Charles University in Prague Institute of Information Studies and

Transkript

I N V E S T I C E
D O
R O Z V O J E
V Z D Ě L Á V Á N Í
Charles University in Prague
Institute of Information Studies and Librarianship
Modul No.4
Information and Knowledge Management
(focusing on the interpretation process, organization and sharing information and knowledge)
Klára Havlíčková
Překlad: Jitka Hradilová
For the project:
Title: Studies of Information and Knowledge Management in the European Context
Reg. No: CZ.1.07/2.2.00/07.0284
OP: Education for Competitiveness
Support area. 2.2 University Education
Realization: VŠB-Technical University of Ostrava, Faculty of Economics, separate unit:
Business Academy and HPS Valašské Meziříčí
CONTENT
PREFACE...................................................................................................................................... 3 1 INTRODUCTION .................................................................................................................... 4 2 RELATION BETWEEN THE CONCEPT OF DATA – INFORMATION – KNOWLEDGE ..................... 6 3 INFORMATION AND KNOWLEDGE MANAGEMENT ............................................................... 12 4 INTERPRETATION OF INFORMATION, KNOWLEDGE AND TEXT CONTENT ............................. 16 5 KNOWLEDGE ORGANIZATION ............................................................................................ 21 6 FOLKSONOMIES – SELECTED TREND IN KNOWLEDGE ORGANIZATION ................................ 26 7 APPLICATION OF TAG-BASED SYSTEMS .............................................................................. 31 EXAMPLES ................................................................................................................................. 45 Tento projekt je spolufinancován Evropským sociálním fondem a státním rozpočtem České republiky
2
PREFACE
The following text is addressed to students of information studies and librarianship as
a supplementary material to teaching subjects concerning knowledge classification and
organization. Its aim is to present to students the lifecycle of information and knowledge. To
present relations between the concept of data – information – knowledge. To outline issues of
a document content analysis with special attention to a subjective interpretation of text. To
present some examples of traditional systems of knowledge organization in comparison with
systems based on the possibilities of Web 2.0 tools. The aim of the text is also to make
students acquainted with a possibility of sharing information on the content of a document as
well as on the content of a non-text (verbal) objects in an internet environment (focused on
selected catalogues and databases of libraries, museums and galleries)
The text is amended by examples and presentations of selected systems. It contains also
practical exercise and training which makes the reader reflect the respective issue and may
become a basis for group discussions or projects in the framework of in-door (class)
education.
Tento projekt je spolufinancován Evropským sociálním fondem a státním rozpočtem České republiky
3
1 INTRODUCTION
Information and knowledge are the basis for the work and functioning of any system,
organization, society as well as for activity of an individual. On such a basis we can make
decisions. All our behaviour is based on information which we put into relations, we think of
them in the light of our previous knowledge and experience and we try to interpret them. On
the basis of such information we make decisions or create new information which can be
further transmitted.
Information and communication technologies can serve as tools and means of information
storage. They enable e.g. preservation of information and knowledge, their classification and
transfer, sharing and retrieval, etc.
To make the work with data, information and knowledge possible it is necessary to interpret
them, assign them a certain meaning. Such a meaning is influenced not only by our
knowledge and experience, eventually by the quality of such information but also by the
respective context and relationship, external and internal interactions.
Information and knowledge has to be not only acquired and processed but also shared with
others. We are very much supported by information and communication technologies in this
respect. An appropriate environment for sharing knowledge and information and for the work
with information in general, among others also for the activities of libraries, museums and
galleries (so called memory institutions), is the Web environment and tools and means of Web
2.0 respectively, which forms the content of the pivotal chapter of this text.
Libraries can make use of the knowledge potential of their users by enabling them to take an
active part in the process of indexation in the framework of their own catalogues. This way
they can make use of the terminological potential and information interpreted by the user on
the basis of content analysis of the respective text. Through this activity new vocabularies
based on users’ language are set up which can be compared with controlled vocabularies, and
also analysed and evaluated. This topic is handled in detail in a subchapter.
Information specialists should therefore keep track of trends, users’ demand, users’ behaviour
and ways in which people work with information: how they share, transmit and communicate
their knowledge. There is a challenge for libraries of running projects and innovations on the
basis of the respective trends. And above all: current trends in individual periods of the
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information and knowledge life cycle could be an indication of future trends in the field
of the work with information and knowledge.
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2 RELATION BETWEEN THE CONCEPT OF DATA – INFORMATION –
KNOWLEDGE
Data, information and knowledge are the basis for our behaviour and decision-making. Those
concepts relate one to another. Such relationship can be formulated in the following way:
DATA Æ understanding relations Æ INFORMATION Æ understanding patterns Æ KNOWLEDGE
Æ understanding principles Æ WISDOM
Fig. 1: Data – information – knowledge – wisdom [BELLINGER, 1999]
VYMĚTAL et al. [2005, s. 12] present the following example of relationship between
concepts of data – information – knowledge: data = notes Æ information = score Æ
knowledge = interpretation of a piece of music by the particular soloist or conductor.
1) DATA
Data is a set of objective facts about events [DAVENPORT, PRUSAK, 1998, p. 2]. It can be
e.g. figures, letters, symbols, etc. which we try to assign a meaning, understand them and
interpret them.
VYMĚTAL et al define data in the following way:
-
Data represent usually something which can be acquired by an experiment,
measurement, observation or by enquiries.
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-
Data therefore present fairly the state or features of objects or running procedures in an
actual environment around us independently on our feeling.
-
The basis of data are characters, which can be represented by figures, letters and
symbols (dots, dashes, notes, etc.).
-
In a broader sense the concept of data is used for numerical (mostly at present), textbased, visual and audio recordings without assessing their relevance for the receiver.
The most important feature is their formulation and storage for future processing.
-
We can consider data to be simple representative tools of factographic materials with
unidimensional and unique meaning.
2) INFORMATION
Information is data with a meaning resulting from the context. The meaning arised in the
process of interpretation, in the process of understanding relations. The input data were
considered in a certain context. Information can be further interpreted, classified, transmitted.
The process of interpertation is subjective however, based on previous knowledge and
experience which influnces it.
Information is a concrete fact, it can take a form of a specific news, communication (not only
text-based, but also in an audible or visible form, as e.g. information in a documentary
photograph, advertissement). In such cases the visual form prevails.
VYMĚTAL et al [2005, p. 12] define information in the following way:
-
Information are data to which the recipient assign certain meaning on the basis of his
knowledge and experience and which restrains recipient’s entropy of his needs and
demands.
