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234 results for “community analysis”
Seasonal Soil Sampling of Grass-dominated, Mesquite-dominated, and Ecotone Sites at the Jornada Basin LTER site for the Analysis of Microbial Community Variance, 2022-2023
Fungal and bacterial soil communities were analyzed to assess the influence of woody shrub encroachment on soil microbial communities. Three study sites in the Jornada Long Term Ecological Research Site were selected to represent a grass-dominated site, a woody shrub dominated site, and an ecotone of woody shrubs and grass. The field sampling began in October 2022 and concluded in July 2023 with five sampling periods that aimed to capture seasonal variation: October 2022, January 2023, March 2023, May 2023, and July 2023. This dataset includes data pertaining to the soil microbial composition, environmental characteristics, microbial sequence processing, and documentation of the code utilized for data processing and statistical analyses. Data on soil microbial composition was collected from Phospholipid Fatty-Acid composition data from soil samples. Data on environmental characteristics were collected from on-site temperature probes, laboratory assessments of soil properties, and Jornada meteorological stations. Information pertaining to microbial sequence processing is included in the documented code as well as in the record of the primers utilized.
Analysis of the planning process for a new park in Minneapolis, Minnesota, at the Upper Harbor Terminal site with planners and community members focusing on redevelopment that addresses green gentrification concerns, 2019 to 2021
This dataset is from a study focuses on the Minneapolis Park and Recreation Board’s planning process for a new park at the Upper Harbor Terminal (UHT) site - a defunct barge-to-rail terminal on the Mississippi River being redeveloped with a mix of housing, commercial uses, and park space (see "UHT_location_map in Other Entities). While the redevelopment affords an opportunity to remediate pollution and provide new greenspace, a high portion of nearby residents are low-income and housing-cost burdened, raising concerns among community members about gentrification. As a counter to green gentrification, the concept of “Just Green Enough” (JGE) became a common theme around the UHT development process. JGE aims to center community-centered greening efforts with broader community development goals in mind (i.e. living-wage jobs and affordable housing). Amidst growing community pressure, the Minneapolis Park and Recreation Board (MPRB) appointed a Community Advisory Committee (CAC). The CAC was tasked with meeting monthly for in-depth deliberations (facilitated by planning staff and external consultants) with the goal of making final park design and programming recommendations, which planning staff would present to the MPRB Board of Commissioners. The Upper Harbor Terminal CAC consisted of 16 members, mostly residents of North Minneapolis and Northeast, and many with a background in nonprofit, environmental, or community organizing work. Meetings began in July 2019 and lasted nearly two years until in May 2021. This dataset includes the qualitative codebooks for the CAC meetings, accompanied by the meeting minutes and other documents related to the UHT planning process. The transcripts of semi-structured interviews with stakeholders in the UHT planning process were also analyzed and coded, but specific quotations are omitted from this dataset to protect the privacy the participants.
