Data Representation - SS3 ICT Past Questions and Answers - page 2

Character sets are essential in data representation because they define the mapping between characters (letters, digits, symbols) and their corresponding binary representations. They allow computers to store, transmit, and process text-based data, enabling communication in human-readable form. Popular character sets like ASCII and Unicode facilitate multilingual support and ensure consistency in how characters are represented across different systems and applications.

In computer graphics, data representation is used to represent images as arrays of pixels, where each pixel's color and intensity are encoded using binary values. For example, a pixel in a black and white image can be represented by a single bit, where 0 represents white and 1 represents black. In color images, each pixel might be represented by multiple bytes, with each byte encoding the intensity of a specific color component (e.g., red, green, blue). This data representation allows computers to display, manipulate, and store graphical information efficiently.

UTF-8 and UTF-16 are both character encoding schemes used in Unicode. The primary difference between them is how they represent characters:

UTF-8: It uses a variable-length encoding, with characters represented using 8, 16, or 24 bits. Commonly used characters, like those in the ASCII set, are represented with 8 bits (1 byte), making it backward compatible with ASCII. This results in more efficient storage for predominantly English text but can require more bytes for less common characters.

UTF-16: It uses a fixed-length encoding with 16 bits (2 bytes) for most characters. This means that all characters, including ASCII characters, are represented using 16 bits. UTF-16 is more space-efficient for languages that predominantly use 16-bit characters but can be less efficient for languages with simpler character sets.

Data representation is critical in digital audio processing as it involves encoding sound waves into a format that computers can understand and manipulate. This representation often uses techniques like Pulse Code Modulation (PCM), where analog audio is sampled at discrete intervals, and each sample is represented as a numerical value. The bit depth (e.g., 16-bit, 24-bit) determines the precision of each sample. Data representation allows for tasks like audio recording, playback, editing, and compression to be performed digitally.

Converting data between numerical systems, such as from binary to decimal or hexadecimal, can introduce rounding errors, loss of precision, or truncation issues. For example, when converting a non-integer binary number to decimal, the result might be an approximation. Additionally, different numerical systems may have varying bases and digit representations, which can complicate conversions. Ensuring accuracy in conversions is crucial, especially in scientific and engineering applications.

Data structures play a crucial role in computer programming by organizing and representing data in memory efficiently. For instance, arrays provide a contiguous memory layout for easy access to elements, while trees enable hierarchical organization. Data structures optimize data storage and retrieval, reducing the time and resources needed for operations like searching, sorting, and manipulation. Choosing the right data structure for a specific task is key to efficient data representation and processing in computer programs.