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Dataset results
17 results for “EU strategy”
PERCEIVE: WP3: Effectiveness of communication strategies of EU projects
<p>This data set contains all the relevant data referred to PERCEIVE WP3, as tasks within WP3 are logically connected. Data analyzed within WP3, but collected in WP5, are included in the data set “<em>PERCEIVE: WP5: The multiplicity of shared meanings of EU and Cohesion Regional and Urban Policy at different discursive levels</em>” (<a href="http://doi.org/10.5281/zenodo.1038041">http://doi.org/10.5281/zenodo.1038041</a>). Data analyzed in Task3.1 are mostly based on transcripts already included in the data set “<em>PERCEIVE. WP1. Framework for comparative analysis of the perception of Cohesion Policy and identification with the European Union at citizen level in different European countries. Task1.2. Focus group with Cohesion Policy practitioners</em>” (focus groups and other interviews).</p> <p>Task3.2 data are the results of a European wide online survey (at the moment this document is being compiled, the website of the survey is no longer online) targeting policy communicators and focused on three strategic aspects of communicating policy: a) factors of success and barriers, b) support from central institutions and c) communication mix and storytelling.</p> <p>Task3.3 data regard the analysis of social media communication from EU communication offices at both local and European level. Data covers a sentiment analysis performed on the Facebook homepages of Local Management Authorities (LMA) of PERCEIVE case study regions as well as twitter networks and timelines for international accounts and hashtags. </p> <p>Task3.4 data contain elements used in the statistical modeling of communication efforts (see Deliverable 3.4, <a href="http://doi.org/10.6092/unibo/amsacta/6111">http://doi.org/10.6092/unibo/amsacta/6111</a> or <a href="http://doi.org/10.5281/zenodo.1318144">http://doi.org/10.5281/zenodo.1318144</a>). Data cover the algorithmic clustering of topics detected in Task5.3, data derived from the PERCEIVE survey, the code (R programming environment) used to run regression analyses, as well as the results of the analyses themselves.</p> <p>Task3.5 data refer to secondary publicly available data. Namely the collection of the PANORAMA magazine available at INFOREGIO, the Directorate of Regional Policy web portal (<a href="https://ec.europa.eu/regional_policy/en/information/publications/panorama-magazine/">https://ec.europa.eu/regional_policy/en/information/publications/panorama-magazine/</a>), and Eurobarometer data on “awareness” available at the Open Data Portal of the EC (<a href="http://ec.europa.eu/commfrontoffice/publicopinion/index.cfm">http://ec.europa.eu/commfrontoffice/publicopinion/index.cfm</a>). The textual content of PANORAMA magazine has been content analyzed and the results are made available as a .csv table of concepts’ frequencies per magazine issue.</p>
PERCEIVE. WP3_ T3-1_ Communication strategies effectiveness in the context of EU Cohesion Policy - Romanian case study – Sud Est NUTS II region
<p>This dataset contains data related to the papers: Tudor MM, Florian V, (2018) "Impactul și eficacitatea strategiilor de comunicare în contextul politicii de coeziune a Uniunii Europene. Studiu de caz - România", published in proceedings of "Economia agroalimentară și dezvoltarea rurală din perspectiva integrării europene". The dataset was built collecting data from the dataset “<em>PERCEIVE. WP1. Framework for comparative analysis of the perception of Cohesion Policy and identification with the European Union at citizen level in different European countries. Task1.2. Focus group with Cohesion Policy practitioners</em>” (focus groups and other interviews) (<a href="http://amsacta.unibo.it/6215/">http://amsacta.unibo.it/6215/</a>). Data used in the above-mentioned paper regarding the Section II from the Focus Group protocol and is related with Romanian PERCEIVE case-study region – Sud EST (RO22).</p>
Spamming the regulator: Exploring a new lobbying strategy in EU competition procedures
