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165 results for “political”
Replication package for: Economic and Social Outsiders but Political Insiders: Sweden's Populist Radical Right
<p>This package contains all the code necessary to replicate the figures and tables in Dal Bo, E., F. Finan, O. Folke, T. Persson, and J. Rickne (forthcoming). "Economic and Social Outsiders but Political Insiders: Sweden's Populist Radical Right", Review of Economic Studies. Detailed instructions are also given about how to access the underlying data. </p>
Replication package for: "Political Selection and Economic Policy"
<p>These files contain the replication package for "Political Selection and Economic Policy", published in the Economic Journal. The files contained within the package allow verifying that the codes used to produce the results reported in the paper are functional, and they also allow a partial replication of the results.</p>
Multilevel strategies of political inclusion
<p>Over the last fifty years, eighteen regional assemblies in Europe have debated the extension of voting rights to foreign residents. Yet only Scotland and the Swiss cantons of Neuchâtel and Jura have adopted such legislation. What explains this variation? Through a comparison of debates that have taken place in Italy and Switzerland, I show that multilevel governance expands access to policymaking, but also multiplies veto points in the system. As a result, attempts by regional assemblies to directly give voting rights to foreign residents are generally doomed to fail. At the same time, multilevel governance can be used as a strategy to indirectly shape the political inclusion of different groups. Even if they are unsuccessful in giving the right to vote to foreign residents, these discussions can lead to broader reforms of political rights at the national level.</p> <p> </p>
A Greek Parliament Proceedings Dataset for Computational Linguistics and Political Analysis
<p>The dataset is a new version of the previous upload and includes the following files:</p> <p>1. <strong>dataset_versions/tell_all.csv: </strong>The initial dataset of 1,280,927 extracted speeches, before preprocessing and cleaning. The speeches extend chronologically from July 1989 up to July 2020 and were exported from 5,355 parliamentary sitting record files. The file has a total volume of 2.5 GB and includes the following columns:</p> <ul> <li>member_name: the name of the individual who spoke during a sitting.</li> <li>sitting_date: the date the sitting took place.</li> <li>parliamentary_period: the name and/or number of the parliamentary period that the speech took place in. A parliamentary period is defined as the time span between one general election and the next. A parliamentary period includes multiple parliamentary sessions.</li> <li>parliamentary_session: the name and/or number of the parliamentary session that the speech took place in. A session is defined as a time span of usually 10 months within a parliamentary period during which the parliament can convene and function as stipulated by the constitution. A session can fall into the following categories: regular, extraordinary or special. In the intervals between the sessions the parliament is in recess. A parliamentary session includes multiple parliamentary sittings.</li> <li>parliamentary_sitting: the name and/or number of the parliamentary sitting that the speech took place in. A sitting is defined as a meeting of parliament members.</li> <li>political_party: the political party of the speaker.</li> <li>government: the government in force when the speech took place.</li> <li>member_region: the electoral district the speaker belonged to.</li> <li>roles: information about the parliamentary roles and/or government position of the speaker.</li> <li>member_gender: the gender of the speaker</li> <li>speech: the speech that the individual gave during the parliamentary sitting.</li> </ul> <p>2. <strong>dataset_versions/tell_all_FILLED.csv: </strong>This file is an intermediate version of the dataset that includes improvements in the consistency and completeness of the dataset, with a total volume of 2.5 GB. Specifically, this file is produced by filling the missing names of chairmen of various parliamentary sittings of the "tell_all.csv". It includes the same columns as the "tell_all.csv" file.</p> <p>3.