Data Capture Methods

1. Data Capture Methods

2. Data Capture Methods • In this topic, we will be looking at: • Methods of data capture • When it would be appropriate to use each method • Advantages and disadvantages of each • The concept of encoding

3. Manual Input • Methods that register movements of the hand include: • mouse • keyboard • tracker ball • graphics tablet • touch-screen – e.g. PDA

4. Advantages and Disadvantages • there shouldn’t be much of a need for training, as most people are already familiar with the concept • ICT systems can be similar to manual ones – no need for specialised data collection sheets • It can be slow to enter data • Transcription (data entry) errors can occur • Handwriting recognition can be unreliable

5. Optical Methods • Methods that read data optically include: • Optical Mark Readers (OMR) • Optical Character Recognition (OCR) • Punched cards, paper tape andKimball tags • Barcodes

6. Advantages and Disadvantages • Large amounts of data can be read quickly • Data can be read without human intervention • Easy for staff to use Kimball tags or barcodes – no specialist knowledge needed • Specialist equipment is needed to prepare the data for entry – e.g. tags or forms • Only good for a limited range of data – closed questions • Medium is often paper – easily damaged (not including optical character recognition)

7. Optical Character Recognition Text is scanned then converted into real, editable text

8. Advantages and Disadvantages • Recognition is not 100% accurate • Converted documents will need to be checked • Dirty or damaged documents are difficult to read • No special data-preparation equipment required – it just uses text on ordinary paper • Data is easily read by humans as well as the computer

9. Voice Recognition • Voice recognition can be used for: • Controlling devices (small vocabulary systems) • Dictation (large vocabulary systems) • Small vocabulary systems are usually more reliable and may not need training

10. Advantages and Disadvantages • No special data-preparation equipment required – you just say the data • Data is easily understood by humans as well as the computer • Little training is required • Recognition is not 100% accurate • Dictation systems need to be trained • Not everything – e.g. mathematical formulae – are easy to describe in words

11. Card Input • Cards can contain data on: • Magnetic strips – e.g. bank cards and train tickets – these contain little data and are easily damaged • Chips (Smart Cards) – such as the new “Chip and Pin” credit cards and some loyalty cards. These contain more data and are harder to copy/forge

12. Magnetic Ink Character Recognition The characters are printed in magnetic ink at the bottom of cheques: Account details

13. Advantages and Disadvantages • Data is easily read by humans as well as the computer • Little training is required – you just feed the cheques into the machine • It’s difficult for forgers to change details • Specialist high-quality printing equipment is required – this obviously costs more!

14. Encoding Information • Sometimes you might want to turn information into data – i.e. to store it – this is called encoding • Your data capture methods will form part of the encoding process – how are you going to collect the information? • How do you code information to make it easy to re-process, without losing it’s meaning?

15. Encoding Example • Often surveys have questions like this: • A level ICT is brilliant! • Disagree strongly • Disagree • Neither agree nor disagree • Agree • Agree strongly • How would you collect the responses? • Would that be the most reliable method?