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632 results for “policies”
PERCEIVE: WP4: Spatial determinants of policy performance and synergies: Task4.4: Cohesion Policy vs Urban and Rural policies to address spatial discrepancies in EU territorial policy
<p>This dataset consists of data addressing the relationship between territorial cohesion objectives and the problems perceived by citizens. In particular a comparative analysis between the case study regions will generate data useful for identifying best practices in mixing the EU policy instruments for a better achievement of regional needs. Data that will be generated via focus groups interviews among representatives of LMA (local management authorities) in 2 Polish regions: Dolnośląskie and Warmińsko-Mazurskie . Interview transcripts and report was used to address how territorial cohesion objectives match the “real problems” of regions. The focus groups were built around the following main topics: 1) governance of the Cohesion Policy projects, in order to understand how different authorities at different levels cooperate and share the responsibilities for the implementation of the Cohesion Policy; 2) level of citizen engagement, in order to understand whether a bottom-up approach is used; 3) how the media inform on the Cohesion Policy programmes, in order to appreciate the discrepancies (if any) about the aims of Cohesion Policy and its construction on the public discourse. Comparing current and past programming periods, we investigate how the policy performs in reducing the gap between territorial cohesion objectives and “real problems” defined by LMAs and citizens. Because it is project-specific data and reflects the concept and methodology of the study under PERCEIVE they are perceived as unique - similar data does not exist. Potential users are be Regional Policy’s European/National/Local policy makers and practitioners, European networks and associations looking to data on LMA opinions on cohesion policy implementation in Poland to be used in policy recommendation, studies and policy making process; next group of potential data users are researchers working on assessment of Cohesion Policy, data may be used as a source for topic-related studies, case studies, comparisons.</p> <p>The dataset is made up of 5 files: 2 files consist of reports from the workshops, 2 files consist in transcripts of interviews to practitioners, beneficiaries and targets of the Cohesion Policy projects in the Polish selected case‐study regions. Interviewees are asked to provide their views and perceptions on the multilevel governance system, on the communication activities of the Operational Programmes and on the effectiveness of Cohesion Policy. 1 readme file is included.</p>
PERCEIVE The use of social media in EU policy communication and implications for the emergence of a European public sphere
<p>This data set contains the underlying data of the paper “<strong>The use of social media in EU policy communication and implications for the emergence of a European public sphere</strong>”, published by The Journal of Regional Research - Investigaciones Regionales (ISSN: 1695-7253; E-ISSN: 2340-2717) in 2019.</p> <p>Data openly available within this dataset are a subset of the two following data sets, which contains all the relevant data of Work Package 3 and Work Package 5 of PERCEIVE project:</p> <ul> <li>Data set:<strong> “PERCEIVE: WP3: Effectiveness of communication strategies of EU projects” </strong><a href="https://doi.org/10.5281/zenodo.3371133">https://doi.org/10.5281/zenodo.3371133</a></li> <li>Data set:<strong> “PERCEIVE: WP5: The multiplicity of shared meanings of EU and Cohesion Regional and Urban Policy at different discursive levels” </strong><a href="https://doi.org/10.5281/zenodo.3371174">https://doi.org/10.5281/zenodo.3371174</a></li> </ul> <p>For the paper we collected Facebook posts referred to EU CP policies. We don’t have the permission to share these data (as they are protected by copyright), but all the sources are described in Deliverable 5.2, which is public (see <a href="http://doi.org/10.6092/unibo/amsacta/5726">http://doi.org/10.6092/unibo/amsacta/5726</a> or <a href="http://doi.org/10.5281/zenodo.1318184">http://doi.org/10.5281/zenodo.1318184</a>). We analyzed the textual content of data to construct a database of discursive topics in Task5.4. Data set includes the results of topic modeling and of a sentiment analysis performed on the Facebook homepages of Local Management Authorities (LMA) of PERCEIVE case study regions. </p>
