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5,061 results for “access”
Josélia Neves: What Does Green Digital Accessibility Mean To You?
<p>In this video, Dr. Josélia Neves from Hamad Bin Khalifa University answers the question: "what does green digital accessibility mean to you?"</p>
Jan-Louis Kruger: What Does Green Digital Accessibility Mean To You?
<p>Professor Jan-Louis Kruger from Macquarie University in Sydney shares his thoughts on the concept of Green Digital Accessibility.</p> <p>https://www.green-scent.eu/gda-conference/</p>
Tom Greenwood: What Does Green Digital Accessibility Mean to You?
<p>Tom Greenwood, co-founder of Wholegrain digital, shares his thoughts on green digital accessibility for the Green Digital Accessibility Conference.</p>
Carlo Eugeni: What Does Green Digital Accessibility Mean to You?
<p>Dr Carlo Eugeni from the University of Leeds shares his thoughts on green digital accessibility for the Green Digital Accessibility Conference.</p>
U.S. Science Journalists' Knowledge and Opinion of Open Access Articles as Sources
<p>Survey data of U.S. science journalists and their knowledge and opinions of OA research as news sources.</p>
All of the same type? The use of 'welfare tourism' to limit the access of EU migrants to social benefits in the UK and Germany 2021
<p><em>List of documents analyzed for book chapter: Gago, Angie (2021) All of the same type? The use of ‘welfare tourism’ to limit the access of EU migrants to social benefits in the UK and Germany </em>In<em> "Social Policy Review 33", edited by Pomati, Marco, Andy Jolly and James Rees, 203-222. Bristol: Bristol University Press, 2021</em></p>
Measuring Space-Time Accessibility: Hansen's Model Vs. Machine Learning
<p>This dataset consists of Hansen accessibility data in 2011 and 2020 in the municipalities of Lombardia and Emilia Romagna (Italy). Neural Network (NN) learns to predict Hansen accessibility based on the number of residents, employed people and travel time.</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>
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>
National Open Access Monitor Survey: Defining Requirements: Responses Dataset
<p>This dataset contains the response data from the ‘National Open Access Monitor Survey: Defining Requirements’ which was carried out between February 2-28th 2023 under the National Open Access Monitor Project: <a href="https://doi.org/10.5281/zenodo.7588787">https://doi.org/10.5281/zenodo.7588787</a></p> <p>To note: </p> <ul> <li>Email addresses have been redacted. </li> <li>Responses have been pseudonymised to the level of stakeholder-group e.g. Contributor 1, Research Funding Organisation #, 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>Detail within responses by individuals who requested pseudonymisation, which might identify the individual or the organisation has been removed and marked "[redacted]".</li> <li>Responses by individuals who did not provide a signed consent form in advance of contributing to the survey were deleted immediately on receipt, as advised in the survey text: <a href="https://doi.org/10.5281/zenodo.7588787">https://doi.org/10.5281/zenodo.7588787</a>. Such responses are not included in these files.</li> </ul> <p>There are five files within in this dataset:</p> <p>- <em>Results.NationalOpenAccessMonitorSurvey.DefiningRequirements.README - </em>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.</p> <p>- <em>Results.NationalOpenAccessMonitorSurvey.DefiningRequirements.Pseudonymised.100323</em> - this is the original raw data, in csv format, as downloaded from the Online Surveys platform and subsequently pseudonymised and redacted.</p> <p>- <em>NationalOpenAccessMonitor.DefiningRequirements.Contributor3Government1.270223 - </em>this PDF file contains a single pseudonymised stakeholder response to the survey, obtained by the Project Manager by email and not through the Online Surveys platform.</p> <p>- <em>NationalOpenAccessMonitorSurvey.MasterChangeFile.080323 </em>- 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 and the survey was closed.</p> <p>- <em>Results.NationalOpenAccessMonitorSurvey.DefiningRequirements.Pseudonymised.Updated.100323 - </em>this is the original raw data, pseudonymised and redacted, with the requested changes implemented. This is the file on which analysis was carried out for the purposes of the <a href="http://doi.org/10.5281/zenodo.7822367">survey outcome report</a> and the resulting National Open Access Monitor tender documents. </p> <p>------------------------</p> <p>The context for the survey files 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></p> <p>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></p>
