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35 results for “SDG”
Aurora SDG Research Dashboard and Classifier - Instructions Videos
<p>Instruction videos about the Aurora SDG Research Dashboard, SDG Classifier, Badges and API.</p><p><a href="https://zenodo.org/doi/10.5281/zenodo.10040524">Also read the User Guides</a>.</p>
NDC-SDG Connections: Data on updated NDC submissions (V2)
<p>NDC-SDG Connections is a joint initiative of the German Institute of Development and Sustainability (IDOS) and the Stockholm Environment Institute (SEI). The research and visualisation project aims at illuminating synergies between the 2030 Agenda for Sustainable Development and the Paris Agreement, and at identifying entry points for coherent policies that promote just, sustainable and climate-smart development.</p> <p>The objective of the NDC-SDG Connections is to: foster a dialogue on meaningful interaction between the 2030 Agenda and the Paris Agreement, globally and at the national level; to increase transparency with easy accessibility to all climate activities; and to cultivate learning and catalyse partnerships between countries and other actors to raise the ambition of future NDCs.</p> <p>With its second version with data on the updated NDC submissions (V2), the NDC-SDG Connections project opened its data for public re-use. In 2025, the V2 is updated with new data to version 1.2.0. The data is provided in the following formats:</p> <ul> <li>single .csv files (data per SDG)</li> <li>zip .csv file (data per SDG for all SDG in one zip) </li> </ul> <p>Visit the Online Data Visualisation to interact directly with the data<strong>: www.NDC-SDG.info</strong></p> <p> </p> <p><strong>Note:This data set contains data for second NDC submissions (V2)</strong>. The terms ‘First’ and ‘Updated’ do not fully follow the UNFCCC nomenclature. For most countries, updated NDCs are called ‘First updated NDC’ or ‘Enhanced NDCs’, while some countries call their updated NDCs for ‘Second NDC’. In order to make it comprehensible, the tool developers have chosen to distinguish between ‘First’ and ‘Updated’. Detailed description of which version is counted as ‘First’ and which as ‘Updated’ has been documented in the data.<br><br></p> <p> </p> <p><strong>Updated NDCs included in version 1.2.0 of V2 - </strong><strong>New data was added for 27 updated NDCs plus one NDC updated to a newer version:</strong></p> <p>New Updated NDCs:</p> <p>Azerbaijan, Benin, Democratic Republic of the Congo, Grenada, India, Kyrgyzstan, Madagascar, Mali, Montenegro, Nepal, Nigeria, Oman, Qatar, Saint Kitts and Nevis, Saint Lucia, Samoa, Sierra Leone, Singapore, South Sudan, Sri Lanka, Suriname, Togo, Tunisia, Tuvalu, Ukraine, United States of America</p> <p>New version of Updated NDC:</p> <p>Namibia’s NDC has been updated to the most recent version.</p>
List of countries and NDCs in the NDC-SDG Connections: Data on updated NDC submissions (V2)
<p>NDC-SDG Connections is a joint initiative of the German Institute of Development and Sustainability (IDOS) and the Stockholm Environment Institute (SEI). The research and visualisation project aims at illuminating synergies between the 2030 Agenda for Sustainable Development and the Paris Agreement, and at identifying entry points for coherent policies that promote just, sustainable and climate-smart development.</p> <p>The objective of the NDC-SDG Connections is to: foster a dialogue on meaningful interaction between the 2030 Agenda and the Paris Agreement, globally and at the national level; to increase transparency with easy accessibility to all climate activities; and to cultivate learning and catalyse partnerships between countries and other actors to raise the ambition of future NDCs.</p> <p>With its second version, the NDC-SDG Connections project opened its data for public re-use. <br><br>This dataset contains a list of the countries and NDCs which are included in the NDC-SDG Connections tool as part of updated NDC submissions (V2), in .xlxs format. It is a complement to the dataset available at: https://doi.org/10.5281/zenodo.11400384 <br><br><strong>Visit the Online Data Visualisation to interact directly with the data: www.NDC-SDG.info</strong></p>
Maps of the Sustainable Development Goal (SDG) indicator 15.3.1 with its sub-indicators for the entire Amazon River Basin
<p>Maps of the SDG indicator 15.3.1 adopted by the United Nations Convention to Combat Desertification (UNCCD) together with its sub-indicators for the Amazon River Basin for the period 2001-2020. The sub-indicators are trajectory (or trend), state, and performance. The SDG indicator 15.3.1 was calculated using the procedures described in the second version of the Good Practice Guidance for SDG Indicator 15.3.1. The annual LCLU maps from the MapBiomas project at 30 m spatial resolution and the 16-day MOD13Q1 NDVI and SoilGrids dataset were used as inputs. In addition, annualized maps of drought severity derived from SPI12, SPEI12, and scPDSI are added. </p> <p>A total of seven GeoTIFF files in Geographic Tagged Image File Format (GeoTIFF) format are provided at 250 m spatial resolution.</p> <p>Coding for the SDG indicator 15.3.1, trajectory, state, and performance.</p> <p>-32768 is ‘No data’</p> <p>-1 is ‘Degraded’</p> <p>0 is ‘Stable’’</p> <p>1 is ‘Improvement’</p> <p>Coding for the drought severity.</p> <p>From 0 (minimum drought severity) to 1 (maximum drought severity).</p>
