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67 results for “Open Review”
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).
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>
A Systematic Review of Open Data in Agriculture
<p>This dataset contains a collection of papers retrieved by using a PRISMA systematic review of Open Data and Public Domain data in Agriculture. This collection of papers uses, creates, or discusses about Open Data and Public Domain.</p><p>The dataset uses the Zotero RDF format and is classified according the source and the topic of the paper</p>
Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review (Article Pool)
<p>This pdf includes all of the articles that analyzed in the study: "Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review".</p>
Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review (Matching articles with categories)
<p>This document includes which primary study falls into which category with respect to the RQs in the following study: “Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review”</p>
Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review (Matching articles with categories)
<p>This document includes which primary study falls into which category with respect to the RQs in the following study: “Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review”</p>
Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review (Matching articles with categories)
<p>This document includes which primary study falls into which category with respect to the RQs in the following study: “Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review”</p>
MapOSR - A Mapping Review Dataset of Empirical Studies on Open Science
<p>Research that investigates respective researchers’ engagement in Open Science varies widely in the topics addressed, methods employed, and disciplines investigated, which makes it difficult to integrate and compare its results. To investigate current outcomes of Open Science research, and to get a better understanding on topicswell-researched and on research gaps we aim at providing an openly accessible overview of empirical studies that focus on different aspects of Open Science in different scientific disciplines, academic groups and geographical regions. The present data set of studies about Open Science practices was retrieved following a PRISM approach to compile a literature review. We include studies from the Scopus and Web of Science databases with keywords relating to Open Science between the years 2000 and 2020, as well as a snowball search for relevant articles. Studies that did not investigate any aspect of Open Science, or weren’t peer reviewed were excluded, resulting in a total of 695 remaining studies. The data set was collaboratively annotated to ensure intercoder reliability of the coded data.</p>
Literature review of Design in Open Source Agriculture - Images
<p>Literature review of Design in Open Source Agriculture - Images</p> <ol> <li>Fig. 1. Publications by subject areas</li> <li>Fig. 2. Publications by country</li> <li>Fig. 3. Yearly output of publications</li> <li>Fig. 4. Network of co-authorship (generated with VOSviewer) <em>(Extra image not included in the article)</em></li> <li>Fig. 5. Network of co-citation (generated with VOSviewer) <em>(Extra image not included in the article)</em></li> <li>Fig. 6. Network of bibliographic coupling(generated with VOSviewer) <em>(Extra image not included in the article)</em></li> <li>Fig. 7. Co-word analysis: network of terms from title and abstract (generated with VOSviewer) <em>(Extra image not included in the article)</em></li> <li>Fig. 8. Co-word analysis: network of keywords (generated with VOSviewer) <em>(Extra image not included in the article)</em></li> <li>Fig. 9. Thematic Map based on Authors’ keywords (generated with bibliometrix) <em>(Extra image not included in the article)</em></li> <li>Fig. 10. Thematic Map based on Titles (just single words - unigrams) (generated with bibliometrix) <em>(Extra image not included in the article)</em></li> <li>Fig. 11. Thematic Map based on Abstracts (just single words - unigrams) (generated with bibliometrix) <em>(Extra image not included in the article)</em></li> <li>Fig. 12. Trend Topics (generated with bibliometrix) <em>(Extra image not included in the article)</em></li> </ol>
Data for study "'Conditional Acceptance' (additional experiments required): A scoping review of recent evidence on key aspects of Open Peer Review"
