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5 results for “community and citizen science”
Datasets containing the results from the analysis on SDGS and eHealth inside the Citizen Science Community on Twitter
<p>This datasets contain the results from our analyses of the Citizen Science Community on Twitter. These analyses have been done to better understand the discussion about SDGs, eLearning and eHealth.</p> <p><strong>T</strong>he purpose of sharing these datasets is to provide the basis to reproduce the results reported in the associated deliverable. These files are not raw data, since due to privacy concerns we can not share personal information from Twitter.</p> <p><strong>dominant_topics_anonym.xlsx</strong>: Excel datasheet. This dataset contians the distribution of the most discussed topics inside the SDGs discussion.</p> <p><strong>Edges_Hashtag_connected.csv</strong>: CSV file. This dataset contains the edges to build the network of connected hashtags. This edges can be used to build a network and explore the connections or to statiscally analyse the results.</p> <p><strong>hashtags.csv</strong>: CSV file. This dataset contains the results of the most used hashtags in the analysis about eLearning. <br> </p> <p><strong>hashtags_treemap_health.xlsx</strong>: Excel datasheet. This dataset contains the results of the most frequent hashtags in the eHealth analysis.</p> <p><strong>ldavis_prepared_ieee17.html</strong>: HTML file. This file contains the Intertopic distance map and most salient terms from the topic modelling analysis done in the SDGs conversation study.</p> <p><strong>Most_retweeted_accounts.xlsx</strong>: Excel datasheet. This dataset contains the top 20 users that receive more retweets in the conversation around eHealth. The column called Indegree refers to the topological value calculated from the network of retweets. This indegree is equivalent to the number of retweets received. On the other hand, Outdegree is the opposite, so number of retweets given to others.</p> <p><strong>Most_retweeting_account.xlsx</strong>: Excel datasheet. This dataset presents the opposite part of the previous one, the accounts that retweet the most from the eHealth analysis. The columns contain the same indicators: Indegree and Outdegree.</p> <p><strong>sdgs_count_publish.csv</strong>: CSV file. This dataset contains the number of tweets assigned to the different SDGs from the analysis done on the conversation about these Goals.</p> <p><strong>sdgs_tweets_sdgsaccess.xlsx</strong>: Excel datasheet. Same file as the previous one in other format to ease the handling in Excel.</p> <p><strong>top_hash_health.xlsx</strong>: Excel datasheet. The most used hashtags inside the conversation about eHealth.</p> <p><strong>topics_tweets_sdgsaccess.xlsx</strong>: Excel datasheet. Tweets by topic extracted using Machine Learning in the SDGs analysis.</p> <p> </p> <p>This repository will receive updates in the future in order to present all the data available and publishable from the different analysis that were described.</p>
Sample Records. Citizen Science and Citizen Energy Communities: A Systematic Review of Potential Alliances for SDGs
<p>Sample Records. Citizen Science and Citizen Energy Communities: A Systematic Review of Potential Alliances for SDGs</p>
Peer Production in Citizen Science: A Community-Centered Approach on the Example of Personal Science - Supplementary Materials
<p>This folder contains supplementary materials for the PhD thesis “Peer Production in Citizen Science: A Community-Centered Approach on the Example of Personal Science” by Katharina Kloppenborg. This project has been led at Université Paris Cité / Inserm U1284 from 2020 to 2023 and was supervised by Bastian Greshake Tzovaras and Ariel Lindner. </p>
Citizen Science to Promote Sustained Physical Activity in Low-Income Communities
ClinicalTrials.gov study NCT03041415. IPD Sharing: YES. Countries: 1. Publications: 2.
Smell Pittsburgh: Engaging Community Citizen Science for Air Quality
<p>Link to the files and description of the Smell Pittsburgh Dataset –<br> <a href="https://eur04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FCMU-CREATE-Lab%2Fsmell-pittsburgh-prediction%2Ftree%2Fmaster%2Fdataset%2Fv2&data=05%7C01%7Cy.c.hsu%40uva.nl%7C89562067341d40d0bad308da2c475652%7Ca0f1cacd618c4403b94576fb3d6874e5%7C0%7C0%7C637870982141190827%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=gWn0nGRUl5EAHvDfJwTlTNJN%2BWFH62NX6Mw%2B2web6XE%3D&reserved=0">https://github.com/CMU-CREATE-Lab/smell-pittsburgh-prediction/tree/master/dataset/v2</a></p> <p>Smell Pittsburgh (<a href="https://smellpgh.org">https://smellpgh.org</a>) is a mobile application for crowdsourcing reports of bad odors, such as those generated from air pollution. The data is used to train a machine learning model to predict the presence of bad smell and create push notifications to inform citizens about the bad smell. The motivation, background, and design of the Smell Pittsburgh application is described in the following paper.</p> <ul> <li>Yen-Chia Hsu, Jennifer Cross, Paul Dille, Michael Tasota, Beatrice Dias, Randy Sargent, Ting-Hao (Kenneth) Huang, and Illah Nourbakhsh. 2020. Smell Pittsburgh: Engaging Community Citizen Science for Air Quality. ACM Transactions on Interactive Intelligent Systems. 10, 4, Article 32. DOI:<a href="https://doi.org/10.1145/3369397">https://doi.org/10.1145/3369397</a>. Preprint:<a href="https://arxiv.org/pdf/1912.11936.pdf">https://arxiv.org/pdf/1912.11936.pdf</a>.</li> </ul>
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.