Presentation prepared for my supervisor on the topics Taxonomy and Metadata

1. Taxonomies and Metadata

2. Agenda
• Introduction to Metadata and Taxonomy
• Folksonomies
• Ontologies
• Metadata and Taxonomy combined
• Taxonomy Development
• Software and Tools
• Current Challenges

4. What is Metadata?
Metadata is structured information that
describes, explains, locates, or otherwise makes it easier
to retrieve, use, or manage an information resource[NISO]
Title
Author(s)
Year of publication
Metadata Types
• Descriptive -> for resource discovery and
identification
• Structural -> defines the physical/logical
structure of resources
• Administrative -> for managing resources
“Metadata is simply data about data”

5. Purposes of Metadata
Additionally…
• Facilitate interoperability between systems
• For Archiving and Preservation
Retrieval
Resource
Discovery &
Identification
Management Classification
Connect with
other resourcesAuthorship &
Access Rights

6. Evolution of global metadata
standards…
Metadata Scheme – set of metadata elements designed for a particular purpose
Metadata Specification – when metadata scheme is
adopted by many other organizations
Metadata Standards – when metadata specification is
accepted by a ‘standards’ body such as ISO
“Metadata Standards are required at a global level mainly
for enforcing Interoperability between systems”

7. Popular Metadata Standards

9. What are Taxonomies
• In KM perspective, taxonomy is a hierarchical topic structure where
information items are assigned through the dual processes of
classification (filing to a location) and categorization (tagging with
corresponding metadata) [centralized taxo]
• Taxonomies facilitate discovery (browsing & searching), retrieval and
content re-use of resources within a system
“Taxonomies are hierarchical classification systems”

10. Where are they?

11. Most commonly used taxonomy

12. Taxonomy and Knowledge Organisation
Systems (KOS)
• In the Information Science domain, Taxonomies are a type of
Knowledge Organisation Systems (KOS) which are meant to
model the underlying semantic structure of a domain [Hodge]
• Among KOS types, taxonomies are somewhere in the “middle”
in terms of creation/maintenance complexity and expressive
power
http://www.slideshare.net/TriviumRLG/from-
taxonomies-to-ontologies

13. Structured KOS and their
applicability
Type Directionality Description Applicability
Taxonomy
Groups resources
into categories
For creating simple
classification
schemes
Thesaurus
Captures different
names of resources
and finds close
relationships
For creating
classification
schemes along with
associative
relationships
Ontology
Captures multi-
dimensional
relationships b/w
both within and
between groups of
resources
For maintaining a
network of resources
with multiple
relationships and
properties

14. Folksonomies – Web 2.0 based alternative
to Taxonomies
• A new breed of web 2.0 resource sharing systems allow users to add their own keywords(or tags) to
resources
• Tags used for both resource description & classification and for later retrieval
• Outcome of tagging activity in a systems => Folksonomy
• Folksonomies are the most dynamic KOS system
• Two types :
– Broad folksonomies: Anyone can add any resource and tag any resource
– Narrow folksonomies: The author adds the resources and adds the tags while other users are restricted in
adding tags
• Popular systems: Flickr (Image sharing system), Delicious (Social bookmarking system)

15. Taxonomy created with Experts Folksonomy developed through users
Professional touch
Highly compliant with
historical resources
Rigid
Dependent on experts
People power
Highly compliant with
current resources
Volatile
Takes time for
vocabulary convergence
Spelling mistakes
Spams
Why Folksonomies ?

16. Leveraging both Taxonomies and
Folksonomies
1. Start with a controlled vocabulary created by experts
2. Create the taxonomies based on the controlled vocabulary
3. Provide the users with the feature to add tags to the resources in
the system
4. Monitor tagging activity and tag convergence for resources
5. Modify the controlled vocabulary to include the popular tags
thereby modifying the taxonomy too
Expert touch + People choice = Relevant Taxonomies
(Controlled (Tags)
Vocabs)

17. Ontologies – most advanced KOS type
• What are Ontologies?
– A networked collection of concepts and their corresponding properties
and relationships in a particular knowledge domain
• Support for all different properties
– Transitive
– Symmetrical
– Functional & Inverse Functional
• The biggest benefit of ontology is its inferencing ability
Can Taxonomies and Ontologies co-exist?
• Both ontologies and taxonomies can be built from each
other
• The relationship between components in a taxonomy is
implicitly understood by users
• The relationship between components in a ontology is
explicitly specified and can be understood by semantic
systems
• In reality, ontology subsumes taxonomy and therefore
taxonomy can be built from ontology without any loss of
data

18. More on Ontology…
• Ontology is the central binding component of the proposed “Semantic
Web” architecture
• Semantic Web represents the next generation
web of data where systems understand data
• Semantic Web technologies such as RDF,
OWL and SPARQL are already used in many
websites
• Anyone can design an ontology using the Web Ontology Language (OWL) or
Resource Description Framework (RDF) and publish in the web
• Simple Knowledge Organisation System (SKOS) is an vocabulary that can
be used by organisations to express their taxonomies, thesauri and other
classification schemes

19. More on SKOS and KM…
• Use SKOS type ontologies in your company if you are interested in
using semantic technologies
• Semantic technologies aid the “Linked Data” vision where the aim is
to connect data in one organisation to data from other organisations
to facilitate re-use and better understanding
• Caveat: These technologies have not reached mainstream adoption
yet
SKOS is able to express both taxonomy
relationships (broader/narrow) and
thesaurus relationships (preferred label)