Life cycle of information
Life cycle of information (or information process) is divided into the following periods
¾ information harvesting (or creation)
¾ processing
¾ organization
¾ storage
¾ searching, retriveval
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¾ disclosure, accessing
¾ distribution
¾ usage
¾ evaluation
¾ sharing
¾ application
3) KNOWLEDGE
Knowledge results from understanding patterns. Knowledge is an information with an added
value. It is organized in the minds of knowers in a way that enables to use it purposefully. On
the basis of knowledge it is possible to take decisions, to imply knowledge in one’s behaviour.
Knowledge is based on experience, interpretation, understanding and cognition. It depends
also on inteligence competence of a knower and his ability to put things to mutual relations.
Knowledge is broader, deeper and richer than data or information. [DAVENPORT, PRUSAC,
1998, p. 5]. Knowledge is a fluid mix of framed experience, values, contextual information . It
forms a part of current processes. In conjunction with the concept of „knowledge“ the concept
of „experience“ is mentioned. It depends on what we acquired in the past, i.e. what we learned
at school or during our practical activities. Experience can be transmitted in the form of model
behaviour or work procedures etc. It is difficult to transmit knowledge. It is based just on our
personal experience. It is something we have inside, something which is difficult to classify
and transmit.
VYMĚTAL et al [2005, p. 209] say that:
-
Knowledge derives from information through comparison, classification, evaluation,
examination and by putting it into context with other information, knowledge and
experience.
Context is important in order to distinguish between different meanings of knowledge – only
after putting an information to a certaint context knowledge originates. Existing knowledge is
able to create a new one. P. GOTTSCHALK [2008, p. 131] defines knowledge as information
combined with experience, context, interpretation, reflection, intution and creativity.
He is claiming further that knowledge is a reusable source with a high value for an
organization if it is used for product manufacturing or offering services. He says also that
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knowledge can’t be stored in a computer, it can be stored only in one’s mind. Knowledge is
the thing which a person know and understand. Knowledge can’t exist without a knower.
DAVENPORT, PRUSAC [1998, p. 5] see knowledge as a fluid mix of framed experience,
values, contextual information and expert insights that provides a framework for evaluating
and incorporating new experience and information.
Knowledge enables us to cooperate, thanks to knowledge we can dispute and argue. We are
able to answer the question „how?“. Knowledge can be retreived, organized, applied,
disseminated. The value of knowledge is increased by experience, relationship and
interpretation.
Life cycle of knowledge (or knowledge flow) can be after RIBIERE and ROMAN [2006,
p. 336] divided to four basic categories:
¾ knowledge creation, discovery, capture
¾ storage, retention, organization
¾ transfer, sharing, distribution
¾ use and maintenance
Basic types of knowledge:
After T. D. WILSON [2002b, p. 3] knowledge involves the mental processes of
comprehension, understanding and learning that go on in he mind and only in the mind,
however much they involve interaction with the world outside the mind, and interaction with
others. He also states that data and information can be controlled but knowledge (it means
what we understand and know) can never be controlled. He sais that we don’t know often
what we know, and the fact that we know something could be discovered in case of a need to
use the respective knowledge for doing something.
Knowledge can be divided into two basic types:
-
explicit knowledge
o codified knowledge
o transmittable knowledge which can be shared
o knowledge able to be stored and preserved (e.g. using technologies)
o formal knowledge as e.g. facts, theories etc.
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-
tacit knowledge
o knowledge difficult fo codify
o knowledge difficult to transmit
o knowledge hiddden in one’s mind
o knowledge based on personal experience
o knowledge difficult to be formalized and transmitted
o e.g. values, experience, ways of behaviour (possibility of transmission by
sharing experience using mental models)
4) WISDOM
Wisdom keeps the highest position in the framework of relations between concepts. Wisdom
can’t be shared as knowledge, because it is connected with the process of individual learning,
when the context is too personal. Thanks to the process of understanding we can answer the
question “why ?”
VYMĚTAL et al. [2005, p. 209] defines wisdom as:
-
a set of knowledge originating from the understanding of the core of issue in
a respective relationship with the use of intellectual and emotional inteligence of an
individual (knowledge competence), his evaluation criteria and individual respect to
the surrounding world and resulting from the high level of human cognition.
[?] EXCERCISE:
Indicate a concrete example of differences between concepts of „data – information –
knowledge“. Find an example of transformation of data to information and knowledge. Think
about aspects influencing the process of transformation.
Bibliography
• BELLINGER, Gene; CASTRO, Durval; MILLS, Anthony. Data, information,
knowledge and wisdom [online]. Copyright 2004 [cit. 2010-08-30]. Dostupný z www:
<http://www.systems-thinking.org/dikw/dikw.htm>.
• BUREŠ, Vladimír. Znalostní management a proces jeho zavádění : průvodce pro praxi.
1. vyd. Praha : Grada, 2007. 212 s. Mangement v informační společnosti. ISBN 978-80247-1978-8.
10
• DAVENPORT, Thomas H.; PRUSAK, Laurence. Working knowledge : how
organizations manage what they know. Boston : Harvard Business School, 1998. xxiv,
201 s. 0-87584655-6.
• GOTTSCHALK, Petter. Knowledge management. In Jennex, Murray E. (ed.).
Knowledge management : concepts, methodologies, tools, and applications [online].
Hershey : Information Science Reference, 2008, s. 130-143. Dostupné v databázi Gale
Virtual Reference Library:
<http://go.galegroup.com/ps/start.do?p=GVRL&u=karlova&authCount=1>.
• RIBIERE, Vincent M.; ROMÁN, Juan A. Knowledge flow. In Schwarz, David G. (ed.).
Encyclopedia of knowledge management [online]. Hershey : Idea Group Reference,
2006, s. 336-343. Dostupné v databázi Gale Virtual Reference Library:
• VYMĚTAL, Jan; DIAČIKOVÁ, Anna; VÁCHOVÁ, Miriam. Informační a znalostní
management v praxi. Praha : LexisNexis CZ, 2005. 399 s. ISBN 80-86920-01-1.
11
3 INFORMATION AND KNOWLEDGE MANAGEMENT
Information management applies managmenet principles in acquisition, organization,
administration, distribution and use of information to make organization of any type function
effectively [WILSON, 2002a,p. 263]. The concept can be also explained as „management of
information flows“ focused on the use of information in management processes, in decisionmaking processes. Information sources are integrated into processes in an organization and as
such, they can increase its effectiveness.
Information management uses information to ensure the activities of the organization itself. It
is based on the quality of information, its content, availability and relevance. It focuses on
new ways of work with information.
VYMĚTAL et al [2005, p. 46] defines information amangament as follows:
-
cross-disciplinary set of knowledge, methods and recommendations of system
approcaches and informatics, which helps to implement rationaly information
processes of managerial thinking and to achieve entrepreneurial targets of the
respective organization.
Knowledge management arises from information management. After TRUNEČEK [2004, p.
