What Is Data Representation? KS3 Computing Guide

Data representation is the study of how computers store every type of information — text, images, sound, video — as binary numbers. At KS3, understanding this topic explains why computers can only work with 0s and 1s, yet still display photos, play music, and run apps. It is the bridge between the physical world and the digital one.

Why does everything in a computer become binary?

A computer is built from billions of transistors — tiny electronic switches that are either on or off. On is represented as 1; off is represented as 0. Because there are only two possible states, every piece of data must be encoded using combinations of just two digits: 0 and 1. This two-digit system is called binary.

The DfE national curriculum for computing requires KS3 students to understand "how data of various types (including text, sounds and pictures) can be represented and manipulated digitally" (gov.uk/government/publications/national-curriculum-in-england-computing-programmes-of-study). Data representation is therefore not just an abstract concept — it directly explains how every app, website and song you encounter actually works.

A single binary digit is called a bit. Eight bits form a byte. Larger units such as kilobytes (KB), megabytes (MB) and gigabytes (GB) describe how much data can be stored.

How is text stored in binary? ASCII and Unicode

ASCII encoding

Each character — every letter, digit, and punctuation mark — is assigned a unique number. That number is then stored in binary. The most widely taught standard at KS3 is ASCII (American Standard Code for Information Interchange), which assigns 7-bit codes to 128 characters.

Character | Decimal value | Binary (8-bit)
Space | 32 | 00100000
A | 65 | 01000001
B | 66 | 01000010
Z | 90 | 01011010
a | 97 | 01100001
b | 98 | 01100010
z | 122 | 01111010
0 | 48 | 00110000

Notice that uppercase A (65) and lowercase a (97) have different codes. That is why "Hello" == "hello" is False in Python — the computer stores them as different binary values.

To find how much storage a piece of text needs, count the characters and multiply by the number of bits per character. The word CAT in ASCII uses 3 characters × 8 bits = 24 bits = 3 bytes.

Unicode

ASCII covers only 128 characters — enough for English but not for the thousands of characters used in other writing systems. Unicode extends the idea to cover over 140,000 characters, including every major script used worldwide, mathematical symbols, and emoji. Modern systems default to Unicode, which is why your phone can display text in many languages and show emoji alongside ordinary letters.

BBC Bitesize (bbc.co.uk/bitesize/subjects/zvc9q6f) has interactive ASCII activities where students can decode secret messages and encode their own names in binary — a good way to make this topic concrete.

How are images stored in binary?

Pixels and resolution

A digital image is made up of a grid of tiny squares called pixels (short for "picture elements"). Each pixel stores colour information as a binary number. The total number of pixels in an image is its resolution — a higher resolution means more pixels and therefore more detail.

Resolution is often expressed as width × height. A 1920 × 1080 image (Full HD) contains 1,920 × 1,080 = 2,073,600 pixels.

Colour depth

Colour depth (also called bit depth) is the number of bits used to store the colour of each pixel. More bits means more possible colours.

Colour depth | Colours available | Use
1 bit | 2 (black or white) | Simple black-and-white images
8 bit | 256 | Basic colour or greyscale
24 bit | 16,777,216 | True colour (standard for photos)

Worked example: calculating image file size

Question: A black-and-white image is 4 pixels wide and 4 pixels tall. Each pixel uses 1 bit (black = 0, white = 1). What is the file size in bits and bytes?

Working:

Total pixels = 4 × 4 = 16 pixels

Bits per pixel = 1

File size = 16 × 1 = 16 bits = 2 bytes

Here is what the 4 × 4 image might look like in binary (1 = black pixel, 0 = white pixel):

0 1 0 1
1 0 1 0
0 1 0 1
1 0 1 0

Extended example: A colour image is 100 pixels wide, 100 pixels tall, and uses 24-bit colour. What is its file size in bytes?

Total pixels = 100 × 100 = 10,000 pixels

Bits per pixel = 24

Total bits = 10,000 × 24 = 240,000 bits

File size = 240,000 ÷ 8 = 30,000 bytes = approximately 29.3 KB

This explains why photographs take up much more storage than text files — each pixel requires many bits of colour information, and a typical photo contains millions of pixels.

How is sound stored in binary?

Sound is a continuous wave — air pressure that rises and falls over time. To store sound digitally, a computer must convert this continuous wave into a series of discrete numbers. This process is called sampling.

Sampling rate

A sample is a measurement of the sound wave's amplitude (height) at a single moment in time. The sampling rate is how many samples are taken per second, measured in hertz (Hz) or kilohertz (kHz).

44,100 Hz (44.1 kHz) — standard CD audio quality; 44,100 samples per second

8,000 Hz — telephone quality; noticeably lower fidelity

A higher sampling rate captures more detail and produces better sound quality, but also creates larger files.

Bit depth

The bit depth (or sample resolution) is the number of bits used to store each sample. More bits means each sample can store more precise amplitude information.

8-bit — 256 possible amplitude values; sounds noticeably "grainy"

16-bit — 65,536 possible values; CD quality

24-bit — 16,777,216 values; used in professional audio recording

A one-second mono audio clip at 44,100 Hz with 16-bit depth requires 44,100 × 16 = 705,600 bits = approximately 86 KB.

Data representation: summary comparison table

Data type | How it is stored | Key terms
Numbers | Directly as binary | Bits, bytes, binary
Text | Each character → ASCII/Unicode number → binary | Character, ASCII, Unicode, encoding
Images | Grid of pixels; each pixel's colour → binary | Pixel, resolution, colour depth, bit depth
Sound | Sampled at regular intervals; each sample → binary | Sampling rate (Hz), bit depth, amplitude

Frequently asked questions

What is data representation in KS3 computing?

Data representation is the way computers convert all types of information — numbers, text, images, and sound — into binary (sequences of 0s and 1s) so that electronic circuits can store and process them. It is a core topic in the KS3 national curriculum because it explains the fundamental link between the physical world and digital technology.

What is ASCII and why is it used in KS3?

ASCII (American Standard Code for Information Interchange) is a character-encoding standard that assigns a unique number from 0 to 127 to each letter, digit, and common symbol. Computers store the binary equivalent of these numbers. ASCII is taught at KS3 because it clearly shows how text is converted to binary in a small, easy-to-follow table.

How do you calculate image file size at KS3?

Multiply the number of pixels (width × height) by the colour depth in bits. Then divide by 8 to convert bits to bytes. For example, a 10 × 10 pixel image with 8-bit colour uses 10 × 10 × 8 = 800 bits = 100 bytes. Increasing resolution or colour depth increases the file size proportionally.

What is the difference between sampling rate and bit depth for sound?

Sampling rate is how often the sound wave is measured per second (e.g. 44,100 times per second for CD quality). Bit depth is how precisely each measurement is stored (e.g. 16 bits per sample gives 65,536 possible values). Both affect sound quality and file size: doubling the sampling rate doubles the file size; doubling the bit depth also doubles the file size.

Why can a computer not store text directly without encoding?

Computers only understand binary — on or off, 1 or 0. A letter like "A" has no natural binary equivalent the way the number 65 does. Character encoding standards such as ASCII and Unicode create an agreed mapping between characters and numbers, so every computer in the world represents "A" in the same binary pattern (01000001 in ASCII). Without a shared encoding standard, files created on one computer could not be read correctly on another.

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