Transcript Data Capture Methods - Computing and ICT in a Nutshell

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
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
• Recognition is not
100% accurate
• Data is easily read by
humans as well as the
computer
• Dirty or damaged
documents are
difficult to read
• Converted documents
will need to be
checked
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 for
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
•Agree strongly
• How would you collect the responses?
• Would that be the most reliable
method?