29]: information management is according to the present understanding a basis and resource
of knowledge management, it makes use of it, utilizes its instruments and develops it further,
but nevertheless remains its component.
Knowledge management strategy is based on a relationship between people, on knowledge
management processes and on technologies used. Knowledge of individuals and its effective
use and sharing is an important resource in an organization. Availability of a pertinent
knowledge for the respective people in a due time. It is based on individual knowledge of
individual employees or staff members of the given organization. This knowledge can be used
in decision-making and managerial processes.
Knowledge management is a strategic process for maintaining competitiveness – use of new
ideas and knowledge, important for decision-making with the aim of improvement of running
the organization. It is based on previous experience and on the need of innovation, on the
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transfer of quality knowledge. Web technologies enabling information retrieval and access to
recorded information and knowledge are important for knowledge management.
Knowledge management is based on a competence to share and use information, particularly
with the use of information and communication technologies. Creation, storage and sharing
information among people and groups with similar interests and needs are the respective
subprocesses of knowledge managment.
It is important not only to have knowledge, but to be able to use it. Transfer of knowledge
among people or organizations in time and space is called „knowledge flow“. Good treatment
of information resources is very important. Sharing information with other people to create
new knowledge is appropriate. Not only knowledge acquisition but also knowledge
application.
TRUNEČEK [2004, p. 28] states, that in general we take knowledge management as
a systematic approach to creation, acquisition, storage, dissemination, sharing and active use
of knowledge with the aim of increasing the effectvity of an organization. And he adds [p. 29]
that in a current concept information management is closely linked with the developement of
information technologies and from the viewpoint of knowledge management it develops above
all explicite knowledge, but knowledge management contains many further components.
VYMĚTAL [2005, p. 207] adds, that in principle it concerns systematic acquisition, analysis,
synthesis and sharing knowledge on the core issues and experience, which all together reduce
the risk in decision-making.
Partial processes of knowledge management
¾ knowledge creation or reveal
¾ selection and retrieval
¾ knowledge acquision or
¾ its derivation, creation of new knowledge
¾ knowledge verification
¾ storage
¾ sharing
¾ use and dissemination
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[?] EXCERCISE 1: Indicate examples of motivation for sharing knowledge.
[?]EXERCISE 2: Analyse individual levels of knowledge management in accordance with the
following figure and choose processes relating to the issue of knowledge and information
organization and retrieval. Explain your choice.
Fig. 2: Levels of knowledge management [SCHWARTZ, 2008, s. 26]
Bibliography
• BUREŠ, Vladimír. Znalostní management a proces jeho zavádění : průvodce pro
praxi. 1. vyd. Praha : Grada, 2007. 212 s. Mangement v informační společnosti.
ISBN 978-80-247-1978-8.
• DAVENPORT, Thomas H.; PRUSAK, Laurence. Working knowledge : how
organizations manage what they know. Boston : Harvard Business School, 1998. xxiv,
201 s. 0-87584655-6.
14
• RIBIERE, Vincent M.; ROMÁN, Juan A. Knowledge flow. In Schwarz, David G.
(ed.). Encyclopedia of knowledge management [online]. Hershey : Idea Group
Reference, 2006, s. 336-343. Dostupné v databázi Gale Virtual Reference Library:
• SCHWARTZ, David G. A birds-eye view of knowledge management : creating a
disciplined whole from many interdisciplinary parts. In Jennex, Murray E. Knowledge
management in modern organization [online]. Hershey : Idea Group Publishing, 2007,
s 18-29. Dostupné v databázi Gale Virtual Reference Library:
• SCHWARTZ, David G. Aristotelian view of knowledge management. In Schwarz,
David G. (ed.). Encyclopedia of knowledge management [online]. Hershey : Idea
Group Reference, 2006, s. 10-16. Dostupné v databázi Gale Virtual Reference Library:
• TRUNEČEK, Jan. Management znalostí. 1. vyd. Praha: Beck, 2004. 131 s. ISBN 807179-884-3.
• VYMĚTAL, Jan; DIAČIKOVÁ, Anna; VÁCHOVÁ, Miriam. Informační a znalostní
management v praxi. Praha : LexisNexis CZ, 2005. 399 s. ISBN 80-86920-01-1.
• WILSON, T. D. (2002a). Information management. In Feather, J.; Sturges, P. (eds.).
International encyclopedia of information and library science. London : Rotledge, s. 263278.
• WILSON, T.D. (2002b). The nonsense of knowledge management. Information
Research [online]. 2002, vol. 18, no. 1 [cit. 2010-08-30]. Dostupný z www:
<http://informationr.net/ir/8-1/paper144.html>.
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4 INTERPRETATION OF INFORMATION, KNOWLEDGE AND TEXT
CONTENT
What is the role of a correct analysis and interpretation of information in the life-cycle of
information and knowledge ? How is the process of sharing information and knowledge
influenced by participants in the information process subjective view ?
In the previous chapter we indicated that the work with information and knowledge is
influenced by understanding and meaning resulting from the context which put the knowledge
in relations. Interpretation is connected with quality analysis of a document focused on
explanation and understanding of the text. Unbiased approach to interpretation of the topic
and content of a document and information forms a basis for the work of an information
specialist.
Interpretation of text means comprehension and understanding of text, its substance.
Interpretation is mentioned both in creating the text, when we try to transform information
and observation to a coherent whole and also in receiving the text by reading or analysing.
Recepients of a text differ one from another and the same applies to text undertanding and
interpretation. Understanding is affected by our knowledge, previous experience, our intention
– and consequently whether we are seeking new information, whether we are approaching the
text in a critical way, or e.g.whether we want to transmit it further (e.g. in the form of
a reduced text as a result of content analysis of the text.
An example of an ambiguous interpretation of text can be legal texts, where a personal
understanding can be used based on own experience, language and professional knowledge,
etc. The main role in interpretation is played by words and their relationship.
The basic information carrier is language. Even if information is e.g. in a graphic form, it is
often necessary to express its message by language. Either in the form of a text or only as an
idea in the form of an inner language which helps us in formulating our thoughts. Language
plays and important role in information transfer e.g. in the form of a particular
communication.
Text is a means of a certain communication and serves information transfer. After PALKA
[1989, p. 202] text is any language denotation either in a written or oral form. After
ČERMÁK [2001, p. 169] we can add that text is an arbitrary or unspecified language
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denotation (written or oral, finished or unfinished etc.), it means act parole as a whole or as
a part; generally it is longer than a sentence.
As concerns the process of interpreation itself, e.g. HŘEBÍČEK [2002, p. 84] points out, that
we have to face the reality that even a very carefully prepared text is often not understood in
the same way by its receipients. He also tackles the issue when each of the recipients applies
his own semantic system and a network of meanings resulting from his educational
background and training and life experience is thus activated.