20. Taxonomy and other KOS systems – a
summary
• Taxonomies are not just a set of folders
• They are an entry point to the pool of resources (documents)
• They are built on top of controlled vocabularies
• Taxonomies can be built through expert analysis
• Folksonomies make use of the public vocabulary for providing
continual updates to taxonomies
• Ontologies help in re-using concepts and applying semantics to the
concepts
• Web based ontologies help in inter-operability across other systems

22. Complimentary relationship of Metadata
and Taxonomy
• Metadata describes a resource well and is very much part of the resource
• Metadata doesn’t capture relationships between resources sufficiently ->
this is where taxonomies come in
• Taxonomies are external to the resource and are good for modelling
relationships between resources
• Taxonomies are road-maps and serve dual purposes of describing current
resources and also predicting where the future resources will be placed
Metadata
Taxonomy
Data about items
Classification
&
Labeling
 Finding resources
 Helping in decision making by
providing a pool of resources
with their corresponding
information

23. Visualizing the integrated working
mechanism of metadata and taxonomies
Document, Content
& Records
Management
Thesauri
Ontologies
Filing & Storage
Resource Metadata
&
Tagging
Search
Engine
Visualisation
Resource
Navigation
Intranet / Portal
User Interface
Back End
Components
Front End
Components
Taxonomies
Knowledge Organisation
Systems
[Centralized taxonomy]

24. What are the indications of a good
taxonomy?
• Taxonomy vocabularies need to be understandable and meaningful to
common users
• The users should be able to get an overall idea of the structure of the
domain by looking at the taxonomy
• The resources are to be easily located in taxonomies with smaller paths
• The users should also be able to anticipate where new resources would be
placed
• Most importantly, taxonomies should be easy to navigate

25. Taxonomy Development
• Taxonomies are essentially “living organisms” with dynamic
nature -> continually evolving over a period of time
• One-time development followed by periodic updates is the
norm with taxonomy management
Whittaker’s seven steps of taxonomy development
Determine
Requirements
Identify
Concepts
Develop draft
taxonomy
Review with
Users and
SMEs
Refine
taxonomy
Apply taxonomy
to content
Manage and
maintain
taxonomy

26. Other Approaches to Taxonomy
Development
Ovum’s approach
• Start with a knowledge/information audit
– Study of the requirements
• Build on top of existing taxonomies and categorisation models
– Use internal draft taxonomies or adopt from other companies
• Develop a draft taxonomy
– By making use of categorisation tools
• Refining the taxonomy
– To ensure navigability and logical correctness
• Testing
– Piloting with few users to iron out the defects
• Applying the classification model
– Bring in the documents
• Monitoring

27. Challenges related to Taxonomy
Development and Management
• There is not just ‘one’ correct taxonomy for the entire
organization
• Development from scratch vs. Adapting someone else’s
• Taxonomy creation at start or end of information lifecycle
• User-oriented or content-oriented taxonomies
• Document-centric or people-centric taxonomies
• Taxonomy integration

28. Popular Software
Software and Tools
• Synaptica – Commercial taxonomy building software
• Poolparty – Thesaurus management software with SKOS editor
• MultiTes Pro – Thesaurus building software
• Protégé – Free ontology building software
• TopBraid Composer – Ontology editing software
• Microsoft Sharepoint – Most popular content and document management
platform with enterprise search

29. References
Academic References
Whittaker, M., & Breininger, K. (2008, August). Taxonomy development for knowledge management. In 74th General
Conference and Council of the World Library and Information, Quebec, Canada.
Woods, E. (2004). Building a corporate taxonomy: Benefits and challenges.Ovum expert advice.
General Web Reference
Hodge, G. (2013, June 18). Taxonomies and ontologies: definitions, differences and use. Retrieved from
http://info.nfais.org/info/Hodge_Post.pdf
Lei Zeng, M. (2004). Metadata standards. Retrieved from http://marciazeng.slis.kent.edu/metadatabasics/standards.htm
NISO. ANSI, (2004). Understanding metadata. Retrieved from website:
www.niso.org/standards/resources/UnderstandingMetadata.pdf
Ten taxonomy myths. (2002, November). Retrieved from http://www.montague.com/review/myths.html
Slideshare References
Barbosa, D. (2008, September 29). Centralized taxonomy management for enterprise information systems. Retrieved from
http://www.slideshare.net/danielabarbosa/centralized-taxonomy-management-for-enterprise-information-systems-
presentation
Champeau, D. (2009, November 24). Taxonomy and metadata. Retrieved from
http://www.slideshare.net/dchampeau/taxonomy-and-metadata
Connors, C. (2010, January 21). From taxonomies to ontologies. Retrieved from
http://www.slideshare.net/TriviumRLG/from-taxonomies-to-ontologies
Cooksey, D. (2008, April 08). Taxonomy is user experience. Retrieved from http://www.slideshare.net/saturdave/taxonomy-
is-user-experience
Metaschool Project. (2006, December 16). Retrieved from http://www.slideshare.net/metaschool/module-37-2731159
White, L. (2012, May 22). Taxonomy: Do i need one. Retrieved from http://www.slideshare.net/ElemSrc/taxonomy-do-i-
need-one