A MangalDataset identifies a collection of networks, possibly containing a single element. A dataset is identified by its id or name (both of which are unique).

name (AbstractString): a unique name describing the dataset.

public (Bool): indicates whether the dataset details are available to others than its owner.

reference (Union{Int64,Nothing}) (optional): a reference to the id of the MangalReference, or nothing if there is no associated reference for this dataset.

user (Int64): id of the user who added the dataset to the database. This is not necessarily the author of the dataset, see reference (and the same field in the MangalNetwork) to get the actual authorship.

description (AbstractString): a free-form description of the dataset.

A MangalNetwork is a wrapper around nodes (and not around interactions, for reasons which are really not worth mentioning here, but see the documentation for MangalNode for some hints).

name (AbstractString): a unique name describing the network.

dataset (Int64): the unique id of the MangalDataset to which the network belongs.

public (Bool): indicates whether the network details are available to others than its owner.

date (DateTime): date and time at which the network was sampled.

position (AbstractGeometry): the location at which the network was sampled. This can be any sort of geospatial construct, most notably points or polygons.

complete (Bool): indicates whether the network was sampled completely, or is a collection of interactions with possible gaps.

reference (Union{Int64,Nothing}) (optional): a reference to the id of the MangalReference, or nothing if there is no associated reference for this network.

user (Int64): id of the user who added the network to the database. This is not necessarily the author of the network, see reference to get the actual authorship.

description (AbstractString): a free-form description of the network.

Interaction

Node in a network

The taxon field is a MangalReferenceTaxon object, so that one can, for example, query the TSN identifier of a node through object.taxon.tsn.

This approach has been chosen because (i) names of nodes in networks can be non unique and (ii) nodes within the same networks can refer to various taxonomic levels. As an example, if a network has four distinct nodes identified as Ascariasis sp., they will represent four nodes in the networks, but map onto the same MangalReferenceTaxon (representing the entire Ascariasis genus). This approach provides a seemless representation of the same taxon across different networks, but also of the same taxon within networks.

Reference taxon (unique identifier of network nodes)

Attribute

MangalUser

Reference