ECO [2004, p. 64-66] mentions two levels of interpretation, and namely semantic
interpretation and critical interpretation. In semantic interpretation the recipient focuses on the
meaning. It is a reader oriented approach. He also states that it is a first alias „naiv level“
(simple-minded). By critical iterpretation the way in which the text expresses its content is
evaluated. Critical interpetation aims after ECO to description and explanation from which
formal reasons the text evokes the respective reaction.
In analysing a text we try to find its deeper meaning. It can be a very simple analysis but also
a deep understanding of a content and its explanation. Such an analysis is combined with
a subjective view, when the process is allied with a person who makes the analysis. This can
result in many different views and interpretations. During interpretation of a text we can face
also several barriers, which can influnce text interpretation.
Barriers to the interpretation of text
¾ misunderstanding of the content or topic (ignorance, unfamiliarity with a specialized
terminology, unsufficient previous knowledge, problem of alternate term without
appropriate context relation)
¾ barrier related to text reduction, if we try to retain main ideas and information and
subsequently we are compressing them
¾ translation barrier (not only on translating, analysing and interpreting natural language
but also translating natural language to a retrieval language)
¾ time barrier (lack of time to make quality analysis and interpretation of text)
Content analysis is focused on the content of a document and its meaning. An important role
is played by our experience and knowledge. We are identifying the topic of a document and
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formulating its content either using natural language (e.g. in reduced texts like annotations,
abstracts, etc.) or by transforming natural language into a retrieval language).
The Terminological Database of Librarianship and Information Science [TDKIV] says that
content analysis contains methods and rules for identification of the topic of a document,
eventually also time and space viewpoint, reader’s orientation or form of a document. Verbal
formulation of the document content in a natural language is transformed into subject
retrieval data in the process of subject classification or into sentences in the process of
semantic reduction of text.
POKORNÝ [2006, p. 51] states that the basic aim of content analysis is to discover the
pragmatics of a text (pragmatics, in other words also „subject intention“ means impetus
provided by the text for human experience.
In case of interpretation of text but also of any symbol we should know its meaning and
sense. Meaning we try to master by learning (be it spontaneus, immediate or knowledgable
and targeted). We try to work with the meaning of the content of a text, but we also analyse
messages brought to us by further entities like pictures atc. We also use our own imaginations.
TONDL [2006b, p. 23] says that pictures, sculptures and texts as components of technical or
culture oriented literature, films, theater or other dramatic works and a range of other fields
of human activity bring us some messages, inform us about something.
Science concerned with meaning of symbols and signs is called semantics. TONDL [2006a,
p. 10] says that semantics or semasiology is considered to be a component part of linguistics,
which is concerned with a language and mainly its elements, words, from the viewpoint of
what is generally called meaning of words.
[?] EXCERCISE:
From your own experience indicate other possible barriers to interpetation of a text. Make
a proposal how to remove them gradually or totally.
Bibliography
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and machines analyze messages and texts for retrieval. Part I: Research, and the nature
of human indexing. Information Processing & Management. 2001, vol. 37, no. 2,
s. 231-254.
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80-246-0740-9.
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objectivity and subjectivity, constraint, and control.. Journal of the American Society for
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<http://onlinelibrary.wiley.com.ezproxy.is.cuni.cz/doi/10.1002/asi.20073/full>.
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practical advice. Frankfurt am Main : Indeks Verlag, 1993. xvi, 250 s. ISBN
3886725006.
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Documentation [online]. 1992, vol. 48, issue 2, s.172-200. Volně dostupné z WWW:
<http://portal.acm.org/citation.cfm?id=175002.175005>.
• HŘEBÍČEK, Luděk. Vyprávění o lingvistických experimentech s textem. 1. vyd. Praha:
Academia, 2002. 196 s. ISBN 80-200-0973-6.
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Bowker-Saur, 1989. 96 s. ISBN 978-0408030311.
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information science. Journal of the American Society for Information Science and
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Učebnice pro vysoké školy. ISBN 80-04-22937-9.
• POKORNÝ, Petr a kol. Hermeneutika jako teorie porozumění : od základních otázek k
výkladu bible. 1. vyd. Praha : Vyšehrad, 2006. 508 s. ISBN 80-246-0740-9.
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sémiotiky v posledních desetiletích. Vyd. 1. Praha : Karolinum, 2006. 109 s. Prameny
k dějinám českého myšlení, 7. ISBN 80-246-1207-0.
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a2adbb732664df62%40sessionmgr111&bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3d%3d#db=
lih&AN=18609871>.
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5 KNOWLEDGE ORGANIZATION
As it was already mentioned knowledge organization is a partial process of knowledge
management. In order to work with information and to enable its retrieval it is necessary to
classify and categorize it. After creation or acquisition of information or knowledge it is
important to analyse it correctly and understand it subsequently and to classify, store, share
a disseminate it after. Process of knowledge organization also includes description of
documents containing the given information; their content analysis, indexation – it means
expression of the document content e.g. by elements of a retrieaval language, classification or
categorization.
Knowledge organization together with their retrieval and acquisition is one of the core
disciplinis of information studies and librarianship. Organization is based on an analysis and
understanding the topic or subject of a document, possibly the content of the respective
communication. During an analysis we find the subject of the document and we discover how
such a subject can be represented – e.g. in the form of terms in mutual relationship.
In an environment of traditional libraries and other memory institutions most of the processes
of information and knowledge organization is based on an intellectual approach, on semantic
analysis of the text content. Creation and allocation of retrieval language elements is
influenced by knowledge of the respective topic and indexer’s experience.
In the framework of knowledge organization we are concerned with knowledge organization
systems, their design, analysis and evaluation. Design, analysis and evaluation of knowledge
organization systems proceeds (is carried on) always in relation with processes of information
storage and retrieval.
In searching information and knowledge we are using terms which we suppose to be
appropriate for their acquisition and retrieval.We can use controlled vocabularies (e.g.
specialised thesauri, etc.) In such a way a term expressed by a concrete information
is interconnected with a term used by an information specialist in searching but also in
organizing information.
Knowledge organization is focusing on a traditional work in libraries, but takes into
consideration also a need of organization of non-text resources, objects in web environment, it
means not only in libraries and traditional memory institutions in general.
21
It is necessary to interconnect traditional approach to knowledge organization (systems and
processes of knowledge organization) with trends seen both from the point of view of
professionals, information specialists and also users, their needs, demands and ways of
information organization and retreival. We are monitoring user needs, trends in a dynamic
web environment (now e.g. current trend of „sharing“ information and knowledge, sharing
digital objects such as photos, possibly information resulting from their content analysis, etc.)
