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48 results for “Network Centrality”
Optimizing properties on the critical rigidity manifold of underconstrained central-force networks
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Data from: Landscape homogenization strengthens the fitness benefits of plant species' centrality in pollination networks
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Interaction networks of nectar-feeding bats and plants in central Mexico
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Data from: Benefits and challenges of scaling up expansion of marine protected area networks in the Verde Island Passage, Central Philippines
Locally-established marine protected areas (MPAs) have been proven to achieve local-scale fisheries and conservation objectives. However, since many of these MPAs were not designed to form ecologically-connected networks, their contributions to broader-scale goals such as complementarity and connectivity can be limited. In contrast, integrated networks of MPAs designed with systematic conservation planning are assumed to be more effective—ecologically, socially, and economically—than collections of locally-established MPAs. There is, however, little empirical evidence that clearly demonstrates the supposed advantages of systematic MPA networks. A key reason is the poor record of implementation of systematic plans attributable to lack of local buy-in. An intermediate scenario for the expansion of MPAs is scaling up of local decisions, whereby locally-driven MPA initiatives are coordinated through collaborative partnerships among local governments and their communities. Coordination has the potential to extend the benefits of individual MPAs and perhaps to approach the potential benefits offered by systematic MPA networks. We evaluated the benefits of scaling up local MPAs to form networks by simulating seven expansion scenarios for MPAs in the Verde Island Passage, central Philippines. The scenarios were: uncoordinated community-based establishment of MPAs; two scenarios reflecting different levels of coordinated MPA expansion through collaborative partnerships; and four scenarios guided by systematic conservation planning with different contexts for governance. For each scenario, we measured benefits through time in terms of achievement of objectives for representation of marine habitats. We found that: in any governance context, systematic networks were more efficient than non-systematic ones; systematic networks were more efficient in broader governance contexts; and, contrary to expectations but with caveats, the uncoordinated scenario was slightly more efficient than the coordinated scenarios. Overall, however, coordinated MPA networks have the potential to be more efficient than the uncoordinated ones, especially when coordinated planning uses systematic methods.
Map of the Burgundian Connectivity within the Network of Western- and Central European Marriages between the Nobility, 1350-1550
<p>Map of the Burgundian Connectivity within the Network of Western- and Central European Marriages between the Nobility, 1350-1550. ArcGIS (Esri). Lines indicate a marital relationship between two individuals based on their place of birth. Red lines indicate marital relationships between the Burgundian dukes and their spouses.</p><p>See: Miara Fraikin and Meike Wiedemann, 'The "Burgundian Model" revisited: Using Digital Approaches to Explore the Reach of Burgundy', in Sanne Maekelberg and Krista De Jonge (eds.), <i>Mapping the Space of the Early Modern Court in Europe. Functionality and Representation, </i>2023, pp.13-34.</p>
Consistency and differences between centrality measures across distinct classes of networks
<p>This is the data reported in Oldham et al., 2019. Consistency and differences between centrality measures across distinct classes of networks (<a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0220061">link to paper</a>). Originally hosted <a href="https://figshare.com/s/22c5b72b574351d03edf">here</a>.</p> <p>GitHub for the code used to generate and use this data is located <a href="https://github.com/StuartJO/CentralityConsistency">here</a>. Unzip the zip file into the main directory into a folder called "Data".</p>
Source data for "In-degree centrality in a social network is linked to coordinated neural activity"
<p>The following includes the source data for the manuscript titled "In-degree centrality in a social network is linked to coordinated neural activity". A second version of the source data ("Source Data_updated_011222.xlsx") includes the source data for the figures in the supplementary materials.</p>
Data for paper: Comparing Measures of Centrality in Bipartite Social Networks: A Study of Drug Seeking for Opioid Analgesics
<p>Data and code for paper: Comparing Measures of Centrality in Bipartite Social Networks: A Study of Drug Seeking for Opioid Analgesics</p>
Supporting material for Kempf, M & Denis, S (2024): Resource dependency and communication networks in Early Neolithic Central-West Europe. Quaternary Environments and Humans
<p><span>Table 1. </span><span>Site names, location, and attributes of the sample used during the analysis. Sites are organised according to stage dependency. Coordinates are in WGS84, EPSG:4326.</span></p> <p><span><span>Table 2</span><span>.</span> Description of the site status<span>, based on the stages of the CO and the frequency of the sites according to the lengths of the calculated LCP at the different chronological stages (see repository for heatmaps of the LCP lengths: 10.5281/zenodo.10617484). Sites are classified following the 4 levels presented in Figure 5 in Kempf & Denis (2024). </span></span></p> <p> </p>
Multidimensional specialization and generalization are pervasive in soil prokaryotes with generalists dominating communities and specialists more central in networks