SAGC-A68: A space access graph dataset for the classification of spaces and space elements in apartment buildings
<p><strong>SAGC-A68</strong>: "a <strong>S</strong>pace <strong>A</strong>ccess <strong>G</strong>raph dataset for the <strong>C</strong>lassification of spaces and space elements in <strong>A</strong>partment buildings"</p> <p><strong>Authors:</strong> "Amir Ziaee, Georg Suter, Laura Keiblinger"</p> <p><strong>Copyright:</strong> "Design Computing Group TU Wien, 2023"</p> <p><strong>Credits:</strong> "Design Computing Group TU Wien"</p> <p><strong>License:</strong> "GNU GENERAL PUBLIC LICENSE Version 3"</p> <p><strong>Version: </strong>"1.0.1"</p> <p><strong>Maintainer:</strong> "Amir Ziaee"</p> <p><strong>Email:</strong> "amir.ziaee@tuwien.ac.at"</p> <p><strong>Url:</strong> <a href="https://github.com/A2Amir/SAGC-A68">https://github.com/A2Amir/SAGC-A68</a></p> <p><strong>Acknowledgments:</strong> "The authors gratefully acknowledge support by Grant Austrian Science Fund (FWF): I 5171-N, Laura Keiblinger, and participants in the course '259.428-2021S Architectural Morphology' at TU Wien for data collection. "</p> <p><strong>Description:</strong> "The analysis of building models for usable area, building safety, and energy efficiency requires accurate classification data of spaces and space elements. To reduce input model preparation effort and errors, automated classification of spaces and space elements is desirable. Although existing space function classifiers use space adjacency or connectivity graphs as input, the application of Graph Deep Learning (GDL) to space layout element classification has not been extensively researched due to the lack of suitable datasets. To bridge this gap, we introduce a dataset named SAGC-A68, which comprises access graphs automatically generated from 68 digital 3D models of space layouts of apartment buildings designed or built between 1952 and 2019 in 13 countries. Each access graph contains nodes representing spaces and space elements and edges representing the connection between them. Nodes are uniquely identified and characterized by 16 features including “Position X”, “Position Y”, “Position Z”, “Width”, “Height”, “Depth”, “Area”, “Volume”, “Is_internal”, “Door_opening_quantity”, “Window_quantity”, “Max_door_width”,” Encloses_ws”, “Is_contained_in_ws”, ”bounding_box”, and “Label” (28 identified lables are shown in bold type in Table 1). Edges are identified by a unique ID and characterized by three features, including “Z_angle”, “Delta_z”, and “Length”. In total, the dataset comprises 4871 nodes and 4566 edges, including disconnected nodes representing shafts. It is suitable for developing GDL models for space element and space function classification in Building information modeling (BIM) authoring systems. "</p> <p> </p> <p>Table 1: Space and space element class hierarchies and instance count in the SAGC-A668 dataset.</p> <table> <tbody> <tr> <td> </td> <td> </td> </tr> <tr> <td><strong>Space function classes</strong></td> <td> </td> <td><strong>Space element classes</strong></td> <td> </td> </tr> <tr> <td><strong>Name</strong></td> <td><strong>Count</strong></td> <td><strong>Name</strong></td> <td><strong>Count</strong></td> </tr> <tr> <td>Space</td> <td> </td> <td>SpaceElement</td> <td> </td> </tr> <tr> <td> ResidentialSpace</td> <td> </td> <td> SpaceEnclosingElement</td> <td> </td> </tr> <tr> <td> CommunalSpace</td> <td> </td> <td> <strong>Opening</strong></td> <td><strong>140</strong></td> </tr> <tr> <td> <strong>DiningRoom</strong></td> <td><strong>3</strong></td> <td> Door </td> <td> </td> </tr> <tr> <td> <strong>FamilyRoom</strong></td> <td><strong>6</strong></td> <td> <strong>InternalDoor</strong></td> <td><strong>1428</strong></td> </tr> <tr> <td> <strong>LivingRoom</strong></td> <td><strong>275</strong></td> <td> <strong>UnitDoor</strong></td> <td><strong>291</strong></td> </tr> <tr> <td> PrivateSpace</td> <td> </td> <td> <strong>SideEntranceDoor</strong></td> <td><strong>84</strong></td> </tr> <tr> <td> <strong>Bedroom</strong></td> <td><strong>495</strong></td> <td> <strong>ElevatorDoor</strong></td> <td><strong>492</strong></td> </tr> <tr> <td> <strong>MasterBedroom</strong></td> <td><strong>23</strong></td> <td> <strong>BalconyDoor</strong></td> <td><strong>10</strong></td> </tr> <tr> <td> <strong>BoxRoom</strong></td> <td><strong>2</strong></td> <td> </td> <td> </td> </tr> <tr> <td> <strong>HomeOffice</strong></td> <td><strong>8</strong></td> <td> </td> <td> </td> </tr> <tr> <td> ServiceSpace</td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> <strong>Shaft</strong></td> <td><strong>403</strong></td> <td> </td> <td> </td> </tr> <tr> <td> <strong>StorageRoom</strong></td> <td><strong>84</strong></td> <td> </td> <td> </td> </tr> <tr> <td> <strong>WalkInCloset</strong></td> <td><strong>2</strong></td> <td> </td> <td> </td> </tr> <tr> <td> SanitarySpace</td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> <strong>Bathroom</strong></td> <td><strong>274</strong></td> <td> </td> <td> </td> </tr> <tr> <td> <strong>Toilet</strong></td> <td><strong>145</strong></td> <td> </td> <td> </td> </tr> <tr> <td> <strong>Kitchen </strong></td> <td><strong>117</strong></td> <td> </td> <td> </td> </tr> <tr> <td> <strong>LaundryRoom</strong></td> <td><strong>57</strong></td> <td> </td> <td> </td> </tr> <tr> <td> CirculationSpace</td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> VerticalCirculationSpace</td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> <strong>Elevator</strong></td> <td><strong>86</strong></td> <td> </td> <td> </td> </tr> <tr> <td> <strong>Stairway</strong></td> <td><strong>70</strong></td> <td> </td> <td> </td> </tr> <tr> <td> HorizontalCirculationSpace</td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> <strong>Entrance </strong></td> <td><strong>67</strong></td> <td> </td> <td> </td> </tr> <tr> <td> <strong>Hallway </strong></td> <td><strong>12</strong></td> <td> </td> <td> </td> </tr> <tr> <td> <strong>MainHallway </strong></td> <td><strong>18</strong></td> <td> </td> <td> </td> </tr> <tr> <td> <strong>InternalHallway</strong></td> <td><strong>152 </strong></td> <td> </td> <td> </td> </tr> <tr> <td> External <strong> </strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> <strong>AccessBalcony </strong></td> <td><strong>19</strong></td> <td> </td> <td> </td> </tr> <tr> <td> <strong>Loggia</strong></td> <td><strong>108 </strong></td> <td> </td> <td> </td> </tr> </tbody> </table> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
Experimental data for "An open-access database for the assessment of particle damper simulation tools"
<p>Experimental data for "An open access database for the assessment of particle damper simulation tools"</p>
Evaluating Institutional Commitments to Open Scholarly Infrastructure: A Review of Open Access Collection Development Policies
<p>Data prepared for the publication "Evaluating Institutional Commitments to Open Scholarly Infrastructure: A Review of Open Access Collection Development Policies."</p> <p><strong>oa-cd-policies.csv</strong></p> <p>Scope: This data represents collection development policies that contain substantial mention of open access.</p> <p>Data collection: The policies were sourced using an Advanced Google Search for "open access" AND "collection development policy" at ".edu" domains.</p> <p>Variables:</p> <ul> <li>institution: Free text, name of the institution.</li> <li>carnegie_class: One of <a href="https://carnegieclassifications.acenet.edu/carnegie-classification/classification-methodology/basic-classification/">these options</a>; the Carnegie classification of the institution.</li> <li>institution_type: One of public or private; the funding source of the institution.</li> <li>policy_name: Free text; the title of the policy.</li> <li>supplemental_policy: Link to a supplemental open access policy if linked in the collection development policy.</li> <li>cd_policy_link: Link to the policy.</li> <li>infrastructure: TRUE or FALSE; whether the policy includes a commitment to open access scholarly infrastructure development, including open source platforms, locally hosted platforms, consortia, or an institutional repository.</li> <li>excerpt: Free text; text from the policy that mentions infrastructure.