We can say therefore, that knowledge organization in web environment, which offers a space
for their sharing, can be used also e.g. in personal information management. We can use
tools for organization and sharing web bookmarks (e.g. Delicious, social bookmarking,
http://www.delicious.com/),
for
archiving
and
sharing
photographs
(Flickr,
http://www.flickr.com/), eventually sharing information on interesting books (see e.g.
LibraryThing Project, http://www.librarything.com/) etc.
When organizing information and knowledge we are focusing on knowledge organization
processes, such as description of documents, content analysis, indexation, classification and
on knowledge organization systems, e.g.:
¾ bibliographic records,
¾ classification systems as e.g.:
o Universal Decimal Classification - http://udcc.org/udcsummary/php/index.php,
http://aip.nkp.cz/mdt/,
o Dewey Decimal Classification http://www.oclc.org/dewey/resources/summaries/,
o Library of Congress Classification - http://www.loc.gov/catdir/cpso/lcco/ etc.,
¾ thesauri as e.g.:
o Eurovoc - http://eurovoc.europa.eu/
o Art & Architecture Thesaurus http://www.getty.edu/research/tools/vocabularies/aat/
o Maternal and Child Health Thesaurus - http://www.mchthesaurus.info/
¾ subject headings as e.g.:
o Library of Congress Subject Headings - http://www.loc.gov/cds/lcsh.html,
¾ authority files as e.g.:
o National authorities of the Czech republic - http://autority.nkp.cz/
22
¾ registers and vocabularies as e.g.:
o WordNet - http://wordnet.princeton.edu/
o Synonym Finder - http://www.synonym-finder.com/,
¾ semantic networks etc.
Traditional systems can be supplemented by systems based on Web 2.0 tools, e.g. systems
based on tagging, so-called folksonomie. Such systems are based on the possibility of
organizing non-text objects in web environment and on the possibility of sharing (e.g.
photographs, digitized objects in museums and galleries, etc.). Here the need is evident of
organization (and consequent availability) both of information contained in the text,
eventually in another form of presentation and of information on the content of non-text
objects (e.g. phohographs, pictures) or concrete objects (e.g. above mentioned digitized
collections of museums and galleries).
Knowledge organization processes are influenced by methods and procedures of further
fields of science. The narrowest relationship is there with linguistics, semantics and logics. It
is therefore necessary to focus on all those fields which penatrate through all processes from
content analysis, indexation, when we formulate the content of a document by elements of
a retrieval language, eventually in the form of a reduced text, up to creation of individual
elements of a retrieval language, implementing this elements to knowledge organization
systems, determining relationship between individual concepts, topics, classification of all the
univers of cognition into categories etc.
[?] EXCERCISE:
1) Choose any of the knowledge organization systems (thesaurus, classification system as
e.g. UDC, authority file etc., which is part of the selected catalogue, specialized
database, information (subject) gateway, etc.
2) Think of the pertinence of the use of the respective system, classification logics,
ranging, relationships, etc.
3) Asses the system from the language viewpoint (e.g. issues of homonyms and
synonyms, one-word or compound terms, etc.); hierarchic relations, relations between
individual elements, between sets of data ; from the viewpoint of semantics (meaning
of individual symbols, interpretation of symbols).
23
4) Pay attention also to a typical user of the given system (information specialist and also
end user who search for information). Try to asses the system also from his viewpoint.
Consider carefully positive and negative features and possibilities of further use.
5) Present the results of the analysis and discuss them in the classroom.
Bibliography
• ANDERSON, J. D. Organization of knowledge. In FEATHER, J. a STURGES, P. (ed.).
International Encyclopedia of Information and Library Science. 2nd. London :
Routledge, 2003, s. 471-490. ISBN 0-415-09860-2.
• DAHLBERG, Ingetraut. Grunlagen universaler Wissensordnung : Probleme und
Möglichkeiten eines universalen Klassifikationssystems des Wissens [Základy
univerzálního pořádání znalostí ...]. Pullach bei München : Verlag Dokumentation,
1974. 18, 336 s. DGD - Schriftenreihe, Bd. 3. ISBN 3-7940-3623-9.
• DAHLBERG, Ingetraut. Knowledge organization : a new science? Knowledge
Organization. 2006, vol. 33, no 1, s. 11-19. ISSN 0943-7444.
• HJØRLAND, Birger. What is knowledge organization (KO)? Knowledge Organization.
2008, vol. 35, no. 2/3, s. 86-101. ISSN 0943-7444
• KTD : Česká terminologická databáze knihovnictví a informační vědy (TDKIV) [online
databáze]. Praha : Národní knihovna České republiky, 2003-. Dostupná z WWW:
<http://aleph.nkp.cz/cze/ktd>
• BALÍKOVÁ, Marie. Problematika věcného pořádání informací a jejich zpřístupnění.
Národní knihovna : knihovnická revue. 2001, roč. 12, č. 3, s. 175-186. Dostupný také z
WWW: <http://full.nkp.cz/nkkr/NKKR0103/0103175.html> nebo
<http://knihovna.nkp.cz/pdf/0103/nk0103175.pdf>.
• Encyclopedia of Library and Information Sciences. 3rd. edition. Boca Raton, FL : CRC
Press, 2009. ISBN 978-0-8493-9712-7. Elektronická verze přístupná také přes EZProxy:
<http://ezproxy.is.cuni.cz/login?url=http://www.informaworld.com/smpp/title~content=
t917508581~db=all> nebo přímý přístup z IP adres UK:
<http://www.informaworld.com/smpp/title~db=all~content=t917508581>
• HJØRLAND, Birger. Lifeboat for knowledge organization [online]. Last edited 200816-02 [cit. 2010-09-28] Dostupný z WWW:
<http://www.iva.dk/bh/lifeboat_ko/home.htm>
• ISKO : International society for knowledge organization. Copyright 2004-2010 [cit.
2010-09-27]. Dostupný z WWW: <http://www.isko.org/>.
• Knowledge Organization. Würzburg : Ergon Verlag, 1993-. 4x ročně. Archiv abstraktů
dostupný z WWW: <http://www.isko.org/ko.html.> ISSN 0943-7444.
24
• LAMBE, Patrick. Organising knowledge: taxonomies, knowledge and organisational
effectiveness. Oxford: Chandos, 2007. ISBN 978-1-84334-227-4
• The Indexer : the International Journal of Indexing. Sheffield : The Society of Indexers,
2006- [cit. 2010-09-27]. 4x ročně. Vychází v tištěné formě od roku 1958. ISSN 00194131. Archiv elektronicke verze dostupný z WWW: http://www.theindexer.org/>. ISSN
1756-0632.
25
6
FOLKSONOMIES – SELECTED TREND IN KNOWLEDGE
ORGANIZATION
During indexation process documents and information contained are assigned elements of
a retrieval language (key words, subject headings, etc.). This process is linked up with an
activity of experts (information specialists) in connection with subject organization of
information and knowledge in traditional catalogues and databases.