<strong> dataset_versions/tell_all_cleaned.csv: </strong>This version of the dataset is the result of further cleaning and preprocessing and is used for our word usage change study. It consists of 1,280,918 speech fragments of Greek parliament members in the order of the conversation that took place, with a total volume of 2.12 GB. It includes the same columns as the aforementioned versions. The preprocessing includes the replacement of all references to political parties with the symbol "@" followed by an abbreviation of the party name, using regular expressions that capture different grammatical cases and variations. It also includes the removal of accents, strings with length less than 2 characters, all punctuation except full stops, and the replacement of stopwords with "@sw".</p> <p>4. <strong>wiki_data</strong>: A folder of modern Greek female and male names and surnames and their available grammatical cases crawled from the entries of the Wiktionary Greek names category (https://en.wiktionary.org/wiki/Category:Greek_names). We produced the grammatical cases of the missing grammatical entries according to the rules of the Greek grammar and saved the files in the same folder by adding to their filenames the string "_populated.json".</p> <p>5. <strong>parl_members_activity_1989onwards_with_gender.csv</strong>: The Greek Parliament website provides a<br> <a href="https://www.hellenicparliament.gr/Vouleftes/Diatelesantes-Vouleftes-Apo-Ti-Metapolitefsi-Os-Simera/">list</a> of all the elected members of parliament since the fall of the military junta in Greece, in 1974. We collected and cleaned the data, added the gender and kept the elected members from 1989 onwards, matching the available parliament proceeding records. This dataset includes the full names of the members, the date range of their service, the political party they served, the electoral district they belonged to and their gender.</p> <p>6. <strong>formatted_roles_gov_members_data.csv</strong>: As government members we refer to individuals in ministerial or other government posts, regardless of whether they were elected in the parliament. This information is available in the website of the <a href="https://gslegal.gov.gr/?page_id=776&sort=time">Secretariat General for Legal and Parliamentary Affairs</a>. The government members dataset includes the full names of the official individuals, the name of the role they were given, the date range of their service at each specific role and their gender.</p> <p>7. <strong>governments_1989onwards.csv</strong>: A dataset of government information including the names of governments since 1989, their start and end dates, and a URL that points to the respective official government web page of each past government. The data is crawled from the website of the <a href="https://gslegal.gov.gr/?page_id=776&sort=time">Secretariat General for Legal and Parliamentary Affairs</a>.</p> <p>8. <strong>extra_roles_manually_collected.csv</strong>: A dataset with manually collected information from Wikipedia about additional government or parliament posts such as Chairman of the Parliament, party leaders, opposition leaders and other information.</p> <p>9. <strong>all_members_activity.csv</strong>: A dataset of all the information of the aforementioned files 3,4,5,6 merged. Each row of the file includes the full name of the individual, the start and end date of their term of office, the political party and electoral district they belonged to, their gender, the parliamentary and/or government positions that they held along with start and end dates, and the name of the government that was in power during their term of office. An individual can change political parties or become an independent member of the parliament during a parliamentary period, thus having more than one entries/rows in the file.</p> <p>10. <strong>freqs_for_semantic_shift_cleaned_data_decade1990.csv & freqs_for_semantic_shift_cleaned_data_decade2010.csv</strong>: Files of frequencies of words in the corpora of the decades 1990-1999 and 2010-2019.</p> <p>11. <strong>compass_top100.csv:</strong> Top 100 most changed words between the decades 1990-1999 and 2010-2019, as computed with the use of the Compass tool by V. D. Carlo et. al. [1].</p> <p>12. <strong>compass_fc_top100.csv</strong>: Top 100 most changed words between the decades 1990-1999 and 2010-2019, as computed with the use of the Compass tool [1] in combination with the frequency cut-offs of the Gonen et. al. approach [3]. For the frequency cut-offs, the files in bullet 8 are used.</p> <p>13. <strong> procrustes_top100.csv</strong>: Top 100 most changed words between the decades 1990-1999 and 2010-2019, as computed with the use of the Orthogonal Procrustes approach of Hamilton et. al. [2].</p> <p>14. <strong>nn_top100.csv</strong>: Top 100 most changed words between the decades 1990-1999 and 2010-2019, as computed with the use of the Gonen et. al. approach [3].