1. Types of Data

2. Numbers Text Pictures Sound Video

3. Numbers Computers use Binary Eg 10000110 in binary is 8 bits (a byte) can only hold numbers up to 255, so how do you hold bigger numbers? – Use more than one byte!

4. Sound Sound can be drawn on a graph

5. Digitizing Sound Time is spit into units called the sampling rate As seen increasing the sampling rate makes the digitised data more accurate

6. Sampling Rate As the sampling rate increases the quality of the digitised sound increases

7. Converting to Digital

8. Conversion Example

9. Final Data This little segment of music has the following code 1011,1101,1101,1100,1010,1000,0110,0011, 0010,0001,0001,0011,0100,0110,0111,0110, 0100 Without the commas 101111011101110010101000011000110010 00010001001101000110011101100100 This is just for a split second CD’s are sampled at 44KHz, ie 44000 times a second!

10. Hardware An Analogue to Digital converter is used to do this digitising. To play back sound a sound card is needed – Converts the digital data back into an analogue sound

11. Midi (Musical Instrument Digital Interface) Electronic instruments use this standard to store data on notes. Allows keyboard to communicate with Guitar! Data stored includes – Pitch – Length – Dynamics – Type of sound – Very small file size (stores via ASCII)

12. Midi Examples

13. Midi PC’s can work with Keyboards and other Midi instruments Songs stored on disk then played through Keyboard etc Editing the song then becomes extremely easy via the PC

14. Images Two ways of creating an image on a PC Bit-map Vector

15. Bit-map Image made up of dots called pixels Each dot can have a colour assigned to it The number of possible colours depends upon the quality of the image Low quality = 2 colours ie black and white High quality = over 4 billion colours

16. Example Each pixel can be assigned either 0 for black or 1 for white This graphic has the value 00011110001011111101110 11110111110110111111100 11111111001111111011011 11101111011010111111010 1110000111 All this for one 10 x 10 black and white picture

17. The Maths 10 x 10 pixels = 100 ones and zeros If you have a high quality image with lots of colours you need 32 ones and zeros for each pixel! 10 x 10 x 32 = 320 ones and zeros This screen is 800 x 600 pixels! 800 x 600 x 32 = 15360000 ones and zeros approx 15Mb of memory! (This is why graphics cards need lots of memory!)

18. Bit-maps Used for photographs Jpeg, Giff, Tiff Easy to edit – Brush / spray Zoom / Resize problem!

19. Zoom / Resize Problems

20. Vectors Sometimes called Object Orientated Drawing Image made up of objects (shapes) Eg – Lines – Rectangles – Circles The shapes are mathematically stored in memory

21. Example A rectangle can be stored with two points plus information about line type and fill.

22. Vectors Very small memory overheads Device-independent Scalable

23. Any Questions