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Dataset results
632 results for “Policy”
WSC 2007 - 2012 Yahara Watershed surface water quality policies and practices created and implemented by public agencies
This dataset was created June 2012 - August 2013 to contribute to research under the Water Sustainability and Climate project. Interventions collected are those land-based policies and practices written and implemented by public agencies. Policies were implemented in Wisconsin's Yahara Watershed the period 2007-2012. They aim to improve surface water quality through nutrient (phosphorus and nitrogen) and sediment reduction. Interventions included in the mapping must have spatially-explicit, publicly available data through personal communication or website.
Organized actors at the biodiversity science-policy-society interface
<p>This database was developed in the context of the Deliverable 2.1 of the BioAgora project 'Developing the Science Service for European Research and Biodiversity Policymaking' (<a href="https://bioagora.eu/)">https://bioagora.eu/)</a>. BioAgora is a collaborative European project funded by the Horizon Europe programme (Horizon Europe research and innovation programme, grant agreement No. 101059438). The project's main outcome is intended to be the development of a Science Service for Biodiversity, the principal EU mechanism to connect research and knowledge on biodiversity to the needs of policy making through a continuous dialogue. The ultimate goal of BioAgora and of the Science Service is to support the implementation of the Biodiversity Strategy for 2030, and more broadly the sustainability transition required by the EU Green Deal. The BioAgora project was launched in July 2022 for a duration of 5 years. It gathers a Consortium of 22 partners, from 13 European countries, led the Finnish Environment Institute (Syke). Partners represent a diversity of actors coming from academia, public authorities, SMEs, and associations. Views and opinions expressed are those of the authors only and do not necessarily reflect those of the European Union or the European Commission. Neither the European Union nor the granting authority can be held responsible for them. </p> <p>In order to develop the database, a thorough desk search was conducted to compile an extensive, albeit not exhaustive, list of organizations operating at the science-policy-society interface in the context of biodiversity and sustainability. In collecting the list, we focused on actors operating at EU level, although we also included particularly relevant international, regional or national organized actors. The desk search built upon the work already developed in the context of two pan-European projects, funded by the Seventh framework programme of the European Community: ‘Developing a Knowledge Network for European Expertise on biodiversity and ecosystem services to inform policy making and economic sectors (KNEU, 2010-2014, grant 265299) and ‘Establishing a European Knowledge and Learning Mechanism to Improve the Policy-Science-Society Interface on Biodiversity and Ecosystem Services’ (Eklipse, 2016-2020, grant 690474). The two above-mentioned projects preceded the BioAgora project in that they aimed at understanding and improving the effectiveness of the biodiversity science-policy(-society) interface in Europe. Such projects had thus already compiled extensive databases of relevant organizations in Europe (including national and international actors, in addition to EU level actors), and quantified the relevance of such organizations based on votes cast by project members and based on interviews with key organizations. The database developed through the desk search conducted was further refined with suggestions for relevant organizations provided by BioAgora’s participants and by the representatives of the organizations interviewed during the other steps of the data collection. The data collection processes started in September 2022 and was updated until June 2024. Note that the categories for network types (Columns E-F) are not mutually exclusive. For further details about the development of the database please see Deliverable 2.1 (<a href="https://bioagora.eu/deliverables/">https://bioagora.eu/deliverables/</a>). </p>
FULFILL dataset - diet policy acceptability - efficacy and acceptability framing Denmark
<p>This dataset represents survey data on sufficiency-oriented policy acceptability in regard to dietary consumption. The study was part of the second round surveys in Denmark in 2023 within the FULFILL project - Fundamental Decarbonisation Through Sufficiency By Lifestyle Changes.</p> <p>As part of Work Package 3 (WP3) in the FULFILL project, we collected quantitative data from two countries: Denmark and Germany, with representative sampling (age, income, gender, current region). In this survey on the acceptability of sufficiency-oriented diet policies we recruited a representative sample with approximately 800 participants from Denmark and Germany, taking into account primarily the individual perspective, added by some questions on the household level.</p> <p>The central part of the survey includes a framing experiment including three groups with participants being randomly assigned to. We were interested in peoples' acceptability on three majorly discussed and sufficiency-relevant policies, i.e. meat tax, carbon label or meat-free day at public canteens. We investigated if an information on either the efficacy of the measures or a combination of information with acceptance information or none of these information could influence people's acceptability (overall, self vs. others perspective). We measured several control variables (socio-economics such as age, gender, income, education, household size, life stage, ideological measures such as political orientation or attitudinal measures such as sufficiency orientation and climate change denial). A quantitative assessment of the carbon footprint in the food consumption domain was also included.</p>
