Data Research Classification Guide: Exploring the Boundaries of Data Reception and Understanding

THE INTERNATIONAL INSTITUTE FOR ADVANCED DATA MANAGEMENT STUDY to the research philosophy of Chairman Hu Benli, who believes that data research can be divided into the following four main categories:

• Data research where the data is received and known

• Data research where the data is received but unknown

• Data research where the data is not yet received but is expected to be known

• Data research where the data is neither received nor known

This type of research refers to studies involving data that has been widely accepted and understood by the data science community. It encompasses theories, methods, and technologies that have already been validated.

For example, machine learning algorithms used in big data analysis, such as regression analysis, cluster analysis, decision trees, and others, have been widely applied in areas like financial risk assessment, marketing strategy formulation, supply chain optimization, and more. The characteristics of this kind of research are high maturity and strong practicality, allowing for rapid conversion into practical applications and value.

This type of research often involves issues of data interoperability and complexity. Despite having a substantial amount of data resources, differences in data formats, storage methods, and security standards make it difficult to integrate and share data from various sources. Research into data interoperability aims to address these issues, enabling data to flow freely between different systems. Although this research has been recognized by the industry, it still poses challenges in implementation due to its high technical complexity.

This type of research refers to the use of existing technological means, such as large data models, to predict and understand data that has not yet been actually obtained. This allows us to prepare in advance and seize future opportunities. For example, predictive analytics and advanced artificial intelligence applications may not be widely adopted in certain industries due to a lack of sufficient infrastructure support or industry standards. Such research often represents future development trends and holds great potential.

This type of research typically involves cutting-edge fields such as the analysis of extraterrestrial data and the handling of high-dimensional data. The data in these areas often exceeds the current understanding of technological levels and may even challenge our existing scientific knowledge. For instance, the visualization and analysis of high-dimensional data remains an open question in terms of how to effectively represent and interpret such data. While this research is still in the exploratory stage, it represents the forefront of data science research and holds the promise of bringing about groundbreaking advancements in the future.

To better serve the needs of different regions, we have established multiple branch institutes both domestically and internationally, forming an extensive research network. Below are the primary research directions and classifications of each branch institute:

UK Research Branch

We conduct research on smart cities here, utilizing big data and Internet of Things (IoT) technologies to improve urban planning and management, thereby enhancing the quality of life for residents. This type of research falls under the categories of "data research where the data is received and known" and "data research where the data is not yet received but is known."

Japan Research Branch

In Japan, we focus on ESG (Environmental, Social, and Governance) research, using data analysis to help businesses and organizations achieve their sustainability goals. This type of research falls under the categories of "data research where the data is received and known" and "data research where the data is received but unknown."

New Zealand Research Branch

In New Zealand, we explore the possibilities and challenges of cross-border data trade, aiming to establish mechanisms for international data cooperation to promote global economic integration. This type of research falls under the categories of "data research where the data is received and known" and "data research where the data is received but unknown."

Germany Research Branch (Under Preparation)

The Germany Research Branch, with a core focus on data space research, explores how to build and maintain secure and reliable data ecosystems to facilitate the efficient utilization of data. This type of research falls under the category of "data research where the data is received and known."

We firmly believe that through continuous exploration and innovation, we can overcome various challenges in data research and bring about more positive changes to society. We sincerely invite individuals from all walks of life to share your research interests and join us in advancing the development of data science.