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18 results for “Opening the Future”
Survey Data on Current Open Access Terms and Future Trends (2024)
<p><strong>Description:</strong><br>This dataset contains the analysis, codebook, and raw survey data from the 2024 survey <em>"Open Access – Current Terms and Future Areas of Focus"</em>. The survey aimed to gather perspectives from Open Access experts in the German-speaking region, focusing on the evaluation of current Open Access terminology, concepts, and emerging trends.</p> <p>The survey highlights how Open Access terminology has evolved over the past two decades and explores current perceptions regarding key terms in the Open Access discourse, as well as the anticipated future developments in this field. A total of 131 complete responses (<em>N=131</em>) were collected, providing valuable insights into the views of professionals working in Open Access publishing, information infrastructures, and scientific publishing houses.</p> <p><strong>Contents:</strong></p> <ol> <li><strong>codebook_oa_2024_2024-11-21.xlsx</strong>: The codebook, including detailed explanations of the variables, codes, and definitions used in the survey.</li> <li><strong>survey_results_oa_2024_2024-11-21.xlsx</strong>: Anonymized raw data from the survey, including both quantitative and qualitative responses from the participants.</li> <li><strong>values_oa_2024_2024-11-21.csv</strong>: CSV file containing the key terms and concepts identified by participants in response to the question on Open Access terminology.</li> <li><strong>values_oa_2024_2024-11-21.csv</strong>: An additional CSV file with detailed classification and analysis of the terms related to Open Access, including their frequency and significance based on participant responses.</li> </ol> <p><strong>Methodology:</strong><br>The survey was conducted via an online questionnaire distributed from September 7 to October 15, 2024, to professionals working in Open Access, both within information infrastructures (e.g., libraries) and in academic publishing houses. The survey gathered both qualitative and quantitative data, focusing on how Open Access terminology is understood and its future developments. The data were cleaned, anonymized, and analyzed using appropriate statistical and content analysis methods.</p> <p><strong>Purpose and Use:</strong><br>This dataset is valuable for researchers and professionals studying Open Access terminology, trends, and future developments. It provides insights into the current understanding of Open Access within the academic community and can be used for comparative studies, policy analysis, and future Open Access research.</p>
Ensemble projections (+ uncertainties) of contemporary (2012-2031) and future (2081-2100) mean annual plankton/phytoplankton/zooplankton species diversity (and species turn-over in time) for the global surface open ocean.
<p><em><strong>Gridded spatial fields (raster objects) containing the species distribution models (SDMs) projections of mean annual plankton total plankton, phytoplankton and zooplankton species diversity from Benedetti et al. (2021). </strong></em></p> <p>The present .grd file ('rasterStack' object in R) contain the fields of mean annual surface plankton/phytoplankton/zooplankton species diversity for the contemporary (2012-2031) and future (2081-2100) conditions of the global open ocean (i.e., data underlying those maps in Figure 1 and Figure 3 of Benedetti et al., 2021). Layers quantifying the uncertainty (i.e., the variablity across models projections estimated through the standard deviation) in ensemble projections were also added (i.e., data underlying the maps in Supplementary Figure 4). See the Methods section of Benedetti et al. (2021) for a full description of the methodology and the ensemble SDMs forecasting framework. The raster layers follow the 1°x1° cell grid of the World Ocean Atlas (https://www.ncei.noaa.gov/).