Safe Country Policies Dataset (SACOP)
<p>The Safe Country Policies Dataset (SACOP) (Version 1.1) provides original information on the adoption and characteristics of Safe Country Policies and National Asylum Frameworks in 195 countries from 1951 until 2021.</p> <p>An interactive visualization by Andreas Perret (nccr <em>–</em> on the move) can be accessed <a href="https://tabsoft.co/3AUKrRu">here</a>.</p>
Survey data on climate policy in three countries (Peru, Ghana, Philippines) within the project "Sustainable Middle Classes in Middle Income Countries: Transforming Carbon Consumption Patterns (SMMICC)"
<p>The unprecedented growth of the new middle classes in middle income developing countries implies a strong growth in both consumption and carbon emissions. The research project Sustainable Middle Classes in Middle Income Countries (SMMICC) investigates the drivers of carbon consumption choices of the new middle classes and policy options to decrease their carbon footprints, including the implementation of carbon taxes</p> <p>The research of the authors generated quantitative data on the acceptability of carbon taxes in three countries (Peru, Ghana, Philippines).</p> <p> </p> <p><strong>The data is provided in the following formats:</strong></p> <p>- 2024-07-26_malerba_10.5281/zenodo.12662722_ghana.csv<br>- 2024-07-26_malerba_10.5281/zenodo.12662722_peru.csv<br>- 2024-07-26_malerba_10.5281/zenodo.12662722_philippines.csv</p> <p>- 2024-07-26_malerba_10.5281/zenodo.12662722_ghana.dta<br>- 2024-07-26_malerba_10.5281/zenodo.12662722_peru.dta<br>- 2024-07-26_malerba_10.5281/zenodo.12662722_philippines.dta</p> <p>Additionally, the codebooks on variables of questionnaire and political parties in each country are attached in a csv format.</p>
FULFILL dataset - diet policy acceptability - health information provision France
<p>This dataset represents survey data on sufficiency-oriented policy acceptability in regard to dietary consumption. The study was part of the second round surveys in France in 2023 within the FULFILL project - Fundamental Decarbonisation Through Sufficiency By Lifestyle Changes.</p> <p>As part of Work Package 3 (WP3) in the FULFILL project, we collected quantitative data from three countries: France, Italy, and Latvia, with representative sampling (age, income, gender, current region). In this survey on the acceptability of sufficiency-oriented diet policies we recruited a representative sample with approximately 800 participants from France, taking into account primarily the individual perspective, added by some questions on the household level.</p> <p>The central part of the survey includes the randomised provision of information on the health-risks associated with meat consumption. We were interested in peoples' acceptability on three majorly discussed and sufficiency-relevant policies, i.e. meat tax, carbon label or meat-free day at public canteens. We investigated if the information provision impacted people's acceptability (overall, self vs. others perspective). We measured several control variables (socio-economics such as age, gender, income, education, household size, life stage, ideological measures such as political orientation or attitudinal measures such as sufficiency orientation and climate change denial). A quantitative assessment of the carbon footprint in the food consumption domain was also included.</p>
FULFILL dataset - diet policy acceptability - health information provision Latvia
<p>This dataset represents survey data on sufficiency-oriented policy acceptability in regard to dietary consumption. The study was part of the second round surveys in Latvia in 2023 within the FULFILL project - Fundamental Decarbonisation Through Sufficiency By Lifestyle Changes.</p> <p>As part of Work Package 3 (WP3) in the FULFILL project, we collected quantitative data from two countries: France, Italy, and Latvia, with representative sampling (age, income, gender, current region). In this survey on the acceptability of sufficiency-oriented diet policies we recruited a representative sample with approximately 500 participants from Latvia, taking into account primarily the individual perspective, added by some questions on the household level.</p> <p>The central part of the survey includes the randomised provision of information on the health-risks associated with meat consumption. We were interested in peoples' acceptability on three majorly discussed and sufficiency-relevant policies, i.e. meat tax, carbon label or meat-free day at public canteens. We investigated if the information provision impacted people's acceptability (overall, self vs. others perspective). We measured several control variables (socio-economics such as age, gender, income, education, household size, life stage, ideological measures such as political orientation or attitudinal measures such as sufficiency orientation and climate change denial). A quantitative assessment of the carbon footprint in the food consumption domain was also included.</p>