DOI's with SDG labels on Target level | 1.4M research articles (2009-2020) related to Sustainable Development Goals
<p>Table content: This data set contains 1.4 million publication DOI's related to the <a href="http://metadata.un.org/sdg/">Targets of the Sustainable Development Goals</a> in the period 2009 - 2020.</p> <p>Table dimensions: rows: 1.4 million, columns: 4 / rows: 1.4 million, columns: 180</p> <p>Table columns: <a href="https://en.wikipedia.org/wiki/Digital_object_identifier">doi</a> | date | <a href="http://metadata.un.org/sdg/ontology#Target">sdg_target</a> | <a href="http://metadata.un.org/sdg/ontology#Goal">sdg_goal</a> / <a href="https://en.wikipedia.org/wiki/Digital_object_identifier">doi</a> | date | <a href="http://metadata.un.org/sdg/ontology#Target">169 sdg_targets</a> | <a href="http://metadata.un.org/sdg/ontology#Goal">17 sdg_goalsl</a></p> <p>Table formats: <a href="https://en.wikipedia.org/wiki/Comma-separated_values">.csv</a> | <a href="https://en.wikipedia.org/wiki/Microsoft_Excel">.xlsx</a> | <a href="https://en.wikipedia.org/wiki/Apache_Parquet">.parquet</a></p> <p><em>How we made this data:</em></p> <p>We have made a search on <a href="https://scopus.com">Scopus </a>using the <a href="https://aurora-network-global.github.io/sdg-queries/">Aurora SDG queries version 5</a> for each of the targets, with a limited year range from 2009 till 2020.</p> <p>Good to know: don't be alarmed if you can find a doi that is labeled with more than one target (~16%). This is not a bug, this is a feature... We used 169 queries, one for each target, a publication can appear in more han one result set.</p> <p>Read this <a href="https://zenodo.org/record/4964606/files/Evaluation_on_accuracy_of_mapping_science_to_the_United_Nations__Sustainable_Development_Goals__SDGs__of_the_Aurora_SDG_queries.pdf?download=1">report to learn more about the accuracy</a> of the queries and the data result sets.</p> <p><em>How can you use this data:</em></p> <p>You can use this data to 1. quickly match your existing publication lists to this list to see how that your publications are related to the targets of the SDG's. 2. use these as a basis / seed set / gold set to train more advanced text / graph classifiers (after you have extracted title, abstract or even full-text using crossref.org, unpaywall.org, etc)</p> <p><em>How can you help:</em></p> <p><a href="https://sites.google.com/vu.nl/aurora-sdg-research-dashboard/sdg-knowledge-base#h.d2pd3c39k276">Let us know</a> how you use this data. We'll put your project on the list in our <a href="https://sites.google.com/vu.nl/aurora-sdg-research-dashboard/sdg-knowledge-base">SDG matching knowledge base.</a></p>
Sustainable Development Goals (SDG) in citizen science - Dataset
<p>The assignment results of SDGs to CS project descriptions are provided in the following dataset. The analysis was conducted based on data retrieved from the CSTRack database on 2022/09/15. </p> <p>See further detail about the study in D2.2 section 7.3.</p> <p><strong>Content and grouping: </strong></p> <ul> <li> <p>The dataset contains the following details: Platform ID (from which platform the CS project descriptions were retrieved), Project Title (Name of the CS project), SDG assignment results (More details about the assignment technique can be found in D3.2 ‘Web Analytics Toolset and Workbench’ - ESA backend), SDG assignment reported in section 7.2 of D2.2 (which only considered the SDG assignment with the highest similarity).</p> </li> </ul>
NDC-SDG Connections: Data on first NDC submissions (V1)
<p>NDC-SDG Connections is a joint initiative of the German Institute of Development and Sustainability (IDOS) and the Stockholm Environment Institute (SEI). The research and visualisation project aims at illuminating synergies between the 2030 Agenda for Sustainable Development and the Paris Agreement, and at identifying entry points for coherent policies that promote just, sustainable and climate-smart development.</p> <p>The objective of the NDC-SDG Connections is to: foster a dialogue on meaningful interaction between the 2030 Agenda and the Paris Agreement, globally and at the national level; to increase transparency with easy accessibility to all climate activities; and to cultivate learning and catalyse partnerships between countries and other actors to raise the ambition of future NDCs.