</p> <p>15. <strong>second_order_top100.csv</strong>: Top 100 most changed words between the decades 1990-1999 and 2010-2019, as computed with the use of the Second-Order Similarity approach by Hamilton et. al. [4].</p> <p>16. <strong>top100_minfreq50.xls</strong>: An .xls file for convinient viewing of the top 100 most changed words per approach with minimum frequency of 50 occurrences, produced by merging the aforementioned files 11, 12, 13, 14, 15 and 16.</p> <p>17. <strong>freqs_for_semantic_shift_cleaned_data_period1997_2007.csv & freqs_for_semantic_shift_cleaned_data_period2008_2018.csv</strong>: Files of frequencies of words in the corpora of the decades before (1997_2007) and during (2008_2018) the Greek economic crisis.</p> <p>18. <strong>semantic_shifts_dichotomy_crisis_compass_1997_2007_2008_2018_atleast50.csv</strong>: A file with the top 100 most changed words between between the decades before (1997-2007) and during (2008-2018) the Greek economic crisis. The computations are implemented with the use of the Compass tool.</p> <p>19. <strong>selected_topics_shift_per_period_compass.csv</strong>: The usage change of selected topics/words of generic political interest between pairs of consecutive parliamentary periods. The computations are implemented with the use of the Compass tool.</p> <p>20. <strong>semantic_shifts_party_embeddings_per_period_merged_compass.csv</strong>: The usage change of selected political party names that have played an important role in recent political history, namely New Democracy (ND), the Panhellenic Socialist Movement (PASOK), the Coalition of the Radical Left - Progressive Alliance (SYRIZA), the Communist Party of Greece (KKE), the Coalition of the Left, of Movements and Ecology (SYN) and Golden Dawn (GD).</p> <p>-------------</p> <p><strong><em>Citations:</em></strong></p> <p>[1] Valerio Di Carlo, Federico Bianchi, and Matteo Palmonari. Training Temporal Word Em- beddings with a Compass. In <em>Proceedings of the Thirty–Third AAAI Conference on Artificial Intelligence</em>, AAAI’19, pages 6326–6334, 2019. doi: 10.1609/aaai.v33i01.33016326.</p> <p>[2] William L. Hamilton, Jure Leskovec, and Dan Jurafsky. Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change. In <em>Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)</em>, ACL 2016, pages 1489– 1501, Berlin, Germany, August 2016. Association for Computational Linguistics. doi: 10. 18653/v1/P16-1141. URL https://www.aclweb.org/anthology/P16-1141.</p> <p>[3] Hila Gonen, Ganesh Jawahar, Djamé Seddah, and Yoav Goldberg. Simple, Interpretable and Stable Method for Detecting Words with Usage Change across Corpora. In <em>Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics</em>, ACL 2020, pages 538– 555, Online, July 2020. Association for Computational Linguistics. doi: 10.18653/v1/2020.acl- main.51. URL https://aclanthology.org/2020.acl-main.51.</p> <p>[4] William L. Hamilton, Jure Leskovec, and Dan Jurafsky. Cultural Shift or Linguistic Drift? Comparing Two Computational Measures of Semantic Change. In <em>Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing</em>, EMNLP 2016, pages 2116–2121, Austin, Texas, November 2016. Association for Computational Linguistics. doi: 10.18653/v1/D16-1229. URL https://www.aclweb.org/anthology/D16-1229.</p> <p>-------------</p> <p><strong><em>Acknowledgments:</em></strong></p> <p>This work was supported by the European Union’s Horizon 2020 research and innovation program ``FASTEN'' under grant agreement No 825328 and the non profit data journalism organization iMEdD.org.</p>
Dateset for "The Political Preferences of LLMs"
<p>results.rar: contains the results of administering 11 political orientation tests to 24 conversational LLMs + 5 base models + 3 politically aligned LLMs.</p> <p>.log files contain the logs during automated test administration </p> <p>.png files contain a screen capture of LLM test results</p> <p>.json files contain the LLM test results in JSON format</p> <p>.jsonl files contain all the LLM responses to test questions</p> <p>stance detection.rar: annotation samples for stance detection accuracy estimation</p> <p>finetuning_politically_aligned_models.rar: data for fine tuning politically aligned models</p> <p>tabulated_results.csv contains the mean and standard deviation of test results across test retakes (n=10) for all models. </p>
From Fear to Love: Dissecting Political Trust in China
<p>The data is about the paper "From Fear to Love: Dissecting Political Trust in China"</p>
Dataset for "Is Wikipedia Politically Biased?"
