods or participant detection methods based on the subfigure caption text. <br> <br> intact_records_and_captions_complete.tsv - This file links available text of subfigure captions to PSI-MI25 codes for the interaction detection method and participant detection method. </p> <p>evidx_run_file.txt - This file provides execution codes for the 'EvidX' machine learning text classifier (https://github.com/SciKnowEngine/evidX/releases/tag/v0.1.0)</p> <p> </p> <p> </p> <p> </p>
Resource Metadata Harvested from Government and Research Open Data Portals
<p>This dataset consists of resource metadata harvested from the APIs of hundreds of government and research data portals from all over the world. This dataset was harvested between the 13<sup>th</sup> and 15<sup>th</sup> of September 2018. The metadata harvested from these portals was translated to a single metadata format (see <em>metadata_format.odt</em>). An overview of all harvested domains is given in <em>portal_list.txt</em>.</p> <p>The harvested data is divided into five gzipped json-lines files, based on the ‘type’ of the resource that is derived from the data of the APIs:</p> <ul> <li><em>dataset_metadata.jsonl.gz</em>: Resources classified as a Dataset, or subsets of dataset (e.g. Dataset:Image and Dataset:Audio) [6 246 250 resources]</li> <li><em>document_metadata.jsonl.gz</em>: Resources classified as a Document, or subset of document (e.g. Document:Paper:Conference and Document:Book) [15 626 541 resources]</li> <li><em>software_metadata.jsonl.gz</em>: Resources classified as Sofware (including Software:Model) [42 036 resources]</li> <li><em>service_metadata.jsonl.gz</em>: Resources classified as a service (e.g. WMS, APIs) [1257 resources]</li> <li><em>other_metadata.jsonl.gz</em>: Resources of which the ‘type’ could not be determined from the data the API returned. This set still contains many datasets [1 502 979 resources]</li> </ul>
Dataset: An Open-hardware Platform for MPSoC Thermal Modeling
<p>This repository contains the experimental data for the paper</p> <p>"An Open-hardware Platform for MPSoC Thermal Modeling"</p> <p>published at 2019 samos conference</p> <p>http://samos-conference.com</p> <p>The data is released under a CC-BY Creative Commons license.<br> If you use this dataset, cite the following paper:<br> Federico Terraneo, Alberto Leva, William Fornaciari, "An Open-hardware Platform for MPSoC Thermal Modeling", 2019 IEEE International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation (SAMOS)</p>
Zambezi dataset to "WHAT-IF: an open-source decision support tool for water infrastructure investment planning within the Water-Energy-Food-Climate Nexus"
<p>This is the dataset used in the HESS publication "<a href="https://www.hydrol-earth-syst-sci-discuss.net/hess-2019-167/">WHAT-IF: an open-source decision support tool for water infrastructure investment planning within the Water-Energy-Food-Climate Nexus</a>"</p> <p>The dataset describes the water-energy-food nexus of the Zambezi River Basin used as input to the <a href="https://github.com/RaphaelPB/WHAT-IF">WHAT-IF model</a>.</p> <p>The file Data_Organization.pdf, summarizes the available data. For more info look at the <a href="https://www.hydrol-earth-syst-sci-discuss.net/hess-2019-167/">publication</a> and/or <a href="https://github.com/RaphaelPB/WHAT-IF">Github</a>.</p>
Toolkit on Open Access for Research Project Coordinators
<p>The materials in this toolkit were created by Romain Féret as a resource for training on how to help project coordinators to comply with their open access requirements. The slides of the training are available on Zenodo at 10.5281/zenodo.3381783. This training day took place on Wednesday the 5th of June 2019, at the University of Lille. It was organized with the support of Couperin as a part of its activities in the project OpenAIRE-Advanced.</p> <p>The tutorials are divided into two folders. The ‘Coordinator’ folder contains documents that can be sent directly to the researchers, while the ‘Support staff’ folder contains tutorials for support staff (librarians, project managers) who help the coordinators to manage their project. Each tutorial is in .pdf and .docx format for easy reuse and modification. Each document is available in French and in English.</p>
Supplementary material to the manuscript: Regionalised Heat Demand and Power-To-Heat Capacities in Germany - An Open Data Set for Assessing Renewable Energy Integration
<p>This is the supplementary material for the manuscript:</p> <p>"Regionalised Heat Demand and Power-To-Heat Capacities in Germany - an Open Data Set for Assessing Renewable Energy Integration"</p> <p>Article DOI: <a href="https://doi.org/10.1016/j.apenergy.2019.114161">https://doi.org/10.1016/j.apenergy.2019.114161</a></p> <p>Open access preprint: <a href="https://arxiv.org/abs/1912.03763">https://arxiv.org/abs/1912.03763</a></p> <p> </p> <p><strong>DESCRIPTION OF THE DATASET AND LICENSES:</strong></p> <p>The subdirectory "04_results" contains the regionalised heat demand an power-to-heat capacity data on administrative district level (NUTS-3) for Germany. The subdirectories "01_census_special_evaluation_data" and "02_other_input_data" contain the utilised input data. The subdirectory "03_code" contains the developed and applied source code.