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8,537 results for “Openness”
REACH Incubator - open-call #2 Awarded SME dataset
<p>This file contain public dataset describing the awarded SME during the 2nd round of the REACH Incubator project.</p>
An Overview of Compact Star Populations and Some of Its Open Problems
<p>This repository contains the orbital parameters (where applicable) and calculated<br> masses of the 35 Galactic black holes collected in Tables 2 and 3 of the paper:<br> 'An Overview of Compact Star Populations and Some of Its Open Problems'<br> by L. M. de Sá, A. Bernardo, R. R. A. Bachega, L. S. Rocha, P. H. R. S. Moraes<br> and J. E. Horvath, Galaxies (2023) 11(1), 9</p>
The benefit of augmenting open data with clinical data-warehouse EHR for forecasting SARS-CoV-2 hospitalizations in Bordeaux area, France
<p><strong>Objective</strong></p> <p>The aim of this study was to develop an accurate regional forecast algorithm to predict the number of hospitalized patients and to assess the benefit of the Electronic Health Records (EHR) information to perform those predictions. Materials and Methods Aggregated data from SARS-CoV-2 and weather public database and data warehouse of the Bordeaux hospital were extracted from May 16, 2020, to January 17, 2022. The outcomes were the number of hospitalized patients in the Bordeaux Hospital at 7 and 14 days. We compared the performance of different data sources, feature engineering, and machine learning models.</p> <p><strong>Results </strong></p> <p>During the period of 88 weeks, 2561 hospitalizations due to COVID-19 were recorded at the Bordeaux Hospital. The model achieving the best performance was an elastic-net penalized linear regression using all available data with a median relative error at 7 and 14 days of 0.136 [0.063; 0.223] and 0.198 [0.105; 0.302] hospitalizations, respectively. Electronic health records (EHRs) from the hospital data warehouse improved median relative error at 7 and 14 days by 10.9% and 19.8%, respectively. Graphical evaluation showed remaining forecast error was mainly due to delay in slope shift detection.</p> <p><strong>Discussion </strong></p> <p>Forecast models showed overall good performance both at 7 and 14 days which was improved by the addition of the data from Bordeaux Hospital data warehouse.</p> <p><strong>Conclusions </strong></p> <p>The development of hospital data warehouses might help to get more specific and faster information than traditional surveillance systems, which in turn will help to improve epidemic forecasting at a larger and finer scale.</p>
Open-source design files for harvesting energy from overhead power line cables
<p>OpenSource_CalculationFile_MEH.xlsx : this is an excel file that provides a calculation tool to select a magnetic core for harvesting energy from powerlines.</p> <p>OpenSource_Schematic_MEH.pdf : this is a schematic file that provides a detailed design of the charging circuit.</p>
A phenotyping weeds image dataset for open scientific research
<p>This in-house-built image dataset consists of 10810 weed images captured through a dedicated phenotyping activity in quasi-field conditions. The targets are seven of the most widespread and hard-to-control weeds in wheat (but also in other winter cereals) in the Mediterranean environment.</p> <p>In the framework of open scientific research, our aim is to share low-cost and high-resolution images representing challenging agricultural environments where weather, lighting and other factors can change by the hour and affect the quality of images. This way the dataset could be used to train Artificial Intelligence architectures designed for weed recognition, allowing the implementation of tools directly available in the field for farmers and technicians for effective and timely weed management.</p> <p>The dataset encompasses weed images ranging from the post-emergence phase (i.e. the complete cotyledons unfolding) until the pre-flowering stage. The weed selection was made by considering (i) bottom-up information and specific requests by farmers and technicians, (ii) weed susceptibility to commercial formulations for chemical control <50%, reported at least twice by field technicians, (iii) the difficulty of control considering any methods, and (iv) the type of growing season (overlapping or not with wheat). The final weeds selection encompassed both monocots (<em>Avena sterilis</em> and <em>Lolium multiflorum</em>) and dicots (<em>Convolvulus arvensis</em>, <em>Fumaria officinalis</em>, <em>Papaver rhoeas</em>, <em>Veronica persica</em> and <em>Vicia sativa</em>).