Developing and communicating responsible data management policies to trainees and colleagues
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Updated: Jun 11, 2026

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
Published on: November 22, 2019
Julia Frugoli1, Anne M Etgen, Michael Kuhar
1Department of Genetics and Biochemistry, Clemson University, 100 Jordan Hall, Clemson, SC 29634, USA. jfrugol@CLEMSON.EDU
Abstract:
The basic components of data management including data ownership, collection, selection, recording, analysis, storage, retention, destruction, and sharing. A number of important principles underlie best practices for each of these components; these include recording details such that another can repeat the experiment, keeping the data safe, managing storage in such a way as to facilitate easy retrieval for the period of time required by regulatory agencies and establishing data sharing principles with colleagues before collaborations begin. Experience as practicing scientists and teachers has aided in developing helpful strategies and approaches for communicating these principles, policies and practices to trainees and colleagues. We recommend didactic instruction focused by discipline, combined with the use of "teachable moments" in a student's career, as well as teaching principles versus rules, because changing methods of data collection and storage have implications for data management practices.
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