Dataset: Analysis of Multidimensional Energy Poverty in the Carmen Soler Community - Limpio, Republic of Paraguay
<p><i><strong>"Analysis of Multidimensional Energy Poverty in the Carmen Soler Community - Limpio, Republic of Paraguay"</strong></i></p><p><i>CHILECON 2023 - </i><a href="https://site.ieee.org/chilesur/ieee-chilecon-2023/"><i>https://site.ieee.org/chilesur/ieee-chilecon-2023/</i></a></p><p>---</p><p>En el marco del trabajo de referencia, los autores ponemos a disposición de los lectores la base de datos utilizada para el cálculo del Índice de Pobreza Energética Multidimensional (MEPI) para el caso de estudio. </p><ol><li>MEPI_CarmenSoler_Data_2018_CHILECON2023.xlsx</li></ol><p>En el archivo, podrán encontrar los extraídos de los resultados de la encuesta realizada en el 2018 por un equipo de investigadores paraguayos (En el artículo podrán encontrar más información). Además de los datos, podrán ver todos los pasos y cálculos llevados a cabo para obtener los resultados obtenidos. </p><p>El material fue puesto a disposición de todos los interesados para fines académicos y científicos. </p><p>Atte. </p><p>Los autores. </p><p>---</p>
Community Established Best Practice Recommendations for Tephra Studies-from Collection through Analysis
<p>Tephra is a unique volcanic product with an unparalleled role in understanding past eruptions, long-term behavior of volcanoes, and the effects of volcanism on climate and the environment. Tephra deposits also provide spatially widespread, extremely high-resolution time-stratigraphic markers across a range of sedimentary settings and are used in a range of disciplines (e.g., volcanology, climate science, archaeology, ecology, and impact assessment). Nonetheless, the study of tephra deposits is challenged by a lack of standardization that often inhibits data integration across geographic regions and across disciplines.</p> <p>Here we present comprehensive recommendations for tephra data gathering and reporting that were developed by the tephra science community to serve as guidelines for future investigators and to ensure that sufficient data are gathered for transparency and interoperability. Recommendations include standardized field and laboratory data collection along with reporting and correlation guidance. These are organized as tabulated lists of key metadata with their definition and purpose. They are system independent and usable for template, tool, and database development. This new standardized framework promotes consistent tephra documentation and archiving, fosters interdisciplinary communication, and improves effectiveness of data sharing among diverse communities of researchers. Wider adoption will help to expand the applicability and usability of tephra data and facilitate scientific collaboration and data reuse.</p> <p>For additional details, see the accompanying manuscript:</p> <p>Wallace, K.*, Bursik, M. Kuehn, S., Kurbatov, A., Abbott, P., Bonadonna, C., Cashman, K., Davies, S., Jensen, B., Lane, C., Plunkett, G., Smith, V. Tomlinson, E., Thordarsson, T., and Walker, D. Community established best practice recommendations for tephra studies—from collection through analysis. <em>Sci Data</em> <strong>9, </strong>447 (2022). <a href="https://doi.org/10.1038/s41597-022-01515-y">https://doi.org/10.1038/s41597-022-01515-y</a></p> <p>*corresponding author: Kristi Wallace, <a href="mailto:kwallace@usgs.gov">kwallace@usgs.gov</a></p> <p>Open access article is available online here <a href="https://doi.org/10.1038/s41597-022-01515-y">https://doi.org/10.1038/s41597-022-01515-y</a> or as a PDF here <a href="https://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.nature.com%2Farticles%2Fs41597-022-01515-y.pdf&data=05%7C01%7Ckwallace%40usgs.gov%7C673f9f39fd3e4122dd9b08da6f3b9667%7C0693b5ba4b184d7b9341f32f400a5494%7C0%7C0%7C637944598967375940%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=%2BKVfwK2FbUKAoJf2gMerCmBMEQE1rvMDkS6xIk3DGKY%3D&reserved=0">https://www.nature.com/articles/s41597-022-01515-y.pdf</a>.</p>
Spatial Analysis on Kemanggisan Community Health Center
<p>This data was collected based on the condition during COVID-19 pandemic and New Normal Era (between 2022-2023)</p>
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>
Data and analysis code from: Micro-scale geography of synchrony in a serpentine plant community
This package includes data and code to reproduce analyses of micro-scale geography of synchrony in the plant community at Jasper Ridge Biological Preserve. Plant cover and soil depth data come from long-term experimental plots established by Richard Hobbs. Plant cover is aggregated into 36 1m2 plots across three treatments (control, gopher exclosure, rabbit exclosure) from 1983 to 2015; included herein are data on the 6 most abundant species (Plantago erecta, Bromus hordeaceous, Lasthenia californica, Microseris douglasii, Vulpia microstachys, and Calycadenia multiglandulosa), total plant cover across all species, and records of gopher disturbance in the plots. The data package also includes time series of monthly precipitation and growing season Palmer’s Drought Severity Index for the same time period. An R Markdown file is included that reproduces all analyses described in the manuscript and reproduces all data figures. Data to support: Walter, Hallett et al. in review “Micro-scale geography of synchrony in a serpentine plant community
MCR LTER: Coral Reef: Benthic Community Dynamics: Island Scale Coral Cover Analysis
These data describe the results of outer reef surveys that are conducted on an irregular schedule to quantify coral reef community dynamics on a scale of kilometers. The first island-wide survey was completed in 2006, and the second in 2010; we anticipate conducting such surveys every 5-6 years or as needed to capture the large-scale effects of disturbance regimes. The island-wide sampling adds 3 new sites per shore (for a total of 5 sites/shore with the fixed LTER sites) in each year that the larger scale analyses are completed.