FULFILL dataset - diet policy acceptability - health information provision Italy
<p>This dataset represents survey data on sufficiency-oriented policy acceptability in regard to dietary consumption. The study was part of the second round surveys in Italy in 2023 within the FULFILL project - Fundamental Decarbonisation Through Sufficiency By Lifestyle Changes.</p> <p>As part of Work Package 3 (WP3) in the FULFILL project, we collected quantitative data from three countries: France, Italy, and Latvia, with representative sampling (age, income, gender, current region). In this survey on the acceptability of sufficiency-oriented diet policies we recruited a representative sample with approximately 800 participants from each country, taking into account primarily the individual perspective, added by some questions on the household level.</p> <p>The central part of the survey includes the randomised provision of information on the health-risks associated with meat consumption. We were interested in peoples' acceptability on three majorly discussed and sufficiency-relevant policies, i.e. meat tax, carbon label or meat-free day at public canteens. We investigated if the information provision impacted people's acceptability (overall, self vs. others perspective). We measured several control variables (socio-economics such as age, gender, income, education, household size, life stage, ideological measures such as political orientation or attitudinal measures such as sufficiency orientation and climate change denial). A quantitative assessment of the carbon footprint in the food consumption domain was also included.</p>
FULFILL dataset - diet policy acceptability - efficacy and acceptability framing Germany
<div> <p>This dataset represents survey data on sufficiency-oriented policy acceptability in regard to dietary consumption. The study was part of the second round surveys in Germany in 2023 within the FULFILL project - Fundamental Decarbonisation Through Sufficiency By Lifestyle Changes.</p> <p>As part of Work Package 3 (WP3) in the FULFILL project, we collected quantitative data from two countries: Denmark and Germany, with representative sampling (age, income, gender, current region). In this survey on the acceptability of sufficiency-oriented diet policies we recruited a representative sample with approximately 800 participants from Denmark and Germany, taking into account primarily the individual perspective, added by some questions on the household level.</p> <p>The central part of the survey includes a framing experiment including three groups with participants being randomly assigned to. We were interested in peoples' acceptability on three majorly discussed and sufficiency-relevant policies, i.e. meat tax, carbon label or meat-free day at public canteens. We investigated if an information on either the efficacy of the measures or a combination of information with acceptance information or none of these information could influence people's acceptability (overall, self vs. others perspective). We measured several control variables (socio-economics such as age, gender, income, education, household size, life stage, ideological measures such as political orientation or attitudinal measures such as sufficiency orientation and climate change denial). A quantitative assessment of the carbon footprint in the food consumption domain was also included.</p> </div>
FULFILL dataset - housing policy acceptability - framing experiment Latvia
<p>This dataset represents survey data on sufficiency-oriented housing gathered in the second round of surveys in Latvia in 2023 within the FULFILL project - Fundamental Decarbonisation Through Sufficiency By Lifestyle Changes.</p> <p>As part of Work Package 3 (WP3) in the FULFILL project, we collected quantitative data from five countries: Denmark, France, Germany, Italy and Latvia. In this survey on sufficiency-oriented housing, we recruited a representative sample of approximately 750 to 800 respondents in Denmark, France, Germany and Denmark and around 550 in Latvia, taking into account primarily the individual perspective, added by some questions on the household level.</p> <p>The survey includes a framing experiment presenting two different ways of framing the aim of two sufficiency-oriented policies in the housing sector. In addition, the survey includes data on policy acceptability of these two policy measures and respondents’ preferences for combinations with different other policy measures. Further, the survey also measures socio-economic factors such as age, gender, income, education, household size, life stage, and political orientation. A quantitative assessment of the carbon footprint in the housing domain was also included.</p>
FULFILL dataset - housing policy acceptability - framing experiment Italy
<p>This dataset represents survey data on sufficiency-oriented housing gathered in the second round of surveys in Italy in 2023 within the FULFILL project - Fundamental Decarbonisation Through Sufficiency By Lifestyle Changes.</p> <p>As part of Work Package 3 (WP3) in the FULFILL project, we collected quantitative data from five countries: Denmark, France, Germany, Italy and Latvia. In this survey on sufficiency-oriented housing, we recruited a representative sample of approximately 750 to 800 respondents in Denmark, France, Germany and Denmark and around 550 in Latvia, taking into account primarily the individual perspective, added by some questions on the household level.</p> <p>The survey includes a framing experiment presenting two different ways of framing the aim of two sufficiency-oriented policies in the housing sector. In addition, the survey includes data on policy acceptability of these two policy measures and respondents’ preferences for combinations with different other policy measures. Further, the survey also measures socio-economic factors such as age, gender, income, education, household size, life stage, and political orientation. A quantitative assessment of the carbon footprint in the housing domain was also included.</p>
