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aves-wildbird-network     (Animal Social Networks)

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This network dataset is in the category of Animal Social Networks



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Metadata

CategoryAnimal Social Networks
CollectionAnimal Networks
AboutReal-world animal interaction network data sets. Animal interaction data from published studies of wild, captive, and domesticated animals.
Tags
Sourcehttps://bansallab.github.io/asnr/data.html
ShortAnimal Networks
Vertex typeAnimal, Bird, wildbirds
Edge typeInteraction
FormatUndirected
Edge weightsWeighted
SpeciesWild birds N/A
Taxon. classAves
Populationfree-ranging
Geo. locationOxford, UK
Data collectionRFID
Interaction typesocial projection bipartite
Definition of interactionGroups were defined as individuals detected on the same nest-box during the same day, and co-memberships represented individuals that overlapped in nest-box exploration patterns during the same day. Networks were calculated from these group-by-individual matrices using the halfweight index.
Edge weight typehalf_weight_index
Data collection duration6 days
Time resolution (within a day)1 sec
Time span (within a day)12 hours
DescriptionEach network represents social data collected for consecutive 6-day time window.
CitationFirth, Josh A., and Ben C. Sheldon. "Experimental manipulation of avian social structure reveals segregation is carried over across contexts." Proceedings of the Royal Society of London B: Biological Sciences 282.1802 (2015): 20142350.
Edge timestampsThird column encodes the weights for the edges and the fourth column represents the edge timestamps. If the graph is unweighted (has only 3 columns), then the third column represents the timestamps.For this temporal network, edge timestamps are not recorded at the finest granularity (sec. or ms.) and are instead discrete approximations of the actual temporal network. Unfortunately, the actual edge timestamps, that is, when the interactions were actually observed (e.g., at the level of seconds) has not been provided.Hence, one can create a sequence of static snapshot graphs by aggregating all edges that occur at each unique edge timestamp and repeating this for all edge timestamps.

Please cite the following if you use the data:

@inproceedings{nr,
     title={The Network Data Repository with Interactive Graph Analytics and Visualization},
     author={Ryan A. Rossi and Nesreen K. Ahmed},
     booktitle={AAAI},
     url={http://networkrepository.com},
     year={2015}
}

Note that if you transform/preprocess the data, please consider sharing the data by uploading it along with the details on the transformation and reference to any published materials using it.

Network Data Statistics

Nodes202
Edges11.9K
Density0.586178
Maximum degree397
Minimum degree2
Average degree117
Assortativity0.290447
Number of triangles2.2M
Average number of triangles11K
Maximum number of triangles42.9K
Average clustering coefficient1.88605
Fraction of closed triangles0.843967
Maximum k-core155
Lower bound of Maximum Clique45

Network Data Preview

Interactive visualization of aves-wildbird-network's graph structure

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Interactive Visualization of Node-level Properties and Statistics

Tools for Interactive Exploration of Node-level Statistics

Visualize and interactively explore aves-wildbird-network and its important node-level statistics!

  • Each point represents a node (vertex) in the graph.
  • A subset of interesting nodes may be selected and their properties may be visualized across all node-level statistics. To select a subset of nodes, hold down the left mouse button while dragging the mouse in any direction until the nodes of interest are highlighted.This feature allows users to explore and analyze various subsets of nodes and their important interesting statistics and properties to gain insights into the graph data
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Interactive Visualization of Node-level Feature Distributions

Node-level Feature Distributions

degree distribution

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degree CDF

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degree CCDF

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kcore distribution

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kcore CDF

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kcore CCDF

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triangle distribution

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triangle CDF

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triangle CCDF

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csv distribution

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csv CDF

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csv CCDF

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All visualizations and analytics are interactive and flexible for exploratory analysis and data mining in real-time and include the following features:

  • Degree, k-core, triangles, and triangle-core distributions. We include plots for each of the fundamental graph features and counts of the number with a particular property (i.e., number of nodes that form k triangles or have degree k, etc.)
  • We also include the CDF and CCDF distributions for each graph in the collection.
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  • Adjust scale and other application dependent-parameters. All interactive visualizations may adjust the scale which is particularly important in certain types of graph data that contain highly skewed graph properties (power-lawed graphs and/or networks) such as degree distribution.

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