Artifact for the EASE 2020 Paper: How Can I Contribute? A Qualitative Analysis of Community Websites of 25 Unix-Like Distributions
<p>Artifact for the EASE 2020 Paper: How Can I Contribute? A Qualitative Analysis of Community Websites of 25 Unix-Like Distributions</p> <p>Jacob Krüger, Sebastian Nielebock, Robert Heumüller</p> <p> </p> <p>Please refer to the readme for more details</p>
Business Models in Energy Communities: an analysis through legal lenses
<p>This research explores energy communities (EC) and their business models’ attributes. We develop a conceptual framework, which combines and extends the social, economic, environmental, and technological dimensions of value generation to include the legal dimension. The latter has been considered only implicitly in previous studies on this sector. Applying this framework to forty business cases of energy communities allows to identify six business model (BM) archetypes representative of ECs. This study can encourage and support new ventures in this sector to model their strategy and comply with the requirements.</p>
Replication package: Dataset and stata-do-file for analysis in "Intragroup communication in social dilemmas: An artefactual public good field experiment in small-scale communities"
<p>This dataset was used for the analysis in "Intragroup communication in social dilemmas: An artefactual public good field experiment in small-scale communities". The data was collected in Namibia in 2017 as part of the SASSCAL research project by Nils Christian Hoenow and Adrian Pourviseh as members of the Chair for Development and Cooperative Economics at the University of Marburg. Funded by the Southern African Science Service Center for Climate Change and Adaptive Land-UseManagement (SASSCAL) through the German Federal Ministry for Education and Research (Grant No. 01LG1201B).</p> <p> </p> <p>Article Title: Intragroup communication in social dilemmas: An artefactual public good field experiment in small-scale communities </p> <p>Authors: Nils Christian Hoenow* and Adrian Pourviseh**</p> <p> </p> <p>*RWI – Leibniz Institute for Economic Research, Essen, Germany and & School of Business and Economics, University of<br>Marburg, Marburg, Germany</p> <p>**School of Business and Economics, University of<br>Marburg, Marburg, Germany</p> <p>Abstract: <br>Communication is well-known to increase cooperation rates in social dilemma situations, but the exact mechanisms behind this remain largely unclear. This study examines the impact of communication on public good provisioning in an artefactual field experiment conducted with 216 villagers from small, rural communities in northern Namibia. In line with previous experimental findings, we observe a strong increase in cooperation when face-to-face communication is allowed before decision-making. We additionally introduce a condition in which participants cannot discuss the dilemma but talk to their group members about an unrelated topic prior to learning about the<br>public good game. It turns out that this condition already leads to higher cooperation rates, albeit not as high as in the condition in which discussions about the social dilemma are possible. The setting in small communities also allows investigating the effects of pre-existing social relationships between group members and their interaction with communication.We find that both types of communication are primarily effective among socially more distant group members, which suggests that communication and social ties work as substitutes in increasing cooperation. Further analyses rule out better comprehension of the game and increased mutual expectations of one’s group members’ contributions as drivers for the communication effect. Finally, we discuss the role of personal and injunctive norms to keep commitments made during discussions.</p>
Algae-Bacteria Community Analysis for Drinking Water Taste and Odour Risk Management