</p> <p>Image acquisition was facilitated by using a white panel as a background; this helped to (i) spread the light and thereby make the plants well-illuminated, while still avoiding strong shadows when using the flash and (ii) simplify image processing. The images were acquired with a Canon EOS 700D hand-held camera set in the macro mode with aperture, shutter speed, ISO and flash in auto mode. Photo capture timing, target distances and light conditions did not have a fixed pattern but were deliberately programmed to vary in such a way as to mimic field conditions. For image shooting at various times of the day, the only precaution was to frame the subject with homogeneous light conditions (full sunlight/full shade). The varied outdoor conditions (light, distance, timing) and camera type (RGB) with auto mode were essential features to make the images photos look similar to those that a user can take in a field, for example with a smartphone camera.</p> <p>After selection and categorization, images were cropped to select the region of interest following the 1:1 ratio but maintaining a minimum size of 512 x 512 pixels.</p> <p> </p> <p>More details on the dataset and its use for weed recognition tasks will be soon available in the proceedings of the forthcoming ECPA conference (2-6 July 2023, Bologna, Italy).</p>
Figure 12. The same mouth-opening characterizes all vertebrates except for adult lampreys. A, a in REVIEW Vertebrate origins are informed by larval lampreys (ammocoetes): a response to Miyashita et al., 2021
Figure 12. The same mouth-opening characterizes all vertebrates except for adult lampreys. A, a tunicate, is included as representing the closest relative of vertebrates, with the same mouth structures. Adult lampreys (C) do not have the typical, primary opening, but a secondary one in the oral funnel formed by their protrusive upper lips. The ammocoete lamprey (B) does not have a secondary mouth-opening, so the dashed blue line in (B) just shows the boundary corresponding to the adult lamprey's. Anaspids (E) are reconstructed with a primary mouth, despite the superficial similarity of their snout to that of adult lamprey; the anaspid snout does not project far enough forward (only three eye-diameters forward as opposed to five for the lamprey in Fig. 11J). Hagfish (D) also differ from adult lampreys in having the primary mouth-opening. In osteostracans (G) and galeaspids (H), the lips have not grown forward to form a secondary mouth, but have simply lain on the ground. I call their mouth openings 'pseudo-secondary.' Most of the pictures are retooled from Figures 10 and 11, but three are new: (A) is redrawn from Mallatt (2009), (E1) from Janvier (1996) and (E2) from Sansom et al. (2010).
WorldCereal open global harmonized reference data repository (CC-BY-SA licensed data sets)
<p>Within the<strong> ESA funded</strong> WorldCereal project we have built an open harmonized reference data repository at global extent for model training or product validation in support of land cover and crop type mapping. Data from 2017 onwards were collected from many different sources and then harmonized, annotated and evaluated. These steps are explained in the harmonization protocol (10.5281/zenodo.7584463). This protocol also clarifies the naming convention of the shape files and the WorldCereal attributes (LC, CT, IRR, valtime and sampleID) that were added to the original data sets.</p> <p>This publication includes those harmonized data sets of which the original data set was published under the CC-BY-SA license or a license similar to CC-BY-SA. See document "_In-situ-data-World-Cereal - license - CC-BY-SA.pdf" for an overview of the original data sets.</p>
WorldCereal open global harmonized reference data repository (CC-BY licensed data sets)
<p>Within the <strong>ESA funded </strong>WorldCereal project we have built an open harmonized reference data repository at global extent for model training or product validation in support of land cover and crop type mapping. Data from 2017 onwards were collected from many different sources and then harmonized, annotated and evaluated. These steps are explained in the harmonization protocol (10.5281/zenodo.7584463). This protocol also clarifies the naming convention of the shape files and the WorldCereal attributes (LC, CT, IRR, valtime and sampleID) that were added to the original data sets.</p> <p>This publication includes those harmonized data sets of which the original data set was published under the CC-BY license or a license similar to CC-BY. See document "_In-situ-data-World-Cereal - license - CC-BY.pdf" for an overview of the original data sets. </p>
Open MatSci ML Toolkit - DGL Graphs for OpenCatalyst IS2RE Task (OC20)
<p>Dataset accompanying the release of the <a href="https://github.com/IntelLabs/matsciml">Open MatSciML Toolkit</a>, an open source software for development graph neural networks on the OpenCatalyst project using the Deep Graph Library (DGL). </p> <p>For more details about the Open MatSci ML Toolkit, check the associated <a href="https://github.com/IntelLabs/matsciml">open-source repository</a> and <a href="https://arxiv.org/abs/2210.17484">paper</a>.</p> <p>Compressed files ~8GB with uncompressed file being ~80 GB.</p>
How can we find an open access scientific journal indexed in the Scopus database?
