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The CNS format is an XML-based file format that can contain multiple relations and attributes. Default file format for NetRepository, used by Ceunet, Indra and SocNet.se.
The CSV format contains a singular relation in matrix format. Easy to import into spreadsheet editors (Excel et al).
The Ucinet DL format is a text-based format that can contain multiple relations. Compatible with Ucinet and other programs. This fullmatrix format is recommended for dense networks.
The Ucinet DL format is a text-based format that can contain multiple relations. Compatible with Ucinet and other programs. This Edgelist1 format is recommended for sparse networks.
The Pajek format is a text-based format that can contain multiple relations, either as directed arcs or symmetric edges. Compatible with Pajek.
The GraphML format is an XML-based format that can store multiple relations and attributes.
This CSV format is for downloading attribute-daata only, i.e. no relational data at all. Easy to import into spreadsheet editors (Excel et al).
Public datasets
Public datasets are available for everyone and currently installed centrally through CNS. Through this web interface (or through Ceunet) you can directly access and download public sets in the format of your choice.
Use the top-left box to navigate through the public directory structure. Double-click on a folder name to enter that folder. Double-click the (..) on the first line to climb up a directory level.
The datasets in the current folder are shown in the top-mid box. If none are shown, the folder is currently empty. Double-click on a dataset, e.g. "Padgett's Florentine Families" found in the Tutorial/Classical datasets" folder, and information about this dataset can be found in the bottom-left box. Use the select-menu in the mid-bottom box to choose which format you want. The bottom-right box will display the specifics of the chosen format. Click "Download dataset" to download the dataset!
Private datasets
If you have a NetRepository user account, you can upload your own private datasets. Uploading is done through the Ceunet program, available through CNS. Once uploaded, you can access your datasets from anywhere, either directly through Ceunet or through this web-interface.
To access your private datasets, you must first be logged in - use the login form at the top-left to do this. Once logged in, there is a link there to get to your private datasets. Click that link, and your datasets are shown in the top-mid box. You can then download your private datasets in the same manner as for the public datasets.
NetRepository is an online storage-and-retrieval system for network-analytical datasets. Integrated with Ceunet/Indra and SocNet.se, the various datasets can also be accessed through this web interface.
NetRepository contains a collection of public datasets, suitable both for tutoring/teaching as well as research. More datasets will be added in the future. The default data format is the CNS-format, the native format for Ceunet/Indra and SocNet.se, but NetRepository makes it possible to download the datasets in a variety of other formats: Ucinet DL, Pajek, GraphML, and various CSV formats.
Through (optional) personal user accounts, it is also possible to upload and download your own private datasets through Ceunet's in-build NetRepository functions. By creating and logging in with your user account on this web page, you can download (though not upload) your datasets, in various formats. Accounts are created using your email address and a private password. This information (which will not leave the NetRepository database) must also be entered into Ceunet when accessing your datasets stored in the NetRepository.
NetRepository is part of the CNS software suite, developed at the Center for Network Science (CNS) at Central European University, Budapest. For further information, development suggestions, or suggestions on possible public datasets to add, please contact Carl Nordlund at cns (at) ceu dot hu.
Datasets in the NetRepository can be downloaded in a variety of formats:
The default data format used by NetRepository is the CNS format, an XML-based file format for storing network data. This data format can store a single set of actors, multiple sociomatrices (aka relational layers, tofts), and multiple attributes (text, value, or boolean-type). The CNS format is the native format for Ceunet/Indra and SocNet.se. XML specifications can be found here.
Although data in the Ucinet DL format can be stored in various ways, the two most common formats are Fullmatrix and Edgelist1, both of which are available in NetRepository. Fullmatrix format is generally recommended for dense matrices (i.e. datasets containing many ties), whereas the Edgelist1 format is best suited for sparse networks. Each DL file can contain multiple sociomatrices, though no attribute values can be stored in this format.
The CSV format (character-separated values) is compatible with most spreadsheet programs (e.g. Excel). As the CSV format can only contain a singular sociomatrix (without any attributes), choosing this format also gives you the choice of which sociomatrix to download. The values in the CSV file can either be separated by semicolon (;), comma (,), tab (\t), or a blank space ( ) character.
The Pajek format can contain multiple sociomatrices, though no attributes. Directional/non-symmetrical sociomatrices are stored as arcs, whereas symmetrical sociomatrices are stored as edges. Please observe that nodal characteristics, such as colors and coordinates, are excluded in this format, even though they could be seen as attributes.
(The GraphML format export filter is currently under construction).
Ceunet/Indra, SocNet.se and NetRepository represent a freeware software suite for network analysis. Sharing a common data format (CNS format), and with NetRepository storage-retrieval functions implemented in Ceunet/Indra and SocNet.se, the three parts can be used independently of eachother.
Ceunet is a Windows client program, written in C#, for analysis, handling/processing, and visualization of social network data. Although still lacking many of the features found in similar programs, Ceunet offers basic functionality for the handling, analysis, and visualization of network data.
Indra is a Windows client component for 3-dimensional visualization of network data. Initially developed as a stand-alone application, the Indra visualizer is currently integrated in the Ceunet program.
SocNet.se is a light-weight web-based version of Ceunet, offering rudimentary functionality for the analysis and handling of network data. Integrated with the NetRepository user accounts, users can access and work with their datasets - as well as accessing the public datasets - through any web browser. It also contains functions for exporting and importing datasets in various SNA-relevant formats.
Ceunet/Indra, SocNet.se and NetRepository is developed at the Center for Network Science (CNS) at Central European University, Budapest. For further information, development suggestions, or suggestions on possible public datasets to add, please contact Carl Nordlund at cns (at) ceu dot hu.