<br> <br> With its second version, the NDC-SDG Connections project opened its data for public re-use. The data on first NDC submissions (V1) is provided in the following formats:</p> <ul> <li>single .csv files (per data per SDG)</li> <li>zip .csv file (data per SDG for all SDG in one zip)</li> <li>.xlxs file (Excel)</li> </ul> <p><strong>Visit the Online Data Visualisation to interact directly with the data: www.NDC-SDG.info</strong></p> <p>Additional files:</p> <ul> <li>.pdf file documenting the methodological framework including the coding and data validation process of the NDC-SDG Connections project</li> <li>.csv file with all NDCs included into the analysis (V1)</li> </ul> <p><br> <strong>Note: This data set contains data for first NDC submissions (V1). </strong>The terms ‘First’ and ‘Updated’ do not fully follow the UNFCCC nomenclature. For most countries, updated NDCs are called ‘First updated NDC’ or ‘Enhanced NDCs’, while some countries call their updated NDCs for ‘Second NDC’. In order to make it comprehensible, the tool developers have chosen to distinguish between ‘First’ and ‘Updated’. Detailed description of which version is counted as ‘First’ and which as ‘Updated’ has been documented in the data.</p> <p> </p>
The STRINGS queries to identify documents related to the SDGs (+ country-SDG data)
<div>This page contains three documents related to the work the STRINGS team has developed on mapping research related to the Sustainable Development Goals (SDGs): <br>1. A document explaining the methodology used to create search queries for identifying documents related to SDGs 1-16. <br>2. An Excel file containing the search queries themselves. <br>3. An additional Excel file containing country-SDG level data used in the paper "Countries’ research priorities in relation to the Sustainable Development Goals".<br><br>The procedure for creating SDG queries was developed for the STRINGS project. For both the project and the paper, the procedure to identify SDG-related publications does not rely exclusively on search queries. We apply each SDG query to research areas obtained from a publication-level clustering algorithm, based on direct backward and forward citations. This enables us to select research areas related to SDGs and include all the publications contributing to that area. This approach has several advantages, including the ability to include publications that do not use SDG-related language in their abstract or title but still contribute to SDG-related research. <br><br>For further insights, the platform, data, and thresholds used to understand which research areas are associated with an SDG are openly available <a href="https://public.tableau.com/profile/ed.noyons#!/vizhome/UKStringsSDGtocommunities/Dashboard1">here</a>.<br><br>In the <a href="https://strings.org.uk/">STRINGS report</a>, you can explore applications to map and characterize publications and patents related to the SDGs. <br><br>Additionally, the paper "Countries’ research priorities in relation to the Sustainable Development Goals" provides a country-level analysis of the alignment between research priorities and SDG challenges. </div>
NDC-SDG Linkages
<p>The NDC-SDG linkage analysis is a comprehensive study, which examines the degree of alignment between the (I)NDCs and the 169 targets of the 2030 Sustainable Development Agenda. Climate action texts were extracted from the NDCs and aligned with relevant targets. The study was carried by WRI to support joint implementation of both the Paris Agreement and the 2030 Agenda.</p> <p> </p> <p>https://www.climatewatchdata.org/data-explorer/emission-pathways?emission-pathways-categories=All%20Selected&emission-pathways-indicators=All%20Selected&emission-pathways-locations=All%20Selected&emission-pathways-models=All%20Selected&emission-pathways-scenarios=All%20Selected&emission-pathways-subcategories=All%20Selected&page=1</p>
A comparison of different methods of identifying publications related to the United Nations Sustainable Development Goals: Case Study of SDG 13: Climate Action
<p>This data set pertains to the following research article: Purnell, P.J. (2022) <em>A comparison of different methods of identifying publications related to the United Nations Sustainable Development Goals: Case Study of SDG 13 – Climate Action</em>. arXiv:2201.02006</p>
National SDG-7 performance assessment to support achieving sustainable energy for all within planetary limits
<p>Supplementary materials for publication Gebara et al. 2022, "National SDG-7 performance assessment to support achieving sustainable energy for all within planetary limits". </p>
Dataset: iShares MSCI Global Sustainable Development Goals ETF (SDG) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
AI for SDG Acceleration - NSG MasterClass in Cooperation with MGG-PRODIGEES
