A novel database management logic designed for some important production stages of farm to table

Inhaltsverzeichnis (Table of Contents)

• Introduction
  • Comparison of different database models
  • Rivarly between NoSQL and SQL
  • Knowledge-based systems development
  • Joker Tao
  • Comparison of JT and ontological modeling
  • Mathematical definitions of the relational database model and JT database model
  • Mathematical definition of the relational database model
  • Mathematical definition of the JT database model
  • State of the art
    • Relational systems
    • NoSQL systems
  • Objectives of my research and development
• Methods
  • Research methods
  • The developed data storage and management methods
    • Four dimension of knowledge stored in data table
    • The developed JT algorithm exerting method
    • Virtual data table management
    • Indexing in JT
    • Converting data tables to one physical data table
  • Storing and processing the unknown, or from the data to the information
  • Technological environment
    • Cloud-based solutions
• Results and discussion
  • Research results
  • Development results
  • JT database management
    • JT seed
    • ID usage
    • JT attribute
    • T_sequence and value
    • The dialectic of entity and attribute
    • JT Shell
    • Application Initialization (login) and access controls
    • Efficiency indicators
    • Development directions
    • Subset determination in JT logic
• Conclusions
  • Conclusions of the research results
  • Conclusions of the development results
• New and novel results

Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)

This dissertation presents a novel database management logic, named Joker Tao (JT), specifically designed for key production stages within the "farm to table" food production chain. The study aims to address the limitations of traditional database models, particularly in handling complex and dynamic data associated with agricultural production and distribution. The research focuses on developing a robust and efficient database system that can effectively capture, store, and manage the various forms of knowledge related to this domain.

• Comparison of different database models, including SQL and NoSQL
• Development and implementation of the JT database logic
• Application of JT in the management of agricultural data
• Analysis of the efficiency and scalability of the JT system
• Evaluation of the potential benefits and limitations of JT in the "farm to table" context

Zusammenfassung der Kapitel (Chapter Summaries)

• Chapter 1: Introduction This chapter sets the stage for the dissertation by discussing the challenges of managing agricultural data, comparing different database models, and introducing the concept of Joker Tao (JT). It outlines the research objectives and the need for a new approach to database management in the context of food production.
• Chapter 2: Methods This chapter details the research methods employed in the dissertation. It discusses the development of the JT algorithm and the underlying principles of the new database management logic. The chapter further explores the technological environment in which the JT system operates, including cloud-based solutions.
• Chapter 3: Results and Discussion This chapter presents the research findings and a detailed discussion of the JT database management system. It explores various aspects of the system, including JT seed, ID usage, JT attributes, and the JT shell.

Schlüsselwörter (Keywords)

This dissertation focuses on the following keywords: database management, Joker Tao (JT), agricultural data, knowledge-based systems, farm to table, NoSQL, SQL, relational database model, ontological modeling, cloud computing, data storage, data processing, information management, efficiency, scalability.