<p><a href="https://www.youtube.com/watch?v=fIcjrwFKdP4&t=33s">To find open access journals indexed by Scopus</a>, you can follow these steps: Go to the Scopus website (www.scopus.com) and click on the "Journals" tab. On the "Journals" page, select "Advanced Search." In the "Advanced Search" page, select "Open Access" under the "Source Type" filter. You can further narrow down your search by using additional filters such as subject area, publication type, and more. The search results will show a list of open access journals indexed by Scopus. <a href="https://www.youtube.com/hashtag/scopus">#Scopus</a> <a href="https://www.youtube.com/hashtag/openaccessjournals">#OpenAccessJournals</a> <a href="https://www.youtube.com/hashtag/scientificjournals">#ScientificJournals</a> <a href="https://www.youtube.com/hashtag/indexedjournals">#IndexedJournals</a> <a href="https://www.youtube.com/hashtag/searchingjournals">#SearchingJournals</a> <a href="https://www.youtube.com/hashtag/findingjournals">#FindingJournals</a> <a href="https://www.youtube.com/hashtag/scopusdatabase">#ScopusDatabase</a> <a href="https://www.youtube.com/hashtag/elsevierscopus">#ElsevierScopus</a> <a href="https://www.youtube.com/hashtag/openaccesspublishing">#OpenAccessPublishing</a> <a href="https://www.youtube.com/hashtag/researchpublishing">#ResearchPublishing</a> <a href="https://www.youtube.com/hashtag/journalsearch">#JournalSearch</a> <a href="https://www.youtube.com/hashtag/scholarlypublishing">#ScholarlyPublishing</a> <a href="https://www.youtube.com/hashtag/scientificpublishing">#ScientificPublishing</a> <a href="https://www.youtube.com/hashtag/journalselection">#JournalSelection</a> <a href="https://www.youtube.com/hashtag/researchcommunication">#ResearchCommunication</a></p> <p> </p>
Evaluation of Open Source Ventilators (OTRL & ODRL)
<ul> <li>applying the open readiness scales introduced in https://doi.org/10.1016/j.procir.2022.05.306 onto the whole dataset of PubInv's evaluation of open source ventilators for COVID-19 crisis response</li> <li>find here: <ul> <li>the evaluation (final scores) of the full dataset (incl. the unfiltered dataset and PubInv's evaluations)</li> <li>the log for all evaluations for details and as a rationale for each evaluation</li> </ul> </li> </ul>
Enrich4All-RoCOVID-Open
<p>The COVID corpus in Romanian collects Romanian documents about the COVID pandemics, about the COVID disease and its diverse aspects that it entails, including medical, sociological and logistical. It was intended to foster the development of an intelligent chatbot, answering Romanian questions about COVID, in the Enrich4All project. It contains two parts: one that can be released publicly (Enrich4All-RoCOVID-Open) and one that contains copyrighted material (Enrich4All-RoCOVID-Restricted).</p> <p>The archive contains a readme file and the publicly released documents: 82 (.txt, UTF-8) files together with their associated metadata files (.xml).