Taxonomies and Metadata

Agenda

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

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”

Purposes of Metadata

Additionally…• Facilitate interoperability between systems• For Archiving and Preservation

Retrieval

Resource

Discovery &

IdentificationManagement Classification

Connect with

other resources

Authorship &

Access Rights

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”

Popular Metadata Standards

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”

Where are they?

Most commonly used taxonomy

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

Structured KOS and their applicability

Type Directionality Description Applicability

Taxonomy Groups resources into categories

For creating simple classification

schemes

ThesaurusCaptures 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

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)

VS

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 ?

Leveraging both Taxonomies and Folksonomies

1. Start with a controlled vocabulary created by experts2. Create the taxonomies based on the controlled vocabulary3. Provide the users with the feature to add tags to the resources in the

system4. Monitor tagging activity and tag convergence for resources5. Modify the controlled vocabulary to include the popular tags thereby

modifying the taxonomy too

Expert touch + People choice = Relevant Taxonomies (Controlled (Tags) Vocabs)

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 abilityCan 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

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

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)

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

Why

Metadata + Taxonomy ?

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

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]

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

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

RequirementsIdentify Concepts

Develop draft

taxonomy

Review with Users

and SMEsRefine taxonomy

Apply taxonomy to

content

Manage and

maintain

taxonomy

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

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

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

ReferencesAcademic ReferencesWhittaker, 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 ReferenceHodge, G. (2013, June 18). Taxonomies and ontologies: definitions, differences and use. Retrieved from http://info.nfais.org/info/Hodge_Post.pdfLei Zeng, M. (2004). Metadata standards. Retrieved from http://marciazeng.slis.kent.edu/metadatabasics/standards.htmNISO. ANSI, (2004). Understanding metadata. Retrieved from website: www.niso.org/standards/resources/UnderstandingMetadata.pdfTen taxonomy myths. (2002, November). Retrieved from http://www.montague.com/review/myths.htmlSlideshare ReferencesBarbosa, 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-presentationChampeau, D. (2009, November 24). Taxonomy and metadata. Retrieved from http://www.slideshare.net/dchampeau/taxonomy-and-metadataConnors, C. (2010, January 21). From taxonomies to ontologies. Retrieved from http://www.slideshare.net/TriviumRLG/from-taxonomies-to-ontologiesCooksey, D. (2008, April 08). Taxonomy is user experience. Retrieved from http://www.slideshare.net/saturdave/taxonomy-is-user-experienceMetaschool Project. (2006, December 16). Retrieved from http://www.slideshare.net/metaschool/module-37-2731159White, L. (2012, May 22). Taxonomy: Do i need one. Retrieved from http://www.slideshare.net/ElemSrc/taxonomy-do-i-need-one