<p><span><span>·<span> </span></span></span><span>This work aims to determine whether there is evidence of political bias in English Wikipedia articles.</span></p> <p><span><span>·<span> </span></span></span><span>Wikipedia is one of the most visited domains on the Web, attracting hundreds of millions of unique users per month. Wikipedia content is also routinely used for training Large Language Models (LLMs), which are the core engines driving cutting edge AI systems.</span></p> <p><span><span>·<span> </span></span></span><span>To study political bias in Wikipedia content, we analyze the sentiment (<em>positive</em>, <em>neutral</em> or <em>negative</em>) with which a set of target terms (N=1,628) with political connotations (i.e. names of recent U.S. presidents, U.S. congressmembers, U.S. Supreme Court Justices, or Prime Ministers of Western countries) are used in Wikipedia articles. </span></p> <p><span><span>·<span> </span></span></span><span>We do not cherry pick the set of terms to be included in the analysis but instead use publicly available pre-existing lists of terms from Wikipedia and other sources.</span></p> <p><span><span>·<span> </span></span></span><span>We find a mild to moderate tendency in Wikipedia articles to associate public figures politically aligned right-of-center with more negative sentiment than left-of-center public figures.</span></p> <p><span><span>·<span> </span></span></span><span>These favorable associations for left-leaning public figures are apparent for names of recent U.S. Presidents, U.S. Supreme Court Justices, U.S. Senators, U.S. House of Representatives Congressmembers, U.S. State Governors, Western countries’ Prime Ministers, and prominent U.S. based journalists and media organizations.</span></p> <p><span><span>·<span> </span></span></span><span>Despite being common, these politically asymmetrical sentiment associations are not ubiquitous. We find no evidence of them in the sentiment with which names of U.K. MPs and U.S. based think tanks are used in Wikipedia articles.</span></p> <p><span><span>·<span> </span></span></span><span>We also find larger associations of negative emotions (i.e. <em>anger</em> and <em>disgust</em>) with right-leaning public figures and positive emotion (i.e. <em>joy</em>) with left-leaning public figures.</span></p> <p><span><span>·<span> </span></span></span><span>The trends just described constitute suggestive evidence of political bias embedded in Wikipedia articles.</span></p> <p><span><span>·<span> </span></span></span><span>We also find some of the aforementioned sentiment political associations embedded in Wikipedia articles popping up in OpenAI’s language models. This is suggestive of the potential for biases in Wikipedia content percolating into widely used AI systems.</span></p> <p><span><span>·<span> </span></span></span><span>Wikipedia’s <em>neutral point of view policy</em> (NPOV) aims for articles in Wikipedia to be written in an impartial and unbiased tone. Our results suggest that Wikipedia’s <em>neutral point of view policy</em> is not achieving its stated goal of political viewpoint neutrality.</span></p> <p><span><span>·<span> </span></span></span><span>This report highlights areas where Wikipedia can improve in how it presents political information. Nonetheless, we want to acknowledge Wikipedia’s significant and valuable role as a public resource. We hope this work inspires efforts to uphold and strengthen Wikipedia’s principles of neutrality and impartiality.</span></p> <p>The set of 1,653 target terms used in our analysis, the sample of Wikipedia paragraphs where they occur (as of 2022) and their sentiment and emotion annotations are provided in the files:</p> <p>- WikipediaParagraphsWithTargetNGramsAndSentiment.csv</p> <p>- WikipediaParagraphsWithTargetNGramsAndEmotion.csv</p>
Comparative Engagement: Political vs. Socio-humanitarian
<p>The war in Ukraine and the resulting flight of millions of people have once again put the reception of refugees at the centre of the public debate in Europe. Similar to 2015, volunteers are pitching in and organising support or politically campaigning for the rights of refugees. It is remarkable that many people are opening the doors of their houses and flats to those seeking protection. Private accommodation is currently making a significant contribution to ensuring the accommodation of arrivals from Ukraine. At the same time, there is a need for other forms of engagement for refugees, be it in accompanying them to the authorities, in language acquisition or in sponsorships.