Data Management

DATA MANAGEMENT PLAN

Introduction

This Data Management Plan (DMP) covers the data which will be collected under the proposed project entitled ‘Causal inference in visual identification: Integrating models, experimental paradigms, and behavioral measures’ and is designed to be consistent with the NSF Policy on Dissemination and Sharing of Research Results. In accordance with this policy, this plan does not include preliminary analyses (including raw data), drafts of scientific papers, plans for future research, peer reviews, or communications with colleagues. Furthermore, data to enable peer review and publication/dissemination and/or to protect intellectual property may be temporarily withheld from distribution and other proposed data management. This plan will make certain that the data produced during the period of this project is appropriately managed to ensure its usability, access and preservation.

Description of Data

The types of data to be produced in the course of the project include background demographic information, accuracy and reaction time for the proposed visual identification tasks, and the results from computational model simulations. The demographic data is needed for published reports to convey the characteristics of the subject population.

Standards for Data and Metadata Format and Content

For preservation and long-term access, data collection will be accompanied with proper documentation and associated metadata. Files will include the data itself saved as Matlab (.mat) files, documentation files which a description of how the data was collected, and metadata in the form of the Matlab routines (Psychophysics toolbox) that administer each behavioral task.

Data Access, Sharing and Archiving

The researchers associated with this study are not aware of any reasons that might prohibit the sharing of the data to be generated under this project for public use and potential secondary uses. The principal investigators retain the right...