<p>Dataset for study "‘Conditional Acceptance’ (additional experiments required): A scoping review of recent evidence on key aspects of Open Peer Review", 2022 preprint by Tony Ross-Hellauer and Serge Horbach.</p> <p>Dataset includes excel file with 10 sheets showing systematic literature search (per PRISMA-SCR protocol) of academic databases (Web of Science, Scopus), snowballing and web-search to identify 52 studies on key aspects of Open Peer Review published from Jan 2017 until May 2022.</p> <p><strong>Study Abstract: </strong>Diverse efforts are underway to reform the journal peer review system. Combined with growing interest in Open Science practices, Open Peer Review (OPR) has become of central concern to the scholarly community. However, what Open Peer Review is understood to encompass and how effective some of its elements are in meeting the expectations of the peer review system, are uncertain. This scoping review updates previous efforts to summarise research on OPR to date. Following the PRISMA methodological framework, it addresses the question: “What evidence has been reported in the scientific literature from 2017 to date regarding uptake, attitudes, and efficacy of two key aspects of Open Peer Review (Open Identities and Open Reports)?” The review identifies, analyses and synthesises 52 studies matching inclusion criteria, finding that OPR is growing, but still far from common practice. Our findings indicate positive attitudes towards Open Reports and more sceptical approaches to Open Identities. Changes in reviewer behaviour seem limited. and no evidence for lower acceptance rates of review invitations or slower turnaround times is reported. Concerns about power dynamics and potential backfiring on critical reviews are in need of further experimentation. We conclude that elements of OPR seem to be gaining acceptance, but more experimentation is needed. Evidence still mainly consists of either survey data or case studies of individual or few journals, not allowing for generalisability across fields and journals, and revealing no studies which compare the quality of review under Open Identities or Open Reports versus other modes of peer review.</p>
Review of Open Call Record Datasets concerning the U.S. 911 Emergency Response System
<p>The data available here identifies and describes a sampling of publicly available datasets about the 911 emergency response system. This list of datasets is a resource for researchers, civic technologists, activists, and journalists seeking to learn more about the 911 emergency response system. The list helps to identify relevant datasets that could be used to understand various types of 911 activity.</p> <p>During the first quarter of 2021, the R911 NAT created a list of priority cities including the top 100 cities by population, all state capitals, and the 82 cities that are home to Code for America Brigades. The team then conducted internet searches for each city using terms like “<em>911 calls for service</em>” and “<em>open 911 data</em>.” The dataset and a codebook defining each of these fields are provided as .csv files within a zip file.</p> <p><strong>Note</strong>: this file <em>does not contain the actual 911 datasets</em>, which often number in the millions of records. The <em>data_link</em> field contains the URL of the site where each dataset is publicly available.</p> <p><strong>See also</strong>: The Reimagine 911 knowledge base at: <a href="https://reimagine-911.gitbook.io/knowledge-base">https://reimagine-911.gitbook.io/knowledge-base</a></p> <p><strong>Contributors</strong>: This open data review was performed by the Code for America Reimagine 911 National Action Team. Contributing team members include: Aleks Hatfield, Brandon Bolton, Chizo Nwagwu, Dan Stormont, Elaine Chow, Em Spalti, Erica Pauls, Gio Sce, Gregory Janesch, Iva Momcheva, Ivelina Momcheva, Jamie Klenetsky Fay, Jason Trout, Jaya Prasad Jayakumar, Jennifer Miller, Jim Grenadier, Joanna Smith, Jonathan Melvin, Katlyn McGraw, Margaret Fine, Mariah Lynch, Micah Mutrux, Michelle Hoogenhout, Patina Herring, Peter Zeglen, Sarah Graham, Sebastian Barajas</p>
Workflow for structured literature reviews using the Open Research Knowledge Graph (ORKG)
<p>Figure showing a workflow of making a structured literature review using the core features of the Open Research Knowledge Graph (ORKG). </p>
Hindsight is 2020: Reviewing How the ORION Project Impacted Open Science
