# Data Representation

Spread the love
Data Representation Study Sheet
A summary of all the numeric conversions, with examples.
Conversion charts
One page reference sheet with binary/octal and binary/hexadecimal conversion tables and powers of 2.
Number Systems Tutorial
Computer Number Systems Tutorial
Quick conversions
A quick method of converting binary numbers to decimal.
Binary, octal, and hexadecimal numbers.
Converting Binary, Decimal, and Hexadecimal Notation
Another page discussing base conversions.
Numeric Conversion Data
Includes a table showing decimal/binary/ternary (that’s base 3)/octal/hexadecimal values and a Java-based conversion calculator.
Arithmetic overflow
Wikipedia discussion
How Many Bytes…
How many bytes does it take to store _____?
Memory Sizes Explained
From MakeUseOf.com
ASCII/ANSI symbol table
ASCII definition from Wikipedia
Alt-Codes
Web site with links to lists of alt-codes for all available characters and how to type them on Windows, Mac OS/X, and Linux systems.
Also include links to Facebook/MySpace text & symbol generators.
Unicode organization home page
includes background information and the current working definition.
Unicode & UTF-8 Character Sets
From Smashing Magazine
The Absolute Minimum Every Software Developer Must Know About Unicode
Introduction to raster graphics

## Key Terms

• Analog: Containing values that may take on any continuous value.
• Arithmetic overflow: Error condition resulting from an operation on a computer that produces an unsigned value greater than 65,535.
• ASCII: The most widely used code for representing characters internally in a computer system.
• Binary numbering system: A system of numbers made out of two values: 0 and 1.
• Compression ratio: Measures how much compression schemes reduce the storage requirements of data.
• Data compression: A process of reducing the amount of space required to store large data files, with or without loss of detail.
• Digitize: To transform analog data into a digital format.
• Lossless compression schemes: No information is lost in the compression, and it is possible to exactly reproduce the original data.
• Lossy compression schemes: Compress data in a way that does not guarantee that all of the information in the original data can be fully and completely recreated.
• Mantissa: The base value of a decimal number written in scientific notation.
• Pixel: A single point sampled from a photographic image and stored in the digital format.
• Raster graphics: Each pixel is encoded as an unsigned binary value representing its gray scale intensity.
• Sampling: The process of reading values from analog data at regular intervals and using the sampled data to represent the analog version.
• Sampling rate: Measures how many times per second we sample the amplitude of the sound wave.
• Scanning: Consists of measuring the intensity values of distinct points located at regular intervals across the image’s surface.
• Sign/magnitude notation: Technique used to represent positive and negative whole numbers.
• True Color: 24-bit color-encoding scheme that allows us to represent 224 distinct colors, about 16.7 million.
• Two’s complement representation: Signed integer representations that do not suffer from the problem of two zeros.
• UNICODE: Uses a 16-bit representation for characters rather than the 8-bit format of ASCII.
• Variable length code sets: Often used to compress text but can also be used with other forms of data.