PERCEIVE. WP4_ T4-5_Citizens vs Practitioners views of the EU Cohesion Policy in 9 PERCEIVE case-study regions
<p>This dataset contains data related to the papers: Tudor MM, Florian V, Rosu, SE, Kruzslicika M (2019) "Citizens’ vs practitioners’ perception on EU regional approach", published by Rural areas and Development & Tudor MM, Florian V (2019) "Percepția cetățenilor vs. percepția practicienilor cu privire la politica de coeziune a UE", published in proceedings of "Piețele Agricole și Spațiul Rural în Contextul Modernizării și Simplificării Politicii Agricole Comune". The dataset was built collecting data from different sources: 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: Survey at citizen level and data relative to regional performance of the Cohesion Policy and institutional quality</em>” (<a href="https://doi.org/10.5281/zenodo.3346047">https://doi.org/10.5281/zenodo.3346047</a>); 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>).</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>
Policies, systemic factors, trade-offs and synergies for agroecological transitions
<table> <tbody> <tr> <td>In order to identify the existing policies, systemic factors, trade-offs and synergies for agroecological transition we collected data via desk research, interviews with policy-makers and focus groups. This dataset presents the interview outcomes for 39 policy-makers from our focal countries</td> </tr> </tbody> </table>
Figure 1 in A new policy to implement CONSORT guidelines for surgical randomized controlled trials
Figure 1. – Smilosicyopus species (males). A: S. chloe (P. Gaucher); B: S. fehlmanni (P. Keith); C: S. nigriradiatus (P. Keith); D: S. sasali (P. Keith); E: S. pentecost (C. Lord); F: S. bitaeniatus (E. Vigneux); G: S. leprurus (P. Keith).
Carbon neutrality policy can deliver disproportionately higher gains for toxic trace elements control in China
<p>The dataset of carbon neutrality policy can deliver disproportionately higher gains for toxic trace elements control in China.</p>
Supplementary materials for paper "Untangling the drivers of change and policy impact in coastal wetland area in the Yangtze Estuary using causal inference"
<h1>Annual coastal wetland vegetation maps of the Yangtze Estuary from 1986 to 2021</h1> <p> </p> <h2><strong>Basic information</strong></h2> <p>Using remotely sensed data from Google Earth Engine, we generated a 30 m resolution annual dataset of Yangtze Estuary wetland vegetation for the period 1986-2021. This dataset includes three dominant vegetation types (<em>Spartina alterniflora</em>, <em>Phragmites australis</em>, and <em>Scirpus mariqueter</em>) and tidal flat areas. We combined fieldwork data and high-resolution images for accuracy assessment, achieving an overall accuracy exceeding 80% in different years. Detailed information about the mapping methods can be found in our paper and accompanying supplementary materials.</p> <h2><strong>Notes:</strong></h2> <p>In the image classification scheme: 0-Tidal flats, 1-<em>Spartina alterniflora, </em>2-<em>Phragmites australis, </em>3-<em>Scirpus mariqueter.</em></p> <h2><strong>Usage Policy:</strong></h2> <p>This dataset is a collaborative effort between East China Normal University and Deakin University. If you plan to use our data in <strong>a scientific analysis paper or other research work</strong>, we strongly recommend contacting us in advance to seek our opinions, <strong>citing the unique DOI of this dataset</strong>, and considering acknowledging our contributions or including us as co-authors.</p>
Colonial trade linkages: Trade policy and imports in South and Southeast Asia colonial markets (1874-1913).
Open the record for dataset details and reuse information.
