Data Capture Methods Data Capture Methods In this

Data Capture Methods

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

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

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

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

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)

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

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

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

Advantages and Disadvantages • No special datapreparation 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

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

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

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 forgers to change details • Specialist highquality printing equipment is required – this obviously costs more!

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?

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