</li> </ul> <p><strong>principles-policies.csv</strong></p> <p>Scope: This data represents those collection development policies from oa-cd-policies.csv that contain commitments in line with the <a href="https://openscholarlyinfrastructure.org/">Principles for Open Scholarly Infrastructure</a>.</p> <p>Variables:</p> <ul> <li>institution: Free text, name of the institution.</li> <li>carnegie_class: One of <a href="https://carnegieclassifications.acenet.edu/carnegie-classification/classification-methodology/basic-classification/">these options</a>; the Carnegie classification of the institution.</li> <li>institution_type: One of public or private; the funding source of the institution.</li> <li>policy_name: Free text; the title of the policy.</li> <li>supplemental_policy: Link to a supplemental open access policy if linked in the collection development policy.</li> <li>cd_policy_link: Link to the policy.</li> <li>principle: One of the three main <a href="https://openscholarlyinfrastructure.org/">Principles</a>.</li> <li>sub_principle: One of the <a href="https://openscholarlyinfrastructure.org/">Sub-Principles</a>.</li> <li>excerpt: Free text; text from the policy that illustrates the sub_principle.</li> </ul>
Supplements for "Solvent Accessibility Promotes Rotamer Errors During Protein Modelling with Major Side-Chain Prediction Programs"
<p><strong>Supplements for "Solvent Accessibility Promotes Rotamer Errors During Protein Modelling with Major Side-Chain Prediction Programs"</strong></p> <p>This supplement includes the following files:</p> <ul> <li>Main_v02.R --- Script in R language to process files (in "PDBs.zip") and produce the dataset ("Dataset_v02.csv")</li> <li>PDBs.zip --- PDB files include filtered structures processed by three programs</li> <li>Dataset_v02.csv --- final filtered version of dataset produced in R language (by "Main_v02.R"). </li> <li>Dataset key.txt --- key to column names in Dataset_v02.csv </li> </ul> <p>The article featuring this dataset is published in:</p> <p>Journal: Journal of Chemical Information and Modeling<br>Title: "Solvent Accessibility Promotes Rotamer Errors During Protein Modelling with Major Side-Chain Prediction Programs"<br>Author(s): Hameduh, Tareq; Mokry, Michal ; Miller, Andrew ; Heger, Zbynek; Haddad, Yazan</p> <p><a href="https://emea01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fpubs.acs.org%2Fdoi%2F10.1021%2Facs.jcim.3c00134&data=05%7C01%7C%7C4876a5c33e5f4bd8daf008db7e55a28d%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C638242678496577396%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=NE%2F0dYvc4m5%2B8T0YQtqxY21yk1pA9ZpiADqzx3vEJ4Q%3D&reserved=0">https://pubs.acs.org/doi/10.1021/acs.jcim.3c00134</a></p> <p> </p>
Austrian Science Fund (FWF) Open Access Compliance Monitoring 2022
<p>I. Executive summary</p> <p>The Austrian Science Fund (FWF), which is Austria's main funding organisation for basic research, encourages and helps all project leaders and project staff members to make their peer-reviewed research results freely available on the Internet. Any exceptions must be clearly indicated and justified. For projects that started after 1 January 2015, open access has been compulsory for all peer-reviewed publications. All principal investigators in FWF-funded projects are obliged to submit a final report within four months of completing their projects.</p> <p>In 2022, a total of 575 final reports were submitted to the FWF, 38 of which could not report any publications so far. The publications and other data mentioned in those reports are archived and analysed by the FWF. This report examines the state of compliance with open access requirements for peer-reviewed publications on the basis of final project reports submitted in the year 2022.</p> <p>Main findings:</p> <p>-A total of 8,312 publications were listed in the final project reports submitted in 2022.</p> <p>-Of those publications, 6,631 were conclusively identified as peer-reviewed.</p> <p>-Regarding compliance with the FWF's Open Access Policy, the analysis shows that 85% of the peer-reviewed publications listed in the final project reports submitted in 2022 were openly accessible (2015: 83%, 2016: 92%, 2017: 90%, 2018: 92%, 2019: 89%, 2020: 84%, 2021 82%).</p> <p>-The most frequently chosen option was hybrid open access (36%). The share of gold open access was 29%, the share of green open access 20%, and no open access 15%.