</p> <p><strong>Example of a metadata file:</strong> </p> <p><em><Metadata><br> <DocumentTitle>Sinteză: Regimul carantinei și condițiile pentru intrarea în România</DocumentTitle><br> <PublicationDate>2020</PublicationDate><br> <SourceName>Code for Romania</SourceName><br> <SourceURL>https://covid19.stirioficiale.ro/sinteza-regimul-carantinei-si-conditiile-pentru-intrarea-in-romania</SourceURL><br> <DocumentTextStyle>Law</DocumentTextStyle><br> <DocumentTextDomain>covid19</DocumentTextDomain><br> <SubjectLanguage>Romanian</SubjectLanguage><br> <CollectionDate>2021</CollectionDate><br> <AccessRight>Open Access</AccessRight><br> <No_of_words>3073</No_of_words><br> </Metadata></em></p> <p><strong>When using our dataset, please cite the following paper</strong>:</p> <p>Ion, Radu, Andrei-Marius Avram, Vasile Păiş, Maria Mitrofan, Verginica Barbu Mititelu, Elena Irimia, and Valentin Badea. "An Open-Domain QA System for e-Governance." <em>arXiv preprint arXiv:2206.08046</em> (2022).</p> <p><strong>Person of contact</strong>: Radu Ion, radu@racai.ro</p>
PyPSA-Eur: An Open Optimisation Model of the European Transmission System (Dataset)
<p><strong>PyPSA-Eur</strong> is an open model dataset of the European power system at the transmission network level that covers the full ENTSO-E area. The software pipeline to assemble the model is developed at <a href="https://github.com/PyPSA/PyPSA-eur">https://github.com/PyPSA/PyPSA-eur</a> and documentation is available at <a href="http://pypsa-eur.readthedocs.io">pypsa-eur.readthedocs.io.</a></p> <p><strong>This repository provides pre-built PyPSA networks resulting from corresponding PyPSA-Eur Releases using the default configuration!</strong></p> <p>The model alternating current lines at and above 220 kV voltage level and all high voltage direct current lines, substations, an open database of conventional power plants, time series for electrical demand and variable renewable generator availability, and geographic potentials for the expansion of wind and solar power.</p> <p>It only includes freely available and open data. It provides a fully automated free software pipeline to assemble the load-flow-ready model from the original datasets, which enables easy configuration, replacement and<br> improvement of the individual parts.</p> <p>The model is suitable both for operational studies and generation and transmission expansion planning studies.</p> <p>Some basic validation is provided in a paper describing the dataset:</p> <ul> <li>Jonas Hörsch, Fabian Hofmann, David Schlachtberger, and Tom Brown. PyPSA-Eur: An open optimisation model of the European transmission system. Energy Strategy Reviews, 22:207-215, 2018. <a href="https://arxiv.org/abs/1806.01613">https://arxiv.org/abs/1806.01613</a>, <a href="http://https://doi.org/10.1016/j.esr.2018.08.012">https://doi.org/10.1016/j.esr.2018.08.012</a>.</li> </ul>
Forschungsdaten zur Masterarbeit: Open-Access-Publikationen in der Medien- und Kommunikationswissenschaft: Bestandsaufnahme
<p><strong>[ English below ] </strong><br> Der Datensatz enthält Daten aus der Masterarbeit an der Fachhochschule Potsdam aus dem Jahr 2023.</p> <p>Titel: Open-Access-Publikationen in der Medien- und Kommunikationswissenschaft: Bestandsaufnahme</p> <p><br> <strong>Forschungsfragen:</strong></p> <p>– Inwieweit wird der Bereich des goldenen Open Access für Medien- und Kommunikationswissenschaften durch Indexierungsdienste abgedeckt?</p> <p>– Wie hoch ist der Anteil der medien- und kommunikationswissenschaftlichen Veröffentlichungen der deutschen WissenschaftlerInnen, die derzeit als Open Access verfügbar sind?</p> <p>– Wie unterscheiden sich die Anteile von Open-Access-Publikationen hinsichtlich unterschiedlicher Erstveröffentlichungsjahre?