</p> <p>In short, we empirically modelled the monthly and mean annual diversity patterns stemming from the distribution of 860 plankton species (336 phytoplankton, 524 zooplankton) spanning 13 phyla, 71 orders and 324 genera through an ensemble approach based on SDMs. The considered species cover a wide range of traits and functions, representing 10 major plankton functional groups (PFGs; three phytoplankton and seven zooplankton groups). We compiled the species occurrence records from various data sources (available here: https://zenodo.org/record/5101349#.YO7Dqm469lM) and aggregated them onto a monthly-resolved 1°x1° grid, excluding observations from regions where the seafloor is shallower than 200 m. We matched these binned open ocean records with observation-based climatologies of environmental predictors (temperature, dissolved oxygen concentration, solar irradiance, macronutrients concentration, chlorophyll a concentration) that reflect the climatic and biogeochemical conditions of the surface open ocean. Four types of SDMs (generalized linear models, generalized additive models, artificial neural networks, and random forests) were fitted to model the species’ current environmental habitat suitability patterns. For each SDMs, we used four alternative pools of predictors. Assuming niche conservatism, we projected each of the 16 resulting species-level habitat suitability models into the future using outputs from five ESMs belonging to the Coupled Model Intercomparison Project 5 (CMIP5) that were forced by the Representative Concentration Pathway 8.5 (RCP8.5) scenario of high greenhouse gas concentrations. To this end, we first computed the modelled monthly climatologies of the selected predictors for the 2012-2031 and 2081-2100 periods, and derive the future monthly anomalies from the differences between these two time periods. These anomalies were added to the observation-based monthly climatologies (i.e., those used to train the SDMs) to estimate the future environmental conditions of the ocean, and projected the SDMs in these future conditions. Finally, we estimated the mean annual present and future alpha diversity (species richness; SR) and beta diversity (species turnover through time) patterns for both trophic levels, for each cell, from the ensemble of SDMs. SR ensembles are estimated as the sum of all species’ habitat suitability patterns averaged across all 80 possible combinations (i.e., "ensemble members") of SDMs (n = 4), ESMs (n = 5) and predictor pools (n = 4). To assess the uncertainties of our diversity projections based on the ensemble members, we compute the interquartile range of the 80 ensemble members SR projections. We calculate species turnover as the change in mean annual species composition between present and future time based on Jaccard’s dissimilarity index and by decomposing this total turnover into the true species turnover (ST, also known as species replacement) and the nestedness (SR change) components. Numerous tests are conducted to ensure the robustness of the results with regard to the spatially and temporally highly uneven sampling effort as well as with regard to the relative role of different predictors.</p> <p><strong>This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 862923. This output reflects only the author’s view, and the European Union cannot be held responsible for any use that may be made of the information contained therein.</strong></p>
Opening the Future... in 60 seconds
<p>A short animated video with key details about <em>Opening the Future</em>, a collective funding model developed by COPIM's Work Package 3, in close collaboration with Central European University Press and Liverpool University Press, the first two university presses implementing the model.</p>
Yes! We're open. Open science and the future of academic practices in translation and interpreting studies - Supplementary material
<p>Supplementary material to the article "<em>Yes! We’re open</em>. Open science and the future of academic practices in translation and interpreting studies" by Christian Olalla-Soler. </p> <ul> <li>Sheet 1: Translation and Interpreting Studies journals and bibliometric indicators.</li> <li>Sheet 2: Translation and Interpreting Studies articles in Scopus.</li> <li>Sheet 3: Pre-registrations related to translation and interpreting.</li> </ul> <p>Reference:</p> <p>Olalla-Soler, Christian (2021). "<em>Yes! We’re open</em>. Open science and the future of academic practices in translation and interpreting studies". <em>Translation & Interpreting</em> 13 (2): 1-28. <a href="https://doi.org/10.12807/ti.113202.2021.a01">https://doi.org/10.12807/ti.113202.2021.a01</a></p>
Dataset for Perspectives on Open Science and The Future of Scholarly Communication: Internet Trackers, Algorithmic Persuasion and Robotic Process Automation
<p>This data set was created between 01-04.2021, to study the current landscape of using web trackers in scholarly communication. The data set is part of an article (manuscript) that is intended to be published under the this title: Perspectives on Open Science and The Future of Scholarly Communication: Internet Trackers, Algorithmic Persuasion and Robotic Process Automation.</p>