</p> <p>The data in this repository are provided under open source licenses. For license information and other general information on the supplementary material, refer to the LICENSE files and README files in the respective subdirectories.</p> <p>For a detailed description of the approach developed by the author, the input data used and the generated results, refer to the manuscript "Regionalised Heat Demand and Power-To-Heat Capacities in Germany - an Open Data Set for Assessing Renewable Energy Integration".</p> <p><strong>METADATA:</strong></p> <p>Sector: Residential Buildings – Space Heating and Domestic Hot Water</p> <p>Geographical scope: Germany</p> <p>Geographical resolution: Administrative districts (NUTS-3)</p> <p>Temporal scope: 2011, three scenarios for 2030</p> <p>Temporal resolution: 15min</p> <p> </p> <p><strong>UNITS:</strong></p> <p>In the final results folders (04_results/01_installed_heating_p2h_capacity; 04_results/02_daily_time_series; 04_results/03_yearly_time_series) the units of the data are indicated in the file names or the column names, e.g. by "in_MW". In case of unit indication in the file name, the unit refers to all columns in the file.</p> <p>In the intermediate results folder (04_results/00_sql_tables_exported_to_csv) all units referring to power are "kW" and all units referring to energy are "kWh".</p> <p><strong>NEWS AND CONTACT:</strong></p> <p>This dataset will be used as part of the <a href="https://wiki.openmod-initiative.org/wiki/Region4FLEX">region4FLEX model</a>. We are currently enhancing the data by temporally and spatially resolved COP time series and determining load shifting potentials. If you wish to receive news or have general questions please contact: wilko.heitkoetter@dlr.de. </p>
Citations to software and data in Zenodo via open sources
<p>In January 2019, the Asclepias Broker harvested citation links to Zenodo objects from three discovery systems: the NASA Astrophysics Datasystem (ADS), Crossref Event Data and Europe PMC. Each row of our dataset represents one unique link between a citing publication and a Zenodo DOI. Both endpoints are described by basic metadata. The second dataset contains usage metrics for every cited Zenodo DOI of our data sample. </p> <p> </p>
Data and Code open availability for the FRETsael paper
<p>This dataset includes the raw files of the measurements of Actin-Myosin interactions in SH-SY5Y cells, as well as the Matlab code for the simulations and analyses used in the paper about FRETsael: "<strong>FRET-sensitized acceptor emission localization (FRETsael) – nanometer localization of biomolecular interactions using fluorescence lifetime imaging</strong>"</p>
Evaluating Open Science Practices in Indoor Positioning and Indoor Navigation Research (Supplementary Material: Full Paper Listing and Analysis)
<p>Supplementary material of the paper:</p> <p>Title: "Evaluating Open Science Practices in Indoor Positioning and Indoor Navigation Research"<br>Subtitle: "A Survey of the IPIN's Reference Papers of 2022 and 2023 Editions"</p> <p>The paper is accepted to the "14th International Conference on Indoor Positioning and Indoor Navigation, IPIN 2024, Hong Kong, October 14-17, 2024, IEEE, 2024.</p> <p>An Author's accepted version of the manuscript is available here: <a href="../records/13684170" target="_blank" rel="noopener">https://zenodo.org/records/13684170</a> </p> <p>If you want to refer to this work, please cite this Zenodo entry as well as the published conference version.</p> <p> </p> <p>---------------------------------------</p> <p>This entry contains two files:</p> <ul> <li>"Paper Characterization Spreadsheet.xlsx": <strong>The spreadsheet of the full analysis of this work</strong>, as described in the paper. It characterizes various features of the analyzed papers and forms the raw data on which the analyses of our work were based.</li> <li>"Main features of the manuscripts analysed in Zenodo Record #12088175.pdf": A document summarizing the main features of the IPIN's Reference Papers of the 2022 and 2023 Editions, that contain some form of open resources (Open Data, Code, or Material).</li> </ul> <p> </p> <p> </p> <p> </p>
La piattaforma di riviste Open Access dell'Università degli Studi di Milano. [Video]
<p>L’intervento percorre i passi fondamentali della creazione della piattaforma di riviste open access dell’Università degli Studi di Milano, come modello in cui una istituzione che produce conoscenza decide di assumersi la responsabilità di validare e diffondere questa conoscenza ad un pubblico che sia il più ampio possibile, liberandosi da scelte e vincoli imposti dagli editori commerciali e dalle logiche editoriali e riportando nelle mani dei ricercatori le attività che da tempo erano state consegnate agli editori.</p>
Open and Lite Techno-economic Dataset for Long-term Energy Systems Modelling in the Republic of South Africa
<p>An open-source lite techno-economic dataset for long term energy systems modelling in the Republic of South Africa. Includes data on electricity generation and demand, electricity imports and exports, power transmission and distribution, residual capacity, capacity factor, operational lifetime, and fixed, variable and capital costs of electricity generation technologies. It also contains estimates for renewable potential and fossil fuel reserves in South Africa.</p>
The International Transport Energy Modeling (iTEM) Open Data & Harmonized Transport Database