</p> <p>– Wie stark ist der Bereich von Gold-Open-Access (GOA) seit 2013 gewachsen? Hat sich die Verteilung der Beachtung der goldenen Open Access bei den populären Indizes geändert?</p> <p>– Wie verbreitet ist die Verwendung von DOI in den deutschen Medien- und Kommunikationswissenschaften?</p> <p>– Wie geeignet sind DOI-basierte Dienste für die Evaluierung des Open-Access-Sektors in den Medien- und Kommunikationswissenschaften?</p> <p><strong>Beschreibung der Daten:</strong><br> 0. Datenmanagementplan.docx</p> <p><br> 0. Codebuch.csv<br> Beschreibt die im Datensatz enthaltenen Variablen, ihre Herkunft, Bedeutung und mögliche Werte.<br> Bearbeitungszeitraum: 10.02.2023.</p> <p>01_DOAJ_Zeitschriften_in_WoS_Scopus_Ebsco.csv<br> Tabelle mit den von DOAJ indexierten Zeitschriften für Medien- und Kommunikationswissenschaften. Enthält bereinigte Daten aus dem DOAJ, die für die Analyse erforderlich sind, und zusätzliche Felder zur Identifizierung von Zeitschriften (Titel, Verlagsdaten, ISSN etc.). Die Tabelle enthält auch die im Rahmen der Studie erzeugten Variablen zur Erfassung von Zeitschriften in den Indizes von WoS, Scopes, EBSCO und OpenAlex.<br> Erhebungszeitraum: 13.10.2022.<br> Quelle: doaj.org </p> <p>02_IAMCR_Zeitschriften.csv<br> Die Tabelle enthält die Namen und URLs von Open-Access-Zeitschriften aus einer Liste, die von der International Association for Media and Communication Research zusammengestellt und auf der Website der Organisation veröffentlicht wurde.<br> Erhebungszeitraum: 13.10.2022.<br> Quelle: iamcr.org/open-access-journals</p> <p>03_Nordicom_Zeitschriften.csv<br> Die Daten stammen von der Seite des NordMedia-Netzwerks.<br> Erhebungszeitraum: 13.10.2022.<br> Quelle: nordmedianetwork.org/resources/journals/</p> <p>04_SCIE.csv<br> ISSN der Zeitschriften von WoS Science Citation Index Expanded.<br> Erhebungszeitraum: 28.11.2022.<br> Quelle: mjl.clarivate.com/collection-list-downloads</p> <p>05_SSCI.csv<br> ISSN der Zeitschriften von WoS Social Science Citation Index.<br> Erhebungszeitraum: 28.11.2022.<br> Quelle: mjl.clarivate.com/collection-list-downloads</p> <p>06_AHCI.csv<br> ISSN der Zeitschriften von WoS Arts &amp; Humanities Citation Index.<br> Erhebungszeitraum: 28.11.2022.<br> Quelle: mjl.clarivate.com/collection-list-downloads</p> <p>07_ESCI.csv<br> ISSN der Zeitschriften von WoS Emerging Sources Citation Index.<br> Erhebungszeitraum: 28.11.2022.<br> Quelle: mjl.clarivate.com/collection-list-downloads</p> <p>08_CCAH.csv<br> ISSN der Zeitschriften von WoS Current Contents Arts &amp; Humanities.<br> Erhebungszeitraum: 28.11.2022.<br> Quelle: mjl.clarivate.com/collection-list-downloads</p> <p>09_ASC.csv<br> ISSN der Zeitschriften von EBSCO Academic Search Complete.<br> Erhebungszeitraum: 28.11.2022.<br> Quelle: www.ebsco.com/title-lists</p> <p>10_CA.csv<br> ISSN der Zeitschriften von EBSCO Communication Abstracts.<br> Erhebungszeitraum: 28.11.2022.<br> Quelle: www.ebsco.com/title-lists</p> <p>11_CMMC.csv<br> ISSN der Zeitschriften von EBSCO Communication &amp; Mass Media Complete.<br> Erhebungszeitraum: 28.11.2022.<br> Quelle: www.ebsco.com/title-lists</p> <p>12_Scopus.csv<br> ISSN der Zeitschriften von Scopus.<br> Erhebungszeitraum: 28.11.2022.