Current and future sources of open citations
<p>Video recording of the presentation done in the context of the Austrian DataCite Consortium on 19 November 2021. The video finishes after the last question.</p>
'Opening the Future' - a new funding model for open-access monographs: introducing an innovative approach to publishing OA books through library membership funding
<p>We showcase a collaborative pilot case study that implements an innovative open access revenue model at the Central European University Press and Liverpool University Press, with assistance from the COPIM Project (Community-led Open Publication Infrastructures for Monographs). Building on existing library subscription models (e.g. OBP, punctum), this is a sustainable OA publishing model that gives library members access to a highly-regarded backlist, with the membership fees then used to make the frontlist openly accessible.<br> Given the current global library environment and existing budget pressures that have been exacerbated by Covid-19, a consortial model of funding promises a cost-effective solution for OA that means no single institution bears a disproportionate burden. This model, then, appeals to both those who wish to pay for subscription-access content (more traditional university acquisition models) and those who support OA initiatives. It brings many institutions together under one roof for an affordable route to open access books.<br> Library members get access to a selection of the publishers’ backlists, DRM free and with perpetual access after three years. In return, the membership revenue is used to make newly-published books openly accessible to anyone with an internet connection.<br> We believe Opening the Future is a trailblazer in scholarly comms, offering a viable and affordable route to OA change for small/medium university presses and which appeals to libraries of all sizes and budgets. We aim to open up research for the public good. The model that we are piloting reduces inequalities in access to open access publication by eradicating exclusionary book processing charges (BPCs).<br> As we progress with the pilot, we are writing up everything we’ve done to implement the model and will release this and any software as a free toolkit, so that other publishers can use it and also take the leap.</p>
CCG: Beyond the Dams: Combatting Hydropower Over-reliance & Securing Pathways for a Low-carbon Future for Laos' Electricity Sector using OSeMOSYS (Open-Source Energy Modelling System)
<p>Seven clicSAND scenario files for <strong>Beyond the Dams: Combatting Hydropower Over-reliance & Securing Pathways for a Low-carbon Future for Laos' Electricity Sector using OSeMOSYS (Open-Source Energy Modelling System).</strong> </p> <p><strong>How to Visualise Results Online and Offline</strong> outline the steps required to re-run the scenarios on OSeMOSYS Cloud</p> <p><strong>Scenario Short Note</strong> outlines the steps to replicate the analysis and rebuild the scenarios</p> <p><strong>Annex - Input Data and Assumptions</strong> listing the data sources and assumptions in the scenarios</p>
Opening the Future... in 60 seconds
<p>An animated video explaining the <a href="https://www.openingthefuture.net/"><em>Opening the Future</em></a> collective funding model for OA monographs</p>
The Breakout Moment for open repositories is now - How can we build the best future for our users?
<p>Closing keynote held at the 14th International Conference on Open Repositories, OR2019 in Hamburg.</p> <p>Chair: Torsten Reimer, British Library</p>
Mutually dependent, yet highly asymmetric? Conversations about the relations and futures of Open Access academic publishing
<p>The research data in this dataset contains verbatim transcripts in PDF and ODT formats each (for reading and broader re-use purposes, respectively) as well as original audio recordings of two interviews. These semi-structured interviews form part of materials for a doctoral research project on recent developments in and possible implications of Open Access publishing models. Further information and full description of the research proposal are available online at http://hdl.handle.net/10760/29265</p>
Clinical Outcome and Future Liver Remnant Regenerative Response in Laparoscopic Versus Open ALPPS
ClinicalTrials.gov study NCT04868149. IPD Sharing: NO. Countries: 1. Publications: 11.
Future Osteoarthritis Treatment - Free Open Online Course for All
ClinicalTrials.gov study NCT07122154. IPD Sharing: NO. Countries: 1. Publications: 5.