<p>Project folder to run analyses in the manuscript "<strong>Multidimensional specialization and generalization are pervasive in soil prokaryotes with generalists dominating communities and specialists more central in networks</strong>" with necessary raw and processed data.</p> <p>Manuscript abstract:</p> <p>Habitat specialization underpins biological processes from species distributions to speciation. However, organisms are often described as specialists or generalists based on a single niche axis, despite facing complex, multidimensional environments. Here, we analyzed 236 prokaryotic communities across the United States demonstrating for the first time that 90% of >1,200 prokaryotes followed one of two trajectories: specialization on all niche axes (multidimensional specialization) or generalization on all axes (multidimensional generalization). We then documented that this pervasive multidimensional specialization/generalization had a wide range of ecological and evolutionary consequences. First, multidimensional specialization and generalization are highly conserved with very few transitions between these two trajectories. Second, multidimensional generalists dominated communities because they were 73 times more abundant than specialists. Lastly, multidimensional specialists played important roles in community structure with ~220% more connections in microbiome networks. These results indicate that multidimensional generalization and specialization are evolutionarily stable with multidimensional generalists supporting larger populations and multidimensional specialists playing important roles within communities likely stemming from their overrepresentation among pollutant detoxifiers and nutrient cyclers. Taken together, we demonstrate that the vast majority of soil prokaryotes are restricted to one of two multidimensional niche trajectories, multidimensional specialization or multidimensional generalization, which then has far-reaching consequences for evolutionary transitions, microbial dominance, and community roles. </p>
Data from: Benefits and challenges of scaling up expansion of marine protected area networks in the Verde Island Passage, Central Philippines
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Social (-ecological) network analysis in environmental governance - central publications, important concepts and areas of application data collected in January 2019
<p>Social and Social-Ecological Network Analysis (S(E)NA) have recently emerged as new methods in the environmental governance (EG) literature. By investigating networks of connections between actors, S(E)NA advances the understanding of who is involved in EG and how. We provide an overview of the EG literature applying S(E)NA and respective metrics of 1) a citation network analysis, 2) topic detection methods and 3) a similarity network analysis. 20 publications occupy central positions as sources, storers or bridges of knowledge in the citation network. While we see S(E)NA applied in diverse resource contexts, these are mainly discussed on the local spatial level, with a focus on “policy” or “collaboration”. We discover that “power structures” and “the production of knowledge” are themes influencing the whole field.</p>
Data from: Matching-centrality decomposition and the forecasting of new links in networks
Networks play a prominent role in the study of complex systems of interacting entities in biology, sociology, and economics. Despite this diversity, we demonstrate here that a statistical model decomposing networks into matching and centrality components provides a comprehensive and unifying quantification of their architecture. The matching term quantifies the assortative structure in which node makes links with which other node, while the centrality term quantifies the number of links that nodes make. We show, for a diverse set of networks, that this decomposition can provide a tight fit to observed networks. Then we provide three applications. First, we show that the model allows very accurate prediction of missing links in partially known networks. Second, when node characteris- tics are known, we show how the matching-centrality decomposition can be related to this external information. Consequently, it offers a simple and versatile tool to explore how node characteristics ex- plain network architecture. Finally, we demonstrate the efficiency and flexibility of the model to forecast the links that a novel node would create if it were to join an existing network.
Data for Perception of own centrality in social networks by Kovarik, Ozaita, Sánchez and Brañas-Garza
<p>Data for the paper "Perception of own centrality in social networks", by Kovarik, Ozaita, Sánchez and Brañas-Garza, submitted for publication. Two .csv files: one with the anonymized, otherwise raw network data, and the second one with the results of analyzing the network reported in the paper</p>
Community Network-driven COVID-19 Testing and Vaccination of Vulnerable Populations in the Central US
ClinicalTrials.gov study NCT04743908. IPD Sharing: NO. Countries: 1. Publications: 0.
Probing the Dorsolateral Prefrontal Cortex and Central Executive Network for Improving Neuromodulation in Depression
ClinicalTrials.gov study NCT05224063. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Interstitial Cystitis: Examination of the Central Autonomic Network
ClinicalTrials.gov study NCT03008382. IPD Sharing: YES. Countries: 1. Publications: 0.
Social network centrality predicts dietary decisions in wild great tits
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Data from: Matching-centrality decomposition and the forecasting of new links in networks
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Data from: Global network centrality of university rankings
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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.