<br> Quelle: https://www.elsevier.com/solutions/scopus/how-scopus-works/content</p> <p>13_ProfessorInnen.csv<br> Liste der ordentlichen ProfessorInnen an deutschen Universitäten mit Bezug zu den Medien- und Kommunikationswissenschaften. Enthält den Namen des Professors und der Universität, Verweis auf den Grund der Einnahme, sowie einen Hinweis auf die Aufnahme in die Stichprobe und auf die Verfügbarkeit der geeigneten Publikationen.<br> Erhebungszeitraum: 1.12.2022 – 10.12.2022.<br> Quelle: www.hochschulkompass.de, universitäre Webseiten (Angaben enthalten im Dokument).</p> <p>14_Zeitschriftenartikel.csv<br> Die Tabelle basiert auf Metadaten aus Publikationslisten von ProfessorInnen auf Universitäts-Websites oder persönlichen Seiten, ergänzt durch Google Scholar, Researchgate und Unpaywall. Die Daten zum Open-Access-Status wurden durch empirische manuelle Überprüfung anhand der DOI ermittelt und mit Unpaywall überprüft. Zusätzlich wurden Daten über grüne Open-Access-Publikationen über Google Scholar gesammelt.<br> Erhebungszeitraum: 7.12.2022 – 30.12.2022.<br> Quelle: universitäre Webseiten (Angaben enthalten im Dokument), unpaywall.org, www.researchgate.net, scholar.google.de<br> <br> 15_Unpaywall.csv<br> Das Ergebnis der Abfrage bei Unpaywall mit einer Liste von DOI. Die Datei wurde verkürzt aber nicht verarbeitet, die Bedeutung der Parameter ist auf der Website des Dienstes beschrieben.<br> Erhebungszeitraum: 5.01.2023 – 8.01.2023.<br> Quelle: unpaywall.org<br> Codebuch: unpaywall.org/data-format </p> <p>16_Datenauswertung.ipynb<br> Enthält ein Skript, das im Laufe der Studie verwendet wurde, um ISSNs aus verschiedenen Datenbanken zu vergleichen und einige der im Text enthaltenen Visualisierungen zu erstellen.<br> Bearbeitungszeitraum: 15.10.2022 – 15.02.2023</p> <p><strong>ENGLISH</strong></p> <p>The dataset contains data from the master's thesis at the Potsdam University of Applied Sciences from 2023.</p> <p>Title: Open Access publications in media and communication studies: review of the current situation.</p> <p><br> Research questions:</p> <p>- To what extent is the field of golden Open Access Journals for media and communication studies covered by indexing services?</p> <p>- What percentage of publications in media and communication studies by German scholars is currently available as open access?</p> <p>- How do the proportions of Open Access publications differ with regard to different years of first publication?</p> <p>- How much has the field of gold Open Access grown since 2013? Has the distribution of attention to gold Open Access Journals changed among popular Indexes?</p> <p>- How widespread is the use of DOI in German media and communication studies?</p> <p>- How suitable are DOI-based services for evaluating the Open Access sector in the media and communication sciences?</p>
Fig. 1 in Species distribution and assemblages of centipedes (Chilopoda) in open xeric sites of Saxony-Anhalt (Germany)
Fig. 1. Locations of study sites. Abbr.: xeric meadows (XM) – FW, Fscha, KK 1, AA, AT, Bi 1, CH 2, EP, SH, BH, Ha 5; mesoxeric meadows (SMM) – Bi 2, Zy, Ha 1, ha 2, ha 3, MTha, ZHei, SBe, SoTr 2, Rü 1, Rü 2, Rü 3, Kö 3, UF 2, UF 3, UF 4, NG, NBG, SBG, TT 1, TT 2; grasslands contaminated by heavy metal (HMG) – Eck 1, Eck 2, Wi, Wo; draw shrub heaths (DSH) – FK 2, FK 3, KB, CH 1, Ha 6, Kö 1, Kö 2, UF 1; advanced succession sites (ASS) – SoGZ 1, SoGO 3, SoGU 4, SoVW 5, Ha 4.