<p><strong>Episode Summary: </strong></p> <p>Season 2 is here! We start by looking back at the last year, and talking for the first time about the Open Science project that we are part of ORION. In particular, we consider the aim and impact of Open Science training and interview two participants: Malte Schäfer from TU Braunschweig and Dr Deirdre Winrow from University College Dublin, from our workshop and our MOOC. </p> <p><strong>Links:</strong></p> <ul> <li><a href="http://tiny.cc/ORIONMOOC2">Enroll in the MOOC 2.0</a></li> <li><a href="https://www.orion-openscience.eu/publications/training-materials">ORION Training Materials</a></li> <li><a href="https://www.orion-openscience.eu/activities/training">ORION Training Workshops</a></li> </ul> <p><strong>Quotes: </strong></p> <p>"He radicalised me"</p> <p>"It gives them space to reflect on Open Science"</p> <p>"The system of science has changed"</p>
Signing up to Open Science: Open Peer Review and Aligning Core Values
<p><strong>Episode Summary:</strong></p> <p>In this episode we are talking to Dr Guillaume Filion from the Center for Genomic Regulation (CRG), Barcelona about his decision to put his name on all his peer reviews, why he feels this makes him more accountable, and what choices researchers need to make about whether their values align with those who they will work with. </p> <p><strong>Resources and Links:</strong></p> <ul> <li><a href="https://www.orion-openscience.eu/node/201">Factsheets</a></li> <li><a href="https://www.crg.eu/en/programmes-groups/filion-lab">Dr Guillaume Filion</a> <ul> <li><a href="https://twitter.com/thegrandlocus">Twitter Page</a></li> </ul> </li> <li><a href="http://blog.thegrandlocus.com/2018/09/on-open-peer-review">Original Blog Post by Dr Guillaume Filion</a></li> <li><a href="https://www.fosteropenscience.eu/learning/open-peer-review/#/id/5a17e150c2af651d1e3b1bce">FOSTER+ Information on Open Peer Review </a></li> </ul> <p><strong>Episode Quotes:</strong></p> <p>“I had the feeling I would do a better job as a reviewer, if I put my name on it, if I put my name on the line then it would force me not to do a bad job”</p>
Open Peer Review Journal Data
<p>This csv file contains a descriptive dataset of <strong>617</strong> scholarly journals that make use of a form of Open Peer Review (OPR) based on Open Reports and/or Open Reviewer Identities. The data file contains the following fields:</p> <p>Journal Title</p> <p>Year of First Identified OPR Occurrence (2001-2019)</p> <p>High Level Discipline of the Journal (Humanities, Medical and Health Sciences, Multidisciplinary, Natural Sciences, Social Sciences, Technology)</p> <p>Journal URL</p> <p>Journal Publisher</p> <p>Publisher Country</p> <p>Use of Open Reports (Decided by Author, Decided by Editor, Mandated by Journal, None)</p> <p>Use of Open Reviewer Identities (Decided by Reviewer, Mandated, None)</p> <p>Notes that provide additional information about the journal</p>
[Dataset] Expanding the Number of Reviewers in Open-Source Projects by Recommending Appropriate Developers
<p>A rich collection of review and development data, including information about reviewers, developers and their<br> commits within five large ASF projects and four Gerrit communities.</p>
Mapping the Landscape of Open Source Health Economic Models: A Systematic Database Review and Analysis
<p><span>Health economic models are crucial for health technology assessment (HTA) to evaluate the value of medical interventions. Open source models (OSMs), where source code and calculations are publicly accessible, enhance transparency, efficiency, credibility, and reproducibility. This study systematically reviews databases to map the landscape of available OSMs in health economics.</span></p>
Open Science Website Review (Team 2)
<p>A document detailing Team 2's analysis of the various websites promoting the concept of open science for the "Open Science" Course and using Zenodo to generate a DOI for the aforementioned document</p>
Dataset: Cultural Openness and desire to learn regarding language education: systematic review
<p>Documental Dataset belonging to the Conference presentation titled:</p> <div> <p><strong>Cultural Openness and desire to learn regarding language education: systematic review. </strong></p> <p>The complete reference is: Peña-Acuña, B. (2024). Cultural Openness and desire to learn regarding language education: systematic review The thirty first international Conference of Learning. Utrech, The Netherlands. July 2024. </p> </div>
Surgical resection for rectal cancer. Is laparoscopic surgery as successful as open approach? A systematic review with meta-analysis
<p>Data Set from the original article Surgical resection for rectal cancer. Is laparoscopic surgery as successful as open approach? A systematic review with meta-analysis.</p>
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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.