Thanks to Web 2.0 tools also end-users of those services join the indexation process by socalled „tagging“ – adding their own key words, so-called „tags“. The initial idea is based on
the organization of the content of digital resources (web bookmarks, digital photographs
collections) by web users themselves, and on their sharing with other users. Regarding the
fact that it is a user attractive and interesting way of knowledge organization, some libraries
(but also e.g. museums) are using the possibility of implementing tagging based systems in
their catalogues and make their users involved in the indexation process of their own
collections.
With those new possibilities and indexing procedures new terms are penetrating into the
special language. References at the end of this chapter show evidence of the use of some of
them in the content analysis and knowledge organization terminology. The most frequent term
is e.g. folksonomies, tagging or social tagging and user tagging, tag (not being translated
into Czech), collaborative tagging systems.
These and also further terms will be explained in the subsequent text. Possibilities of Web 2.0
tools application in traditional catalogues, databases and other online resources will be
presented further. In conclusion topics appropriate for further analysis and research will be
presented.
Folksonomies, tags, tagging
A question arises how to organize efficiently the huge amount of content available in web
environment and how to search and find it. Efficiency of searching is always connected with
a good organization of a collection. One of the possibility how to organize it is a traditional
approach based on classification systems, thesauri and further controlled vocabularies
mentioned in the previous chapter.
26
These systems having a certain formal structure are supplemented by further approaches
linking up authors or users of the content with the organization process. They are based on
collaboration in the framework of groups (or communities). Such a community can involve
a group of individuals with similar interests, similar profession or students participating in
a chosen lecture at a university.
Web users are creating, publishing and sharing their own content (e.g. text, photographs,
videos). Thanks to software they are able not only to save the content on the web, in
repositories and digital libraries, but also to share it with other web users. For an easy retrieval
they assign the content their own key words without use of a controlled vocabulary. Such key
words are called „tags“. They are words from the user’s own vocabulary, where the meaning
of a tag is given by understanding the respective content.
The content means not only the content of oral or written text, but also pictures, sounds and
messages they bring us. Pictures are very interesting objects for indexation. Indexation of
pictures is based on subjectivity, on personal perception of the object, on personal
interpretation. The idea that „a picture is worth a thousand words“ can be fully approved.
[BAR-ILAN, J. et al., 2006]. The best way how to describe a picture and express its contents
is based on a verbal description. The description emanate not only from what is displayed,
from the visual content such as e.g. colour, shape, etc., but also from the meaning of an
picture, interpretation of a message and of a main idea. Emotional aspects, difficult to be
described by words, can be also interesting for interpretaion of a picture.
We can take as an example a photograph from the collection for organization and sharing of
pictures „Flickr“ (fig. 3) . The author of the photograph discribes by means of key words
(tags) not only the person which is being desplayed, eventually the place, situation and time of
taking a photograph, but also such characteristics like „beauty, beautiful“ or expression of
own emotion in viewing the picture: „impressed beauty“.
27
Fig. 3: Tags describing a photograph (Flickr)
The process during which web users index its content (e.g. the photograph mentioned above)
is called tagging or social tagging1. Social tagging is based on metadata generated by users or
authors of the content without use of a controlled vocabulary. It means that there are no
indexation rules, no control of individual tags used and control of tags creators. Authors of
objects are indexing according to their own needs, according to their own interpretation of the
relevance of key words used. It can be expected that they will use the same key words in
searching further sources.
Indexation of documents without use of a controlled vocabulary is a basis for so called
folksonomies. Folksonomies is a new concept created artificially by Thomas Vander Wal in
2004. It is an association of two concepts „folks“ + „taxonomy“ which may be interpreted as
content structures created by people.
1
we can come accross also the concept of collaborative taggin, social clasification, social indexation
28
T. VANDER WAL [2005] himself defines folksonomies as „the result of personal free
tagging of information and objects (anything with a URL) for one's own retrival. The tagging
is done in a social environment (shared and open to others). Folksonomies can be also
understood as “social classification – user created metadata” [SPITERI, L.F., 2006], or as
a „user generated tags“ [SMITH, T., 2007 - DALY, E., BALL NTYNE, N., 2009 NORUZI, A., 2007] or as a „system which uses tags created collaboratively by users as
descriptors“. [KAKALI, C., PAPATHEODOROU, Ch., 2010]. A. NORUZI [2007] state
(indicate, mention) that it concerns „user-generated taxonomy used to categorize and retrieve
web content such as web resources, online photographs and web links“, S.A. GOLDER
a B.A. HUBERMAN [2005] see a parallel between the concept of folksonomies and
collaborative tagging, where collaborative tagging describes the „process by which many
users add metadata in the form of key words to shared content“.
Folksonomies are based on interpetation of an object by user or author of the object
himself. There is no authority to control usage of individual tags or correct usage of terms. It
can be both strong and weak points of the whole system. There are no rules and standarts to
limit creation of tags and usage of words, it is a very simple way of information organization.
On the other hand indexers view the use of synonyms, structure of individal tags etc. to be
problematic. See the concluding chapter.
Benefits and problems of folksonomies is tackled in the article by I. PETERS A W.G.
STOCK [2005]. The most essential can be considered e.g.:
benefits:
folksonomies
¾ are the only way to index mass information on the Web
¾ are cheap methods of indexing
¾ are sources for the development of ontologies, thesauri or cassification patterns
¾ it enables retrieval and searching
¾ can help to identify communities
¾ represent an authentic use of language
¾ recognize neologisms
¾ make people sensitive to information indexing
29
problems:
¾ absence of controlled vocabulary
¾ hidden paradigmatic relations
¾ use of misleading keywords
Further strong and weak points of folksonomies seen by E. KROSKI [2005]:
strong points:
¾ folksonomies are current
¾ users create tags as quickly as they create content
¾ possibility to swift responses to changes in terminology
¾ users can uncover related resource
¾ folksonomies are democratic – everybody can add something to the whole
¾ folksonomies offer insight into user behaviour, we can observe how users tag their
own resources
¾ Web 2.0 is based on sharing and community in user related tagging sites
weak points :
¾ there is no synonym control
¾ there is a lack of precision
¾ there is a lack of hierarchy – no relationship between tags
¾ each indexer has his own idea of tagging (usage of broader or narrower terms).
[!] NOTICE:
Excercise to this chapter and resources will be presented with the following chapter according
to their thematic coherency.
30
7
APPLICATION OF TAG-BASED SYSTEMS
During information retrieval a problem arises with formulation of an inquiry and namely how
to formulate an information need or idea so as to be retrievelable in the system. How to
translate a concept in user’s mind to a concept applicable in retrieval. Users need to work with
a natural language, not to be limited by a controlled vocabulary. Therefore a possibility of
using tags created by users themselves seams to be one of the ways of accessing catalogues,
databases and further on-line resources, as e.g. digital collections of photographs in museums
and galleries.