<p>Original dataset associated with the article "Spamming the regulator: Exploring a new lobbying strategy in EU competition procedures". Covers all 108 final decisions in EU merger procedures with a Phase II investigation (Council Regulation 139/2004) of which a public version was available in the electronic registry of DG COMP in September 2020.</p>
Towards a taxonomically unbiased EU Biodiversity Strategy for 2030
<p>Through the Habitats Directive (92/43/EEC) and the LIFE projects financial investments, Europe has been the world's experimental arena for biological conservation. With an estimated budget of €20 billion/year, the EU Biodiversity Strategy for 2030 has set an ambitious goal of reaching 30% Protected Areas and ensure no deterioration in conservation trends and status of all protected species. We analyzed LIFE projects focused on animals from 1992 to 2018 and we found that investment towards vertebrates has been six times higher than that for invertebrates (€970 vs €150 million), with birds and mammals alone accounting for 72% species and 75% total budget. Budget allocation is primarily explained by species' popularity. We propose a roadmap to achieve unbiased conservation targets for 2030 and beyond.</p>
Model runs - Reconciling the EU forest, biodiversity, and climate strategies
<p>These are the model runs for the paper "Reconciling the EU forest, biodiversity, and climate strategies" published in Global Change Biology in 2024, by Gregor et al.</p> <p>The data can be used to re-run the optimizations.</p>
Towards a taxonomically unbiased EU Biodiversity Strategy for 2030
Open the record for dataset details and reuse information.
Data from: Identification of top-priority areas to achieve EU Biodiversity Strategy for 2030 key commitments
<p>Data from: Identification of top-priority areas to achieve EU Biodiversity Strategy for 2030 key commitments. The dataset includes all files to run prioritization analyses included in Iulia V. Miu, Laurentiu Rozylowicz, Viorel D. Popescu, Paulina Anastasiu (2020) Identification of areas of very high biodiversity value to achieve the EU Biodiversity Strategy for 2030 key commitments. </p> <p>To run analyses, unzip the files in your computer (drive C) and use Zonation v4 developed by CBIG - CONSERVATION BIOLOGY INFORMATICS GROUP, Department of Biosciences of the University of Helsinki (<a href="https://www.helsinki.fi/en/researchgroups/digital-geography-lab/software-developed-in-cbig#section-52992">https://www.helsinki.fi/en/researchgroups/digital-geography-lab/software-developed-in-cbig#section-52992</a>). Files are available for nationwide prioritization of terrestrial Natural 2000 in Romania, taxa specific prioritization of terrestrial Natural 2000 in Romania (amphibians, mammals, plants, reptiles, invertebrates, and fish), and at biogeographical level prioritization of terrestrial Natural 2000 in Romania (Alpine, Continental, Pannonian, Steppic & Black Sea).</p>
Supplementary material 2 from: Runnel V, Wetzel F, Groom Q, Koch W, Pe'er I, Valland N, Panteri E, Kõljalg U (2016) Summary report and strategy recommendations for EU citizen science gateway for biodiversity data. Research Ideas and Outcomes 2: e11563. https://doi.org/10.3897/rio.2.e11563
EU BON conducted a survey to assess how willing are researchers to recruit volunteers in their work, what are the main effects, motivators and hindrances.
Supplementary material 3 from: Runnel V, Wetzel F, Groom Q, Koch W, Pe'er I, Valland N, Panteri E, Kõljalg U (2016) Summary report and strategy recommendations for EU citizen science gateway for biodiversity data. Research Ideas and Outcomes 2: e11563. https://doi.org/10.3897/rio.2.e11563
Citizen science and biodiversity observations – EU BON best practice cases of initiatives, systems and tools.
Supplementary material 1 from: Maes J, Liekens I, Brown C (2018) Which questions drive the Mapping and Assessment of Ecosystems and their Services under Action 5 of the EU Biodiversity Strategy? One Ecosystem 3: e25309. https://doi.org/10.3897/oneeco.3.e25309
This supplement contains three tables with policy (Table1), business (Table 2) and societal (Table 3) questions.