</p> <p>At the moment, however, we know little about what exactly engagement looks like in times of war in Ukraine. We don't know who is getting involved, for what reasons and with what attitude patterns. Are they the same people who were already active in 2015/2016, or is the Ukraine war activating other population groups? Similarly, we know little about the concrete practice of housing, such as the spatial conditions, the support and counselling needs of people hosting refugees, and the challenges. Has their engagement in general and private hosting in particular changed how they perceive refugees? By answering these questions, we can capture the current extent, shape, opportunities and challenges of refugee engagement. The findings will also enable us to better support engaged people and the government agencies, initial reception centres and charities that work with them.</p> <p>In order to close the research gap and address the acute lack of data, the project pursues an integrated research design that combines findings from different surveys with different sampling strategies, content-related foci and cooperation partners. This includes firstly a quantitative survey of private accommodation providers (including the extent, form and duration of accommodation, access to support services, practices and challenges of private accommodation (in short "private accommodation survey") and secondly a population survey of engaged people (in short "engagement survey"). Building on and inspired by previous surveys on refugee engagement (Volunteer Survey 2019, Allensbach Study on Refugee Engagement 2018), the survey allows for more differentiated insights into fields of activity, motivations, and experiences in engagement (including reasons for engagement termination). Finally, we supplement the quantitative surveys with qualitative background interviews to gain relevant contextual knowledge, an analysis of social media debates, and possibly, from 2023 onwards, discussion rounds on selected key questions with volunteers ("focus groups").</p> <p>The results of the project will enable us to formulate recommendations for action for politics and society on how to sustainably strengthen the engagement for refugees and improve the accommodation situation.</p>
Dataset Political Gender Stereotypes in Flanders
<p>Dataset of online survey experiment conducted in 2017 among 2 500 Flemish (Belgian) respondents on the topic of political gender stereotypes. </p>
Picture this, power politics in international aid: A visual content analysis of the 2014 Ebola epidemic in West Africa, Dataset
<p>Literature on framing of the African continent is rich, however, similar framing literature on international actors in Africa is significantly under explored. This study investigated the visual frames through which Chinese, French, and U.S. newspapers engaged in nation branding by portraying international aid during the 2014 Ebola outbreak in West Africa. Data from the <em>People’s Daily</em>, <em>Le Monde</em>, and <em>The New York Times</em> showed that while Western coverage was negatively toned on frames of medical aid and culture, Chinese coverage was more positively toned on frames of medical aid and the military. Such findings contribute to scholarly understandings of visual media framing as functions of political power struggles and nation branding. </p>
EUCROWD - Citizen's crowdsourcing in politics and policy-making
<p>TRILLION project and platform presentation as a case presentation on citizen's crowdsourcing in politics and policy-making.</p>
CATCH-EyoU: Processes in Youth's Construction of Active EU Citizenship: Cross-national Wave 1 Questionnaires: Italy, Sweden, Germany, Greece, Portugal, Czech Republic, UK, and Estonia – EXTRACT_Political passivity
<p>This dataset contains the data underlying the following publication: Dahl, V., Amnå, E., Banaji, S., Landberg, M., Šerek, J., Ribeiro, N., ... & Zani, B. (2017). Apathy or alienation? Political passivity among youths across eight European Union countries.European Journal of Developmental Psychology, 1-18, https://doi.org/10.1080/17405629.2017.1404985.</p>
CATCH-EyoU: Meanings and Practices of Youth Participation and Cases of Successful Participation: Cross-national Documentary Evidence of Youth Civic and Political Participation Initiatives