We can take as an example application of tagging system in Danbury Library catalogue (fig.
4), possibility of free tagging in master thesis catalogue at Montana State University (fig. 5) or
a project focused on social tagging in digitized collections of museums and galleries under the
title “Steve” (fig. 6). In this projects institutions like Cleveland Museum of Art, San Francisco
Museum of Modern Art , etc. are participating.
Fig. 4: Subject headings and tags in the catalogue record (Danbury Library Catalog)
31
Fig. 5: Subject headings and tags in the bibliographic record (Montana State University – ETDs)
Fig. 6: Formulation of the content of a non-text object (painting) by means of tags (Steve
Project)
32
Social tagging becomes a means of information indexing and organization on the basis of
user’s own needs. In this context we can face a problem of using different words to describe
the same entity by different users. Each user can view the respective resource in a different
way and interpret it different. Tagging of an object can be done either impartially without any
subjective feeling, on the basis of what is ensuing from the content, or subjectively, when
some assessing aspects are used (this can be influenced by e.g. community activities when
some recommendation is offered to groups of readers by tags as e.g. “to read” or “my
favourite author”, etc.
Different interpretation is not the only problem occuring in connection with social tagging of
online resources. For an “internet language” use of short words, words based on a colloquial
language, a lot of neologisms and influence of a colloquial language is characteristic. The
following is an example of the most often used tags and tags used most recently in the
collection of photographs Flickr (fig. 7).
Fig. 7: Tag cloud : most popular tags; most recently added tags (Flickr)
33
Structured tagging
A typical tag is a one word noun. It could be however any word (or phrase) which need not
have any structure or limitation by spelling rules. Tags are taken from the language of
a respective user or community. The choice of a tag depends on knowledge and personal
experience of the user, his interests or preferences. Tagging is influenced also by
a community surrounding the user be it physically or virtually. The user uses the language of
the respective community. It can be a language used for a common communication or specific
language used in the given field, or words charactersitic for the respective field. The
following tagging again from the museums Steve Project, can serve as an interesting example
in which words and terms concerning art, museum collections etc. are prefered, e.g. colours
and materials used (fig. 8)
Fig. 8: Description of a content of a non-text object (3D object) by means of tags (Steve
Project)
34
Authors of tags often infringe spelling rules, either syntax or upper and lower cases. The
following different recording of tags can serve as an interesting example of different
description of a compound term “music history” and a chronologic term “20th century”. Both
examples are taken from the Library Thing system, which focuses on free tagging of books.
Includes: music history, Music History, history of music, musikhistoria, Musikgeschichte, muziekgeschiedenis,
musical history, Music history, History; music, Music - History, music--history, Historia de la música, music history, music-history, Music (history), History/Music, History of Music, History Music, Music - history, Music-History, Muziekgeschiedenis, music (history), historia de la música, history/music, history; music, history music history, history-music, History - Music, music_history, history: music, History: Music, HISTORY-MUSIC,
Music History, Historia de la Música, musikgeschichte, Historia de la musica, history - music, 04a Music history,
04a music history, music history., history music, historia de la musica, History - Music History, History: music,
MUSIC HISTORY, Musical history, Music history., muziek geschiedenis, Music_history, music History, History of
music, History-Music, Music HIstory, Musical History, Musikhistoria
Fig. 9: Tag „music history“ – different recording (LibraryThing)
Fig. 10: Tag „20th century“ – different recording (LibraryThing)
These exaples show, that infringing grammatical rules in tagging is not the only problem.
There is another problem and namely the use of synonyms, recording of tags in different
languages, use of singular and plural and homonyms.
35
Problems related to the creation of tags are summed up by G. MACGREGOR a E.
McCULLOCH, [2006] as follows:
¾ low precision of tags
¾ lack of collocation
¾ dropping out basic syntax relations
¾ lack of association between terms
¾ lack of hierarchic structure
¾ lack of semantic relations (synonyms, homonyms)
¾ using both singular and plural
¾ use of ungramatical forms
¾ use of user’s own vocabulary
There are no limits in free tagging. In a speech by [BAR-ILAN, J. et al., 2006] however, an
idea of structured tagging which enables more detailed description is outlined. It concerns
predefined metadata as e.g. main topic, description of event, location and time of event, type
of the object, etc.
Even though there is no relationship between tags formulated as e.g. in controlled
vocabularies, there is a certain form of visualization of relations namely in the form of „tag
clouds“. Tag cloud is a list of tags in an alphabetical order where most frequent tags are
displayed in a bigger and bold form (fig. 11)
Fig. 11: Tag cloud – „most popular tags“ (WorldCat)
36
Tag clouds serve as orientation elements enabling search in online resources. In case of using
tags in library catalogues or museums and galleries collections tag clouds represent interesting
tools for users’ language analysis. It is possible to trace the word-stock of users in the
respective institution (see the above mentioned note of using tags in the Steve Project - fig. 8).
Controlled v. uncontrolled (“active” vocabulary)
In the indexing process an information specialist - indexer – is limited by a retrieval language
and barriers of a controlled vocabulary. M. BUCKLAND [1999] states that „vocabulary
commonly refers to the stylized adaption of natural language to form indexes and thesauri“.
Controlled vocabulary is a list of words and terms used in information indexing and also
retrieving. It shows relations between terms and helps users in an efficient searching.
Controlled vocabulary is an authority file which should ensure consistency of indexation, i.e.
among others a uniform use of terms in the framework of the given system. There are basic
semantic relations established between individual terms such as equivalency, association and
hierarchy.
Systems based on tagging don’t use any controlled vocabulary. Each user uses its own
vocabulary from which he choose freely individual words and terms to describe an object or
a document. In tagging there is no need of neither regulations for using words nor of
requirements of previous knowledge of controlled vocabulary creation. We can call this an
uncontrolled vocabulary.
With regard to missing relationship between individual concepts we can also speek about an
unstructured vocabulary, or better “free structure vocabulary” [SMITH, T., 2007]. K.
WELLER [2007] uses in contrast to controlled a term „active vocabulary“ as it concerns an
active use of a vocabulary by the respective community.
Regarding problems with structuring and usage of tags e.g. A. NORUZI [2007] thinks about
thesauri being part of folksonomies based systems. E.g. to cut out singular and plural,
eventually for the use of synonyms.
As it was mentioned above some libraries but also museums and galleries have applied social
tagging function in their catalogues and databases. Folksonomies are being added as
a supplementary technologies to an existing classification system. They are increasing subject
processing by a user’s view. Tags are used in parallel with traditional elements of a retrieval
37
language. The result is an overlap of freely created tags and lexical units chosen from
a controlled vocabulary. See examples from „Danbury Library Catalog“ (fig 4), „Electronic
Theses and Dissertations – Montana State University“ catalogue (fig. 5), Panteion University
catalogue (fig. 12) or WorldCat (fig. 11) as already mentioned above.
