cultural tourism taxonomies and folksonomies chris tweed school of planning, architecture and civil...
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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