<p>The video contains the lecture by Dr Reevana Balmahoon on artificial intelligence as a tool for accelerating the achievement of the Sustainable Development Goals (SDGs). Her presentation was part of the joint conference “International Capacity Development for the Civil Service - The Sustainable Digitalisation Agenda”, May 5-8, 2024, Cape Town, South Africa. The conference was jointly organised by the German Institute of Development and Sustainability (IDOS) and the National School of Government of South Africa (The NSG) in the framework of the ‘Managing Global Governance (MGG) network and its PRODIGEES project on digitalisation towards sustainable development. Dr Balmahoon is an AI and extended reality research lead of the South African Council for Scientific and Industrial Research (CSIR). The lecture and ensuing discussion, with responses from Dr Sven Grimm (IDOS) and Serusha Govender (Chatham House), were part of the NSG Master Class Series.</p>
SDG Knowledge Hub Dataset of SDG-labeled News Articles
<p>Dataset of articles published on the IISD SDG Knowledge Hub (<a href="http://sdg.iisd.org/">sdg.iisd.org</a>). The SDG Knowledge Hub is an online resource publishing news and commentary regarding the implementation of the United Nations’ 2030 Agenda for Sustainable Development and the Sustainable Development Goals (SDGs). Labels assigned by the authors and validated by SDG Knowledge Hub editors indicate which of the 17 SDGs an article addresses.</p> <p>The data set was generated for the following publications. Please consider citing the publication if you use the data. </p> <p>Wulff, D. U., Meier, D. S., & Mata, R. (2023). Using novel data and ensemble models to improve automated labeling of Sustainable Development Goals. <em>arXiv preprint arXiv:2301.11353</em>.</p> <p>The data contain 9,172 articles downloaded on September 15th, 2021, and are shared with permission from the SDG Knowledge Hub.</p> <p>The comma-separated data file includes the following columns:</p> <p>url - URL of the article.</p> <p>title - Title of the article.</p> <p>type - Type of article. Either "News", "Policy briefs", "Guest articles", or "Generation 30". </p> <p>text - Text of the article. </p> <p>date - Publishing date of article.</p> <p>sdgs - SDG labels assigned by authors and editors. </p> <p>SDG-01 to SDG-17 - SDG indicators extracted from the author and editor label. </p>
Capacity Building for GIS-based SDG Indicator Analysis with Global High-resolution Land Cover Datasets - training datasets
<p>Sample datasets for the <strong>Case Studies</strong> section of the <em> Capacity Building for GIS-based SDG Indicator Analysis with Global High-resolution Land Cover Datasets </em>web book (<a href="https://isprs-gis-sdg.readthedocs.io">https://isprs-gis-sdg.readthedocs.io</a>)</p>
SDG EDUCATION DATASET
<p>Dataset created in order to analyse the existence of documents around the Sustainable Development Goals in the scientific literature in Education produced since 2015</p>
SDG Mapping Results for 1,000 Publications from Large Language Models: GPT-4o, Mixtral, Llama 2, Llama 3, Gemma 2, Qwen 2 and GPT-4o-mini
<p>Randomly selected 1,000 publications from the Swinburne University of Technology research bank were used for SDG mapping tasks with the large language model GPT-4o and the open-source models Mixtral, Llama 2, Llama 3, Gemma 2, Qwen 2 and GPT-4o-mini.</p> <p>The input to each model consisted of the publication’s title and abstract.</p> <p>The designed prompt is as follows: </p> <p>PROMPT = '''Analyze the publication and determine the SDGs it aligns with. Evaluate against all the 17 SDGs provide the reason for alignment. In the end summarise the confidence levels(%) for each assigned SDG in JSON format. For example: {example}. Title: {title} Description: {description}'''</p> <p>example = '''{ 'Goal 6': 0.67, 'Goal 11': 0.50, 'Goal 3': 0.25}'''</p>
SDG Paper Datasets
<p>This resource contains dataset used in the paper describing the SDG software framework: "A Sequence Distance Graph framework for genome assembly and analysis".</p> <p>Specifically for the section of the paper "Hybrid assembly of short and long reads", the folder "ecoli" contains the Illumina Miseq 2x300bp reads that were used.</p> <p>Specifically for the section of the paper "Analysing a simulation of heterozygous parent-child trio with short reads", the "trio" folder contains the simulated genomes of the trio's 2 parental individuals and 1 offspring individual, as well as simulated reads produced from those genomes.</p>
Puntuaciones SDG por Empresa según Robeco
<p>Dataset simulado. El dataset Puntuaciones SDG por Empresa según Robeco (companies_sdg_scores.csv) contiene información sobre la contribución de empresas individuales a los Objetivos de Desarrollo Sostenible de las Naciones Unidas (SDGs).</p> <p>Este dataset no solo muestra la puntuación total de SDG de cada empresa, sino que también detalla su rendimiento en objetivos específicos, como el hambre cero, la igualdad de género, y la acción por el clima, entre otros. Atributos: Company Name, Total SDG Score, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17. No se encuentra la columna con el número 10 debido a que ninguna de las compañías lo contiene.</p>
Eight archetypes of Sustainable Development Goal (SDG) synergies and trade-offs
<p>Data S1 - Details of system archetype application articles reviewed systematically.</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.