DyNetML: Interchange Format for Rich Social Network Data

Abstract

The authors define a universal data interchange format to enable the exchange of rich social network data and to improve the compatibility of analysis and visualization tools. DyNetML is an XML-derived language that provides a means to express rich social network data. DyNetML also provides an extensible facility for linking anthropological, process description, and other data with social networks. DyNetML has been implemented and in use by the CASOS group at Carnegie Mellon University as a data interchange format. The authors also have implemented parsing and conversion software for interoperability with other software packages

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2004
Accession Number
ADA459444

Entities

People

  • Jeff Reminga
  • Kathleen Carley
  • Maksim Tsvetovat

Organizations

  • Carnegie Mellon University

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Bayesian Networks
  • Coding
  • Computer Science
  • Computers
  • Conversion
  • Factor Analysis
  • Information Operations
  • Language
  • Petri Nets
  • Prototypes
  • Simulations
  • Social Networks
  • Specifications
  • Standards
  • Triangles
  • Universities

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Database Systems and Applications