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The legal guidelines for nursing documentation are essential for ensuring accurate, professional, and ethical recording of patient care. The guidelines are discussed here:
Archival Research01:40

Archival Research

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Epigenetic Regulation

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Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
09:43

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

Data management in academic settings: an intellectual property perspective.

Lisa Geller1

  • 1Boston University School of Law, Boston, MA 02215, USA. lgeller@bu.edu

Science and Engineering Ethics
|November 25, 2010
PubMed
Summary

Academic institutions must prioritize robust data management to protect valuable intellectual property assets. Responsible data handling is crucial for capturing, developing, and safeguarding institutional innovations.

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Last Updated: Jun 6, 2026

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
09:43

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

Area of Science:

  • Intellectual Property Law
  • Data Management
  • Academic Research

Background:

  • Intellectual property (IP) represents a significant asset for academic institutions.
  • Effective data management is fundamental for the capture, development, and protection of these IP assets.
  • The intersection of data management and IP protection is critical for research integrity and commercialization.

Purpose of the Study:

  • To review key issues concerning the relationship between data management practices and intellectual property.
  • To advocate for the ethical and responsible management of research data within academic settings.
  • To underscore the importance of data stewardship in maximizing the value of institutional IP.

Main Methods:

  • Literature review of selected issues at the interface of data management and intellectual property.
  • Analysis of existing frameworks and best practices for data governance in academia.
  • Synthesis of arguments supporting the thesis of responsible data management.

Main Results:

  • Identified critical data management practices essential for IP asset lifecycle.
  • Highlighted the legal and ethical implications of inadequate data stewardship.
  • Demonstrated the direct correlation between data quality and IP value.

Conclusions:

  • Academic institutions and scientists have a fiduciary duty to manage data responsibly.
  • Implementing strong data management protocols is imperative for securing intellectual property.
  • Responsible data management enhances research output and institutional reputation.