SensEURCity: A multi-city air quality dataset collected using networks of open low-cost sensor systems
<p>We provide a unique curated dataset of urban air quality measurements acquired using dense networks of low-cost sensor systems in three European cities for the years 2020 and 2021. The dataset includes the raw sensor data of quality-controlled sensor networks along with co-located reference data sets. Sensor data are collected using the AirSensEUR sensor system, including sensors to monitor NO, NO2, O3, CO, PM2.5, PM10, PM1, CO2, and meteorological parameters. In total, 85 sensor systems were deployed throughout the years 2020 and 2021 in three European cities (Antwerp , Oslo and Zagreb), resulting in a dataset comprising different meteorological and ambient conditions. The main data collection included two co-location campaigns in different seasons at an air quality monitoring station in each city and a deployment at different locations in each city (including also locations at other air quality monitoring stations). The dataset consists of data files with sensor and reference data, and metadata files with description of locations, deployment dates and description of sensors and reference instruments. </p>
WaivOps HH-LFBB: Open Audio Resources for Machine Learning in Music
<p><strong>WaivOps HH-LFBB Dataset</strong></p> <p>HH-LFBB is an open audio dataset composed of a series of drum recordings in the style of lofi hip-hop music. The dataset contains 3332 audio loops recorded in uncompressed stereo WAV format, produced with custom drum samples and MIDI-programmed rhythms at various tempo rates.</p> <p><strong>Dataset</strong></p> <p>The primary objective of this dataset is to provide accessible content for machine learning applications in music and audio research. Some potential use cases for this dataset include tempo detection and classification, drum rhythm analysis, audio-to-MIDI conversion, source separation, automated mixing, music information retrieval, AI music generation, sound design, and signal processing.</p> <p>Specifications</p> <ul> <li>3332 audio loops (19.3 hours)</li> <li>24-bit WAV format</li> <li>BPM labeled</li> <li>Tempo range: 60-96bpm</li> <li>Expressive drum swings</li> <li>Lofi and boom bap style rhythms</li> </ul> <p><strong>License</strong></p> <p>This dataset was compiled by WaivOps, a crowdsourced music project managed by the sound label company Patchbanks. All recordings have been compiled by verified sources for copyright clearance.</p> <p>The HH-LFBB dataset is licensed under Creative Commons Attribution 4.0 International <a href="https://creativecommons.org/licenses/by/4.0/">(CC BY 4.0)</a>.</p> <p><strong>Additional Info</strong></p> <p>For audio examples or more information about this dataset, please refer to the <a href="https://github.com/patchbanks/WaivOps-HH-LFBB">GitHub repository</a>.</p>
Low Emission Oil and Gas Open (LEOGO) platform specification
<p>This dataset describes the integrated energy system of a hypothetical but realistic offshore oil and gas platform referred to as the LEOGO reference platform. It reflects what would be considered a typical installation on the Norwegian Continental Shelf.</p> <p>Included with the dataset is</p> <ul> <li>input data for analysis with the open-source Oogeso (https://github.com/oogeso/oogeso) operational optimisation/simulation tool, including simplified links between electricity and heat demand and the gas/oil/water flow rates through the processing system.</li> <li>A detailed electrical model implemented in the Digsilent PowerFactory tool</li> </ul> <p> </p>
The State of Open Science in Indonesia: a preliminary analysis of digitalisation's impact on science regimes
<p>This presentation is a discussion on Open Science in Indonesia from the field of the Sociology of Knowledge Approach to Discourse. Boasting the largest number of Open Access Journals in the world, and steadily capitalising on a burgeoning technological economy, Indonesia would seem ripe for a science and knowledge-sharing renaissance. In the past five years, science and education institutions have been consolidated into one “super entity”, the Indonesian National Research and Innovation Agency (BRIN), stirring the imagination for a publicly funded and centralised open access system for indexing, storing and sharing scientific research, data and results. Further, on the back of the 2022 G20 Presidency, Indonesia holds the 2023 ASEAN Presidency, which provides it with agenda setting powers towards regional science and technology cooperation. The potential is high for Open Science, and thus the global sustainable development agenda, to find precedence in Indonesia’s policymaking discourse. Interviews conducted with BRIN staff, professors and PhD Candidates of leading Indonesian universities, think-tank policy advisers, and grass roots organisers illuminate common challenges to implementation of Open Science policies and the Open Science mindset. This discussion addresses where Open Science sits in Indonesia’s development agenda, where there are promises, where there are challenges and what the role of CSIS is in facilitating the transition to Open Science.</p>
UK Grid Frequency data in Open-ENF .fredb format
<p>This file contains the mains grid frequency for each second betwen 1st Jan 2014 00:00 UTC and 1st Jan 2022 00:00 UTC. This data was originally published by the UK National Grid, and subsequently cleaned and reformatted in OpenENF .freqdb format</p>
ScienceDex guides
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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.