A study on the development of data technology taxonomy for data economy

Area of Science:

• Information Science
• Technology Management
• Data Science

Background:

• The accelerating data economy and digital transformation highlight the critical importance of data technology.
• A lack of comprehensive data technology taxonomy hinders systematic policy development and R&D investment.
• Existing taxonomies have limitations that necessitate a new, validated classification system.

Purpose of the Study:

• To propose a novel data technology taxonomy for policy making, business planning, and national R&D investment.
• To define the concept of data technology and develop a robust classification system.
• To validate the taxonomy's utility through expert assessment and analysis of R&D projects.

Main Methods:

• Defining the concept of data technology.
• Developing a classification system by analyzing limitations of existing taxonomies.
• Collecting expert opinions to establish classification validity.
• Conducting an expert adequacy assessment.
• Classifying national R&D projects using the proposed taxonomy.

Main Results:

• A validated data technology taxonomy has been developed.
• The taxonomy's applicability in the field was verified through expert assessment.
• An analysis of national R&D projects based on the taxonomy provides insights into the current landscape.

Conclusions:

• The proposed taxonomy offers a structured approach to understanding data technology.
• It serves as a valuable tool for improving data policy formulation and R&D planning.
• This framework supports informed decision-making in the evolving data economy.