FULFILL dataset - housing policy acceptability - framing experiment France
<p>This dataset represents survey data on sufficiency-oriented housing gathered in the second round of surveys in France in 2023 within the FULFILL project - Fundamental Decarbonisation Through Sufficiency By Lifestyle Changes.</p> <p>As part of Work Package 3 (WP3) in the FULFILL project, we collected quantitative data from five countries: Denmark, France, Germany, Italy and Latvia. In this survey on sufficiency-oriented housing, we recruited a representative sample of approximately 750 to 800 respondents in Denmark, France, Germany and Denmark and around 550 in Latvia, taking into account primarily the individual perspective, added by some questions on the household level.</p> <p>The survey includes a framing experiment presenting two different ways of framing the aim of two sufficiency-oriented policies in the housing sector. In addition, the survey includes data on policy acceptability of these two policy measures and respondents’ preferences for combinations with different other policy measures. Further, the survey also measures socio-economic factors such as age, gender, income, education, household size, life stage, and political orientation. A quantitative assessment of the carbon footprint in the housing domain was also included.</p>
FULFILL dataset - housing policy acceptability - framing experiment Germany
<p>This dataset represents survey data on sufficiency-oriented housing gathered in the second round of surveys in Germany in 2023 within the FULFILL project - Fundamental Decarbonisation Through Sufficiency By Lifestyle Changes.</p> <p>As part of Work Package 3 (WP3) in the FULFILL project, we collected quantitative data from five countries: Denmark, France, Germany, Italy and Latvia. In this survey on sufficiency-oriented housing, we recruited a representative sample of approximately 750 to 800 respondents in Denmark, France, Germany and Denmark and around 550 in Latvia, taking into account primarily the individual perspective, added by some questions on the household level.</p> <p>The survey includes a framing experiment presenting two different ways of framing the aim of two sufficiency-oriented policies in the housing sector. In addition, the survey includes data on policy acceptability of these two policy measures and respondents’ preferences for combinations with different other policy measures. Further, the survey also measures socio-economic factors such as age, gender, income, education, household size, life stage, and political orientation. A quantitative assessment of the carbon footprint in the housing domain was also included.</p>
FULFILL dataset - housing policy acceptability - framing experiment Denmark
<p>This dataset represents survey data on sufficiency-oriented housing gathered in the second round of surveys in Denmark in 2023 within the FULFILL project - Fundamental Decarbonisation Through Sufficiency By Lifestyle Changes.</p> <p>As part of Work Package 3 (WP3) in the FULFILL project, we collected quantitative data from five countries: Denmark, France, Germany, Italy and Latvia. In this survey on sufficiency-oriented housing, we recruited a representative sample of approximately 750 to 800 respondents in Denmark, France, Germany and Denmark and around 550 in Latvia, taking into account primarily the individual perspective, added by some questions on the household level.</p> <p>The survey includes a framing experiment presenting two different ways of framing the aim of two sufficiency-oriented policies in the housing sector. In addition, the survey includes data on policy acceptability of these two policy measures and respondents’ preferences for combinations with different other policy measures. Further, the survey also measures socio-economic factors such as age, gender, income, education, household size, life stage, and political orientation. A quantitative assessment of the carbon footprint in the housing domain was also included.</p>
Privacy Policies Paragraph containing Personal Data
<p>The data consists in crawled privacy policies from European privacy policies. They were split into paragraphs and annotated as containing or not personal data.</p> <p>The question that was asked to annotators was "Does this paragraph contain the explicit mention of specific personal data (e.g. name, phone number, social security, …) being collected?".</p> <p>A full description of the dataset can be found in D3.4 of the SMOOTH project</p>
IPBES Data Management Tutorials - Session 2.1: Introduction to the data management policy
<p>The <em>IPBES data management tutorials</em> are short videos to help experts implement the IPBES data management Policy. They cover topics ranging from data management policy, reports, active research data, tools, and examples.</p> <p>The <em>IPBES data management Policy </em>chapter provides an introduction of the IPBES data management policy. It discusses why IPBES has a data management policy and who is responsible for what in the implementation and further development of this policy. </p> <p>This session,<em> Introduction to the data management policy</em><em>, </em>defines what a data management policy is and why it is important.</p>