City's Low Hanging Fruit: Exploring Policy Alternatives for Exploiting Urban Fruit Trees
<p>City's Low Hanging fruit:<br><br>Map, Thematic analysis, Three quistionnaires, questionnaire answers<br><br>מפה, ניתוח תמטי, שלושת השאלונים, תשובות לשאלונים<br><br></p> <p>Abstract + methods - below<br>תקציר - למטה</p>
Datasets and Code for the paper "Toward Futuristic Autonomous Experimentation—A Surprise-Reacting Sequential Experiment Policy"
<p>This page has the data and code used in the paper "Toward Futuristic Autonomous Experimentation—A Surprise-Reacting Sequential Experiment Policy", to be published in IEEE Transactions on Automation Science and Engineering.</p>
Opinions and data on short food supply chains related policy analysis in 9 EU countries generated in the H2020 SMARTCHAIN Project grant number: 773785
<p>Questionnaires: Opinions and data on short food supply chains related policy analysis in 9 EU countries generated in the H2020 SMARTCHAIN Project grant number: <strong>773785</strong></p>
SOILCARE_WP_7_D7.2_Adoption factors and policy actions
<p>Dataset accompanying D7.2: “Report on the selection of good policy alternatives at EU and study site level”. The file provides data collected from stakeholders at the European level as well as at national, regional and local level within the 16 SoilCare study site countries. The data set provides stakeholder views on factors enabling and hampering the uptake of Soil Improving Cropping Systems as well as actions to facilitate their adoption. The methodology for collecting the data is detailed in D7.2 available at <a href="https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.soilcare-project.eu%2Fresources%2Fdeliverables&data=04%7C01%7CMelanie.Muro%40milieu.be%7Cf7dfe7d3270749a707f008d95ca21180%7C3c6af27b55264b71983fbcaca8bf2b0b%7C0%7C0%7C637642673432698641%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=vvJUvwtnIu2DXzu1DTLD56g4sg%2F5kRwJbMWDl5BE8os%3D&reserved=0">https://www.soilcare-project.eu/resources/deliverables</a>.</p>
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: Survey at citizen level and data relative to regional performance of the Cohesion Policy and institutional quality
<p>1. Orignal PERCEIVE survey data (STATA file)</p> <p>2. description of survey questions, descriptive results (word file)</p> <p>3. EU Deliverable document with descriptive analysis of survey questions</p> <p> </p> <p>***please cite the following when using the microdata:</p> <p>Bauhr, M., & Charron, N. (2020). The EU as a savior and a saint? Corruption and public support for redistribution. <em>Journal of European Public Policy</em>, <em>27</em>(4), 509-527.</p> <p>https://www.tandfonline.com/doi/full/10.1080/13501763.2019.1578816</p>
Data set: Europeana Metadata to Analyse The EU's Policy Effectiveness in Digitising European Heritage
<p>This dataset was produced as a part of a research MSc thesis project, “<em>Using Europeana Metadata to Analyse The EU’s Policy Effectiveness in Digitising European Heritage</em><em>” </em>published by the KU Leuven in joint cooperation with Europeana.</p> <p>The dataset contains the data from the Europeana API call, graphs created form the data and the code needed to collect the CH metadata from Europeana digital collections which was used to evaluate the policy aims used in the study. Within this repository one will find the code scripts used to make the API calls, three Raw data files and two cleaned data spreadsheets with graphs used in the published revised research thesis</p> <p>Links to the research produced with this dataset and the Original Thesis published by the KU Leuven can be found below.</p> <p>Research Report: Morgenstern, Paul Simon. (2022). Using Europeana Metadata to Analyse The EU's Policy Effectiveness in Digitising European Heritage. Zenodo. https://doi.org/10.5281/zenodo.7278645</p> <p> </p> <p>Thesis: Morgenstern, P., Truyen, F., & Nyi Nyi Htun, ’. (2022). Using Europeana Metadata to Analyse The EU’s Policy Effectiveness in Digitising European Heritage. KU Leuven. Faculteit Wetenschappen.</p>
A Policy and Infrastructure Evaluation Model of Commodity Flows through Inland Waterway Ports (Dataset)
<p>The purpose of this project is to guide strategic investment into port capacity through the development of a policy and infrastructure evaluation model of inland waterway commodity flows. A multi-stage stochastic optimization model will be developed to evaluate tradeoffs in strategic, long-term port infrastructure investment with mid-term capacity expansion decisions and provision of complementary highway infrastructure made by public and private stakeholders, and shorter-term operational practices made by shippers and carriers. This work builds on prior MarTREC projects which developed a Multi-Commodity Assignment Problem to estimate annual commodity flows through inland waterway ports from truck Global Positioning System (GPS), marine Automatic Identification System (AIS), and the Lock Performance Management System (LPMS). The proposed project will explore critical extensions of the assignment model: 1) disaggregation of the temporal scope to reflect monthly