Fig. 12: Subject headings and tags as part of catalogue (Panteion University, Atheny)
Tags help to describe sources in a much more flexible, dynamic and open way towards users.
At the same time they can be (in specialized libraries and databases in particular) an
inspiration for including new indexing words to a controlled vocabulary of a given institution.
Consequently new local authority files appear based on users’ language, so called „user
community vocabularies“. Such vocabularies contain neologisms or concepts translated into
different languages. They can be appropriate tools for understanding both user and indexer
approach to indexing the content.
J. FURNER [2007] assesses user tagging in the following way:
¾ user tagging is user oriented, tags for the resources in a given collection are generated
by the members of the community of people who have demonstrated interest in
searching the collection
38
¾ user tagging is empowering. People who might in the past have been accustomed to
searching by attempting to predict the descriptors used by „experts“ are given the
opportunity to record their own knowledge about sources
¾ users can tag themselves according to their interests and aims
¾ user tagging is cheap
¾ user tagging is collaborative
¾ user tagging is distributed. No single person is required to tag all of the resources in
a given collection
¾ user tagging is dynamic, the description of a given resource may change over time
¾ it can be interesting for community members how the respective field and its
terminology is developing according to the appearance of new tags
Tags are currently becoming one of the entry element to the library catalogues and digital
collections of museums and galleries.
[!]COMMENTS TO CONCLUDING EXCERCISES:
Interconnection between traditional approach to knowledge organization and possibilities
offered by tagging based systems consequently offer a lot of interesting views of further work
in the field of subject organization of information and knowledge, possibly of the whole
indexing process. In the following five excercises, or better – group projects, students can
focus on selected issues or current topics.
[?] EXCERCISES, GROUP PROJECTS:
¾ Compare users’ tags with lexical units in selected controlled vocabularies. Pay
attention to the consistency of indexing, tag structure, frequency of the tag use, etc.
You can find inspiration in studies tackling the issues. Frequency analysis of the tag
use you can find e.g. in KIPP, M.E., CAMPBELL, D.G., 2006); comparison of tags
with lexical units of selected controlled vocabularies from the point of view of
indexing
consistency
e.g.
in
ROLLA,
P.J.,
2009;
or
KAKALI,
C.,
PAPATHEODOROU, Ch., 2010.
¾ Try to analyse users’ behaviour when choosing tags (representative sample taken from
e.g. group of schoolfellows, colleagues from work, members of an interest group, etc.)
39
¾ Set down a hypothesis how efficient is to use folksonomies in library catalogues, if
tags could replace a controlled vocabulary, eventually if and how it is possible to
interconnect both vocabularies. Try to testify or disprove your arguments on the basis
of personal discussion with specialist in the given field, your colleagues etc.
¾ Make an analysis of complience of freely assigned tags with terms from a controlled
vocabulary, of resemblance of tags and subject headings and above all of reliability
and punctuality of the subject description in your chosen system (e.g. catalogue, etc.).
¾ Put down a list of subject fields or knowledge which are in any aspect in relationship
with tagging systems, or which can be used in analysing the systems and their
elements. E.g. linguistics in creating lexical units, statistical methods in determining
frequency of selected tags, user motivation in choosing the given tag, influence of
learning etc.
Bibliography (chapter 6 and 7)
•
AGEE, Victoria. Controlling our own vocabulary : a primer for indexers working in the
world of taxonomy. Key Words. 2008, vol. 16, no. 1, s. 30-31.
• BAR-ILAN, Judit et al. Structured vs. unstructured tagging – a case study [online].
Edinburgh, 2006 [cit. 2010-09-09]. Paper presented at WWW2006, Collaborative Web
Tagging Workshop, Edinburgh. Dostupný z WWW:
<http://www.ra.ethz.ch/CDstore/www2006/www.rawsugar.com/www2006/12.pdf>.
• BUCKLAND, Michael. Vocabulary as a central concept in library and information
science. In Digital libraries : interdisciplinary concepts, challenges, and opportunities :
proceedings of the Third International Conference on Conceptions of Library and
Information Science, Dubrovnik, Croatia, 23-26 May 1999 [online]. Zagreb : Lokve,
1999 [cit. 2010-09-09]. Dostupný z WWW:
<http://www.sims.berkeley.edu/~buckland/colisvoc.htm>.
• DALY, Ellen; BALLANTYNE, Neil. Ensuring the discoverability of digital images for
social work education : an online "tagging" survey to test controlled vocabularies.
Webology [online]. 2009, vol. 6, nr. 2 [cit. 2010-09-09], s. 1-16. Dostupný z WWW:
<http://www.webology.ir/2009/v6n2/a69.html>.
• FURNER, Jonathan. User tagging of library resources : toward a framework for system
evaluation. In World Library and Information Congress : 73rd IFLA General
Conference and Council, 19-23 August 2007, Durban, South Africa [online]. IFLA,
2007 [cit. 2010-09-09]. Dostupný z WWW:
<http://archive.ifla.org/IV/ifla73/papers/157-Furner-en.pdf>.
40
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44
EXAMPLES
• Art & Architecture Thesaurus: http://www.getty.edu/research/tools/vocabularies/aat/
• Danbury Library Catalog, Connecticut: http://cat.danburylibrary.org
• Delicious, social bookmarking: http://www.delicious.com/
• Dewey Decimal Classification: http://www.oclc.org/dewey/resources/summaries/,
• Eurovoc: http://eurovoc.europa.eu/
• Flickr: http://flickr.com
• Library of Congress Classification: http://www.loc.gov/catdir/cpso/lcco/
• Library of Congress Subject Headings: http://www.loc.gov/cds/lcsh.html,
• LibraryThing: http://librarything.com
• Maternal and Child Health Thesaurus: http://www.mchthesaurus.info/
• Montana State University (Electronic Theses and Dissertations):
http://etd.lib.montana.edu/etd/view/index.php
• National authorities of the Czech republic: http://autority.nkp.cz/
• Panteion University, Atheny (OPACIAL): http://library.panteion.gr/opacial/
• Steve : the museum social tagging project: http://www.steve.museum,
http://tagger.steve.museum
• Synonym finder: http://www.synonym-finder.com/
• Universal Decimal Classification: http://udcc.org/udcsummary/php/index.php,
http://aip.nkp.cz/mdt/,
• WordNet : a lexical database for English: http://wordnet.princeton.edu/
• WorldCat: http://www.worldcat.org/
45

Charles University in Prague Institute of Information Studies and

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