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Data Reporting and Recording01:24

Data Reporting and Recording

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Related Experiment Video

Updated: Jul 2, 2026

Combining Multiple Data Acquisition Systems to Study Corticospinal Output and Multi-segment Biomechanics
08:48

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ActSds and OdfSds: programs for converting INTERACT and The Observer data files into SDIS timed-event sequential data

Roger Bakeman1, Vicenç Quera

  • 1Department of Psychology, Georgia State University, Atlanta, Georgia 30302, USA. bakeman@gsu.edu

Behavior Research Methods
|August 14, 2008
PubMed
Summary

This study introduces programs to convert INTERACT and The Observer data files into Sequential Data Interchange Standard (SDIS) format. This conversion enables users to leverage advanced data analysis with the Generalized Sequential Querier tool.

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Area of Science:

  • Behavioral Science
  • Data Science
  • Computer Science

Background:

  • Behavioral research often generates complex timed-event data.
  • Specialized software like INTERACT and The Observer are widely used for data collection.
  • Interoperability between different data analysis tools is a common challenge.

Purpose of the Study:

  • To present software tools for converting INTERACT and The Observer data files.
  • To facilitate the use of the Generalized Sequential Querier for data analysis.
  • To enhance data processing capabilities for behavioral researchers.

Main Methods:

  • Development of conversion programs for INTERACT data files.
  • Development of conversion programs for The Observer data files.
  • Formatting converted data into Sequential Data Interchange Standard (SDIS).

Main Results:

  • Successful conversion of INTERACT and The Observer data to SDIS format.
  • Demonstrated compatibility of SDIS files with the Generalized Sequential Querier.
  • Enabled access to advanced data modification and computation.

Conclusions:

  • The developed programs improve data interoperability in behavioral research.
  • Researchers can now utilize powerful analytical tools on previously incompatible data.
  • Facilitates more efficient and comprehensive analysis of timed-event sequential data.