Monday, September 12, 2011
Exercise 3
Library of Congress Classification (LC)
In library science, a method of classifying knowledge for the purpose of cataloging books and other library materials, devised by the staff of the Library of Congress in Washington, D.C.
In the Library of Congress Classification system (familiarly known as LC), all knowledge is divided into 21 large classes, indicated more or less arbitrarily by capital letters—as
follows:
A General Works
B Philosophy, Psychology, and Religion
C Auxiliary Sciences of History
D General and Old World History
E History of America
F History of the United States and British, Dutch, French, and Latin America
G Geography, Anthropology, and Recreation
H Social Sciences
J Political Science
K Law
L Education
M Music
N Fine Arts
P Language and Literature
Q Science
R Medicine
S Agriculture
T Technology
U Military Science
V Naval Science
Z Bibliography, Library Science, and General Information Resources
Within each of these classes, material is arranged from general considerations to specific treatments and from theory to practical applications; specific topics are indicated by combinations of capital letters, and further subject breakdowns by 3-digit numbers. The classification scheme is continually revised.
Dewey Decimal Classification (DDC)
Dewey Decimal Classification (familiarly known as DDC), in library science, a method of classifying knowledge for the purpose of cataloging books and other library materials, devised by Melvil Dewey.
The system is made up of ten main classes or categories, each divided into ten secondary classes or subcategories, each having ten subdivisions.
• 000 – Computer science, information & general works
• 100 – Philosophy and psychology
• 200 – Religion
• 300 – Social sciences
• 400 – Language
• 500 – Science (including mathematics)
• 600 – Technology
• 700 – Arts and recreation
• 800 – Literature
• 900 – History, geography, and biography
Source :
http://en.wikipedia.org/wiki/Library_of_Congress_Classification
http://encarta.msn.com/encyclopedia_761566591/library_of_congress_classification.html
http://encarta.msn.com/encyclopedia_761578295/Dewey_Decimal_Classification.html
9.2) Links :
The Library of Congress Website
British Library
Thai National Library
Sripatum University Library
ASEAN Community Website
Monday, September 5, 2011
Subjective opinion vs Objective fact
Subjective opinion
Subjective opinion is a type of thinking, judgment and experience people can have that is not connected with factual data. For instance, while the texture that a chair is made out of is the same to everyone, whether or not the chair is comfortable is subjective. Understanding the difference between subjectivity and objectivity can aid in critical thinking. Subjective opinion is also part of an individual's opinion. Subjective opinions tend to vary from one person to another.
Ex : Winter is a pleasant season for some...others dislike cold weather and may find winter unpleasant...
Objective fact
Objective fact is often seen as the opposite of subjective opinion. That which is objective tries to find truth that is common among all people. An objective fact is a non-biased statement. That is basically stating something with fairness, and not having a personal opinion about it. There are usually objective facts stated all the time on the news.
Ex : If it is verified that a student, in fact, has secured a grade-B, then it becomes an objective fact.
Source : www.chacha.com, answers.yahoo.com
Ex : If it is verified that a student, in fact, has secured a grade-B, then it becomes an objective fact.
Source : www.chacha.com, answers.yahoo.com
Chapter 1
Data, Information, Knowledge, and Wisdom
According to Russell Ackoff, a systems theorist and professor of organizational change, the content of the human mind can be classified into five categories:
- Data: symbols
- Information: data that are processed to be useful; provides answers to "who", "what", "where", and "when" questions
- Knowledge: application of data and information; answers "how" questions
- Understanding: appreciation of "why"
- Wisdom: evaluated understanding.
A further elaboration of Ackoff's definitions follows:
Data... data is raw. It simply exists and has no significance beyond its existence (in and of itself). It can exist in any form, usable or not. It does not have meaning of itself. In computer parlance, a spreadsheet generally starts out by holding data.
Information... information is data that has been given meaning by way of relational connection. This "meaning" can be useful, but does not have to be. In computer parlance, a relational database makes information from the data stored within it.
Knowledge... knowledge is the appropriate collection of information, such that it's intent is to be useful. Knowledge is a deterministic process. When someone "memorizes" information (as less-aspiring test-bound students often do), then they have amassed knowledge. This knowledge has useful meaning to them, but it does not provide for, in and of itself, an integration such as would infer further knowledge. For example, elementary school children memorize, or amass knowledge of, the "times table". They can tell you that "2 x 2 = 4" because they have amassed that knowledge (it being included in the times table). But when asked what is "1267 x 300", they can not respond correctly because that entry is not in their times table. To correctly answer such a question requires a true cognitive and analytical ability that is only encompassed in the next level... understanding. In computer parlance, most of the applications we use (modeling, simulation, etc.) exercise some type of stored knowledge.
Understanding... understanding is an interpolative and probabilistic process. It is cognitive and analytical. It is the process by which I can take knowledge and synthesize new knowledge from the previously held knowledge. The difference between understanding and knowledge is the difference between "learning" and "memorizing". People who have understanding can undertake useful actions because they can synthesize new knowledge, or in some cases, at least new information, from what is previously known (and understood). That is, understanding can build upon currently held information, knowledge and understanding itself. In computer parlance, AI systems possess understanding in the sense that they are able to synthesize new knowledge from previously stored information and knowledge.
Wisdom... wisdom is an extrapolative and non-deterministic, non-probabilistic process. It calls upon all the previous levels of consciousness, and specifically upon special types of human programming (moral, ethical codes, etc.). It beckons to give us understanding about which there has previously been no understanding, and in doing so, goes far beyond understanding itself. It is the essence of philosophical probing. Unlike the previous four levels, it asks questions to which there is no (easily-achievable) answer, and in some cases, to which there can be no humanly-known answer period. Wisdom is therefore, the process by which we also discern, or judge, between right and wrong, good and bad. I personally believe that computers do not have, and will never have the ability to posses wisdom. Wisdom is a uniquely human state, or as I see it, wisdom requires one to have a soul, for it resides as much in the heart as in the mind. And a soul is something machines will never possess (or perhaps I should reword that to say, a soul is something that, in general, will never possess a machine).
Personally I contend that the sequence is a bit less involved than described by Ackoff. The following diagram represents the transitions from data, to information, to knowledge, and finally to wisdom, and it is understanding that support the transition from each stage to the next. Understanding is not a separate level of its own.
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