</p> <p>-The majority of peer-reviewed publications submitted were journal articles (85%), 86% of which were openly accessible.</p> <p>-The lowest rate of compliance with the FWF's Open Access Policy could be found in editions, contributions to edited volumes, and monographs 41%).</p> <p>-The absolute number of publications listed in final reports in 2022 included 354 publications that were mentioned several times in different projects; however, those repetitions did not affect the relative share of open access publications (85%).</p> <p>II. Bias</p> <p>All publications were submitted to the FWF via a research documentation system (provided by ©Researchfish), in which FWF-funded researchers are able to enter and update their research data on an ongoing basis. The last check of the open access status was performed in March 2023. In some cases, the embargo period may have already expired, and publications labelled ‘closed’ in the FWF’s database may now be accessible through green open access.</p> <p>Whenever the status ‘peer-reviewed’ could not be clearly identified according to the FWF’s guidelines, the publications were classified as non-peer reviewed.</p> <p>Openly available non-peer reviewed publications were entered as 'openly available’.</p>
Data and supplementary materials in support of "Development and Preliminary Validation of an Open Access, Open Data and Open Outreach Indicator"
<p>Data and supplementary materials in support of "Evgenios Vlachos, Regine Ejstrup, Thea Marie Drachen, Bertil Fabricius Dorch (2023) Development and Preliminary Validation of an Open Access, Open Data and Open Outreach Indicator, Frontiers in Research Metrics and Analytics, doi: 10.3389/frma.2023.1218213" </p> <p>It includes the anonymized dataset with the OADO values for all researchers from 10 departments (2 per faculty), the R code to perform the analysis and the graphs, the Scopus search string for the background search on Open Access and metrics, and the documentation for pulling data out from Pure.</p>
Data set - Measured in a context : making sense of open access book data
<p>For more than a decade, open access book platforms have been distributing titles in order to maximise their impact. Each platform offers some form of usage data, showcasing the success of their offering. However, the numbers alone are not sufficient to convey how well a book is actually performing.</p> <p>Our data set is consists of 18,014 books and chapters. The selected titles have been added to the OAPEN Library collection before 1 January 2022, and the usage data of twelve months (January to December 2022) has been captured. During that period, this collection of books and chapters has been downloaded more than 10 million times. Each title has been linked to one broad subject and the title’s language has been coded as either English, German or other languages.</p> <p>The titles are rated using the TOANI score.</p> <p>The acronym stands for Transparent Open Access Normalised Index. The transparency is based on the application of clear regulations, and by making all data used visible. The data is normalised, by using a common scale for the complete collection of an open access book platform. Additionally, there are only three possible values to score the titles: average, less than average and more than average. This index is set up to provide a clear and simple answer to the question whether an open access book has made an impact. It is not meant to give a sense of false accuracy; the complexities surrounding this issue cannot be measured in several decimal places.</p> <p>The TOANI score is based on the following principles:</p> <ul> <li>Select only titles that have been available for at least 12 months;</li> <li>Use the usage data of the same 12 months period for the whole collection;</li> <li>Each title is assigned one – high level – subject;</li> <li>Each title is assigned one language;</li> <li>All titles are grouped based on subject and language;</li> <li>The groups should consists of at least 100 titles;</li> <li>The following data must be made available for each title: <ul> <li>Platform</li> <li>Total number of titles in the group</li> <li>Subject</li> <li>Language</li> <li>Period used for the measurement</li> <li>Minimum value, maximum value, median, first and third quartile of the platform’s usage data</li> </ul> </li> <li>Based on the previous, titles are classified as: <ul> <li>“Less than average” – First quartile; 25 % of the titles</li> <li>“Average” – Second and third quartile; 50% of the titles</li> <li>“More than average” – Fourth quartile; 25 % of the titles</li> </ul> </li> </ul>