<p>The datasets and accompanying R script included in this upload are provided to complement the manuscript titled <em>"Algae-Bacteria Community Analysis for Drinking Water Taste and Odour Risk Management."</em> These resources are intended to facilitate the replication and verification of the analyses presented in the paper.</p> <p> </p> <p> </p>
Comparative analysis of surface sanitization protocols on the bacterial community structures in the hospital environment
<p>In this study, we used 16S rRNA gene sequencing approaches to characterize the bacterial microbiota on different surfaces of the hospital environment. The longitudinal data was then subjected to comprehensive comparisons between different sanitation strategies (disinfectants, detergents and probiotics) to measure their potential effect on the microbial community structures in the hospital environment.</p> <p>This archive contains results and data of the 16S rRNA amplicon sequencing performed on 1019 environmental and 271 patient DNA samples collected over the time course of 40 weeks in a newly opened ward in the neurological station at the Charité Hospital (Berlin). The files include a study information and sample metadata sheets, BIOM-tables and information about the taxonomy results and diversity metrics.</p>
Characterizing Measures for the Assessment of Cluster Analysis and Community Detection
<p><strong>Description. </strong>The dataset is constituted of:</p> <ul> <li>`figs.zip`: an archive containing the plot files;</li> <li>`data&results.zip`: an archive containing the necessary data to perform our analysis, as well as result files.</li> </ul> <p>These are the resources used in the following articles:</p> <ol> <li>N. Arınık, V. Labatut and R. Figueiredo, "Characterizing measures for the assessment of cluster analysis and community detection", Modèles & Analyse des Réseaux : Approches Mathématiques & Informatiques (MARAMI), 2020. ⟨<a href="https://hal.archives-ouvertes.fr/hal-02993542">hal-02993542</a>⟩</li> <li>N. Arınık, R. Figueiredo, and V. Labatut, “Characterizing and comparing external measures for the assessment of cluster analysis and community detection,” <em>IEEE Access </em>9:20255–20276, 2021. DOI: <a href="http://doi.org/10.1109/access.2021.3054621">10.1109/access.2021.3054621</a> ⟨<a href="https://hal.archives-ouvertes.fr/hal-03124118">hal-03124118</a>⟩</li> </ol> <p><strong>Source code. </strong>The associated source code is available on GitHub: <a href="https://github.com/CompNet/ExtMeasEval">https://github.com/CompNet/ExtMeasEval</a></p> <p><strong>Citation. </strong>If you use these data, please cite the paper [2].</p> <p><br><code>@Article{Arinik2021,</code><br><code> author = {Arınık, Nejat and Figueiredo, Rosa and Labatut, Vincent},</code><br><code> title = {Characterizing and Comparing External Measures for the Assessment of Cluster Analysis and Community Detection},</code><br><code> journal = {IEEE Access},</code><br><code> year = {2021},</code><br><code> volume = {9},</code><br><code> pages = {20255-20276},</code><br><code> doi = {10.1109/access.2021.3054621},</code><br><code>}</code></p>
Research data management for bioimaging: the 2021 NFDI4BIOIMAGE community survey - Extended Data 4 - Analysis Data Sheet
<p>This dataset is extended data to the manuscript "Research data management for bioimaging: the 2021 NFDI4BIOIMAGE community survey" by Schmidt C., Hanne J, Moore J, Meesters C, Ferrando-May E, Weidtkamp-Peters S, and members of the NFDI4BIOIMAGE initiative. [version 1; peer review: awaiting peer review] F1000Research 2022, 11:638, https://doi.org/10.12688/f1000research.121714.1</p> <p>This extended data includes:</p> <p>- Data Analysis Sheet and results table</p> <p>Note: The data is anonymized (i.e., all IP addresses as well as personal comments were deleted)</p> <p>The revised version was published after the peer-review process of the original article on zenodo.org</p>