<p>The data set integrates documentary evidence of national youth civic and political participation initiatives in Italy, Sweden, Germany, Greece, Portugal, Czech Republic, UK, and Estonia. The evidence are represented as pamphlets, brochures, leaflets, newsletters, social media and websites, you tube videos, meme and vine campaigns. The participation initiatives are selected with a focus on initiatives used by national youth citizenship organizations for generating, supporting, communicating and engaging young people’s active participation in diverse and varied causes (the environment, voting at 16, anti-fees and cuts campaigns, rights around civic spaces and youth centers, employment and jobs-related campaigns, issues around race and religion, volunteering, refugees, local housing and education).</p> <p> </p> <p>The data set consists of: (1) a spreadsheet integrating data from all partner countries, and containing qualitative descriptions of activities and cataloguing associated materials of youth civic and political organizations; (2) a textual report containing exemplar images of publicly available online newsletters, minutes, reports and campaign materials from across the consortium (where feasible), copyright cleared and creative commons screenshots of websites, invitation letters, records of personal conversations with members of youth civic teams, quotes from researcher-conversations on social media or f-2-f with members of teams with names redacted.</p> <p>Personal data and all non-public data has been anonymized in order to protect participants’ privacy.</p> <p>The data can be re-used by researchers who want to compare our cross- European data with similar data collected in different countries, to perform textual analysis (content analysis and/or data mining) on our data. Also other stakeholders may be interested in reanalyzing our data for comparative aims.</p>
Political ethnic stereotypes in Flanders - Student sample
<p>Dataset of an online survey experiment conducted in 2017 among Flemish university students on the topic of political ethnic stereotypes.</p>
India, political map 1857
<p>India, political map 1857</p>
Data, code snippets, and resources of BMF CP51: Political ideology, climate change belief, and potable water reuse willingness in the USA
<p>The dataset, data description, code snippets, and figures related to the Bayesian analysis of BMF CP 51 on SM3D Portal were uploaded to Zenodo to enhance transparency and assist in later replication and validation (https://mindsponge.info/posts/246). The original dataset can be found at: https://www.sciencedirect.com/science/article/pii/S2352340920301839</p>
Political Advertising on Facebook During the 2022 Australian Federal Election
<p>This repository contains data on political advertisements posted on Facebook and Instagram during the three months leading up to the 2022 Australian federal election. The data was collected using the Meta Ad Library API and provides insights into digital political campaigning strategies in Australia.</p> <h2>Contents</h2> <p>The repository includes the following files:</p> <ul> <li><code>datasheet.txt</code>: A detailed datasheet following the guidelines of Gebru et al. (2021), providing transparency about data collection, preprocessing, and handling procedures.</li> <li><code>party_information.csv</code>: Manually annotated data matching candidates, electorates, and parties based on ad funding entity information.</li> <li><code>maps_australia.zip</code>: A set of Australian maps used for visualizing the geographical distribution of ads during the campaign period.</li> <li><code>2022_AU_election_raw.zip</code>: Raw data collected from the Meta Ad Library API, containing comprehensive information on political ads run on Facebook and Instagram in Australia during the specified period.</li> <li><code>keywords.csv</code>: A curated list of keywords relevant to the 2022 Australian federal election, useful for content analysis and topic modeling of the advertisements.</li> </ul> <h2>Related Code Repository</h2> <p>The code used to analyze this data and reproduce the results presented in the paper "Political Advertising on Facebook During the 2022 Australian Federal Election" can be found in a separate repository:</p> <p><a href="https://anonymous.4open.science/r/Political-Advertising-2022-AU-Federal-Election-3E75/README.md">https://anonymous.4open.science/r/Political-Advertising-2022-AU-Federal-Election-3E75/README.md</a></p> <h2>References</h2> <p>Gebru, T., Morgenstern, J., Vecchione, B., Vaughan, J. W., Wallach, H., Iii, H. D., & Crawford, K. (2021). Datasheets for datasets. Communications of the ACM, 64(12), 86–92.</p>
Modelling Political Aggression On Social Media Platforms
<p>This dataset was curated from social media for the purpose of research. LICENSE: CC-BY-SA-NC 4.0</p>
Flemish Political Ambition Survey
<p>Dataset based on a survey about political ambition among a random sample of the youth population ( aged 18-35) in Flanders (Belgium), N = 1,000</p>
Quotatives Indicate Decline in Objectivity in U.S. Political News
<p>Data to reproduce results for the paper </p> <p>Quotatives Indicate Decline in Objectivity in U.S. Political News (ICWSM 2023)</p> <p>Code: https://github.com/epfl-dlab/quotative_bias</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.