Week 11

Lecture: This week we learned about Data, Information and Knowledge. There are some definition we were taught that are important which are: Datum - a fact or proposition, Information - a collection of facts or data, Knowledge - learned information. These 3 definitions also have characteristics which are: Data - factual, non-judgemental, non-inferential, transient, has no meaning and has no value. Information - summative, relational, dimensional, permanent, has meaning and uncertain value. Knowledge - inferential, experimental, judgemental, subjective and is very valuable. Also the definitions have importance like: data - must be quantitative and representative, information - must be inform, relational and meaningful, and knowledge - origins should be clear, must have a logical conclusion and have justification of data. Some examples of these are: data - price, shares, weather and census data. Information - tables of census data, almanacs and budgets. Knowledge - white pages, press release and marketing strategies. they all have relationships to each other which starts with data and then moves to information to where it can be stored as knowledge.

Workshop: We were given some tasks to do which are: to visit some dictionary websites to find the definitions of data, information and knowledge.
Data - raw facts and figures which is turned into information.
Information - is a collection of raw data but can also be data itself.
Knowledge - there was no term for knowledge as it is only what the person knows.

The relationship between data, information and knowledge is, raw data is recorded and transferred into readable accessible information and then we learn the information to which it becomes knowledge.

5 organisations that collect information are Bureau of Statistics, Australian Medical Association, City of Gosnells, Westpac Bank, Health Department of Australia, and Census of Australia.
They all collect information to produce statistic data so it can be analysed.

as posted on Jud's Blog