Open Access on GNSS Permanent Networks Data in Case of Disaster
<p>Earthquakes, as a natural phenomenon causing large physical and social destruction, are the subject of intensive research throughout the world. Spurred by the fact that in year 2020, two catastrophic earthquakes hit Croatia, in March with epicenter near Zagreb and December with epicenter near Petrinja, at the Faculty of Geodesy, University of Zagreb activities were initiated with the aim of strengthening the ability to react in these situations. Focus of those activities is on providing fast, adequate, and complete information on the disaster in the field of geodesy and geoinformatics. The research was focused on interpretation of kinematics of surface motion during the earthquake itself for what high rate permanent GNSS (Global Navigation Satellite System) network stations registrations are necessary. The Croatian earthquakes experience as well as the Mexico (June 2020) and Samosa earthquake (October 2020), pointed out, related to the use of high-rate registration GNSS data, that the primary problem in the use of this data is open access to the data itself. That is why this study has been launched - to gain a global picture of the availability of data from permanent GNSS networks around the world. The research included the collection and processing of information on open access policies for permanent GNSS networks data in the event of natural disasters with an emphasis on earthquakes. A global survey of institutions around the world responsible for managing GNSS permanent networks has been conducted. The survey contains three groups of questions that include general information on the type of permanent networks, models of access to network data and the readiness of countries to reach an international agreement on the opening data of the GNSS network in the event of a disaster. The results indicated that a high percentage of countries participating in the survey were ready to agree to open the data and introduce a common international portal through which scientists and researchers would be able to download GNSS permanent network data free of charge in the event of natural disasters.</p>
Balancing Innovation and Responsibility: The e-DIPLOMA Project's Approach to Ethical, Inclusive, Accessible, and Sustainable Research (video)
<p>This video includes project motivation, primary objective and methodology developed at e-DIPLOMA project and emphasize the Responsible Research and Innovation actions implemented in the project. e-DIPLOMA ensures the consideration of ethics, gender equality, legal aspects, and data privacy as well as it prioritizes transparency and accessibility.</p> <p>Project website: https://e-diplomaproject.eu/</p>
Accessible Chemical Space for Metal Nitride Perovskites
<p>Supporting data to manuscript "Accessible Chemical Space for Metal Nitride Perovskites"</p> <p>The folders contain respectively:</p> <ul> <li>25_Candidates_HSE06: The structures of the 25 candidates presented in the manuscript and relaxed with HSE06</li> <li>Competing_phases: The structures of the 86 competing phases considered for thermodynamic stability and relaxed with HSE06</li> <li>Json_summaries: Json files containing all the relevant information. This includes structures and energies for: <ul> <li>the 279 candidates in 15 possible tilts</li> <li>the lowest energy tilted structure for all 279 candidates</li> <li>the intermediate structures found during the phonon mapping process</li> <li>the ten lowest energy structures for each of the 25 candidates obtained with AIRSS</li> <li>the summary of all lowest-energy structures identified in both workflows</li> <li>the materials already reported in literature and recomputed in this work</li> <li>the energy above the hull for all considered structures calculated with HSE06 and PBEsol</li> </ul> </li> <li>Switching_paths: The structures along the switching path and the Born effective charges of the material calculated in the initial configuration</li> </ul>
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.