<p>This dataset and documentation contains detailed information of the iTEM Open Database, a harmonized transport data set of historical values, 1970 - present. It aims to create transparency through two key features:</p> <ul> <li>Open-Data: Assembling a comprehensive collection of publicly-available transportation data</li> <li>Open-Code: All code and documentation will be publicly accessible and open for modification and extension. <a href="https://github.com/transportenergy">https://github.com/transportenergy</a></li> </ul> <p>The iTEM Open Database is comprised of individual datasets collected from public sources. Each dataset is downloaded, cleaned, and harmonised to the common region and technology definitions defined by the iTEM consortium https://transportenergy.org. For each dataset, we describe the name of the dataset, the web link to the original source, the web link to the cleaning script (in python), variables, and explain the data cleaning steps (which explains the data cleaning script in plain English).</p> <p>Shall you find any problems with the dataset, please report the issues here <a href="https://github.com/transportenergy/database/issues">https://github.com/transportenergy/database/issues</a>. </p> <p> </p>
Monitoring and evaluation of UKRI's Open Access Policy: Exploring the use of open data sources to inform baseline values - Dataset
<p>This dataset accompanies the report <em>"Monitoring and evaluation of UKRI's Open Access Policy: Exploring the use of open data sources to inform baseline values"</em>, which is available via Zenodo.<br><br>It provides record-level data of UKRI-funded and UK-affiliated research output (limited to journal articles with Crossref DOIs) published between 2012 and 2022 - including bibliographic metadata as well as data on open access availability, publisher, national and international collaborations, citations, views and downloads, altmetrics and subjects (fields). All variables are documented in the data dictionary included in this Zenodo record.</p> <p>The code used to generate the dataset from open data sources is available on GitHub. </p> <p>The following data sources were used:</p> <ul> <li> <p>Gateway to Research (records downloaded between 2023-11-05 and 2023-11-13)</p> </li> <li> <p>Crossref (Metadata Plus snaphot 2023-10-31, Crossref member route API 2024-01-23)</p> </li> <li> <p>OpenAlex (data snapshot 2023-10-18)</p> </li> <li> <p>Unpaywall (data snapshot 2023-11-27)</p> </li> <li> <p>IRUS UK (2024-04-03)</p> </li> <li> <p>Crossref Event Data (2023-04-01)</p> </li> </ul> <p><strong></strong><br><br>The project made use of Curtin Open Knowledge Initiative (COKI) infrastructure, which is documented on GitHub: <a href="https://github.com/The-Academic-Observatory">https://github.com/The-Academic-Observatory</a>. </p>
Secondary Data from Insights from Publishing Open Data in Industry-Academia Collaboration
<h1>Secondary Data from Insights from Publishing Open Data in Industry-Academia Collaboration</h1> <h2>Authors</h2> <p>Per Erik Strandberg [1], Philipp Peterseil [2], Julian Karoliny [3], Johanna Kallio [4], and Johannes Peltola [4].</p> <p>[1] Westermo Network Technologies AB (Sweden).<br>[2] Johannes Kepler University Linz (Austria)<br>[3] Silicon Austria Labs GmbH (Austria).<br>[4] VTT Technical Research Centre of Finland Ltd. (Finland).</p> <h2>Description</h2> <p>This data is to accompany a paper submitted to Elsevier's data in brief in 2024, with the title <em>Insights from Publishing Open Data in Industry-Academia Collaboration</em>.</p> <p><em>Tentative Abstract:</em> Effective data management and sharing are critical success factors in industry-academia collaboration. This paper explores the motivations and lessons learned from publishing open data sets in such collaborations. Through a survey of participants in a European research project that published 13 data sets, and an analysis of metadata from almost 281 thousand datasets in Zenodo, we collected qualitative and quantitative results on motivations, achievements, research questions, licences and file types. Through inductive reasoning and statistical analysis we found that planning the data collection is essential, and that only few datasets (2.4%) had accompanying scripts for improved reuse. We also found that authors are not well aware of the importance of licences or which licence to choose. Finally, we found that data with a synthetic origin, collected with simulations and potentially mixed with real measurements, can be very meaningful, as predicted by Gartner and illustrated by many datasets collected in our research project.</p> <h2>Secondary data from Survey</h2> <p>The file <code>survey.txt</code> contains secondary data from a survey of participants that published open data sets in the 3-year European research project InSecTT.</p> <h2>Secondary data from Zenodo</h2> <p>The file <code>secondary_data_zenodo.json</code> contains secondary data from an analysis of data sets published in Zenodo. It is accompanied with a <code>py</code>-file and a <code>ipynb</code>-file to serve as examples.</p> <h2>License</h2> <p>This data is licenced with the Creative Commons Attribution 4.0 International license. You are free to use the data if you attribute the authors. Read the license text for details.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.