IPBES Data Management Tutorials - Session 2.4: Implementation of the data management policy
<p>The <em>IPBES data management tutorials</em> are short videos to help experts implement the IPBES data management Policy. They cover topics ranging from data management policy, reports, active research data, tools, and examples.</p> <p>The <em>IPBES data management Policy </em>chapter provides an introduction of the IPBES data management policy. It discusses why IPBES has a data management policy and who is responsible for what in the implementation and further development of this policy.</p> <p>This session on the<em> Implementation of the data management policy </em>provides a brief overview of the contents of the following chapters and how it all works together to improve the transparency and credibility of IPBES. </p>
Climate Policy Database
<p><strong>Recommended Citation</strong></p> <p><strong>Citing this version</strong></p> <pre><code>NewClimate Institute, Wageningen University and Research &amp; PBL Netherlands Environmental Assessment Agency. (2024). Climate Policy Database. DOI: 10.5281/zenodo.154329464</code></pre> <p><strong>Citing all CPDB versions</strong></p> <pre><code>NewClimate Institute, Wageningen University and Research &amp; PBL Netherlands Environmental Assessment Agency. (2016). Climate Policy Database. DOI: 10.5281/zenodo.7774109</code></pre> <p><strong>Peer reviewed publication</strong></p> <p><strong>Description</strong></p> <p>The <a href="http://www.climatepolicydatabase.org">Climate Policy Database</a> (CDPB) is an open, collaborative tool to advance the data collection of the implementation status of climate policies. This project is funded by the European Union H2020 ELEVATE and ENGAGE projects and was, in its previous phase, funded under CD-Links. The database is maintained by NewClimate Institute with support from PBL Netherlands Environmental Assessment Agency and Wageningen University and Research.</p> <p>Although the CPDB exists since 2016, annual versions of the database have only been stored since 2019. </p> <p>The Climate Policy Database is updated periodically. The latest version of the database can be downloaded on the CPDB website or accessed through a <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fpypi.org%2Fproject%2Fcpdb-api%2F&data=05%7C01%7C%7C49011f9a98bd4ff09fa708db92950abd%7C585861118d7348a084329a4ebaecc491%7C1%7C0%7C638264941080639305%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=S7DUrVJOMBNLT1gOB8S7%2FcnlWqFw8z6mBD3wHI%2F9krY%3D&reserved=0">Python API</a>. Each year, we also create a static database, which is included here for version control.</p>
MESSAGEix-GLOBIOM 1.1 R11 no-policy baseline
<p>This dataset contains the parameterization of a no-policy baseline scenario of the global 11-regional <a href="https://docs.messageix.org/projects/global/en/">MESSAGEix-GLOBIOM</a> integrated assessment model. <a href="https://docs.messageix.org/projects/models/en/latest/pkg-data/node.html#region-aggregation-r11">Regions</a>, <a href="https://docs.messageix.org/projects/models/en/latest/pkg-data/year.html">time periods</a>, <a href="https://docs.messageix.org/projects/models/en/latest/pkg-data/codelists.html#commodities-commodity-yaml">commodities</a>, <a href="https://docs.messageix.org/projects/models/en/latest/pkg-data/codelists.html#commodities-commodity-yaml">technologies</a> and <a href="https://docs.messageix.org/projects/models/en/latest/pkg-data/relation.html">relations</a> included in this model are described in a separate <a href="https://docs.messageix.org/projects/models/">repository</a>. The dataset relies on the <a href="https://docs.messageix.org/en/stable/">MESSAGEix modeling framework</a> (<a href="https://doi.org/10.1016/j.envsoft.2018.11.012">Huppmann et al. 2019</a>) and can be imported into MESSAGEix via the <a href="https://docs.messageix.org/en/stable/api.html?highlight=read_xls#message_ix.Scenario.read_excel">read_excel()</a> functionality, for which a <a href="https://github.com/iiasa/message_ix/blob/main/tutorial/westeros/westeros_baseline_using_xlsx_import_part1.ipynb">tutorial</a> is available, or via <a href="https://docs.messageix.org/projects/models/en/latest/api/model-snapshot.html#message_ix_models.model.snapshot.load">snapshot.load()</a> as described <a href="https://docs.messageix.org/projects/models/en/latest/api/model-snapshot.html">here</a>. After the import the scenario can be solved and modified to create new scenarios. Note that the published scenario as included in the <a href="../record/5553976">ENGAGE global scenarios dataset</a> has been run with a release candidate of <a href="https://docs.messageix.org/en/stable/whatsnew.html#v3-4-0-2022-01-27">version 3.4.0</a> of MESSAGEix.</p>
Database of permacultural adoption responses in Mexicali, BC, Mexico. based on Circular Economy, Knowledge Management, and Sustainability policies
<p>Database documenting the perspectives of citizens in Mexicali, Baja California, Mexico, regarding the adoption of permaculture practices. The study is analyzed through the lenses of Knowledge Management, Circular Economy, and Sustainability Policies. The data was collected during the summer of 2024. </p>
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.