Cultural tourism taxonomies and folksonomiesChris Tweed

School of Planning, Architecture and Civil Engineering

Queen’s University Belfast

The problem

Aims and objectives

To develop a comprehensive map of the elements of cultural heritage that attract different people to towns and cities by:

– identifying and categorising a comprehensive range of cultural attractors

– identifying interests and motivators for different types of tourists

– identifying relations of attraction between attractors and interests

To identify governance strategies based on analysis of the relations

Existing classification taxonomies

Prentice’s typology—23 main types

– natural history attractions, science based attractions, attractions concerned with primary production, craft centres and craft workshops, attractions concerned with manufacturing industry, transport attractions, socio-cultural attractions, attractions associated with historic persons, performing arts attractions, pleasure gardens, theme parks, galleries, festivals and pageants, fieldsports, stately and ancestral homes, religious attractions, military attractions, genocide monuments, towns and townscape, villages and hamlets, countryside and treasured landscapes, seaside resorts and 'seascapes', regions

not all cultural, not all urban, though difficult to exclude from “culture”

Existing classification taxonomies

PICTURE D7 list—16 main types, with many sub-types

– tangible heritage within the surrounding environment/landscapes, cultural clusters, individual monuments, public spaces, heritage attractions, traditional local markets, festivals and special events, traditional crafts, languages (living and used/signs), information systems, industry and commerce, religious sites, iconic buildings, sites associated with historic or legendary events and famous people, sport and leisure activities, traditional food and drinks, modern pop culture

offers a list which is more closely related to PICTURE tasks

Classification problems

Dewey, 200: Religion

210 Natural theology220 Bible230 Christian theology240 Christian moral & devotional theology250 Christian orders & local church260 Christian social theology270 Christian church history280 Christian sects & denominations290 Other religions

Classification problems

US Library of CongressD: History (general)

DA: Great BritainDB: AustriaDC: FranceDD: GermanyDE: MediterraneanDF: GreeceDG: ItalyDH: Low CountriesDJ: Netherlands

DK: Former Soviet UnionDL: ScandinaviaDP: Iberian PeninsulaDQ: SwitzerlandDR: Balkan PeninsulaDS: AsiaDT: AfricaDU: OceaniaDX: Gypsies

Existing classification approaches are …

designed for specific purposes

object-oriented rather than experience-oriented

generally too complicated for anyone without specialised training

require strict control over the creation of new entities and branches

become fixed and inflexible

A design analogy

From taxonomy to folksonomy

Folksonomy

folksonomy = folk + taxonomy

Also known as ethnoclassification

Main feature is user-generated metadata in the form of tags or keywords

Tags exist in a flat namespace with no hierarchy

It is a bottom-up as opposed to a top-down approach

A folksonomy is more about categorisation than classification

Traditional hierarchy

Hierarchy with links

Just links (no hierarchy)

Limitations of folksonomies

Ambiguity

The same tag may be used in different ways

Different tags may be used for the same concept

Acronyms not differentiated from actual words, e.g. ANT

Imprecision

Lack of controlled vocabularies allows great inaccuracies

Chaos

Lack of structure creates possibility of chaos

Strengths of folksonomies

Accessibility

Low barriers to entry for general public

Low cognitive costs

Folksonomies reflect response of general public

Generate socially shared data

Dynamic

Feedback on tagging is immediate

Tags evolve to reflect new concerns

Developing a folksonomy of cultural tourism attractions

Develop a Web-based questionnaire providing opportunities for visitors to record their:

descriptions

feelings

evaluations and

relevant personal details

for selected sites (represented as Web pages)

Analyse data for emergent relations across attractions and visitors

Provide tools for browsing explicit and implicit relations

Potential added value

Work to be done

Finalise Web questionnaire and database

Identify selected sites

Collect data from tourists

Analyse data