Accession Number:

ADA459444

Title:

DyNetML: Interchange Format for Rich Social Network Data

Descriptive Note:

Research paper

Corporate Author:

CARNEGIE-MELLON UNIV PITTSBURGH PA SCHOOL OF COMPUTER SCIENCE

Report Date:

2004-02-01

Pagination or Media Count:

25.0

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

Subject Categories:

  • Information Science
  • Psychology
  • Computer Programming and Software

Distribution Statement:

APPROVED FOR PUBLIC RELEASE