seasonality among commodities, 2) incorporation of uncertainty related to observed vehicle and vessel movement data, and 3) inclusion of transportation costs. With these extensions the team expects to increase the accuracy and resolution of the commodity-based port throughput estimates and to allow the model to be used to not only describe the current system but to prescribe policy and project investment strategies for public and private sector transportation decision makers. Calibration and validation of the multi-stage optimization model will be done through two case studies. The regional-based study will use historical truck GPS, marine AIS, and LPMS datasets. The national-based study will use data from the Billion Ton Study led by the US Department of Energy. This will ensure a feasible and realistic base-case on which to compare future policy scenarios. This project aligns with MarTREC’s research focus area in Maritime and Multimodal Logistics Management by modeling commodity flows through ports that serve as critical connections for the multimodal freight supply chain.</p>
COVID-19 Non-Pharmaceutical Interventions: Data Annotation for Rapidly Changing Local Policy Information
<p><strong>Main Dataset Attributes (npi_data/*.xlsx)</strong></p> <ul> <li>FIPS: FIPS of the county.</li> <li>Location name: Name of the county.</li> <li>NPI measure: Type of NPI measure.</li> <li>Start Date: Date the NPI was first started.</li> <li>End Date: Date the NPI was first lifted.</li> <li>Start Link: Source link of the start date.</li> <li>End Link: Source link of the end date.</li> <li>Start Notes: Contains tags that apply to both dates, and the start date individually. Tag description can be found in Table 3. This also includes notes on nuances not included in the tags.</li> <li>End Notes. Contains tags that only apply to the end date go here. Tag description can be found in Table 3. This also includes notes on nuances not included in the tags.</li> <li>Validated (Correctness): Binary field indicating if the record was validated for correctness</li> </ul>
Dataset for the climate-related financial policy index (CRFPI)
<p>Data on the climate-related financial policy index (CRFPI) - comprising the global climate-related financial policies adopted globally and the bindingness of the policy - are provided for 74 countries from 2000 to 2020. The data include the index values from four statistical models used to calculate the composite index as described in D’Orazio and Thole 2022. The four alternative statistical approaches were designed to experiment with alternative weighting assumptions and illustrate how sensitive the proposed index is to changes in the steps followed to construct it. The index data shed light on countries’ engagement in climate-related financial planning and highlight policy gaps in relevant policy sectors.</p> <p> </p>
Timestamped RDF-star datasets according to the rdfstar policy
<p>All three datasets were built on the basis of independent snapshots of the <a href="https://aic.ai.wu.ac.at/qadlod/bear.html">BEAR datasets</a>.</p> <p>Each triple was together with a creation and deletion timestamp cast into a <a href="https://w3c.github.io/rdf-star/tests/sparql/syntax/manifest.html#sparql-star-nested-1">nested quoted triples in subject position</a>. </p> <p>The timestamps for both datasets do not reflect the original timestamps of the triples but were for the sake of evaluating the RDF-star policies incremented by 1sec from the initial system timestamp.</p> <p>The main script used to construct these datasets can be found <a href="https://github.com/GreenfishK/starvers_eval/blob/master/scripts_dev/3_construct_datasets/construct_datasets.py">here</a>, which contains the logic on how to assemble these datasets. However, the script was run within a Docker container found on the <a href="https://github.com/GreenfishK/starvers_eval">starvers_eval</a> Github page.</p> <p> </p>
TRANSFORM video: Citizen engagement TRANSFORMing regional R&I policy making
<p>Over the past three years, the TRANSFORM project (funded under H2020) has explored and tested citizen engagement practices in the governance of regional research and innovation (R&I), in particular in the context of Smart Specialisation Strategies (S3) in three regional clusters: Lombardy (Italy), Catalonia (Spain), Brussels-Capital (Belgium). Under the common framework of Responsible Research and Innovation (RRI), each territory has implemented different methodologies and pilot actions with the common goal of better aligning regional R&I priorities with societal needs and aspirations.</p> <p>This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 872687. This video reflects only the authors' view. The European Research Executive Agency (REA) and the European Commission are not responsible for any use that may be made of the information it contains.</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
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Annotated Behaviour and Observability Dataset (ABODe)
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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.