Data archive: Trophic structure of cold-water coral communities revealed from the analysis of tissue isotopes and fatty acid composition
<p>Data belonging to the paper: </p> <p>Dick van Oevelen, Gerard C. A. Duineveld, Marc S. S. Lavaleye, Tina Kutti and Karline Soetaert (2017) Trophic structure of cold-water coral communities revealed from the analysis of 55 tissue isotopes and fatty acid composition. Marine Biology Research, DOI: https://doi.org/10.1080/17451000.2017.1398404</p> <p>Abstract:</p> <p>The trophic structure of cold-water coral reef communities at two contrasting locations, the 800-<br> m deep Belgica Mounds (Irish margin) and 300-m deep Træna reefs (Norwegian Shelf), was<br> investigated using stable isotope (δ13C and δ15N) and fatty-acid composition analysis. A<br> broad range of specimens, with emphasis on (commercial) fish species, and organic matter<br> sources were sampled using a variety of tools. Irrespective of the environmental and<br> geographical setting, the δ15N values indicated that the food web encompasses roughly 1.5<br> to 3 trophic levels. Mobile echinoderms, i.e. sea urchins and sea stars, had highest δ15N<br> values, indicative of a high trophic position in the food web. The fraction of bacterial fatty<br> acids in reef fauna was generally low (<5%), indicating that enhanced bacterial production in<br> the water column through seafloor seepage of nutrients (‘hydraulic theory’) does not form a<br> significant energy pathway into the food web. The high fraction of algal and essential fatty<br> acids in reef fauna and fish at both locations indicates a close coupling with surface<br> productivity, but the transport mechanism depends on the hydrographic setting. At Træna,<br> Calanus copepods and euphausiids form an additional link between primary production and<br> fish, which is largely absent at Belgica Mounds. At Belgica Mounds, the reef community is<br> primarily supported by phytodetritus, as evidenced by the high contribution of algal fatty<br> acids in faunal tissue and seasonal chlorophyll a deposition and marine snow at the reef. The<br> environmental setting of cold-water coral reefs influences the structure of the associated<br> food web.</p>
Fig. 1 in Eukaryotic Microbial Communities Associated with Rock-dwelling Foliose Lichens: A Functional Morphological and Microecological Analysis
Fig. 1. Photograph of a portion of a Flavoparmelia thallus showing an example of a radially oriented lobe with three segments sampled in analyzing the microbial communities: A – inner, B – middle, and C – outer. Scale bar: 5 mm.
FIGURE 4 in What are the best modern analogs for ancient South American mammal communities? Evidence from ecological diversity analysis (EDA)
FIGURE 4. Linear regression of MAP on correspondence axis 1 (CA1) score; estimated MAP for each of fossil locality based on CA1 score is indicated. Abbreviations: LV, La Venta; QH, Quebrada Honda; RU, Rümikon; SC, Santa Cruz; TG, Tinguiririca.
FIGURE 6. Classification Tree results and predictions for the five fossil localities. A in What are the best modern analogs for ancient South American mammal communities? Evidence from ecological diversity analysis (EDA)
FIGURE 6. Classification Tree results and predictions for the five fossil localities. A) Results and predictions for CT1, vegetative cover. B) Results and predictions for CT2, biogeographic realm. Abbreviations: LV, La Venta; QH, Quebrada Honda; RU, Rümikon; SC, Santa Cruz; TG, Tinguiririca.
FIGURE 3 in What are the best modern analogs for ancient South American mammal communities? Evidence from ecological diversity analysis (EDA)
FIGURE 3. Axes three and four of the correspondence analysis. A) Positions of the fossil localities and 179 modern ecoregions; B) Positions of the 22 variables. Note that the scale is not the same in the two graphs.
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.