Intellectual property and data governance

No specific legal background is required.

Students should possess a general understanding of innovation processes, research and development activities, and data-driven technologies. Familiarity with digital technologies, software development, or artificial intelligence applications may facilitate the understanding of certain examples but is not mandatory.

By the end of this course, students will be able to:

• Understand the role of Intellectual Property (IP) in innovation and value creation.
• Identify the main forms of intellectual property protection and their respective scopes.
• Distinguish between patents, trademarks, designs, copyrights, software protection, and database rights.
• Analyze an innovation from a legal perspective and identify appropriate protection strategies.
• Understand the contractual mechanisms commonly used to manage intellectual property rights.
• Recognize the strategic importance of data governance in organizations.
• Understand the concepts of data quality, data excellence, and data stewardship.
• Identify the roles and responsibilities involved in data governance frameworks.
• Develop awareness of legal, ethical, and organizational issues related to the creation, use, sharing, and protection of data.

Innovation increasingly relies on the creation, exploitation, and protection of intangible assets such as knowledge, software, data, algorithms, and scientific discoveries. This course introduces students to the fundamental principles of Intellectual Property (IP) and Data Governance, two essential dimensions of innovation management in modern organizations.

Students will learn how innovations can be legally protected, how intellectual property rights contribute to value creation, and how organizations manage ownership, exploitation, and transfer of intangible assets. The course also introduces the foundations of data governance, focusing on data quality, responsibilities, compliance, and best practices for managing data throughout its lifecycle.

Through practical case studies and workshops, students will learn to identify intellectual assets, assess potential protection mechanisms, and evaluate governance challenges associated with data-intensive projects.

Innovation and Entrepreneurship

• Understand the strategic value of innovation and intangible assets.
• Integrate intellectual property considerations into innovation processes.
• Evaluate opportunities and risks associated with technology transfer and commercialization.

Legal and Ethical Awareness

• Develop awareness of legal frameworks governing innovation and data.
• Understand rights, obligations, and responsibilities related to intellectual property and data management.
• Incorporate ethical and compliance considerations into digital projects.

Data Governance and Digital Responsibility

• Understand the principles of data governance and data quality management.
• Recognize organizational roles and responsibilities related to data stewardship.
• Promote responsible and sustainable data practices.

Project and Innovation Management

• Identify intellectual property risks and opportunities during project development.
• Collaborate effectively with legal, technical, and business stakeholders.
• Integrate governance considerations into digital and AI projects.

Assessment is based on participation in practical workshops and case-study analyses.

Students are evaluated through:

• Qualification and analysis of innovation scenarios.
• Identification of appropriate intellectual property protection mechanisms.
• Assessment of data governance challenges and responsibilities.
• Oral or written presentation of workshop outcomes.
• Quality of reasoning and justification of proposed protection and governance strategies.

The evaluation focuses on the ability to apply concepts to realistic innovation and data-management situations.

Intellectual Property

• WIPO. Understanding Intellectual Property. World Intellectual Property Organization.
• Cornish, W., Llewelyn, D., Aplin, T. Intellectual Property: Patents, Copyright, Trademarks and Allied Rights. Sweet & Maxwell.
• Bainbridge, D. Intellectual Property. Pearson Education.

Innovation Management

• Tidd, J., Bessant, J. Managing Innovation. Wiley.
• Chesbrough, H. Open Innovation. Harvard Business Review Press.

Data Governance

• Ladley, J. Data Governance: How to Design, Deploy and Sustain an Effective Data Governance Program. Academic Press.
• Seiner, R. Non-Invasive Data Governance. Technics Publications.
• DAMA International. DAMA-DMBOK: Data Management Body of Knowledge.

Regulations and Standards

• General Data Protection Regulation (GDPR).
• European Data Governance Act.
• OECD Principles on Digital Governance and Data Management.

• Juliette Spinnato