Relational data model || CHAP 3 || Design & Implementation of GIS || IOE || 7th sem

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 📚 Design & Implementation of GIS – Chapter 3: Relational Data Model (Full Chapter + Free PDF + Key Concepts for GIS)

🚀 Curious how GIS software stores and connects spatial data efficiently? Chapter 3 of Design & Implementation of GIS introduces the Relational Data Model—a core concept behind every modern GIS and database system.

📥 Download the Free PDF Notes, learn about relations, tuples, keys, and how spatial data fits into relational tables. This chapter is essential for 7th semester Geomatics Engineering students and NEC License exam preparation.

📌 Overview

The Relational Data Model (RDM) is the backbone of many GIS applications, enabling structured storage, manipulation, and querying of both spatial and non-spatial data.

In this chapter, you’ll learn why GIS databases like PostGIS, Oracle Spatial, and ArcSDE use relational structures to store real-world entities like land parcels, roads, and buildings. From keys and constraints to how data is linked across tables, this chapter is short but powerful.

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📚 What’s Covered in Chapter 3: Relational Data Model?

This chapter focuses on understanding how spatial and tabular data are represented in relational structures. You'll explore the need for relational models, the key terminologies, and how constraints ensure data consistency.

📌 Key Topics in This Chapter

✔️ Need for Relational Data Model
Understand why relational models are preferred in GIS over file-based or hierarchical systems.

✔️ Terminologies You Must Know

  • Relation = Table

  • Tuple = Row

  • Attribute = Column

  • Schema = Structure definition

  • Instance = Actual data at a moment
    These are crucial when working with SQL and spatial queries.

✔️ Relational Constraints
Learn how constraints ensure data integrity, like:

  • Primary Key: Unique identifier (e.g., Parcel ID)

  • Foreign Key: Linking attribute between tables (e.g., Owner ID)

  • Unique / Not Null Constraints: Ensure meaningful, valid data

✔️ Keys in Relational Models

  • Candidate Key: Potential primary key

  • Super Key: Any key that can uniquely identify rows

  • Composite Key: A combination of two or more attributes

📂 Download Free PDF Notes – Chapter 3: Relational Data Model
Perfect for:

✅ Fast-track exam revision
✅ NEC License Theory section
✅ SQL practice and GIS lab reports

🔽 [Download Notes – Chapter 3: Relational Data Model]

🧩 Understanding the Relational Data Model

The RDM organizes data into tables (relations), where each table consists of rows (tuples) and columns (attributes). This tabular structure allows for:​

  • Data Integrity: Ensuring accuracy and consistency through constraints.

  • Flexibility: Easily adding, updating, or deleting data without affecting the overall structure.

  • Scalability: Handling large datasets efficiently.​

In GIS, this model supports the integration of spatial data (like coordinates) with attribute data (like names or IDs), facilitating complex spatial analyses.​

🔑 Key Terminologies

  • Relation (Table): A set of tuples sharing the same attributes.

  • Tuple (Row): A single record in a table.

  • Attribute (Column): A specific property or characteristic of a tuple.

  • Schema: The structure defining the organization of data in a database.

  • Instance: The actual content of the database at a particular moment.

🛡️ Relational Constraints

Constraints ensure the validity and integrity of the data:​

  • Primary Key: Uniquely identifies each record in a table.

  • Foreign Key: Establishes a link between two tables.

  • Unique Constraint: Ensures all values in a column are distinct.

  • Not Null Constraint: Ensures that a column cannot have a NULL value.​

🗝️ Types of Keys in RDM

  • Candidate Key: A minimal set of attributes that can uniquely identify a tuple.

  • Super Key: A set of attributes that can uniquely identify a tuple (may include extra attributes).

  • Composite Key: A key composed of two or more attributes to uniquely identify a tuple.​

🌐 Application in GIS: Real-World Example

Land Ownership Database

In a GIS application managing land ownership:​

  • LandParcel Table:

    • ParcelID (Primary Key)

    • Area

    • Location

    • OwnerID (Foreign Key)

  • Owner Table:

    • OwnerID (Primary Key)

    • Name

    • Contact Information

These tables are linked via the OwnerID, allowing for efficient queries such as:​


SELECT Name, Area
FROM LandParcel
INNER JOIN Owner ON LandParcel.OwnerID = Owner.OwnerID;

This query retrieves the names of landowners along with the area of their respective parcels.​

📘 Study Tips

  • Create Sample Tables: Use tools like Excel or database software to design and populate tables.

  • Draw ER Diagrams: Visualize relationships between entities to understand the schema better.

  • Practice SQL Queries: Write and execute queries to reinforce your understanding.

  • Explore GIS Software: Use applications like QGIS or ArcGIS to see the RDM in action.​

🎯 Key Takeaways

  • The Relational Data Model is essential for organizing and managing GIS data.

  • Understanding keys and constraints is crucial for maintaining data integrity.

  • Practical application of RDM enhances the efficiency and scalability of GIS projects.​

🧠 Real-World GIS Example

📌 Land Ownership Database
A relational database can have:

  • LandParcel table: (ParcelID, Area, Location, OwnerID)

  • Owner table: (OwnerID, Name, Contact)

These are linked by a foreign key, making spatial data both efficient and scalable. You can run SQL queries like:


SELECT Name, Area FROM LandParcel INNER JOIN Owner ON LandParcel.OwnerID = Owner.OwnerID;

🔍 Sample Questions from Chapter 3

  • Define the relational data model and its advantages.

  • Differentiate between primary key and foreign key.

  • What are the key terminologies used in a relational schema?

  • Why are constraints necessary in relational databases?

  • Explain how relational models support spatial data storage.

💡 Study Tips to Master Chapter 3

🔹 Create a Table from Real Data
Use Excel or a database tool to create your own relational tables—e.g., road networks, ward boundaries, school locations.

🔹 Draw Relationship Diagrams
Visualize how tables are connected using arrows for keys—this helps in both design and SQL writing.

🔹 Practice with SQL
This chapter is a bridge to the next: SQL. So start thinking in SELECTs and JOINs.

🔹 Use PostgreSQL/PostGIS or QGIS
Try using a real GIS database to import and query spatial tables.

🎯 Lessons Learned from Chapter 3: Relational Data Model

✅ Learn the structure of relational tables used in GIS
✅ Understand how keys and constraints maintain data quality
✅ Build the foundation for spatial SQL queries
✅ Prepare for higher-level spatial database concepts like joins, indexing, and schema design

📌 Explore More from Design & Implementation of GIS

📚 Chapter 1: Introduction to DBMS– Download PDF
📚 Chapter 2: Data Models and Database Languages – Download PDF
📚 Chapter 3: Relational Data Model – Download PDF
📚 Chapter 4: SQL – Download PDF
📚 Chapter 5: Spatial Database Technology – Download PDF
📚 Chapter 6: Spatial Concepts and Models – Download PDF
📚 Chapter 7: Spatial Query Language – Download PDF
📚 Chapter 8: Computational Geometry – Download PDF

📚 Chapter 9: Spatial Storage & Access Methods – Download PDF🎥 📚 Subscribe to STUDY WITH ME – Your Ultimate GIS Study Partner!
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