Supplementary material 1 from: Runnel V, Wetzel F, Groom Q, Koch W, Pe'er I, Valland N, Panteri E, Kõljalg U (2016) Summary report and strategy recommendations for EU citizen science gateway for biodiversity data. Research Ideas and Outcomes 2: e11563. https://doi.org/10.3897/rio.2.e11563
Species occurrence data sources metadata
Figure 4 from: Runnel V, Wetzel F, Groom Q, Koch W, Pe'er I, Valland N, Panteri E, Kõljalg U (2016) Summary report and strategy recommendations for EU citizen science gateway for biodiversity data. Research Ideas and Outcomes 2: e11563. https://doi.org/10.3897/rio.2.e11563
Figure 4 - European Starling Sturnus vulgaris (Linnaeus, 1758) occurrences visualized in GBIF portal (A), distribution map in Fauna Europaea (B) and occurrences in Latvian national observation portal dabastati.lv (C).
Figure 3 from: Runnel V, Wetzel F, Groom Q, Koch W, Pe'er I, Valland N, Panteri E, Kõljalg U (2016) Summary report and strategy recommendations for EU citizen science gateway for biodiversity data. Research Ideas and Outcomes 2: e11563. https://doi.org/10.3897/rio.2.e11563
Figure 3 - Peacock Butterfly Aglais io (Linnaeus, 1758) occurrences visualized in GBIF portal (A), distribution map in Fauna Europaea (B) and occurrences in Latvian national observation portal dabastati.lv (C).
Figure 2 from: Runnel V, Wetzel F, Groom Q, Koch W, Pe'er I, Valland N, Panteri E, Kõljalg U (2016) Summary report and strategy recommendations for EU citizen science gateway for biodiversity data. Research Ideas and Outcomes 2: e11563. https://doi.org/10.3897/rio.2.e11563
Figure 2 - Break-out group discussion at the 2nd Stakeholder Roundtable (Credit: Florian Wetzel)
Figure 5 from: Runnel V, Wetzel F, Groom Q, Koch W, Pe'er I, Valland N, Panteri E, Kõljalg U (2016) Summary report and strategy recommendations for EU citizen science gateway for biodiversity data. Research Ideas and Outcomes 2: e11563. https://doi.org/10.3897/rio.2.e11563
Figure 5 - Biodiversity observation - from observation to data usage
Figure 1 from: Runnel V, Wetzel F, Groom Q, Koch W, Pe'er I, Valland N, Panteri E, Kõljalg U (2016) Summary report and strategy recommendations for EU citizen science gateway for biodiversity data. Research Ideas and Outcomes 2: e11563. https://doi.org/10.3897/rio.2.e11563
Figure 1 - Totally recorded occurrences in 80 European CS data portals and publicly shared in GBIF.
Table of Identified and Categorised Challenges for Implementing the EU Biodiversity Strategy for 2030
<p>Since the beginning of this century, the European Union (EU) has been committed to tackling the continuously accelerating biodiversity crisis. Yet, both its 2010 and 2020 Biodiversity Strategy failed to deliver their main targets of halting and reversing biodiversity loss. The design of the new Biodiversity Strategy for 2030 acknowledges lessons learned from the evaluation of these past strategies. However, improving on the ground implementation of biodiversity protection efforts requires a comprehensive understanding of the challenges occurring on the target-level. Horizon Europe project BioAgora aims to set up the scientific pillar of the European Commission to ratchet up the EU BDS implementation. As first task of BioAgora, this research investigates target-specific challenges of implementing past strategies. By applying a combined methods approach, we identified and categorised a variety of target-specific challenges which, if not addressed, are likely to remain barriers to achieving the 2030 objectives. By revealing those challenges, this typology fundamentally supports ratcheting up the Biodiversity Strategy 2030. We conclude by recommending further, ideally systematic, research on identifying challenges and continuously updating this work throughout the strategy’s timeframe to allow for the impact of adapted governance instruments to be reflected.</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.