Figure 2 from: Penev L, Kress W, Knapp S, Li D, Renner S (2010) Fast, linked, and open – the future of taxonomic publishing for plants: launching the journal PhytoKeys. PhytoKeys 1: 1-14. https://doi.org/10.3897/phytokeys.1.642
Figure 2 - Dynamic webpage (taxon profile) of the the English oak (Quercus robur L. ) generated "on the fly" by the Pensoft Taxon Profile tool (PTP, http://ptp.pensoft.eu)
Figure 1 from: Penev L, Kress W, Knapp S, Li D, Renner S (2010) Fast, linked, and open – the future of taxonomic publishing for plants: launching the journal PhytoKeys. PhytoKeys 1: 1-14. https://doi.org/10.3897/phytokeys.1.642
Figure 1 - Editorial process in PhytoKeys based on XML mark up workflow and extensive internal and extrenal cross-linking to taxon databases, leading biodiversity platforms, indexers and aggregators.
Survey on the Future of the Barcamp Open Science (Dataset)
<p>In September 2021, the Leibniz Research Alliance Open Science and Wikimedia Germany, as the organizer of Barcamp Open Science (<a href="https://www.barcamp-open-science.eu">www.barcamp-open-science.eu</a>), conducted a survey on the future direction of this event. The resulting survey data is located in this dataset:</p> <ul> <li> The questionnaire as PDF</li> <li> A summary of the results as XLS / ODS</li> <li> All answers as CSV (personal "referrer URL" have been replaced by an empty string)</li> </ul> <p>A report on how the results are taken up can be found here: <a href="https://www.leibniz-openscience.de/future-of-the-barcamp-open-science-a-survey-and-what-we-take-from-it">www.leibniz-openscience.de/future-of-the-barcamp-open-science-a-survey-and-what-we-take-from-it</a></p> <p>Lambert Heller had the lead in creating and evaluating the questionnaire.</p>
Data From: The Future of OA: A large-scale analysis projecting Open Access publication and readership
<p>This is the raw data behind the publication on bioRxiv at https://doi.org/10.1101/795310: </p> <p><strong>Piwowar, Priem, Orr (2019) The Future of OA: A large-scale analysis projecting Open Access publication and readership. bioRxiv: <a href="https://doi.org/10.1101/795310">https://doi.org/10.1101/795310</a></strong></p> <p>The jupyter notebook that produces the manuscript using the data here is available at: <a href="https://github.com/Impactstory/future-oa">https://github.com/Impactstory/future-oa</a></p> <p> </p> <p>Summary:</p> <p>Understanding the growth of open access (OA) is important for deciding funder policy, subscription allocation, and infrastructure planning.</p> <p>This study analyses the number of papers available as OA over time. The models includes both OA embargo data and the relative growth rates of different OA types over time, based on the OA status of 70 million journal articles published between 1950 and 2019.</p> <p>The study also looks at article usage data, analyzing the proportion of views to OA articles vs views to articles which are closed access. Signal processing techniques are used to model how these viewership patterns change over time. Viewership data is based on 2.8 million uses of the Unpaywall browser extension in July 2019.</p> <p>We found that Green, Gold, and Hybrid papers receive more views than their Closed or Bronze counterparts, particularly Green papers made available within a year of publication. We also found that the proportion of Green, Gold, and Hybrid articles is growing most quickly.</p> <p>In 2019:</p> <ul> <li> <p>31% of all journal articles are available as OA</p> </li> <li> <p>52% of article views are to OA articles</p> </li> </ul> <p>Given existing trends, we estimate that by 2025:</p> <ul> <li> <p>44% of all journal articles will be available as OA</p> </li> <li> <p>70% of article views will be to OA articles</p> </li> </ul> <p>The declining relevance of closed access articles is likely to change the landscape of scholarly communication in the years to come.</p>
Figure 1 in Open Access and the Future of the Scientific Research
Figure 1. Growth in manuscript submissions to the BioMed Central open access journals.
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